Multi Mobile Media V2

Arbitrage statistici avanzati per MetaTrader MT4 - Versione 3 tecniche di arbitraggio di negoziazione statistiche (a volte sa come la convergenza o di scambio coppie) si basano sul concetto di mean reversion. Il sistema monitora costantemente le prestazioni dei due strumenti storicamente altamente correlati, che definisce il commerciante. Quando la correlazione tra i due strumenti indebolisce o diverge oltre un livello predefinito - V3 automaticamente e simulataneously acquistare lo strumento più debole e vendere il più forte. Una volta mean reversion si svolge la posizione netta creata dai due mestieri sarà generalmente in profitto. Questa strategia di trading richiede una buona conoscenza della leva finanziaria e controllo dei rischi, la capacità di analizzare strumenti altamente correlati tra diverse classi di attività e la comprensione di come interpretare spread. (Lo spread è la differenza effettiva tra i due strumenti da monitorare per i potenziali opportunità di arbitraggio. L'immagine sotto introduce quotThe Spreadquot che è un componente fondamentale di qualsiasi sistema di arbitraggio. Video Walkthrough per Basics diffondere la screenshot sopra dimostrano il potenziale per i profitti sani utilizzando statistiche conversione di arbitraggio tecniche di trading eyed appassionati noteranno il lasso di tempo durante il quale sono stati fatti questi traffici concettuali era dall'aprile 2009 fino a settembre 2012 -. 7 mestieri in oltre 3 anni si qualifica sicuramente per la negoziazione a bassa frequenza, anche se le potenziali opportunità di rialzo da operazioni di arbitraggio a lungo termine può essere eccezionale. Tuttavia, la maggior parte commercianti richiedono frequenze commerciali più alte in modo un sistema di arbitraggio deve essere in grado di operare su tempi molto più basso e con frequenze di trading molto più elevate. tempistiche Arbitrage Trading e l'esempio prospettiva l'SampP500GER40 sopra elegantemente mostrato la semplicità della mean reversion tecnica. Tuttavia, quando le attività altamente correlate sono analizzate in tempi più brevi la situazione diventa più complessa. Teoricamente il momento ideale per eseguire operazioni ARB con ingresso convenzionale e la logica di uscita è quando lo spread è definito stazionaria. Questo è dove lo spread (la differenza tra i prezzi dei due strumenti) oscilla abbastanza sinusoidale intorno alla sua media mobile. Idealmente la media mobile dovrebbe essere più piatta possibile. La schermata qui sopra per Oro e Argento dimostra come i cambiamenti diffondersi da un direzionale per natura stazionaria oltre piuttosto un breve periodo di tempo. Uno spread fisso è ideale per lo scambio di ARB in quanto permette commerci in entrambe le direzioni - vale a dire la vendita GoldBuying argento quando lo spread è al di sopra del livello di trigger d'argento e di acquisto Goldselling superiore quando lo spread è al di sotto del livello di trigger inferiore. La sfida si verifica quando la dinamica di diffusione cambiano da stazionario direzionale. Una diffusione direzionale è dove la media mobile viene increasingdecreasing nel corso del tempo. In altre parole una coppia è continuamente rafforzando mentre l'altra è immutata o indebolimento. In questo scenario è necessario un motore di arbitraggio automatizzato per essere in grado di rilevare automaticamente la direzione della diffusione. Nel corso del programma di sviluppo V3 abbiamo sperimentato vari algoritmi per tracciare e monitorare la diffusione di tendenza. Nell'ultima versione stiamo usando un algoritmo di rilevamento multi-temporale per determinare se la diffusione è ferma (va) o direzionale (trend). Questi sono descritti in dettaglio nelle rassegne modulari che seguono. V3 Architettura Le prime versioni V3 sono stati rilasciati nel giugno 2011 e il prodotto è stato aggiornato e migliorato in modo sistematico dal lancio. V3 offre una nuova interfaccia utente grafica e tutta una serie di altre caratteristiche di seguito dettagliato. Il sistema V3 Arbitrage è costituito da due componenti principali: - Il consulente esperto Gen Starb (EA) L'indicatore STD In termini semplici, l'indicatore STD monitora la diffusione e fornisce segnali di entrata. Il consulente esperto svolge funzioni di esecuzione delle negoziazioni e di gestione. In sostanza le due applicazioni di comunicare in tempo reale utilizzando la tabella delle variabili MetaTrader globale (GVAR). Entrambi siedono su un generico archtecture distribuzione FX AlgoTrader mostrato nell'immagine qui sotto. INFORMATIVA SUI RISCHI I prodotti presenti su questo sito sono di negoziazione strumenti e non sono destinate a sostituire ricerche individuali o sugli investimenti in licenza. Le performance passate non garantisce risultati futuri. Valute comporta dei rischi notevoli, e c'è sempre il rischio di perdita. Nessuna rappresentazione è stato fatto che questi prodotti garantire profitti o meno risultare in perdite da negoziazione. Qualsiasi spiegazione o dimostrazione del funzionamento dei prodotti non devono essere interpretati come una raccomandazione commercio o la prestazione di consulenza per gli investimenti. L'acquisto o la vendita di una moneta possono essere eseguite solo da un dealer autorizzato. L'indicatore V3 STD Indicator STD produce statistiche diffuse in tempo reale, che sono messi a disposizione del motore di arbitraggio generico tramite la tabella delle variabili MetaTrader globale. L'indicatore STD è costituito da diversi componenti che sono descritte nello schema qui sotto. STD multipla - Questo parametro consente agli operatori di ottimizzare i livelli limite per i punti di ingresso arb. Il multiplo STD viene regolata mediante l'accesso ai parametri di ingresso esterni dell'indicatore STD. Idealmente i commercianti dovrebbero cercare di impostare il multiplo STD in modo che i picchi di diffusione divergenza coincidono con i livelli limite superiore e inferiore. Nello screenshot qui sotto possiamo vedere il multiplo STD è stata regolata fino a 0,7 sul grafico giornaliero in coincidenza con i picchi tipici diffusione divergenza. Uscite dati - L'indicatore STD calcola la media mobile (MA), la diffusione e modificare i livelli limite superiori e inferiori (sulla base del multiplo STD) in tempo reale. Reversion Target - Il target di reversione mostra il livello fosse il sistema tenterà di chiudere il arb. Per impostazione predefinita, la media viene sempre utilizzato come destinazione di uscita ARB ma i commercianti possono modificare manualmente per indirizzare alla band grilletto opposta modificando il parametro di ingresso esterno ReversionToMA FALSE nelle opzioni indicatore STD. Trend - L'indicatore di tendenza si basa su un algoritmo di EMA impilati multi-temporale Proprietory. Gli operatori possono registrare fino a 8 filtri di tendenza che calcolano la tendenza sulla base di analisi dei trend multi-temporale. Ad esempio, un commerciante di maggio preferisce innescare i loro commerci ARB dal grafico 15 minuti e può essere utile per bloccare i traffici in direzione delle tendenze M30, M60 e M240. In questo caso il commerciante sarebbe semplicemente impostare i TFilters M30, M60 e M240 a Vero, come mostrato nello screenshot qui sotto. Dati Check: Questa è una nuova funzione che esegue 4 test di integrità dei dati sulla diffusione quando il suo caricati su un grafico inizialmente. Se la diffusione passa l'integrità controlla l'etichetta dati OK verrà mostrato. Il motore di arbitraggio non può fare trading a meno che il Data Check bandiera legge OK Il V3 Expert Advisor I motori di arbitraggio generici monitorare costantemente la tabella variabile globale MetaTrader per l'immissione di dati commerciali e di uscita per i vari arbs che il commerciante ha istituito in ogni grafico. È importante ricordare che ogni grafico deve avere un'istanza separata sia l'indicatore STD e il motore di arbitraggio esecuzione insieme. L'immagine sotto mostra un completo Stat Arb V3 impostato su un grafico MetaTrader. Schermata della EA V3 e l'indicatore STD su un grafico MetaTrader. Nota: Nessun dato viene popolato come un fine settimana. Il modulo System Modulo dati I dati di sistema visualizza l'ora corrente del sistema, quali strumenti vengono scambiati, lo stato del sistema, la modalità del sistema e lo stato di allerta e-mail. Per i dettagli chiarimenti si prega di fare riferimento alla scheda tecnica. INFORMATIVA SUI RISCHI I prodotti presenti su questo sito sono di negoziazione strumenti e non sono destinate a sostituire ricerche individuali o sugli investimenti in licenza. Le performance passate non garantisce risultati futuri. Valute comporta dei rischi notevoli, e c'è sempre il rischio di perdita. Nessuna rappresentazione è stato fatto che questi prodotti garantire profitti o meno risultare in perdite da negoziazione. Qualsiasi spiegazione o dimostrazione del funzionamento dei prodotti non devono essere interpretati come una raccomandazione commercio o la prestazione di consulenza per gli investimenti. L'acquisto o la vendita di una moneta possono essere eseguite solo da un dealer autorizzato. opzioni automatiche e manuali di profitto mira sul grafico commerciali analisi Email impianto di allarme (quando eseguito in modalità non automatica) tempistica commercio granulare controlla il controllo del rischio configurabile Automated Trend di rilevamento e la funzionalità di blocco del sistema di aggregazione Profit Auto copertura Caratteristica molto globale di dimensionamento e di aggregazione obiettivi sistema di allarme di sintesi vocale Utile Meccanismo di bloccaggio variabile Leg Aleg B Posizione dimensionamento supporto multi-strumento - indici del commercio, materie prime, forex, CFD. algoritmi di reversione, di canale e di diffusione più accurate logica più accurata visualizzazione ingresso ritardato algoritmo di rilevamento tendenza diffusione Entry Multi-time di controllo integrato diffondere i dati di controllo impianto Revised interfaccia grafica semplificata per uso commerciale di controllo I prodotti presenti su questo sito sono trading strumenti e non sono destinati a sostituire individuale di ricerca o di consulenza per gli investimenti in licenza. Le performance passate non garantisce risultati futuri. Valute comporta dei rischi notevoli, e c'è sempre il rischio di perdita. Nessuna rappresentazione è stato fatto che questi prodotti garantire profitti o meno risultare in perdite da negoziazione. Qualsiasi spiegazione o dimostrazione del funzionamento dei prodotti non devono essere interpretati come una raccomandazione commercio o la prestazione di consulenza per gli investimenti. L'acquisto o la vendita di una moneta possono essere eseguite solo da un dealer autorizzato. V3 Expert Advisor Interfaccia per V3 STD indicatore unilaterale Arb Trading Tecniche I prodotti presenti su questo sito sono di negoziazione strumenti e non sono destinate a sostituire ricerche individuali o sugli investimenti in licenza. Le performance passate non garantisce risultati futuri. Valute comporta dei rischi notevoli, e c'è sempre il rischio di perdita. Nessuna rappresentazione è stato fatto che questi prodotti garantire profitti o meno risultare in perdite da negoziazione. Qualsiasi spiegazione o dimostrazione del funzionamento dei prodotti non devono essere interpretati come una raccomandazione commercio o la prestazione di consulenza per gli investimenti. L'acquisto o la vendita di una moneta possono essere eseguite solo da un dealer autorizzato. Stat Arb V3 permette completamente automatizzato incustodito Arbitrage Trading dai grafici preconfigurati utilizzando tecniche di arbitraggio aumenta la probabilità di fruttuosi scambi commerciali (lasso di tempo dipendente) Stat Arb V3 fornisce una serie di dati altamente granulari che consente agli operatori di vedere i profitti potenziali di reversione dalla specifica ARB set up prima di entrare nel mercato. Stat Arb V3 è un collaudato, robusto set di strumenti di trading, che è stato sviluppato in modo iterativo dal 2009. I prodotti presenti su questo sito sono trading strumenti e non sono destinati a sostituire ricerche individuali o sugli investimenti in licenza. Le performance passate non garantisce risultati futuri. Valute comporta dei rischi notevoli, e c'è sempre il rischio di perdita. Nessuna rappresentazione è stato fatto che questi prodotti garantire profitti o meno risultare in perdite da negoziazione. Qualsiasi spiegazione o dimostrazione del funzionamento dei prodotti non devono essere interpretati come una raccomandazione commercio o la prestazione di consulenza per gli investimenti. L'acquisto o la vendita di una moneta possono essere eseguite solo da un dealer autorizzato. Dati di performance: per ricevere i dati sulle prestazioni V3 Inserisci il tuo indirizzo email qui sotto. Nota: La prestazione precedente è semplicemente una rappresentazione di ciò che può essere realizzato utilizzando il set di strumenti. In definitiva, le prestazioni del sistema varia notevolmente a seconda che le attività sono negoziati, i tempi ed i parametri utilizzati e la capacità dei commercianti. Il sistema Stat Arb V3 è semplicemente un set di strumenti per facilitare una strategia di trading automatizzato di arbitraggio sulla base di una serie di commercianti requirements. FX AlgoTrader NON trasmettere indirizzi e-mail a terzi. I prodotti presenti su questo sito sono strumenti di trading e non sono destinati a sostituire ricerche individuali o sugli investimenti in licenza. Le performance passate non garantisce risultati futuri. Valute comporta dei rischi notevoli, e c'è sempre il rischio di perdita. Nessuna rappresentazione è stato fatto che questi prodotti garantire profitti o meno risultare in perdite da negoziazione. Qualsiasi spiegazione o dimostrazione del funzionamento dei prodotti non devono essere interpretati come una raccomandazione commercio o la prestazione di consulenza per gli investimenti. L'acquisto o la vendita di una moneta possono essere eseguite solo da un dealer autorizzato. Scheda tecnica avanzata di statistica arbitraggio V3 Compila i dettagli nel modulo sottostante e clicca su Invia. È quindi si riceve una mail con un link alla scheda FX AlgoTrader non passano su indirizzi e-mail a terzi. contenuto degli allegati - Nuovo Arb Trader si riferisce a strumenti ARB FX AlgoTrader come FxAlgo. FxAlgo è stato selezionato dopo una ricerca esaustiva di Internet per i prodotti software di arbitraggio automatizzati che hanno lavorato all'interno dell'ambiente di trading MetaTrader 4. FxAlgo è stato poi testato su quattro conti demo di broker per un periodo di due settimane di trading solo prodotti FX. FxAlgo fornito sia una piattaforma di trading automatico stabili e un più che accettabile ROCE, mentre in prova. FxAlgo è stato poi implementato su un conto di trading dal vivo e ha fornito rendimenti di oltre il 48 sul nostro apporto di capitale iniziale su un solo periodo di scambio sei giorni. Il supporto fornito dall'autore e proprietario di FxAlgo sia durante il periodo di prova e dal movimento in funzione dal vivo è stato eccellente il livello di supporto che abbiamo vissuto non si può criticare. Tutte le richieste di assistenza via e-mail sono state esaudite quasi per il ritorno e il proprietario ha mostrato un vivo interesse per garantire siamo stati pienamente valutati tra i migliori metodi di applicazione FxAlgo per soddisfare i nostri obiettivi commerciali. Le coppie di valute che abbiamo scambiati sono stati selezionati utilizzando FxAlgos indicatore di correlazione, che ha dimostrato di essere un'aggiunta estremamente utile per il motore di trading FxAlgo V2.5. FxAlgo è utilizzato da noi per il commercio coppie di valute sui tempi H1 e D1. Il lasso di tempo H1 è stato impiegato inizialmente per ottenere un apprezzamento più veloce di funzionamento FxAlgos e come controllare il suo commercio. Dal conseguimento di un apprezzamento di base del motore di FxAlgo V2.5 di trading il lasso di tempo D1 è stato aggiunto e profitti sono aumentati come arbitraggi nell'arco di tempo che D1 sembra offrire margini di profitto più elevati in generale, anche se che richiedono più tempo per chiudere. Le impostazioni di trigger standard fornite con FxAlgo sono stati inizialmente impiegati per innescare mestieri arbitraggio. Questi sono stati trovati perfettamente adeguata e hanno prodotto una più che accettabile ROCE. Le variabili EB consigliati nella documentazione fornita con FxAlgo funzionano bene e hanno dimostrato di essere estremamente utile, mentre per conoscere FxAlgo. Essi controllano il rischio di trading fondamentale e sono un'estensione utile al motore V2.5. Abbiamo impiegato FxAlgo in solo il suo modo di riaccoppiamento cancelleria. Al momento il commercio FxAlgo attraverso un numero considerevole di coppie di valute e in due differenti frazioni di tempo e abbiamo trovato variabili globali FxAlgos di essere di aiuto prezioso. Questi variabile globale ci consentono di gestire il rischio e prelievo di capitale in tutta la nostra attività di trading con coerenza e facilità. Gestiamo rischio commerciale individuale manipolando gli ampi parametri previsti su ciascuna coppie di valute singolo foglio di trading. Non abbiamo ancora avuto alcun spread erranti o qualsiasi derivanti dalle compravendite erranti. Il rapporto winloss che abbiamo raggiunto fino ad oggi è 6535. Abbiamo impiegato solo FxAlgo nel nostro trading FX fino ad oggi. Tuttavia, abbiamo in programma di estendere il nostro uso di FxAlgo a materie prime e il commercio indici dopo abbiamo effettuato ulteriori prove contro queste due classi di attività. Abbiamo trovato FxAlgo V2.5 e la correlazione Indicatrice di essere non solo un software eccellente e robusta scritto, ma anche da una prospettiva di business di avere più che soddisfatto le nostre obiettivi dichiarati fino ad oggi. Abbiamo inoltre recentemente acquisito il prodotto FxAlgo Zeus Risk Controller, ma non hanno ancora avuto il tempo di provare questo prodotto. Il ROCE raggiunto nel trading dal vivo (solo 6 giorni fino ad oggi) ha già incontrato la maggior parte dei costi di acquisizione di entrambi FxAlgo V2.5 e la correlazione Indicator e completamente ci aspettiamo il punto di pareggio si verifichi entro i primi 10 giorni di negoziazione. Nuovo Arb commercianti di equità Curve - conto Live I prodotti presenti su questo sito sono di negoziazione strumenti e non sono destinate a sostituire ricerche individuali o sugli investimenti in licenza. Le performance passate non garantisce risultati futuri. Valute comporta dei rischi notevoli, e c'è sempre il rischio di perdita. Nessuna rappresentazione è stato fatto che questi prodotti garantire profitti o meno risultare in perdite da negoziazione. Qualsiasi spiegazione o dimostrazione del funzionamento dei prodotti non devono essere interpretati come una raccomandazione commercio o la prestazione di consulenza per gli investimenti. L'acquisto o la vendita di una moneta possono essere eseguite solo da un dealer autorizzato. Quanto posso fare usando EA arbitraggio statistico per MT4 Quanto velocemente si può correre. Ci sono un sacco di persone in cerca di fuoco e dimenticare sistemi di trading che possono cadere su un grafico, sedersi e guardare il loro 50 iniziale equità crescere in 10 milioni nel primo anno. Sì. persone veramente credono strumenti del genere esiste e c'è purtroppo non mancano di venditori felici per posizionare i loro prodotti come rispondenti queste fantasie FX AlgoTrader non sono uno di questi fornitori. Gli strumenti Stat Arb EA in questo sito sono strumenti non robot. Essi forniscono una ricca serie di strumenti di arbitraggio, che consente agli operatori di automatizzare la loro strategia di trading arb su qualunque periodo di tempo che preferiscono. Se non hai mai fatto un centesimo FX negoziazione o altre attività le probabilità di fare soldi utilizzando strumenti ARB, purtroppo, non sta in alto. Si suole trasformano un commerciante di perdere in un trader vincente ma potranno automatizzare una strategia ARB e fornire controllo del rischio solida. Quanto si fanno dipenderà da quanto sei bravo come un commerciante. Alcune persone possono correre più velocemente di altri - se avete ottenuto una buona attrezzatura rende il lavoro più facile Avete dati backtest per il n ° strumenti di arbitraggio Purtroppo non la sua possibile backtest EA in MetaTrader 4 che il commercio più coppie. Ho notato la nuova versione del sistema ha la possibilità di variare le dimensioni di posizione per ogni tappa del arb. Come si fa a determinare quale sia la dimensione corretta posizione per ogni gamba dovrebbe essere con micro piccoli conti di trading o mini lotti sua non critici per ottenere un equilibrio gambe. All'aumentare della dimensione Postion questo diventa più significativo. Per esempio eventuali coppie che hanno USD come le major ad esempio, valuta di quotazione, come EURUSD GBPUSD avranno lo stesso valore di pip. Così un lotto standard per EURUSD e GBPUSD avrà entrambi hanno lo stesso valore pip di 10pip. Se le coppie ARB sono costituiti da una croce, come EURJPY valore pip (basato su odierni tassi) sarebbe 12.88pip. Quindi, al fine di rendere l'equilibrio gambe avremmo bisogno di ridurre le dimensioni posizione della gamba EURJPY da 11.2880.78. Quindi, per creare un EURUSDEURJPY equilibrata ARB si avrebbe bisogno di usare 1 lotto per l'EURUSD gamba e 0,78 lotti per la gamba EURJPY. Se si riduce la dimensione del grado di 0.1 lotti (10,000 un mini lotto) le dimensioni di posizione avrebbero bisogno di essere regolato per 0,1 e 0,078. Quindi, a meno che non si ha un account di micro si dovrebbe eseguire due mini lotti per entrambe le gambe. Una volta che si riduce la dimensione grado di micro lotti l'effetto di bilanciamento della arb diventa sempre meno significativo. Il modo più semplice per calcolare il valore pip è quello di utilizzare un calcolatore pip in linea È possibile eseguire la stessa ARB su più tempi Eg EURUSDGBPUSD su H1 e su M15 NO. Dont fare questo I prodotti ARB solo permetterà un caso unico di un particolare arb per l'esecuzione. Se si carica la stessa messa ARB su un altro grafico sarà confondere le variabili interne utilizzate per la gestione commerciale. Il sistema non si comporta logicamente come i due arbs saranno costantemente sovrascrivere le variabili interne che potrebbero creare un comportamento errato del commercio. È possibile eseguire qualsiasi numero di arbitraggi unici sulla piattaforma MT4 utilizzando lo strumento - ma devono essere univoci. ad esempio, una istanza di EURUSDGBPUSD o AUDUSDNZDUSD ecc ecc Per i commercianti ARB avanzate è possibile creare lo stesso ARB su un arco di tempo diverso invertendo la coppia di sequenziamento creando così un ARB inversa. Ad esempio EURUSDGBPUSD su H1 e GBPUSDEURUSD su M15. Tuttavia, l'operatore dovrà controllare la direzione commercio di entrambe le configurazioni ARB utilizzando la tendenza opzioni di bloccaggio. Questo approccio può essere utilizzato per coprire e anche di ridurre prelievo su arbitraggi a più lungo termine, ma questa strategia è complessa a causa della abilità necessaria a chiudere la componente ARB inversa quando lungo termine revsersion media avviene. Qual'è la differenza tra V2 e V3 è V3 per le medie e stat arb lungo termine e V2 è semplicemente a breve termine stat arb V2 e V3 può essere utilizzato su qualsiasi periodo di breve termine o di arbitraggio a lungo termine. V3 è una versione migliorata del V2 in quanto utilizza i registri per l'analisi diffusione che ha molti vantaggi come targetting profitto dinamica e una vasta gamma di parametri di input esterni commerciante definito. V3 è la progressione logica da V2 e contiene molti miglioramenti commerciante richiesto. Ho bisogno di essere in grado di stimare i parametri esternamente al modello o fa il prodotto li do a me Come potrei fare per accertare le correlazioni necessarie Sarebbe questi essere indicatori MT4 voglio solo per ottenere un senso del processo di attuazione del prodotto. Entrambi i prodotti ARB hanno due componenti di un consulente esperto e un indicatore. L'indicatore fornisce il componente di analisi statistica. V2 Arb prodotti calcolare la diffusione delle coppie dividendo uno per l'altro, hanno poi calcolare la media mobile (dello spread) allora trama commerciante definite deviazioni standard entrambi i lati di questa media mobile. Le soglie commercio entrata e di uscita sono determinati dalla multipla STD nell'indicatore (questo può essere regolato dal commerciante) Le soglie d'ingresso commercio (MST) sono stabiliti dal eyeballing la partenza tipica dalla media prima dei innestato diffusione. Ovviamente calendario e di sistema parametri sono di fondamentale importanza. 5 grafici minuti possono mostrare quello che sembra uno spread fisso, ma questo può cambiare molto rapidamente e diventare altamente direzionale. D'altra parte un grafico settimanale offre molto di più comprensione delle dinamiche di diffusione mediumlong termine. Arbing a breve termine è molto difficile e la sua facile farsi prendere quando le coppie disaccoppiano. Questo è spesso visto verso la fine della sessione asiatica e vicino alla aperto Francoforte. Come liquidità sfocia nel spread di mercato può diventare direzionale in brevi tempi. In termini di adeguata selezione della coppia di ARB è possibile utilizzare la FX AlgoTrader indicatore di correlazione in tempo reale per selezionare le coppie di arbitraggio altamente correlate sulle qualsiasi periodo di tempo. Il sistema V3 utilizza un algoritmo di diffusione di registro che permette al trader di vedere il potenziale ritorno in termini di dollari. Ciò consente agli operatori di vedere la potenza del arb più lungo termine rispetto alla negoziazione arb a breve termine. Quali conoscenze ho bisogno di sapere al fine di utilizzare il prodotto Stab Arb Si avrebbe bisogno di sapere di mean reversion, la correlazione, couplingdecouplingdivergence ecc Si avrebbe bisogno di capire che ci sono è alcuna garanzia mean reversion avverrà quando ci si aspetta di . Ho notato che l'impostazione predefinita per l'EA erano 5 lotti e 20 rischio così ho deciso di ridurre questo a solo 0,1 molto e come 5, che può o non può essere una buona idea. Quando ho ricaricato il modello le impostazioni sono tornati indietro per l'impostazione predefinita. E 'possibile ottenere le impostazioni di default di essere molto meno. quindi se per qualche motivo ricarico l'EA e dimenticare le impostazioni si pretende molto soffiare il conto Il modello sarà sempre utilizzare le impostazioni di default, quindi se si voleva cambiare loro e mantenere le modifiche solo creare un nuovo modello chiamato nuove impostazioni Arb o Whetever piace. Poi ogni volta che si apre il nuovo modello le impostazioni modificate verranno utilizzate al posto delle impostazioni predefinite. Che cosa è la dimensione minima considerazione per il trading forex ARB È possibile eseguire arbitraggi su un micro conto 500 che fornisce a mantenere la posizione di dimensionamento al minimo. Non sarebbe saggio per eseguire arbs su un mini acocunt con soli 500 dollari di patrimonio netto. Entrambi i prodotti ARB V2 e V3 possono essere eseguiti su micro, mini e conti MT4 standard. Quali tempi hai trovato ad essere il migliore per il commercio arbs 5m oraria giornaliera dipende da voi e ciò che si vuole raggiungere, se vi piace ARB durante la notte a breve termine basate sul mercato della liquidità sottile asiatico di 5 minuti potrebbe essere un bene per voi. In alternativa, se vi piace fare i soldi decente senza dover dare i lotti mediatore dei costi di diffusione - grafici giornalieri fornirebbero un minor numero di compravendite con profitti molto più grandi per ARBs, che è ritornato alla media. Generalmente più lungo è il periodo di tempo maggiore è il profitto. Un cliente ha fatto 1200 dollari fuori un conto di 5000 dollari in una settimana. Il ragazzo è un commerciante x commerciale in modo da tenere a mente Lo strumento è solo buono come il commerciante in termini di raccolta delle coppie giuste per il commercio e l'impostazione dei parametri giusti. Così, in sintesi, i commercianti ARB avranno bisogno di sperimentare per trovare le migliori impostazioni di sistema che corrispondono alla loro stile di trading, il rischio e le aspettative generali. In generale, è questo EA molto redditizio. Che cosa è il ROI approssimativo in termini di ROI è difficile dire quanto dipende da quale lasso di tempo è il commercio. Il profitto potenziale viene visualizzato dal EA sotto l'etichetta di dati potenziale reversione sul grafico principale. Questo dato è calcolato sulla differenza tra spread e la sua media mobile. Se il bersaglio reversione è impostato per la band di fronte al profitto potenziale sarà aumentata notevolmente, ma il commerciante avrebbe bisogno di un pieno svolgimento da una banda all'altra cioè da 1 a -1 STD o Whetever parametri di trigger il commerciante ha definito. In termini di intervallo di tempo si possono fare molti più soldi sui grafici a lungo termine rispetto a ARB alta frequenza compravendite a breve termine. Noi non produrre dati ROI o curva di equità più come i risultati variano enormemente da operatore a operatore. Gli strumenti riflettono solo la capacità del commerciante per selezionare le attività ottimali, i tempi ei parametri per il commercio. Tutto risale a quanto velocemente si può eseguire :) Il V3 sembra essere la chiusura alcuni mestieri in perdita - come può succedere Ci sono una serie di ragioni per cui questo potrebbe accadere che sono: - I mestieri ARB hanno violato i parametri massimi di rischio e il sistema ha automaticamente chiuso entrambe le posizioni il sistema è in esecuzione in modalità di aggregazione e l'obiettivo di profitto giornaliero è già stato raggiunto - una volta che l'obiettivo di profitto è colpito il sistema chiuderà tutte arbs aperte - questo potrebbe tradursi in arbs perdita rendendo essere chiuso automaticamente per proteggere il vostro obiettivo aggregato raggiunto. Il commerciante ha fissato i punti di ingresso arb troppo vicino al canale di diffusione dei costi e il potenziale di profitto è così piccolo slittamento è ribaltare il PL del arb negativo durante la procedura di stretta arb. Questo può essere facilmente risolto con negoziazione in tempi più lunghi Andor aumentando la STD multipla per spostare la voce di commercio più lontano dal canale di diffusione dei costi. Potete aiutarmi a capire il motivo per cui l'EA non ha chiuso un mestiere, anche se si è già verificato reversione Questo potrebbe accadere a causa dei seguenti motivi: - V3 può solo chiudere ARB mestieri che sono in profitto. Se il arb attuale non è in utile (possibilmente come è stato aperto su un altro periodo di tempo) il sistema non chiude i mestieri ARB. I paramters TradeOffTimeframe non sono abilitati per questo lasso di tempo grafico Il commercio ARB è stato coperto il sistema si disattiva cosa succede La variabile globale Disabilita Gen Starb è stato impostato dal sistema. Premere F3 per visualizzare la tabella GVAR - ci sono alcune ragioni per cui questo può accadere, che sono: - 1) parametro CloseAllTrades è impostata su true. 2) L'obiettivo di profitto giornaliero aggregato è stato raggiunto e ripristino automatico è disabilitata 3) Il conto del patrimonio netto è inferiore al limite minimo Per risolvere questo problema andare alla tabella globale delle variabili in MT4 - premere F3 - In cerca di una variabile globale denominata Disabilita Gen Starb con un valore di 1. Se si elimina la variabile di sistema si riattiverà. Il sistema esegue riequilibrio dinamico Al momento non vi è alcun riequilibrio dinamico. Ho considerato applicando un fattore di scala in sistema per consentire la posizione arbitraria di aumentare se uno spread continuato a disaccoppiare questo è simile a un media down ma la leva ovviamente aumenta con la dimensione della posizione aumentando così il rischio di interrompere se la posizione netta PL raggiunge i parametri massimi di rischio impostati nel sistema. Ci sono diverse scuole di pensiero in materia di ridimensionamento inaveraging verso il basso. Un approccio alternativo è quello di scambiare il lato opposto della ARB su un lasso di tempo inferiore che creerebbe una siepe dinamica (in misura) Ulteriori Commento: Alcuni clienti V3 stanno sperimentando con un approccio alternativo al riequilibrio dinamico nei casi in cui il commercio arb aperto è il disaccoppiamento dalla sua MA e la creazione di un drawdown. Rather di riequilibrare il dimensionamento sacco di ARB esistente un nuovo arb è impostato che è l'esatto opposto del arb corrente. Per esempio se si ha un 5 molto per gamba arb EURUSDGBPUSD che è stato innescato un grafico houly si impostare un ARB GBPUSDEURUSD in esecuzione su un grafico a 15 minuti e utilizzare i parametri LockLong o LockShort per forzare eventuali nuovi mestieri fuori il grafico 15 minuti a l'esatto opposto del arb sul lasso di tempo più lungo. Questo crea una copertura perfetta e permette anche di ridurre il prelievo come ARB breve termine gradualmente mangiare nel prelievo creato da termine disaccoppiato ARB più a lungo. Il principio si basa semplicemente sul trading volatilità degli spread a breve termine visto il lasso di tempo più breve. Questo approccio non è un Get garantito di prigione carta libera, ma può posizioni in cui il disaccoppiamento significativo ha avuto luogo e in tandem ridurre la grandezza di una potenziale perdita sostanzialmente rischio de. Io uso l'indicatore di correlazione FX AlgoTrader e vorrei un sistema per il commercio quando vengono soddisfatte due condizioni. Essi sono: 1) la correlazione giornaliera è superiore a 75 2) la correlazione 5min è inferiore a -75. Queste condizioni sono soddisfatte soltanto un numero limitato di volte al giorno. E 'molto difficile aspettare tutto il giorno davanti al mio PC. La mia domanda per voi è. quale dei tuoi prodotti in grado di identificare divergencedecoupling negativo quando correlazione quotidiana è ancora al di sopra 75 in un giorno In caso affermativo, qual è il prodotto Il motore di arbitraggio V2 o V3 farà questo, se li si imposta di conseguenza. L'indicatore di correlazione è stato progettato per essere utilizzato per gli operatori ARB per aiutare nella loro selezione pair. Quindi, se youre criteri è gt75 correlazione quotidiana e 5 min di correlazione lt-75 è possibile impostare il prodotto ARB sul grafico 5 minuti (probabilmente più facile da usare un oraria in realtà) e quindi impostare sei multipla STD nell'indicatore di STD in modo che il commercio trigger di ingresso erano dove vuoi. Si potrebbe fare questo visivamente e cercare di commerciare solo le più grandi divergenze ciascuna day. Clearaudio ha cominciato a fare le cartucce in movimento-coil nel 1970, e solo più tardi ha ottenuto nel business magnete mobile. Magnete mobile cartucce progettisti devono ora essere consapevoli che la maggior parte di oggi bracci sono di medio-alta massa e che, pertanto, per essere compatibili, le loro MMS deve essere di medio-bassa compliance e di massa superiori a quelli degli anni 1960 e '70. Al 1200, il Maestro V2 è tra i più costosi, se non il più costoso, MM cartucce si possono acquistare oggi. Come tutti, ma uno degli altri quattro modelli della linea V2, è dotato di un corpo di risonanza ottimizzata di ebano. Clearaudios specifications for the Maestro V2 are: weight of 8.4gm, output voltage of 3.6mV, channel separation greater than 30dB, channel balance less than or equal to 0.2dB, and coil impedance of 660 ohms (the last three all at 1kHz). That coil impedance of 660 ohms is way higher than the typical MC impedance of 41508 ohms, the reason for which should by now be obvious: many more coil turns are required to achieve the higher output, with no mechanical price to pay151the coils are fixed. The Maestro V2s coil inductivity is rated at 429 millihenrys compared to the MC range of 5EcircH1505mH. The nominal loading resistance is the standard 47k ohms (though its often argued, correctly, that the nominal accepted resistive load is a standard based more on convenience than on the mathematical necessity dictated by the other numbers that are part of the circuit). Once youve calculated the actual loading for your MM cartridge, you can go into your MM preamp and, if possible, substitute the correct loading resistors for the ones supplied. Most MM owners stick with 47k ohms, though because the resistive load is what damps the systems resonant frequency, its critical. The Clearaudios loading capacitance is specified as 100 picofarads. While loading capacitance is not critical with MCs, it is critical for MMs because the high inductance can lower the systems resonant frequency to well within the audioband. But the relationship between inductance, capacitance, bandwidth, and resonant frequency is complex. (See this page of the Graham Slee website .) Because the specified capacitance includes the capacitive contribution of the tonearm cable, its a good idea to know what it is, if possible, before setting the phono preamps capacitive loading. The capacitance of most tonearm wires plus interconnect is at least 100pF (the longer the cable, the higher the capacitance) so, on average, to achieve a total loading of 100pF, the phono preamps DIP switches should be set not to 100pF but to 0pF. The Maestro V2 features a Micro HD stylus attached to a boron cantilever151a combination found only in Clearaudios most expensive MC cartridges, including the Goldfinger Statement (15,000). The lesser MMs in the V2 line151the Performer V2 (400), the Artist V2 (600), and the Virtuoso V2 (900)151have aluminum cantilevers and elliptical styli. The advantage of boron over aluminum is that boron is both far more stiff and lighter. The advantages of a Micro HD over an elliptical stylus are twofold: lower mass and improved traceability. Traceability is a styluss ability to get into the grooves tightest crevices, nooks, and crannies. ( Trackability is its ability to remain in the groove and maintain effective contact with it.) The rounder the styluss cross section, the less well it can find its way into the grooves tighter corners. The more severe ( ie . narrow and tall) the profile, the greater its ability to get all the way into those crevices to deliver all of the detail the recording contains, especially the clean reproduction of high-frequency transients. A severe stylus profile has another advantage. Think of a sinewave viewed from the side (a hill), negotiated by a round stylus (a disc). The disc moves to the top of the hill on its leading circumferential edge, but instead of immediately starting back down the hill, theres a pause as the front of the disc, which has just negotiated the uphill climb, hands the job off to the discs rear edge for the ride down the hills other side. The larger the circles diameter, the longer it takes for the circles trailing edge to begin the downward journey. The pauses of the handoffs at each crest of the groove, in both the vertical and horizontal dimensions, produce audible timing errors. Now imagine squeezing the circular disc into an ellipse, to narrow the distance between the styluss leading and trailing edges. The advantages of a stylus of such shape, which has a narrower contact patch than a spherical stylus, should be obvious. Now imagine a stylus with a severe profile that results in an even smaller contact patch. A stylus of this shape can reach deeply into crevices of the groove while producing an almost instantaneous handoff at the crest of each hill. The physical differences and distances may be microscopic, but the sonic consequences are enormous. However, to get the full benefits of a severe stylus profile, you must take greater care in setting the overhang, zenith angle (groove tangency), and, especially, the stylus rake angle (SRA). If the styluss vertical ridge inaccurately traces the grooves vertical modulations by banging against them instead of sliding smoothly up and down them, it will produce large amounts of audible intermodulation distortion (IM). Therefore, while severe stylus profiles151 eg . the Micro HD, Geiger, Replicant, and Shibata151have obvious advantages, unless all of these parameters are properly set, the disadvantages can outweigh the advantages151whether in an MC or an MM. Other ways in which the Maestro V2 resembles an MC cartridge: Its stylus cant be replaced by the owner, and it tracks at a relatively heavy 1.81502.6gm (2.2gm optimal). And like Clearaudios MCs, the Maestro V2 unprotected cantilever protrudes from the front of its ebony body, with zero margin of error for an errant finger swipe. I hear you loud and clear: Why should I buy a 1200 Maestro V2 moving-magnet cartridge when I can buy a 1200 moving - coil with many of the same advantages and disadvantages Well, if you have an MM phono stage that you really love, youre ready to go151instead of having to replace it or add a costly step-up transformer or head amp. Moving to a costly MC cartridge by adding a budget-priced step-up transformer or head amp usually produces a sideways move in sound quality. If the Maestro V2s sonic characteristics are MC-like, you can both step up the quality and save yourself some money. MC Sound from an MM I ran the Maestro V2 through the MM input of the Ypsilon VPS-100 phono preamplifier (26,000). But to keep things in the real world, I did most of my listening through the Graham Slee Era Gold Mk. V phono preamplifier (999). The Maestro V2 didnt have the speed or high-frequency extension of a good moving-coil, but it had other equally attractive151some might say more attractive151qualities, and in some ways its sound did resemble that of an MC. If you like a combination of midband richness, openness, and detail, the Maestro V2 delivered. In a single listening session, I sat through all six LPs of Oscar Petersons Exclusively for My Friends (MPS 0209478MSW) and suffered neither fatigue nor boredom as the Maestro V2 reproduced the pianos rich, woody tonality without exaggerating or greatly softening transients. Yes, some far more expensive MCs can enhance transients and better capture the woody sustain, as well as give you longer decays and thus a greater sense of space. But this set was recorded in Hans Georg Brunner-Schwers private studio151his living room, I think. There isnt much space to lose. Not as well resolved was the cymbal shimmer produced by Petersons various drummers (Louis Hayes, Ed Thigpen, Bobby Durham), which sounded somewhat closed-in compared to the far more expensive and expansive MCs I compared the Maestro V2 to151but initial transients were fast and clean, more like an MC than an MM. The Maestro V2s ability to reproduce fast transients sets it apart from most, if not all, MM cartridges Ive heard. I then played a superb reissue, on 200gm vinyl, of a 1978 recording of Mahlers Symphony 3 by Zubin Mehta and the Los Angeles Philharmonic, recorded in UCLAs Royce Hall by James Lock and Simon Eadon, and mastered from the original master tape by Willem Makkee (2 LPs, Analogue Productions LAP0117). It made a good case for why all audiophiles might consider adding a great MM cartridge to their arsenals, if swapping out is practical. The tonal balance was more middle-to-rear-of-hall, but the richness and fullness of the brass and strings were to die for: well burnished, and the Maestros ability to reproduce orchestral weight surpassed that of many MCs of any price. The horns and violins induced chills the piccolo, clarinet, and tambourine were somewhat less impressive, but overall, the Maestro V2s speed far surpassed my expectations of MM cartridges, and made up for the loss of top-end air and extension. Measured with a digital oscilloscope, the Maestro V2s channel separation of 27dB, L150R, and 28.5dB, R150L, were close to the specified 30dB it produced a wide stage. Like Shures V-15xMR, the Maestro V2 tracked and traced well everything I threw at it151but the Clearaudio had greater weight, depth and. majesty. The Maestro V2 reproduced male voices particularly well: Its overall warmth was accompanied by the speed necessary to prevent its sound from deteriorating into baritone mud. Even Capitols great series of recordings by guitarist Laurindo Almeida fared well151with these LPs, MCs usually have it all over MMs. Yes, Almeidas pluckings of his instruments strings sound faster and more precise through MCs, but the Maestro V2 reproduced the body of his guitar well151again, more of a trade-off than an outright stomping. Another great MM cartridge is Ortofons 2M Black (755), but the Maestro beat it in terms of dynamics and, especially, weight and slam151as well it should, for 445 more. However, neither MM can match the dynamic majesty of the great151and far more expensive151MCs. Summing Up In the months I spent listening to Clearaudios Maestro V2, I never felt I was missing anything. Instead, I was given an entirely different perspective on some very familiar recordings. Can a greater compliment be paid a 1200 moving-magnet cartridge Submitted by Venere 2 on May 22, 2015 - 2:03am Michael, thanks for the well written and thought out review (as usual). I do wonder if you ever feel that reviewing a 1200 cartridge in 2015 is a service Its not the dollar amount in itself that is pejorative but rather the amount compared to alternatives in the non analog realm. For the longest time I defended turntables as the best sounding front end. For the longest time, I spent my money on an analog front end, and the vinyl LPs to play on it. As recently as a few months ago, I still did. Then after much denial and lost time, I admitted to myself that digital was no longer the awful sounding crap it once was. I did not want to believe it. I certainly did not want to make the change, much less embrace it but I did. I traded my turntable for a high quality DAC. I couldnt be happier When I see people getting into vinyl buying a turntable and start building a vinyl record collection now in 2015, I feel bad for them. They remind me of the people who invest in a stock when everyone is talking about it Those people buy the stock at the wrong time (too late), and lose. Now music is so much more than dollars and cents, and the enjoyment of music has no price. But, for the guy buying a 5000 turntable NOW and building up a multi thousand dollar vinyl collection, that he will sell for pennies on the dollar in 2-3 years, I feel its a disservice to push analog right now. Mark this post if you wish, and gloat in 2 years if I am wrong. But, I have seen these kinds of trends and waves before. The vinyl bubble will burst, sooner than later. I dont wish it. But it will happen. Turntables improve, but at a slow rate. Digital improves much faster, and it keeps getting faster. Submitted by Gorm on May 27, 2015 - 4:25pm Venere: please dont feel sorry for me. I never sold my treasured albums (had a lot of duds too thought) and I own an expensive EMM Labs XDs1 for SACD and HiDef downloads. I still buy good albums and I also pay for good downloads. They can all be great, or not - depending mostly on the Musicians and engineers. The sad thing is that on HD Tracks downloads I get no information, and therefore all the players, engineers and those responsible for the final product are ignored. I can say (having invested equally in both formats) that everything being equal - the analogue gives more pleasure. But I am happy for both. So dont patronize me please and save the tears for those whose entire collection on digital could suddenly disappear one day. Submitted by geekonstereo on July 4, 2015 - 12:03pm Hello, In a comparison of various cartridges on Analog Planet, you wrote: . after youve become used to hearing this track on the other cartridges hearing it for the first time via the 2M Black is startling. Youll hear heretofore buried parts and see the singers with an ease most of the other cartridges cant come close to reproducing. Plus the Blacks rhythmic drive takes the track to another level of sonic and musical intensity. But the Blacks most salient quality is its utter transparency. It sounds less like a recording and more like live. I agreed with this after listening to the various test files on that comparison. My question is whether you think the Clearaudio Maestro beats the Black in terms of making the listener see performers and give a sense of hearing music live with better rhythmic drive. As such, would the Maestro also startle listeners I realise that its difficult to make a comparison because the set-ups may have been very different, but I wanted your opinion And while we are at it, your take on the Black or Meastro versus the Dynavector 10x5 I am planning to buy a VPI Traveler and am hunting for a suitable MM or high-output MC cartridge for it. Thank you. Several of the temperature diagrams on this site begin in the year 1979, where the fine satellite record begins. This is chosen as a general start date to make comparison between different data sources (satellite, surface, etc.) easy. On the other hand, this approach may conceal the fact that Earths climate record is much longer. It is the purpose of the present short paragraph to introduce modern climate change to this longer time perspective. Fig. 1. Geological stratigraphic chart for the entire geological history of planet Earth. Modern time is indicated by the thin red line at the top of the left column. Please note that the time scale is highly compressed, and increasing so towards higher ages. The left hand column fits on top of the next column to the right, column no 2 on top of no 3, and the right hand column should be at the bottom. Planet Earth has an age of about 4600 million years. The diagram above (Subcommission for Stratigraphic Information ) shows a geological stratigraphic chart for the entire geological history, subdivided into a vast number of epochs, each consisting of a number of stages. Most (if not all) of these geological divisions are based on the recognition of environmental changes affecting the entire planet that is, past global climate changes. In other words, global climate change has been the rule for the entire history of Earth, not the exception. If each year in the time scale above (Fig.1) was represented by one millimetre, the entire stratigraphic chart would be about 4600 km (2858 miles) long. In Europe, this corresponds roughly to the distance between Madrid (Spain) to Sverdlovsk in the Ural Mountains (Russia). In North America 4600 km roughly corresponds to the distance between San Francisco (USA) and Quebec (Canada). On this scale modern humans would appear within the last 200 m, the Polar Bear within the last 150 m, and the entire global meteorological record since about 1850 would take up the last 16 cm. The period with satellite observations would fit into the final 3 cm. From time to time the planet has been affected by millions of years with relatively cold climate, each such period leading to a long succession of glacial and interglacial periods. During the last couple of millions of years, planet Earth has been in such a cold stage. The last (until now) ice age ended around 11,600 years ago, and we are for the time living in a so-called interglacial period, until the next ice age will begin some time into the future. The last four glacial periods and interglacial periods are shown in the diagram below (Fig.2), covering the last 420,000 years in Earths climatic history. Fig.2. Reconstructed global temperature over the past 420,000 years based on the Vostok ice core from the Antarctica (Petit et al. 2001 ). The record spans over four glacial periods and five interglacials, including the present. The horizontal line indicates the modern temperature. The red square to the right indicates the time interval shown in greater detail in the following figure . The diagram above (Fig.2) shows a reconstruction of global temperature based on ice core analysis from the Antarctica. The present interglacial period (the Holocene) is seen to the right (red square). The preceding four interglacials are seen at about 125,000, 280,000, 325,000 and 415,000 years before now, with much longer glacial periods in between. All four previous interglacials are seen to be warmer (1-3 o C) than the present. The typical length of a glacial period is about 100,000 years, while an interglacial period typical lasts for about 10-15,000 years. The present interglacial period has now lasted about 11,600 years. According to ice core analysis, the atmospheric CO 2 concentrations during all four prior interglacials never rose above approximately 290 ppm whereas the atmospheric CO 2 concentration today stands at nearly 390 ppm. The present interglacial is about 2 o C colder than the previous interglacial, even though the atmospheric CO 2 concentration now is about 100 ppm higher. The last 11,000 years (red square in diagram above) of this climatic development is shown in greater detail in the diagram below (Fig.3), representing the main part of the present interglacial period. Fig.3. The upper panel shows the air temperature at the summit of the Greenland Ice Sheet, reconstructed by Alley (2000) from GISP2 ice core data. The time scale shows years before modern time. The rapid temperature rise to the left indicate the final part of the even more pronounced temperature increase following the last ice age. The temperature scale at the right hand side of the upper panel suggests a very approximate comparison with the global average temperature (see comment below). The GISP2 record ends around 1854, and the two graphs therefore ends here. There has since been an temperature increase to about the same level as during the Medieval Warm Period and to about 395 ppm for CO 2 . The small reddish bar in the lower right indicate the extension of the longest global temperature record (since 1850), based on meteorological observations (HadCRUT3 ). The lower panel shows the past atmospheric CO 2 content, as found from the EPICA Dome C Ice Core in the Antarctic (Monnin et al. 2004 ). The Dome C atmospheric CO 2 record ends in the year 1777. The diagram above (Fig.3) shows the major part of the present interglacial period, the Holocene, as seen from the summit of the Greenland Ice cap. The approximate positions of some warm historical periods are shown by the green bars, with intervening cold periods. Clearly Central Greenland temperature changes are not identical to global temperature changes. However, they do tend to reflect global temperature changes with a decadal-scale delay (Box et al. 2009 ), with the notable exception of the Antarctic region and adjoining parts of the Southern Hemisphere, which is more or less in opposite phase (Chylek et al. 2010 ) for variations shorter than ice-age cycles (Alley 2003 ). This is the background for the very approximate global temperature scale at the right hand side of the upper panel. Please also note that the temperature record ends in 1854 AD, and for that reason is not showing the post Little Ice Age temperature increase. In the younger part of the GISP2 temperature reconstruction the time resolution is around 10 years. Any comparison with measured temperatures should therefore be made done using averages over periods of similar lengths. During especially the last 4000 years the Greenland record is dominated by a trend towards gradually lower temperatures, presumably indicating the early stages of the coming ice age (Fig.3). In addition to this overall temperature decline, the development has also been characterised by a number of temperature peaks, with about 950-1000 year intervals. It may even be speculated if the present warm period fits into this overall scheme of natural variations The past temperature changes show little (if any) relation to the past atmospheric CO 2 content as shown in the lower panel of figure 3. Initially, until around 7000 yr before now, temperatures generally increase, even though the amount of atmospheric CO 2 decreases. For the last 7000 years the temperature generally has been decreasing, even though the CO 2 record now display an increasing trend. Neither is any of the marked 950-1000 year periodic temperature peaks associated with a corresponding CO 2 increase. The general concentration of CO 2 is low, wherefore the theoretical temperature response to changes in CO 2 should be more pronounced than at higher concentrations, as the CO 2 forcing on temperature is decreasing logarithmic with concentration. Nevertheless, no net effect of CO 2 on temperature can be identified from the above diagram, and it is therefore obvious that significant climatic changes can occur without being controlled by atmospheric CO 2 . Other phenomena than atmospheric CO 2 must have had the main control on global temperature for the last 11,000 years. The following diagram shows the period since 1850 (indicated by the reddish bar in the diagram above), where it is possible to estimate global temperature changes from meteorological observations (Fig.4). Fig.4. Global monthly average surface air temperature since 1850 according to Hadley CRUT, a cooperative effort between the Hadley Centre for Climate Prediction and Research and the University of East Anglia s Climatic Research Unit (CRU ), UK. The blue line represents the monthly values. An introduction to the dataset has been published by Brohan et al. (2005). B ase period: 1961-1990. Last month shown: December 2010. Last diagram update: 3 January 2011. Click here to download the entire series of estimated HadCRUT3 global monthly surface air temperatures since 1850. Click here to read a description of the data file format. From figure 3 it is obvious that the global meteorological record (Fig.4) begins in the final part of the Little Ice Age, and thereby documents the following temperature increase, especially clear since about 1915. In other words, the temperature increase documented by meteorological records represents the temperature recovery following the cold Little Ice Age. The ongoing climate debate is essentially about this being mainly a natural temperature recovery, or caused by atmospheric CO 2 . especially for the time after 1975 It can, however, from figures 2, 3 and 4 be concluded that the temperature increase 1975-2000 is not unique when compared with past records, and that the net effect on temperature by atmospheric CO 2 has been small or even absent (Fig.3). From all diagrams shown above the still very short time period covered by the fine satellite observations is obvious. The period since 1979 only covers the most recent example of global warming (ca.1977-2001), but no examples of the many previous periods of warming or cooling. This should prudently be borne in mind when interpreting the temperature record since 1979 only, such as shown in several of the diagrams found on this website. As mentioned above the time since 1979 would only take up the final 3 cm of the entire 4600 km long geological climatic record, if each year is represented by one millimetre. Click here to jump back to the list of contents. Click here to view the recent (daily) global satellite temperature (AMSU-A) at various altitudes in the atmosphere. Indicate which level in the atmosphere you want to see Indicate your preference as to o C or o F Then click Draw graph You will need to have a recent version of JAVA TM installed on your computer to make use of this facility kindly made available by Dr. Roy Spencer and Dr. Danny Braswell. If you receive an error message after clicking Draw graph, try downloading the latest version (free) of Java from java. Click here to jump back to the list of contents. Land surface temperature 16 February 2017 (degrees K degrees C 273.15), at 02 and 14 hr (UTM-time), respectively. White areas are oceans or land areas without data. Map source: NOAA. Please use this and this link if you want to see the original diagrams (NOAA 18 ) or want to check for more recent updates than shown above. Click here to see the recent sea surface temperatures. Click here to jump back to the list of contents. Recent global air temperature change, an overview All temperature diagrams shown below have 1979 as starting year. This roughly marks the beginning of the recent period of global warming, after termination of the previous period of global cooling from about 1940. In addition, the year 1979 also represents the starting date for the satellite-based global temperature estimates (UAH and RSS). For the three surface air temperature estimates shown (HadCRUT, NCDC and GISS) the reference period differs. HadCRUT refers to the official normal WMO period 1961-1990, while NCDC and GISS as reference instead uses 1901-2000 and 1951-1980, respectively, which results in higher positive temperature anomalies. For all three surface air temperature records, but especially NCDC and GISS, administrative changes to anomaly values are quite often introduced, even for observations several years back in time. Some changes may be due to the delayed addition of new station data, while others probably have their origin in a change of technique to calculate average values. It is clearly impossible to evaluate the validity of such administrative changes for the outside user of these records. In addition, the three surface records represent a blend of sea surface data collected moving ships or by other means, plus data from land stations of partly unknown quality and unknown degree of representativeness for their region. Many of the land stations have also moved geographically during their existence, and their instrumentation changed. The satellite temperature records also have their problems, but these are generally of a more technical nature and therefore correctable. In addition, the temperature sampling by satellites is more regular and complete on a global basis than that represented by the surface records. It therefore is realistic to recognise that the temperature records are not of equal scientific quality. At the same time the big efforts being put into all five temperature databases should be gratefully acknowledged by all interested in climate science. On this background, the present website has decided to operate with three quality classes (1-3) for global temperature records, with 1 representing the highest quality level: The main reasons for discriminating between the three surface records are the following: 1) While both NCDC and GISS often experience quite large administrative changes. and therefore essentially must be considered unstable records, the changes introduced to HadCRUT are fewer and smaller. For obvious reasons, as the past do not change, an unstable record cannot be correct all the time. 2) A comparison with the superior Argo float sea surface temperature record shows that while HadCRUT uses a sea surface record (HadSST3) nicely in concert with the Argo record. a comparison between Argo and NCDC and GISS data shows a marked discrepancy. The differences between the individual diagrams shown below demonstrate the difficulties associated with calculating a correct average global temperature. Essex et al. (2006) have an interesting discussion of the whole concept of calculating an average global temperature. In addition, global surface air temperatures should only be considered a poor indicator of global climate heat changes, as air has relatively little mass associated with it. Ocean heat changes remain the dominant factor for global heat changes. Global air temperatures, however, continues to attract widespread interest, and many scientist assume that the air temperature at least may be considered a useful proxy for the present state of the global climate system. In the temperature diagrams below, the thick line represents the running 37 month average and the thin line the monthly temperature. Both values are the result of a number of mathematical manipulations with the original temperature data, and especially so the running average. In the text below each diagram you will find a link enabling you to download and analyze the data yourself. All diagrams below are using the same temperature scale, to enable easy visual comparison. Click here to jump back to the list of contents. Global monthly average lower troposphere temperature since 1979 according to University of Alabama at Huntsville (UAH), USA. This graph uses data obtained by the National Oceanographic and Atmospheric Administration (NOAA) TIROS-N satellite, interpreted by Dr. Roy Spencer and Dr. John Christy. both at Global Hydrology and Climate Center, University of Alabama at Huntsville, USA. The thick line is the simple running 37 month average, nearly corresponding to a running 3 yr average. The cooling and warming periods directly influenced by the 1991 Mt. Pinatubo volcanic eruption and the 1998 El Nio, respectively, are clearly visible. Reference period 1981-2010. Last month shown: January 2017. Last diagram update: 9 February 2017. Click here to see the latest UAH MSU global monthly lower troposphere temperature anomaly with comments. Click here to download the series of UAH MSU global monthly lower troposphere temperature anomalies since December 1978. Click here to see a maturity diagram for the MSU UAH data series. Click here to read about the latest version (6.0) of the UAH Temperature Dataset (April 28, 2015). Global monthly average lower troposphere temperature since 1979 according to Remote Sensing Systems (RSS). This graph uses data obtained by the National Oceanographic and Atmospheric Administration (NOAA) TIROS-N satellite, and interpreted by Dr. Carl Mears (RSS). The thick line is the simple running 37 month average, nearly corresponding to a running 3 yr average. The cooling and warming periods directly influenced by the 1991 Mt. Pinatubo volcanic eruption and the 1998 El Nio, respectively, are clearly visible. Click here for a description of RSS MSU data products. Please note that RSS January 2011 changed from Version 3.2 to Version 3.3 of their MSUAMSU lower tropospheric (TLT) temperature product. Click here to read a description of the change from version 3.2 to 3.3, and previous changes. Last month shown: January 2017. Last diagram update: 3 February 2017. Click here to download the series of RSS MSU global monthly lower troposphere temperature anomalies since January 1979. Click here to see a maturity diagram for the MSU RSS data series. Click here to read a description of the MSU products. Click here to jump back to the list of contents. Global monthly average surface air temperature since 1979 according to Hadley CRUT, a cooperative effort between the Hadley Centre for Climate Prediction and Research and the University of East Anglia s Climatic Research Unit (CRU ), UK. The thin line represents the monthly values, while the thick line is the simple running 37 month average, nearly corresponding to a running 3 yr average. An introduction to the dataset has been published by Brohan et al. (2005). Lower down the present page you will find a graph showing the entire series since 1850. Base period: 1961-1990. Last month shown: December 2016. Last diagram update: 21 January 2017. Click here to download the series of estimated HadCRUT4 global monthly surface air temperature anomalies since 1850. Click here or here to download the series of estimated HadCRUT3 global monthly surface air temperature anomalies since 1850. Click here to read a description of the data file format. Click here to see a maturity diagram for the HadCRUT data series. Click here to open a web interface to all the weather station data used by the Hadley Centre, a very useful facility developed by Clive Best, also known for his blog . Please note that the stations are split into 3 groups. 1) those going back to before 1860 2) Those going back to between 1860 and 1930 3) Those with data going back later than 1930. The last option is all stations together - but is very slow to load (gt5000 stations). Drag a rectangle to zoom in. Click on a station to see the graph of temperatures and anomalies. October 2, 2014: Please note that HadCRUT4 was released in a new version (HadCRUT.4.3.0.0). The main changes introduced by this new version is a decrease of temperatures 1850-1875 and an increase affecting observations since 2005. For further details of this version change click here. Click here to jump back to the list of contents. Global monthly average surface air temperature since 1979 according to the National Climatic Data Center (NCDC), USA. This time series is calculated using land surface data from the Global Historical Climatology Network (Version 2) and sea surface temperature anomalies from the United Kingdom MOHSST data set and the NCEP Optimum Interpolated SSTs (Version3 note version change on May 2, 2011). The thick line is the simple running 37 month average, nearly corresponding to a running 3 yr average. Base period: 1880-2016. Last month shown: January 2017. Last diagram update: 17 February 2017. Click here to download the series of the NCDC global monthly surface air temperature anomalies since 1880. Click here to see a maturity diagram for the NCDC data series. June 18, 2015: NCDC has introduced a number of rather large administrative changes to their sea surface temperature record. The overall result is to produce a record giving the impression of a continuous temperature increase, also in the 21st century. As the oceans cover about 71 of the entire surface of planet Earth, the effect of this administrative change is clearly seen in the NCDC record for global surface air temperature above. May 2, 2011: NCDC transitioned to GHCN-M version 3 as the official land component of its global temperature monitoring efforts. GHCN-M version 2 mean temperature dataset will continue to be updated through May 30, 2011, but no support for this version of the dataset will be provided. The global anomalies using GHCN-M version 2 can be accessed here: GHCN-M v2. The net effect of the change from version 2 to 3 can be seen here. Global monthly average surface air temperature since 1979 according to the Goddard Institute for Space Studies (GISS), at Columbia University, New York City, USA. GISS is a laboratory of the Earth-Sun Exploration Division of NASAs Goddard Space Flight Center and a unit of the Columbia University Earth Institute. The thick line is the simple running 37 month average, nearly corresponding to a running 3 yr average. Discussions of reasons why the GISS temperature estimate differs from other estimates can be read by clicking here. here and here. Base period: 1951-1980. Last month shown: January 2017. Last diagram update: 16 February 2017 . Click here to download the series of the GISS global monthly surface air temperature anomalies since 1880. Click here to see a maturity diagram for the GISS data series. Click here to download pre-version 3 (v.2) individual GISS station data. Click here to jump back to the list of contents. It is interesting to compare the various global air temperature estimates as to their internal degree of stability for the whole temperature record as such. Especially for surface air temperature estimates, a certain degree of change over time affecting especially the last few months is to be expected, as additional station data may be reported and incorporated in the database. But for the older part of the temperature record numerical stability over time would be expected, provided that the mathematical procedure used for estimating the global temperature is considered mature by the research team preparing the data series considered. In this context, maturity would imply that, for example, the November 1985 temperature reported by a certain database in February 2009 would be identical to the November 1985 value reported previously by the same database. Below a series of diagrams is shown to illustrate the degree of maturity, calculated for various databases by plotting the net change in their global temperature record since May 2008 (or February 2009). May 2008 (or February 2008) has been chosen as start date for this test as this represents the oldest version of the individual temperature records available to the webmaster. All diagrams below are using the same temperature scale, to enable easy visual comparison. A fine study of temporal instability can be inspected here (in Norwegian). Maturity diagram showing net change since 8 May 2008 in the global monthly lower troposphere temperature record prepared by the University of Alabama at Huntsville, USA. This temperature estimate extends back to December 1978. Click here to see a graph showing the most recent version of the UAH MSU global temperature estimate. Click here to download the entire series of UAH MSU global monthly lower troposphere temperatures since December 1978. Click here for explanation of temporal stability. Last diagram update: 9 February 2017. Click here to download the most recent version of UAH MSU global monthly lower troposphere temperature anomalies since December 1978. Click here to read about UAH version 6.0 change April 2012. Maturity diagram showing net change since 8 May 2008 in the global monthly lower troposphere temperature record prepared by the Remote Sensing Systems (RSS). This temperature estimate extends back to January 1979. Click here to see a graph showing the most recent version of the RSS MSU global temperature estimate. Please note that RSS January 2011 changed from Version 3.2 to Version 3.3 of their MSUAMSU lower tropospheric (TLT) temperature product. Click here to read a description of the change from version 3.2 to 3.3, and previous changes. Click here to download the entire series of RSS MSU global monthly lower troposphere temperatures since January 1979. Click here for explanation of temporal stability. Last diagram update: 3 February 2017. Click here to download the most recent version of RSS MSU global monthly lower troposphere temperature anomalies since January 1979. Click here to download the May 2008 version of RSS MSU global monthly lower troposphere temperature anomalies since January 1979. Maturity diagram showing net change since 25 February 2008 in the global monthly surface air temperature record prepared by the Hadley Centre for Climate Prediction and Research and the University of East Anglia s Climatic Research Unit (CRU ), UK. This temperature estimate extends back to January 1850. Click here to see a graph showing the most recent version of the HadCRUT3 and 4 global temperature estimate. Previous to the version change 3 to 4 (October 2012), the HadCRUT temperature record showed a high degree of temporal stability. The diagram below shows a comparison between the two versions of HadCRUT (stand October 2012). Another version change was made on October 2, 2014. Click here for an explanation of temporal stability. Last diagram update: 21 January 2017 . Click here to download the series of estimated HadCRUT4 global monthly surface air temperature anomalies since 1850. Click here or here to download the series of estimated HadCRUT3 global monthly surface air temperature anomalies since 1850. Click here to download the February 2008 version of estimated HadCRUT3 global monthly surface air temperature anomalies since 1850. It is interesting to note that the overall net adjustment shown by the HadCRUT surface temperature record since February 2008 (see figure above ) is that of more or less equal warming for the entire record since 1850. This is in contrast to the net adjustment of the two other surface records, NCDC and GISS. which both display a net cooling adjustment before 1950-60, and a net warming adjustment for the more recent part of the record, resulting in an overall increasing temperature increase since 1880. Diagram showing the global 37 month running average for HadCRUT3 (blue) and HadCRUT4 (red), and the difference between these averages (lower panel use scale to the right). One of the most important effects of the version change is a reduction of the post 1940 cooling. Last diagram update: 10 May 2013. Click here or here to download the series of estimated HadCRUT3 global monthly surface air temperature anomalies since 1850. Click here to download the series of estimated HadCRUT4 global monthly surface air temperature anomalies since 1850. Maturity diagram showing net change since 17 May 2008 in the global monthly surface air temperature record prepared by the National Climatic Data Center (NCDC), USA. The net result of the adjustments made are becoming substantial, and adjustments since May 2006 occasionally exceeds 0.1 o C. Before 1945 global temperatures are generally changed toward lower values, and toward higher values after 1945, resulting in a more pronounced 20th century warming (about 0.15 o C) compared to the NCDC temperature record published in May 2008. Arrows indicate two months where the adjustments over time are illustrated in the figure below. Last diagram update: 17 February 2017. Click here to download the most recent version of the NCDC global monthly surface air temperature anomalies since 1880. Click here to download the May 2008 version of the NCDC global monthly surface air temperature anomalies since 1880. Click here for a summary of the July 2009 (Smith et al. 2008 ) methodological changes in the land-ocean NCDC temperature analyses. Click here for information about the November 2011 version change (GHCN-M version 3.1.0 replaced GHCN-M version 3). Click here and here for information about the September 2012 version change (GHCN-M version 3.2.0 replaced GHCN-M version 3.1.0). Click here for an explanation of temporal stability. The two arrows in the diagram above indicate two months for which the adjustments over time is shown below . On May 2, 2011, NCDC transitioned to GHCN-M version 3 as the official land component of its global temperature monitoring efforts. GHCN-M version 2 mean temperature dataset will continue to be updated through May 30, 2011, but no further support for this version of the dataset will be provided. In November 2011, the GHCN-M version 3.1.0 replaced the GHCN-M version 3. For more information about the GHCN-M version 3.1.0. The overall net effect of the transition from GHCN-M version 2 to version 3 is to increase global temperatures before 1900, to decrease them between 1900 and 1950, and to increase temperatures after 1950. The diagram below exemplify adjustments made by NCDC since May 2008 for two months (see arrows in diagram above ) January 1915 and January 2000. Diagram showing the adjustment made since May 2008 by the National Climatic Data Center (NCDC) in the anomaly values for the two months January 1915 and January 2000. See also this diagram. Last diagram update 17 February 2017 . Maturity diagram showing net change since 17 May 2008 in the global monthly surface air temperature record prepared by the Goddard Institute for Space Studies (GISS), at Columbia University, New York City, USA. This temperature estimate extends back to January 1880. Click here to see a graph showing the most recent version of the GISS global temperature estimate. The net effects of the adjustments made since May 2008 are to generate a more smoothly increasing global temperature since 1880. Discussions on the background for the lack of temporal stability for the GISS temperature record can be read here. here and here. Arrows indicate two months where the adjustments over time are illustrated in the figure below. Last diagram update 16 February 2017 . Click here to download the most recent version of the GISS global monthly surface air temperature anomalies since 1880. Click here to download the May 2008 version of the GISS global monthly surface air temperature anomalies since 1880. Click here to see a fine study of GISS temporal instability (in Norwegian). Diagram showing the adjustment made since May 2008 by the Goddard Institute for Space Studies (GISS) in anomaly values for the months January 1910 and January 2000. See also this diagram. Last diagram update 16 February 2017 . Note added 15 (17) September 2012: Unless there is an error in the GISS temperature anomaly values downloaded on 15 September 2012 (or 15 August 2012), a major change appears to have taken place since 15 August 2012. The GISS maturity diagram below show the status per 15 August 2012, and should be compared with the diagram above from 15 September 2012. Apparently the change may reflect the September 2012 NCDC change from GHCN-M version 3.1.0 to GHCN-M version 3.2.0. Click here and here for more information on this. GISS Maturity diagram per 15 August 2012. Compare with the diagram per 15 September 2012 . Based on the above it is not possible to conclude which of the above five databases represents the best estimate on global temperature variations. The answer to this question remains elusive. All five databases are the result of much painstaking work, and they all represent admirable attempts towards establishing an estimate of recent global temperature changes. At the same time it should however be noted, that a temperature record which keeps on changing the past hardly can qualify as being correct. With this in mind, it is interesting that none of the global temperature records shown above are characterised by high temporal stability. Presumably this illustrates how difficult it is to calculate a meaningful global average temperature. A re-read of Essex et al. 2006 might be worthwhile. In addition to this, surface air temperature remains a poor indicator of global climate heat changes, as air has relatively little mass associated with it. Ocean heat changes are the dominant factor for global heat changes. Click here to jump back to the list of contents. Comparing global air temperature estimates In order to enable a visual comparison of the five different global temperature estimates shown above, the diagrams below show some or all series superimposed. As the base period differs for the different temperature estimates (see above), they are not directly comparable. All data series were therefore normalised by setting the average value of the initial 30 years from January 1979 to December 2008 equal to zero. before inclusion in the diagram below. In addition to the visual analysis below, the reader might also find it useful to inspect the maturity analysis presented above. Superimposed plot of Quality Class 1 global monthly temperature estimates. As the base period differs for the different temperature estimates, they have all been normalised by comparing to the average value of 30 years from January 1979 to December 2008. The heavy black line represents the simple running 37 month (c. 3 year) mean of the average of both temperature records. The numbers shown in the lower right corner represent the temperature anomaly relative to the above average. Values are rounded off to the nearest two decimals, even though some of the original data series come with more than two decimals. Last month shown: January 2017. Last diagram update: 15 February 2017. Superimposed plot of Quality Class 1 and Quality Class 2 global monthly temperature estimates. As the base period differs for the different temperature estimates, they have all been normalised by comparing to the average value of 30 years from January 1979 to December 2008. The heavy black line represents the simple running 37 month (c. 3 year) mean of the average of all three temperature records. The numbers shown in the lower right corner represent the temperature anomaly relative to the above average. Values are rounded off to the nearest two decimals, even though some of the original data series come with more than two decimals. Last month shown: December 2016. Last diagram update: 21 January 2017. Superimposed plot of Quality Class 1 and Quality Class 2 and Quality Class 3 global monthly temperature estimates. As the base period differs for the different temperature estimates, they have all been normalised by comparing to the average value of 30 years from January 1979 to December 2008. The heavy black line represents the simple running 37 month (c. 3 year) mean of the average of all five temperature records. The numbers shown in the lower right corner represent the temperature anomaly relative to the above average. Values are rounded off to the nearest two decimals, even though some of the original data series come with more than two decimals. Last month shown: December 2016. Last diagram update: 21 January 2017. It should be kept in mind that satellite - and surface-based temperature estimates are derived from different types of measurements, and that comparing them directly as done in the diagram above therefore in principle is problematical. For that reason, in the analysis below these two different types of global temperature estimates are compared to each other. However, as both types of estimate often are discussed together, the above diagram may nevertheless be of interest. In fact, the different types of temperature estimates appear to agree quite well as to the overall temperature variations on a 2-3 year scale, although on a short term scale there may be considerable differences. However, as shown in the paragraph below. surface temperature records seems to be drifting towards higher temperature anomalies than the satellite records. Diagram showing the average global temperature change (anomaly) during the satellite observational period (since January 1979), according to five global temperature estimates shown above. The upper panel show the average anomalies for the last 12 months, the mid panel show the average anomalies for the last 5 years, while the lower panel show the average anomalies for the last 10 years. As the base period differs for the different temperature estimates, they have all been normalised by comparing to the average value of 30 years from January 1979 to December 2008. Last month included in analysis: December 2016. Last diagram update: 21 January 2017. Usually modern surface air temperatures are compared to the so-called normal temperature, representing the so-called normal climate. This normal temperature is calculated as the average for values recorded during a 30-year period. The period 1961-1990 is the official World Meteorological Organisation (WMO) normal period. and is therefore often the time period referred to. Another 30-year period used as reference for comparisons is 1951-1980. This is partly because the total number of meteorological stations during this period reached a maximum, and since has undergone a marked reduction in number. Unfortunately, both these periods are dominated by the cold period 1945-1980, and almost any comparison with such a low average value will therefore appear as high or warm. This makes it difficult to decide if surface air temperatures at present are increasing or decreasing The only thing that will be clear is that modern temperatures are higher than back in this cold period. Click here to see a diagram showing the entire global temperature series (HadCRUT4) since 1850 with the 1945-1980 cold period and the WMO normal period indicated on the time line. Click here to jump back to the list of contents. Plot showing the average of monthly global surface air temperature estimates (HadCRUT4. GISS and NCDC ) and satellite-based temperature estimates (RSS MSU and UAH MSU ). The thin lines indicate the monthly value, while the thick lines represent the simple running 37 month average, nearly corresponding to a running 3 yr average. The lower panel shows the monthly difference between surface air temperature and satelitte temperatures. A s the base period differs for the different temperature estimates, they have all been normalised by comparing to the average value of 30 years from January 1979 to December 2008. Last month shown: December 2016. Last diagram update: 21 January 2017. As is shown by the diagram above, the average of surface based temperature estimates is not identical to that obtained by satellites. In general, however, the visual agreement is quite good on a time scale of few months. However, since about 2003, the average global surface air temperature is drifting away in positive direction from the average satellite temperature, meaning that the surface records show warming in relation to the troposphere records. The reasons for this is not clear, but is probably at least partly a result of the recurrent administrative changes of the surface records, see here. here and here. Global monthly average surface air temperature (HadCRUT4. NCDC. GISS ) minus global monthly average lower troposphere temperature (UAH MSU. RSS MSU ) since 1979. The thin blue line shows the monthly temperature difference between anomalies calculated for surface and lower troposphere observations, respectively. The thick blue line is the simple running 37 month average, nearly corresponding to a running 3 yr average. The dotted red line is the linear fit line, statistics of which is presented in the lower right corner of the diagram. As the five data series are using different reference (normal) periods, they have all been normalised by comparing to the average value of 30 years from January 1979 to December 2008. Last month shown: December 2016. Last diagram update: 21 January 2017. Please note that the linear regression is done by month, not year Click here to see the HadCRUT4 temperature anomaly diagram since 1979. Click here to see the NCDC temperature anomaly diagram since 1979. Click here to see the GISS temperature anomaly diagram since 1979. Click here to see the UAH MSU temperature anomaly diagram since 1979. Click here to see the RSS MSU temperature anomaly diagram since 1979. According to the above temperature records, the surface air temperature have been rising more rapid than the temperature in the lower troposphere since January 1979, about 0.1 o C. Click here to jump back to the list of contents. Diagram showing the latest 5, 10, 20 and 30 yr linear annual global temperature trend, calculated as the slope of the linear regression line through the data points, for two satellite-based temperature estimates (UAH MSU and RSS MSU), the Quality Class 1 series. Last month included in analysis: December 2016. Last diagram update: 21 January 2017. Diagram showing the latest 5, 10, 20, 30, 50, 70 and 100 yr linear annual global temperature trend, calculated as the slope of the linear regression line through the data points, for three surface-based temperature estimates (HadCRUT4 and GISS NCDC), the Quality Class 2 and 3 series, respectively. Last month included in analysis: December 2016. Last diagram update: 21 January 2017. The two diagrams above show the calculated linear annual global temperature trend ( calculated as the slope of the linear regression line through the data points ) for the last 5, 10, 20, 30, 50, 70 or 100 yr period. The difference between satellite - and surface-based temperatures is clear. Linear trends depend on the length of the time period considered. The shorter the period considered, the more variable the calculated trend will be as new monthly data are added to the data series. In addition, linear trends calculated for short periods often have higher numerical values than trends calculated for longer periods. When comparing linear temperature trends. is is therefore important always to use time periods of similar length. As an visual example of this effect, the diagrams below show trends calculated for the last 20, 15, 10 and 5 years, using the combined Quality Class 1 series. Linear trend analyses represent a relatively crude way of numerical analysis, and often a better approximation to the original data may be obtained by using other data models, e. g. polynomial, as shown in the diagrams below. The R 2 value may be considered an indicator of the degree of success of the data model adopted, but the number of data must also be considered. It should also be emphasized, that linear trend analyses are sensitive to values near the ends points of the data series considered, and especially for short series. Finally, any trend calculated only informs about past behaviour, and not about the future. Before attempting any linear trend (or any other) analysis of time series, a proper statistical model should be chooosen, based on statistical justification. For temperature time series t here is no a priori physical reason why the long-term trend should be linear in time. In fact, climatic time series often have trends for which a straight line is not a good approximation, as is clearly seen from several of the diagrams above and below. For a clear description of the problem encountered by many temperature time series analyses, please see Keenan, D. J. 2014: Statistical Analyses of Surface Temperatures in the IPCC Fifth Assessment Report. Last 20 years global monthly average surface air temperature according to the two satellite-based temperature estimates (UAH MSU and RSS MSU), Quality Class 1 . The thin blue line represents the monthly values. The thick black line is the linear fit, with 95 confidence intervals indicated by the two thin black lines. The thick green line represents a 5-degree polynomial fit, with 95 confidence intervals indicated by the two thin green lines. A few key statistics is given in the lower part of the diagram (note that the linear trend is the monthly trend). Last month included in analysis: January 2017. Last diagram update: 15 February 2017. Please note that the linear regression is done by month, not year Click here to download the series of UAH MSU global monthly lower troposphere temperature anomalies since December 1978. Click here to download the series of RSS MSU global monthly lower troposphere temperature anomalies since January 1979. Fits (linear as well as polynomial) only attempt to describe the past, and have little or no predictive power. Last 15 years global monthly average surface air temperature according to the two satellite-based temperature estimates (UAH MSU and RSS MSU), Quality Class 1 . The thin blue line represents the monthly values. The thick black line is the linear fit, with 95 confidence intervals indicated by the two thin black lines. The thick green line represents a 5-degree polynomial fit, with 95 confidence intervals indicated by the two thin green lines. A few key statistics is given in the lower part of the diagram (note that the linear trend is the monthly trend). Last month included in analysis: January 2017. Last diagram update: 15 February 2017. Please note that the linear regression is done by month, not year Click here to download the series of UAH MSU global monthly lower troposphere temperature anomalies since December 1978. Click here to download the series of RSS MSU global monthly lower troposphere temperature anomalies since January 1979. Fits (linear as well as polynomial) only attempt to describe the past, and have little or no predictive power. Last 10 years global monthly average surface air temperature according to the two satellite-based temperature estimates (UAH MSU and RSS MSU), Quality Class 1 . The thin blue line represents the monthly values. The thick black line is the linear fit, with 95 confidence intervals indicated by the two thin black lines. The thick green line represents a 5-degree polynomial fit, with 95 confidence intervals indicated by the two thin green lines. A few key statistics is given in the lower part of the diagram (note that the linear trend is the monthly trend). Last month included in analysis: January 2017. Last diagram update: 15 February 2017. Please note that the linear regression is done by month, not year Click here to download the series of UAH MSU global monthly lower troposphere temperature anomalies since December 1978. Click here to download the series of RSS MSU global monthly lower troposphere temperature anomalies since January 1979. Fits (linear as well as polynomial) only attempt to describe the past, and have little or no predictive power. Last 5 years global monthly average surface air temperature according to the two satellite-based temperature estimates (UAH MSU and RSS MSU), Quality Class 1 . The thin blue line represents the monthly values. The thick black line is the linear fit, with 95 confidence intervals indicated by the two thin black lines. The thick green line represents a 5-degree polynomial fit, with 95 confidence intervals indicated by the two thin green lines. A few key statistics is given in the lower part of the diagram (note that the linear trend is the monthly trend). Last month included in analysis: January 2017. Last diagram update: 15 February 2017. Please note that the linear regression is done by month, not year Click here to download the series of UAH MSU global monthly lower troposphere temperature anomalies since December 1978. Click here to download the series of RSS MSU global monthly lower troposphere temperature anomalies since January 1979. Fits (linear as well as polynomial) only attempt to describe the past, and have little or no predictive power. Click here to jump back to the list of contents. Running 50 year linear annual temperature trend calculated from monthly global average surface air temperature anomaly provided by to Hadley CRUT, a cooperative effort between the Hadley Centre for Climate Prediction and Research and the University of East Anglia s Climatic Research Unit (CRU ), UK. The blue line represents the 50x12 month linear trend, plotted at the last month included in the analysis. As the HadCRUT3 record begins in January 1850, the first 50 yr plot is for December 1899. Last month included in analysis: December 2016. Last diagram update: 21 January 2017. Click here to download the series of estimated HadCRUT4 global monthly surface air temperature anomalies since 1850. The variation shown by the moving 50 yr linear global temperature trend suggests the existence of an 60-65 yr long periodic natural temperature variation. The diagram was kindly suggested by a visitor to this web site. Click here and here to see two other examples of apparent cyclic natural climate variations, relating to sea surface temperature and atmospheric pressure, respectively. Click here to jump back to the list of contents. The Central England surface air temperature series is the longest existing meteorological record. Thin lines annual values. Thick lines running 11 yr average. The above graphs for annual, summer and winter temperatures have been prepared using the composite monthly meteorological series originally painstakingly homogenized and published by the late professor Gordon Manley (1974). The data series is now updated by the Hadley Centre. Last diagram update: 2 December 2015. Click here to see a larger version of the above diagram. Click here for the Met Office UK year to date plot. Click here to download the entire Central England data series since 1659 (shown above) Click here to jump back to the list of contents. Global monthly average lower troposphere temperature since 1979 for the tropics and the northern and southern extratropics, according to University of Alabama at Huntsville, USA. This graph uses data obtained by the National Oceanographic and Atmospheric Administration (NOAA) TIROS-N satellite, interpreted by Dr. Roy Spencer and Dr. John Christy. both at Global Hydrology and Climate Center, University of Alabama at Huntsville, USA. Thick lines are the simple running 37 month average, nearly corresponding to a running 3 yr average. The cooling and warming periods directly influenced by the 1991 Mt. Pinatubo volcanic eruption and the 1998 El Nio, respectively, are clearly visible, especially in the tropics and the northern extratropics. Reference period 1981-2010. Last month shown: January 2017. Last diagram update: 9 February 2017. Click here to download the entire series of UAH MSU global monthly lower troposphere temperatures since December 1978. Global monthly average lower troposphere temperature since 1979 for the tropics and the northern and southern extratropics, according to Remote Sensing Systems (RSS). These graphs uses data obtained by the National Oceanographic and Atmospheric Administration (NOAA) TIROS-N satellite, and interpreted by Dr. Carl Mears (RSS). Thick lines are the simple running 37 month average, nearly corresponding to a running 3 yr average. Click here for a description of RSS MSU data products. Please note that RSS January 2011 changed from Version 3.2 to Version 3.3 of their MSUAMSU lower tropospheric (TLT) temperature product. Click here to read a description of the change from version 3.2 to 3.3, and previous changes. Last month shown: January 2017. Last diagram update: 3 February 2017. Click here to download the entire series of RSS MSU global monthly lower troposphere temperatures since January 1979. Global monthly average lower troposphere temperature since 1979 for the North Pole and South Pole regions, according to University of Alabama at Huntsville, USA. This graph uses data obtained by the National Oceanographic and Atmospheric Administration (NOAA) TIROS-N satellite, interpreted by Dr. Roy Spencer and Dr. John Christy. both at Global Hydrology and Climate Center, University of Alabama at Huntsville, USA. Thick lines are the simple running 37 month average, nearly corresponding to a running 3 yr average. Reference period 1981-2010. Last month shown: January 2017. Last diagram update: 9 February 2017. Click here to download the entire series of UAH MSU global monthly lower troposphere temperatures since December 1978. Global monthly average lower troposphere temperature since 1979 for the northern (60-82.5N) and southern (60-70S) polar regions, according to Remote Sensing Systems (RSS). These graphs uses data obtained by the National Oceanographic and Atmospheric Administration (NOAA) TIROS-N satellite, and interpreted by Dr. Carl Mears (RSS). Thick lines are the simple running 37 month average, nearly corresponding to a running 3 yr average. Click here for a description of RSS MSU data products. Please note that RSS January 2011 changed from Version 3.2 to Version 3.3 of their MSUAMSU lower tropospheric (TLT) temperature product. Click here to read a description of the change from version 3.2 to 3.3, and previous changes. Last month shown: January 2017. Last diagram update: 3 February 2017. Click here to download the entire series of RSS MSU global monthly lower troposphere temperatures since January 1979. Click here to jump back to list of contents. Global monthly average lower troposphere temperature since 1979 measured over land and oceans, respectively, according to University of Alabama at Huntsville, USA. This diagram uses data obtained by the National Oceanographic and Atmospheric Administration (NOAA) TIROS-N satellite, interpreted by Dr. Roy Spencer and Dr. John Christy. both at Global Hydrology and Climate Center, University of Alabama at Huntsville, USA. Thick lines are the simple running 37 month average, nearly corresponding to a running 3 yr average. Reference period 1981-2010. Last month shown: January 2017. Last diagram update: 9 February 2017. Click here to download the entire series of UAH MSU global monthly lower troposphere temperatures since December 1978. Northern hemisphere monthly average lower troposphere temperature since 1979 measured over land and oceans, respectively, according to University of Alabama at Huntsville, USA. This diagram uses data obtained by the National Oceanographic and Atmospheric Administration (NOAA) TIROS-N satellite, interpreted by Dr. Roy Spencer and Dr. John Christy. both at Global Hydrology and Climate Center, University of Alabama at Huntsville, USA. Thick lines are the simple running 37 month average, nearly corresponding to a running 3 yr average. Reference period 1981-2010. Last month shown: January 2017. Last diagram update: 9 February 2017. Click here to download the entire series of UAH MSU global monthly lower troposphere temperatures since December 1978. Southern hemisphere monthly average lower troposphere temperature since 1979 measured over land and oceans, respectively, according to University of Alabama at Huntsville, USA. This diagram uses data obtained by the National Oceanographic and Atmospheric Administration (NOAA) TIROS-N satellite, interpreted by Dr. Roy Spencer and Dr. John Christy. both at Global Hydrology and Climate Center, University of Alabama at Huntsville, USA. Thick lines are the simple running 37 month average, nearly corresponding to a running 3 yr average. Reference period 1981-2010. Last month shown: January 2017. Last diagram update: 9 February 2017. Click here to download the entire series of UAH MSU global monthly lower troposphere temperatures since December 1978. Click here to jump back to list of contents. Tropics-Polar monthly anomaly difference from average lower troposphere temperatures since 1979, according to University of Alabama at Huntsville, USA. This diagram uses data obtained by the National Oceanographic and Atmospheric Administration (NOAA) TIROS-N satellite, interpreted by Dr. Roy Spencer and Dr. John Christy. both at Global Hydrology and Climate Center, University of Alabama at Huntsville, USA. Thick lines are the simple running 37 month average, nearly corresponding to a running 3 yr average. Reference period 1981-2010. Last month shown: January 2017. Last diagram update: 9 February 2017. Click here to download the entire series of UAH MSU global monthly lower troposphere temperatures since December 1978. Click here to jump back to list of content The diagram table below contains clickable monthly spatial temperature diagrams since 2005, to illustrate the changeable geographical pattern of surface air temperature variations, integrated by graphs like that above. These diagrams are geographical asymmetrical to cover most of the planets land areas, ranging from 72 o N to 60 o S. Spatial distribution of monthly surface air temperature deviation between 72 o N and 60 o S in relation to the average for the period 1998-2006. Warm colours indicates areas with higher temperature than the 1998-2006 average, while blue colours indicate lower than average temperatures. Starting from 2015, the past 10 years are used as reference level. In the individual diagrams the month is indicated by a number: 1 January, 2 February, etc. Click on the individual small diagrams to open full-size diagrams. Please also read the notes below before interpreting the diagrams. Similar spatial temperature diagrams showing the polar regions can be seen by clicking here. Data source: NASA Goddard Institute for Space Studies (GISS). Last diagram update 16 February 2017. It is important to note that the map projection used above is of the type Mercator. This is a useful cylindrical map projection that preserves angles at all locations, but scale varies from place to place, distorting the size of land areas. In particular, areas closer to the poles are more affected, making land areas of similar size looking increasingly oversized towards the poles. To exemplify this effect, the areas of Mexico (1,972,550 km 2 ) and Greenland (2,166,086 km 2 ) are comparable in size. Greenland, however, in the map looks very much bigger than Mexico, even though only the southern half of Greenland is shown. The visual effect of this popular map type is to overstate the importance of temperature variations near the poles, compared to equatorial regions. To avoid the worst effects of this cartographic distortion of areas, the two Polar Regions are therefore shown in separate, polar projections. Click here to go to the polar spatial temperature diagrams. To monitor the present global temperature trend, up or down, it is not efficient to compare with some past period like, e. g. 1961-1990. even though this is what is frequently done. This will not inform about the current temperature trend. It seems to make more sense to compare with a more recent period. This is why the diagrams in the table above all use 1998-2006 as reference period. In addition, by using this recent reference period, is will gradually be possible to visualize if 1998-2006 represents a peak period for the global average temperature, or if modern temperatures are increasing to a even higher level. It should therefore be carried in mind that such a visual comparison does not represent a statistical test, but only a way of obtaining an visual overview of temperature patterns within the month considered. Positive or negative temperature deviations represent the result of monthly weather variations, and any clear pattern of overall climatic warming or cooling will take several years to be identified in a statistical sense. All the diagrams in the table above were prepared using gridded data downloaded from the public domain NASA Goddard Institute for Space Studies (GISS) web page. For surface interpolation of the gridded data a kriging algorithm was used, plotting all data in a polar projection map. The kriging procedure attempts to express trends and is widely considered one of the more flexible interpolation methods, producing a smooth map with few bull eyes. It is usually recommended for gridding almost any type of data set, especially data sets with a heterogeneous point distribution, such as characterising the present data set. It should be noted that the observation network within the two regions considered is not of equal density or quality all over the geographical regions covered by the diagrams. Click here to jump back to the list of contents. Anomalies of global annual surface air temperature (MAAT) since 1850 according to Hadley CRUT, a cooperative effort between the Hadley Centre for Climate Prediction and Research and the University of East Anglia s Climatic Research Unit (CRU ), UK. The average for 1979-2008 (30 yrs) has been set to zero, to make comparison with other temperature data series (above and below) easy. Last year shown: 201 6. Last figure update: 21 January 2017. Click here to download the entire series of estimated HadCRUT4 global monthly surface air temperatures since 1850. Click here to open a web interface to all the weather station data used by the Hadley Centre, a very useful facility developed by Clive Best, also known for his blog . Please note that the stations are split into 3 groups. 1) those going back to before 1860 2) Those going back to between 1860 and 1930 3) Those with data going back later than 1930. The last option is all stations together - but is very slow to load (gt5000 stations). Drag a rectangle to zoom in. Click on a station to see the graph of temperatures and anomalies. Anomalies of global annual surface air temperature (MAAT) since 1880 according to the National Climatic Data Center (NCDC), USA. This time series is calculated using land surface data from the Global Historical Climatology Network (Version 2) and sea surface temperature anomalies from the United Kingdom MOHSST data set and the NCEP Optimum Interpolated SSTs (Version2). The average for 1979-2008 (30 yrs) has been set to zero, to make comparison with other temperature data series (above and below) easy. Last year shown: 201 6. Last figure update: 21 January 2017. Click here to download the entire series of the NCDC global annual surface air temperatures since 1850 Anomalies of global annual surface air temperature (MAAT) since 1880 according to the Goddard Institute for Space Studies (GISS), at Columbia University, New York City, USA. GISS is a laboratory of the Earth-Sun Exploration Division of NASAs Goddard Space Flight Center and a unit of the Columbia University Earth Institute. The average for 1979-2008 (30 yrs) has been set to zero, to make comparison with other temperature data series (above and below) easy. Last year shown: 201 6. Last figure update: 19 January 2017 . Click here to download the entire series of the GISS global monthly surface air temperatures since 1880. Anomalies of global annual surface air temperature (MAAT) since 1979 according to the University of Alabama at Huntsville, USA. This graph uses data obtained by the National Oceanographic and Atmospheric Administration (NOAA) TIROS-N satellite, interpreted by Dr. Roy Spencer and Dr. John Christy. both at Global Hydrology and Climate Center, University of Alabama at Huntsville, USA. The average for 1979-2008 (30 yrs) has been set to zero, to make comparison with other temperature data series (above and below) easy. Last year shown: 201 6. Last figure update: 4 January 2017. Click here to download the entire series of UAH MSU global monthly lower troposphere temperatures since December 1978. Anomalies of global annual surface air temperature (MAAT) since 1979 according to the Remote Sensing Systems (RSS). This graph uses data obtained by the National Oceanographic and Atmospheric Administration (NOAA) TIROS-N satellite, and interpreted by Dr. Carl Mears (RSS). The average for 1979-2008 (30 yrs) has been set to zero, to make comparison with other temperature data series (above and below) easy. Last year shown: 201 6. Last figure update: 6 January 2017 . Click here to download the entire series of RSS MSU global monthly lower troposphere temperatures since January 1979. Click here to jump back to the list of contents. Anomalies of Northern Hemisphere annual surface air temperature (MAAT) since 1850 according to Hadley CRUT, a cooperative effort between the Hadley Centre for Climate Prediction and Research and the University of East Anglia s Climatic Research Unit (CRU ), UK. The average for 1979-2008 (30 yrs) has been set to zero, to make comparison with other temperature data series (above and below) easy. Last year shown: 201 6. Last figure update: 21 January 2017. Click here to download the entire series of estimated HadCRUT3 global monthly surface air temperatures since 1850. Click here to open a web interface to all the weather station data used by the Hadley Centre, a very useful facility developed by Clive Best, also known for his blog . Please note that the stations are split into 3 groups. 1) those going back to before 1860 2) Those going back to between 1860 and 1930 3) Those with data going back later than 1930. The last option is all stations together - but is very slow to load (gt5000 stations). Drag a rectangle to zoom in. Click on a station to see the graph of temperatures and anomalies. Anomalies of Northern Hemisphere annual surface air temperature (MAAT) since 1880 according to the National Climatic Data Center (NCDC), USA. This time series is calculated using land surface data from the Global Historical Climatology Network (Version 2) and sea surface temperature anomalies from the United Kingdom MOHSST data set and the NCEP Optimum Interpolated SSTs (Version2). The average for 1979-2008 (30 yrs) has been set to zero, to make comparison with other temperature data series (above and below) easy. Last year shown: 201 6. Last figure update: 21 January 2017. Click here to download the entire series of the NCDC global annual surface air temperatures since 1850 Please note that the early part of the NCDC record has now been changed so much towards lower values than just a few years ago, that the graph now extents below the x-axis. Click here for further details on temporal instability of the NCDC temperature record. Anomalies of Northern Hemisphere annual surface air temperature (MAAT) since 1880 according to the Goddard Institute for Space Studies (GISS), at Columbia University, New York City, USA. GISS is a laboratory of the Earth-Sun Exploration Division of NASAs Goddard Space Flight Center and a unit of the Columbia University Earth Institute. The average for 1979-2008 (30 yrs) has been set to zero, to make comparison with other temperature data series (above and below) easy. Last year shown: 201 6. Last figure update: 19 January 2017 . Click here to download the entire series of the GISS global monthly surface air temperatures since 1880. Anomalies of Northern Hemisphere annual surface air temperature (MAAT) since 1979 according to the University of Alabama at Huntsville, USA. This graph uses data obtained by the National Oceanographic and Atmospheric Administration (NOAA) TIROS-N satellite, interpreted by Dr. Roy Spencer and Dr. John Christy. both at Global Hydrology and Climate Center, University of Alabama at Huntsville, USA. The average for 1979-2008 (30 yrs) has been set to zero, to make comparison with other temperature data series (above and below) easy. Last year shown: 201 6. Last figure update: 4 January 2017. Click here to download the entire series of UAH MSU global monthly lower troposphere temperatures since December 1978. Anomalies of Northern Hemisphere annual surface air temperature (MAAT) since 1979 according to the Remote Sensing Systems (RSS). This graph uses data obtained by the National Oceanographic and Atmospheric Administration (NOAA) TIROS-N satellite, and interpreted by Dr. Carl Mears (RSS). The average for 1979-2008 (30 yrs) has been set to zero, to make comparison with other temperature data series (above and below) easy. Last year shown: 201 6. Last figure update: 6 January 2017 . Click here to download the entire series of RSS MSU global monthly lower troposphere temperatures since January 1979. Click here to jump back to the list of contents. Anomalies of Southern Hemisphere annual surface air temperature (MAAT) since 1850 according to Hadley CRUT, a cooperative effort between the Hadley Centre for Climate Prediction and Research and the University of East Anglia s Climatic Research Unit (CRU ), UK. The average for 1979-2008 (30 yrs) has been set to zero, to make comparison with other temperature data series (above and below) easy. Last year shown: 201 6. Last figure update: 21 January 2017. Click here to download the entire series of estimated HadCRUT3 global monthly surface air temperatures since 1850. Click here to open a web interface to all the weather station data used by the Hadley Centre, a very useful facility developed by Clive Best, also known for his blog . Please note that the stations are split into 3 groups. 1) those going back to before 1860 2) Those going back to between 1860 and 1930 3) Those with data going back later than 1930. The last option is all stations together - but is very slow to load (gt5000 stations). Drag a rectangle to zoom in. Click on a station to see the graph of temperatures and anomalies. Anomalies of Southern Hemisphere annual surface air temperature (MAAT) since 1880 according to the National Climatic Data Center (NCDC), USA. This time series is calculated using land surface data from the Global Historical Climatology Network (Version 2) and sea surface temperature anomalies from the United Kingdom MOHSST data set and the NCEP Optimum Interpolated SSTs (Version2). The average for 1979-2008 (30 yrs) has been set to zero, to make comparison with other temperature data series (above and below) easy. Last year shown: 201 6. Last figure update: 21 January 2017. Click here to download the entire series of the NCDC global annual surface air temperatures since 1850 Anomalies of Southern Hemisphere annual surface air temperature (MAAT) since 1880 according to the Goddard Institute for Space Studies (GISS), at Columbia University, New York City, USA. GISS is a laboratory of the Earth-Sun Exploration Division of NASAs Goddard Space Flight Center and a unit of the Columbia University Earth Institute. The average for 1979-2008 (30 yrs) has been set to zero, to make comparison with other temperature data series (above and below) easy. Last year shown: 201 6. Last figure update: 19 January 2017 . Click here to download the entire series of the GISS global monthly surface air temperatures since 1880. Anomalies of Southern Hemisphere annual surface air temperature (MAAT) since 1979 according to the University of Alabama at Huntsville, USA. This graph uses data obtained by the National Oceanographic and Atmospheric Administration (NOAA) TIROS-N satellite, interpreted by Dr. Roy Spencer and Dr. John Christy. both at Global Hydrology and Climate Center, University of Alabama at Huntsville, USA. The average for 1979-2008 (30 yrs) has been set to zero, to make comparison with other temperature data series (above and below) easy. Last year shown: 201 6. Last figure update: 4 January 2017. Click here to download the entire series of UAH MSU global monthly lower troposphere temperatures since December 1978. Anomalies of Southern Hemisphere annual surface air temperature (MAAT) since 1979 according to the Remote Sensing Systems (RSS). This graph uses data obtained by the National Oceanographic and Atmospheric Administration (NOAA) TIROS-N satellite, and interpreted by Dr. Carl Mears (RSS). The average for 1979-2008 (30 yrs) has been set to zero, to make comparison with other temperature data series (above and below) easy. Last year shown: 201 6. Last figure update: 6 January 2017 . Click here to download the entire series of RSS MSU global monthly lower troposphere temperatures since January 1979. Click here to jump back to the list of contents. Global monthly average temperature in different altitudes according to University of Alabama at Huntsville (UAH). The thin lines represent the monthly average, and the thick line the simple running 37 month average, nearly corresponding to a running 3 yr average. Last month shown: December 2016. Last diagram update: 6 January 2017. Click here. Qui. here and here to download the series of UAH MSU global monthly atmosphere temperature anomalies since December 1978. Global monthly average temperature in different altitudes according to Remote Sensing Systems (RSS). The thin lines represent the monthly average, and the thick line the simple running 37 month average, nearly corresponding to a running 3 yr average. Last month shown: January 2017. Last diagram update: 3 February 2017. Click here to download the series of RSS MSU global monthly atmosphere temperature anomalies since January 1979. Click here to read a description of the MSU products. Click here to jump back to the list of contents. Modelled zonally averaged, equilibrated temperature change with altitude associated with doubling atmospheric CO 2 (Lee et al. 2007 ). Units for modelled temperature change are given in degrees Celcius. The horizontal axis begins at 90 o N to the left, and ends at 90 o S to the right. The vertical axis begins at the planet surface and extends to 10 hPA (ca. 16 km height). For the 200, 300 and 1000 hPa levels (ca. 12, 9 and 0 km altitude, respectively) the observed temperature change since 1979 is shown in the diagrams below . Lindzen (1999 and 2007) argued that the surface temperature anomalies are not the best way of identifying the effect of an atmospheric CO 2 increase. He stressed that the radiation in the energy flux balance relations can be thought of as coming mainly from the atmospheric layer where the infrared optical depth is near 1. This characteristic emission layer is high above the surface and is typically located at an altitude somewhat below the tropopause. The height of the tropopause varies with latitude. In the tropics, the tropopause height is about 16-17 km, near 30 latitude about 12 km, and near the poles the tropopause height is around 8 km above the surface. The diagrams above shows how temperature changes when CO 2 is doubled in 4 different General Circulation Models (Lee et al. 2007 ). These model runs differ from those that were run for the IPCC in that the models were simplified to isolate the effects of CO 2 forcing and climate feedbacks (Lindzen 2007 ). Also the models were run until equilibrium was established rather than run in a transient mode in order to simulate the past. Thus, they tend to isolate greenhouse warming from other things that might be going on. The model runs shown in the above diagrams all suggest warming due to CO 2 doubling to peak not at the surface in the tropics, but in the troposphere near the 200-300 hPa level, roughly corresponding to 12-9 km altitude. The main reason for the inter-model variation is that the amount of water vapour differs among the models. The expected warming above the tropics is 2-3 times larger than near the surface, regardless of the sensitivity of the particular model. This is, in fact, the very signature of greenhouse warming (cf. Lindzen 2007 ). In the diagrams below the temperature change at and above Equator is shown, using the Hadley Centres radiosonde temperature product HadAT (200 and 300 hPa), and HadCRUT3 meteorological surface data. HadAT consists of temperature anomaly time series on 9 standard reporting pressure levels (850hPa to 30hPa), and is derived from 676 individual radiosonde stations with long-term records. Data uncertainties and limitations are described here. The latitudinal band used in the diagrams below is from 20 o N to 20 o S. To enable easy comparison with the global temperature changes shown higher up this page, 1979 has been chosen as start year. The full HadAT data series, however, goes back to 1958. Please note that the temperature scale in these diagrams are different from the scale used above, to accommodate the larger temperature variations at height. All data series were normalised by setting their starting value in January 1979 0, before inclusion in the diagrams below. Temperature change at 200hPa (c. 12 km height) between 20 o N and 20 o S since 1979, according to HadAT. The thin blue line shows the monthly values, while the thick blue line represents the simple running 37 month average, nearly corresponding to a running 3 yr average. The stippled red line shows the linear fit for the period shown, with basic statistics shown in the upper left corner of the diagram. The data were normalised by setting the average of their initial 120 months (10 years) from January 1979 to December 198 8 0. Last month shown: December 2012. Last diagram update: 4 May 2013. Please note that the linear regression is done by month, not year Click here to download the entire HadAT series since 1958. Temperature change at 300hPa (c. 9 km height) between 20 o N and 20 o S since 1979, according to HadAT. The thin blue line shows the monthly values, while the thick blue line represents the simple running 37 month average, nearly corresponding to a running 3 yr average. The stippled red line shows the linear fit for the period shown, with basic statistics shown in the upper left corner of the diagram. The data were normalised by setting the average of their initial 120 months (10 years) from January 1979 to December 198 8 0. Last month shown: December 2012. Last diagram update: 4 May 2013. Please note that the linear regression is done by month, not year Click here to download the entire HadAT series since 1958. Temperature change at surface between 20 o N and 20 o S since 1979, according to HadCRUT4 . The thin blue line shows the monthly values, while the thick blue line represents the simple running 37 month average, nearly corresponding to a running 3 yr average. The stippled red line shows the linear fit for the period shown, with basic statistics shown in the upper left corner of the diagram. The data were normalised by setting the average of the initial 120 months (10 years) from January 1979 to December 198 8 0. Last month shown: April 2013. Last diagram update: 8 June 2013. Please note that the linear regression is done by month, not year Click here to download the entire HadCRUT3 series since 1850. The initial versions of satellite and radiosonde datasets suggested that the tropical surface had warmed more than the troposphere, while climate models consistently showed tropospheric amplification of surface warming in response to human-caused increases in well-mixed greenhouse gases, as shown by the diagrams above. This observation gave rise to deep concern, and resulted in a number of studies (e. g. NRC 2000 ) where strong attempts were made to find warming in the troposphere. As new data sets have been made available and new corrections introduced, the scientific literature have witnessed a number of attempts of reconciling the modelled and the observed atmospheric warming pattern. Conflicting conclusions have, however, been reached. Some scientists conclude that a discrepancy between modelled and observed trends in tropical lapse rates still exists, while other argue that there is no longer a serious discrepancy. A few key references on this debate are represented by Lindzen 1999 and 2007. NRC 2000. Douglass et al 2007. and Santer et al 2008. Ongoing web-based discussions can be followed here and here. This debate reflects the importance of the point raised by Lindzen (1999) on monitoring temperature changes at the height in the troposphere corresponding to an infrared optical depth near 1. Diagram showing observed linear decadal temperature change at surface, 300 hPa and 200 hPa, between 20 o N and 20 o S, since January 1979. Data source: HadAT and HadCRUT4. Click here to compare with modelled altitudinal temperature change pattern for doubling atmospheric CO 2 . Last month included in analysis: December 2012. Last diagram update: 4 May 2013. The three diagrams above (using data from HadAT and HadCRUT4 ) show the linear trend of the temperature change since 1979 between 20 o N and 20 o S to be ca. 0.00089 o Cmonth at the surface, 0.00095 o Cmonth at 300 hPa, and -0.00009 o Cmonth at 200 hPa, corresponding to 0.10698, 0.11414 and -0.01022 o Cdecade, respectively (see bar chart above). Thus, these radiosonde and surface meteorological data from the Equatorial region do not at the moment display the signature of enhanced greenhouse warming. With the observed warming rate of about 0.10698 o Cdecade at the surface, a warming rate of about 0.21-0.31 o Cdecade would have been expected at the 200 and 300 hPa levels to comply with the prognosis on this derived from the CO 2 hypothesis. Click here to jump back to the list of contents. Weekly a bsolute (above) and anomaly (below) outgoing long wave radiation (OLR) at the top of the atmosphere 10-16 February 2017. Base period January 1979 - December 1995. Source: National Oceanographic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL). Last diagram update: 18 February 2017 . Click here to see the original ESRL diagram showing OLR absolute values, or to check for a more recent diagram. Click here to see the original ESRL diagram showing OLR anomaly values, or to check for a more recent diagram. First of all, it should be noted that the above maps are Mercator projection maps, whereby the polar regions are visually highly exaggerated as to their apparent surface area. In reality, it is the regions near Equator which are important as to the real surface area. The general long wave (infrared) pattern is characterised by a gradient towards relatively low values at high latitudes, and higher values near the Equator (upper panel). This zone of relative high long wave radiation follows the sun throughout the seasons, being displaced north during the Northern Hemisphere summer, and vice versa during the Northern Hemisphere winter. The strongest contrast within latitudinal belts exist in the low latitudes, where the high outgoing radiation of the subtropical anticyclones (high pressure zones) and other dry zones contrast sharply with the low outgoing radiation of the major cloudy regions of the tropics. Also at middle latitudes there may be substantial longitudinal variations, particular in the Northern Hemisphere. Such variations are often caused by massive penetration of cold air from the polar regions to middle latitudes, associated with strong blocking patterns in higher latitudes (Gruber and Winston 1978 ), and are most frequently observed in the Northern Hemisphere during Northern Hemisphere winter. Average total (left) and anomaly (right) outgoing long wave radiation (OLR) between 10 o N and 10 o S at the top of the atmosphere, since 18 February 2016 (top of diagram). Base period January 1979 - December 1995. Source: National Oceanographic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL). Last day shown: 16 February 2017 (bottom of diagram). Last diagram update: 18 February 2017 . Click here to see the original ESRL diagram showing OLR absolute values, or to check for a more recent diagram. Click here to see the original ESRL diagram showing OLR anomaly values, or to check for a more recent diagram. The region near the Equator is of high importance because of the huge surface areas involved. Variations are seen to be especially large within the region 60 o E-120 o W, covering the Indian Ocean, Indonesia and most of the Pacific Ocean between 10 o N and 10 o S. The red area of the Suns spectrum (upper panel in figure above) is absorbed by the atmosphere and the Earths surface. The warmed surface emits infrared radiation as indicated by the white areas on the individual molecules spectrum (lower panels). The grey bits are the parts of the spectra that are absorbed by the atmosphere. The blue area on the Earths emission spectrum (upper panel) is known as the infrared window through which most of the Earths radiation passes to space unhindered by being absorbed by any of the greenhouse gases. This short text is from Barett Bellamy Climate. where a more thorough description of the greenhouse effect is provided. The diagrams below all show infrared radiation within this window. Outgoing longwave radiation (OLR) at the top of the atmosphere between 180 o W and 179 o E (0 o E and 359.5 o E) and 90 o N and 90 o S since June 1974 according to the National Oceanographic and Atmospheric Administration (NOAA). The thin blue line represents the monthly value, while the thick red line is the simple running 37 month average, nearly corresponding to the running 3 yr average. The infrared wavelength covered is 10.5-12.5 m ( Gruber and Winston 1978 ) and covers the main part of the atmospheric infrared window. Last month shown: October 2010. Last diagram update: 13 February 2011. Click here to download the entire series of NOAA monthly OLR-values since June 1974. Choose first OLR then Select field. Scatter plot showing outgoing longwave radiation (OLR) at the top of the atmosphere between 180 o W and 179 o E (0 o E and 359.5 o E) and 90 o N and 90 o S since June 1974, as function of atmospheric CO 2 . OLR data from the National Oceanographic and Atmospheric Administration (NOAA). CO2 data measured at the Mauna Loa Observatory. Hawaii, reported as a dry mole fraction defined as the number of molecules of carbon dioxide divided by the number of molecules of dry air (water vapour removed), multiplied by one million (ppm). The red line represent a two-degree polynomial fit, specified in the lower left corner of the diagram. As the amount of atmospheric CO2 has been increasing over the entire period (ignoring annual variations), the x-axis can be seen as as rough timeline from 1974 (left) to 2010 (right). The infrared wavelength covered is 10.5-12.5 m ( Gruber and Winston 1978 ) and covers the main part of the atmospheric infrared window. Last month shown: October 2010. Last diagram update: 13 February 2011 . Click here to download the entire series of NOAA monthly OLR-values since June 1974. Choose first OLR then Select field. Click here to download the entire series of monthly CO 2 values since March 1958. Diagram showing outgoing longwave radiation (OLR) at the top of the atmosphere between 180oW and 179oE (0oE and 359.5oE) and 90oN and 90oS since December 1978 ( red line National Oceanographic and Atmospheric Administration (NOAA), and the g lobal monthly average lower troposphere temperature (blue line University of Alabama at Huntsville, USA). The thin lines represent the monthly values, while the thick lines are the simple running 37 month averages, nearly corresponding to running 3 yr averages. The infrared wavelength covered is 10.5-12.5 m (Gruber and Winston 1978 ) and covers the main part of the atmospheric infrared window. Last month shown: October 2010 (OLR) and January 2011 (UAH). Last diagram update: 13 February 2011 . Click here to download the entire series of NOAA monthly OLR-values since June 1974. Choose first OLR then Select field. Click here to download the entire series of UAH MSU global monthly lower troposphere temperatures since December 1978. Click here to jump back to the list of contents. Outgoing longwave radiation (OLR) at the top of the atmosphere between 180oW and 179oE (0oE and 359.5oE) and 20oN and 20oS since June 1974 according to the National Oceanographic and Atmospheric Administration (NOAA). The thin blue line represents the monthly value, while the thick red line is the simple running 37 month average, nearly corresponding to the running 3 yr average. The infrared wavelength covered is 10.5-12.5 m (Gruber and Winston 1978 ) and covers the main part of the atmospheric infrared window. Last month shown: October 2010. Last diagram update: 13 February 2011. Click here to download the entire series of NOAA monthly OLR-values since June 1974. Choose first OLR then Select field. Scatter plot showing outgoing longwave radiation (OLR) at the top of the atmosphere between 180oW and 179oE (0oE and 359.5oE) and 20oN and 20oS since June 1974, as function of atmospheric CO2. OLR data from the National Oceanographic and Atmospheric Administration (NOAA). CO2 data measured at the Mauna Loa Observatory. Hawaii, reported as a dry mole fraction defined as the number of molecules of carbon dioxide divided by the number of molecules of dry air (water vapour removed), multiplied by one million (ppm). The red line represent a two-degree polynomial fit, specified in the lower left corner of the diagram. As the amount of atmospheric CO2 has been increasing over the entire period (ignoring annual variations), the x-axis can be seen as as rough timeline from 1974 (left) to 2010 (right). The infrared wavelength covered is 10.5-12.5 m (Gruber and Winston 1978 ) and covers the main part of the atmospheric infrared window. Last month shown: October 2010. Last diagram update: 13 February 2011 . Click here to download the entire series of NOAA monthly OLR-values since June 1974. Choose first OLR then Select field. Click here to download the entire series of monthly CO 2 values since March 1958. Diagram showing outgoing longwave radiation (OLR) at the top of the atmosphere between 180oW and 179oE (0oE and 359.5oE) and 20oN and 20oS since December 1978 ( red line National Oceanographic and Atmospheric Administration (NOAA), and the g lobal monthly average lower troposphere temperature (blue line University of Alabama at Huntsville, USA). The thin lines represent the monthly values, while the thick lines are the simple running 37 month averages, nearly corresponding to running 3 yr averages. The infrared wavelength covered is 10.5-12.5 m (Gruber and Winston 1978 ) and covers the main part of the atmospheric infrared window. Last month shown: October 2010 (OLR) and January 2011 (UAH). Last diagram update: 13 February 2011 . Click here to download the entire series of NOAA monthly OLR-values since June 1974. Choose first OLR then Select field. Click here to download the entire series of UAH MSU global monthly lower troposphere temperatures since December 1978. Outgoing longwave radiation (OLR red graph) anomaly at the top of the atmosphere above Equator between 160oE and 160oW since 1979 according to the National Oceanographic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC). Base period: 1979-1995. Surface air t emperature change (blue graph) between 20oN and 20oS since 1979, according to HadCRUT3. The thin lines represent the monthly values, while the thick lines is simple running 37 month averages, nearly corresponding to running 3 yr averages. Within the time period 1996-2009, light blue areas indicate periods of surface cooling, and light red areas indicate surface warming. The entire OLR data series goes back to June 1974, but is here shown from January 1979 to enable easy comparison with the temperature diagrams shown above. The infrared wavelength covered is 10.5-12.5 m (Gruber and Winston 1978 ) and covers the main part of the atmospheric infrared window. Last month shown: January 2011 (OLR) and December 2010 (HadCRUT3). Last diagram update: 12 February 2011 . Click here to download the entire series of NOAA monthly OLR-values since June 1974. Click here to download the entire HadCRUT3 series since 1850. For the equatorial region, the diagram above suggests a certain chain of events, indicating the existence of a mechanism regulating the surface temperature: Periods of surface warming appears initially to be associated with decreasing outgoing longwave radiation (OLR). After some surface warming, OLR then stops decreasing and instead begins to increase, and after a while, surface air temperature then begins to decrease, etc. This chain of events is clearly illustrated by, e. g. the time period around the 1998 El Nio event (diagram above). Part of the explanation of the above succession of events might be that tropical surface warming leads to enhanced atmospheric convectional transport of heat to high levels of the atmosphere above the Equator, resulting in enhanced longwave radiation at the top of the atmosphere. This, in turn, eventually leads to surface cooling, which results in reduced atmospheric convection, etc. Also the potential connection to variations in tropical sea surface temperatures and the tropical cloud cover is interesting, and should be considered in a more detailed analysis. Click here to jump back to the list of contents. Outgoing longwave radiation (OLR) at the top of the atmosphere between 180oW and 179oE (0oE and 359.5oE) and 70oN and 90oN since June 1974 according to the National Oceanographic and Atmospheric Administration (NOAA). The thin blue line represents the monthly value, while the thick red line is the simple running 37 month average, nearly corresponding to the running 3 yr average. The infrared wavelength covered is 10.5-12.5 m (Gruber and Winston 1978 ) and covers the main part of the atmospheric infrared window. Last month shown: October 2010. Last diagram update: 13 February 2011 . Click here to download the entire series of NOAA monthly OLR-values since June 1974. Choose first OLR then Select field. Scatter plot showing outgoing longwave radiation (OLR) at the top of the atmosphere between 180oW and 179oE (0oE and 359.5oE) and 70oN and 90oN since June 1974, as function of atmospheric CO2. OLR data from the National Oceanographic and Atmospheric Administration (NOAA). CO2 data measured at the Mauna Loa Observatory. Hawaii, reported as a dry mole fraction defined as the number of molecules of carbon dioxide divided by the number of molecules of dry air (water vapour removed), multiplied by one million (ppm). The red line represent a two-degree polynomial fit, specified in the lower left corner of the diagram. As the amount of atmospheric CO2 has been increasing over the entire period (ignoring annual variations), the x-axis can be seen as as rough timeline from 1974 (left) to 2010 (right). The infrared wavelength covered is 10.5-12.5 m (Gruber and Winston 1978 ) and covers the main part of the atmospheric infrared window. Last month shown: October 2010. Last diagram update: 13 February 2011. Click here to download the entire series of NOAA monthly OLR-values since June 1974. Choose first OLR then Select field. Click here to download the entire series of monthly CO 2 values since March 1958. Diagram showing outgoing longwave radiation (OLR) at the top of the atmosphere between 180oW and 179oE (0oE and 359.5oE) and 70oN and 90oN since December 1978 ( red line National Oceanographic and Atmospheric Administration (NOAA), and the g lobal monthly average lower troposphere temperature (blue line University of Alabama at Huntsville, USA). The thin lines represent the monthly values, while the thick lines are the simple running 37 month averages, nearly corresponding to running 3 yr averages. The infrared wavelength covered is 10.5-12.5 m (Gruber and Winston 1978 ) and covers the main part of the atmospheric infrared window. Last month shown: October 2010 (OLR) and January 2011 (UAH). Last diagram update: 13 February 2011 . Click here to download the entire series of NOAA monthly OLR-values since June 1974. Choose first OLR then Select field. Click here to download the entire series of UAH MSU global monthly lower troposphere temperatures since December 1978. Click here to jump back to the list of contents. Outgoing longwave radiation (OLR) at the top of the atmosphere between 180oW and 179oE (0oE and 359.5oE) and 70oS and 90oS since June 1974 according to the National Oceanographic and Atmospheric Administration (NOAA). The thin blue line represents the monthly value, while the thick red line is the simple running 37 month average, nearly corresponding to the running 3 yr average. The infrared wavelength covered is 10.5-12.5 m (Gruber and Winston 1978 ) and covers the main part of the atmospheric infrared window. Last month shown: October 2010. Last diagram update: 13 February 2010. Click here to download the entire series of NOAA monthly OLR-values since June 1974. Choose first OLR then Select field. Scatter plot showing outgoing longwave radiation (OLR) at the top of the atmosphere between 180oW and 179oE (0oE and 359.5oE) and 70oS and 90oS since June 1974, as function of atmospheric CO2. OLR data from the National Oceanographic and Atmospheric Administration (NOAA). CO2 data measured at the Mauna Loa Observatory. Hawaii, reported as a dry mole fraction defined as the number of molecules of carbon dioxide divided by the number of molecules of dry air (water vapour removed), multiplied by one million (ppm). The red line represent a two-degree polynomial fit, specified in the lower left corner of the diagram. As the amount of atmospheric CO2 has been increasing over the entire period (ignoring annual variations), the x-axis can be seen as as rough timeline from 1974 (left) to 2010 (right). The infrared wavelength covered is 10.5-12.5 m (Gruber and Winston 1978 ) and covers the main part of the atmospheric infrared window. Last month shown: October 2010. Last diagram update: 13 February 2011 . Click here to download the entire series of NOAA monthly OLR-values since June 1974. Choose first OLR then Select field. Click here to download the entire series of monthly CO 2 values since March 1958. Diagram showing outgoing longwave radiation (OLR) at the top of the atmosphere between 180oW and 179oE (0oE and 359.5oE) and 70oS and 90oS since December 1978 ( red line National Oceanographic and Atmospheric Administration (NOAA), and the g lobal monthly average lower troposphere temperature (blue line University of Alabama at Huntsville, USA). The thin lines represent the monthly values, while the thick lines are the simple running 37 month averages, nearly corresponding to running 3 yr averages. The infrared wavelength covered is 10.5-12.5 m (Gruber and Winston 1978 ) and covers the main part of the atmospheric infrared window. Last month shown: October 2010 (OLR) and January 2011 (UAH). Last diagram update: 13 February 2011 . Click here to download the entire series of NOAA monthly OLR-values since June 1974. Choose first OLR then Select field. Click here to download the entire series of UAH MSU global monthly lower troposphere temperatures since December 1978. Click here to jump back to the list of contents. Diagram showing the HadCRUT4 estimate for the global annual surface temperature anomaly since 1885, and the average annual excess of duration of the day, defined as the difference between the astronomically determined duration of the day and 86400 seconds, and also called the length of day (LOD). The thin lines are showing the annual values, and the thick lines are the running 11 yr average. Temperature data source: the Hadley Centre for Climate Prediction and Research and the University of East Anglia s Climatic Research Unit (CRU ), UK. LOD data source: International Earth Rotation and Reference Systems Service (IERS). Last year shown: 2014. Last diagram update: 13 June 2015. Click here to download the entire series of HadCRUT4 global monthly surface air temperature anomaly data since 1850. Click here to read more about how to measure the irregularities of planet Earths rotation. Diagram showing the monthly HadCRUT4 estimate for the global surface temperature anomaly since January 1962 (upper panel), the average angular velocity of Earth (mid panel), and the average monthly excess of duration of the day (lower panel). The excess duration of the day (LOD) is defined as the difference between the astronomically determined duration of the day and 86400 seconds. The thin lines are representing the monthly values, and the thick lines are the running 37 month average (about 3 yr). Temperature data source: the Hadley Centre for Climate Prediction and Research and the University of East Anglia s Climatic Research Unit (CRU ), UK. Angular velocity and LOD data source: International Earth Rotation and Reference Systems Service (IERS). Last month shown: April 2014. Last diagram update: 13 June 2015. Click here to download the entire series of HadCRUT4 global monthly surface air temperature anomaly data since 1850. Click here to read more about how to measure the irregularities of planet Earths rotation. The length of day (LOD) as shown above are subject to variations due to variations in oceanic tides (smaller than 0.03 ms in absolute value), variations in the atmospheric circulation, and to internal effects and to transfer of angular momentum to the Moon orbital motion. Also t he dynamical influence of the liquid core of the earth may account for slow variations, but then generally expressed as overall long-term trends (Akoi et al. 1982 ). Zatman and Bloxham (1997) found that torsional oscillations have their sources at the outer-inner core boundary of earth. Duhau and de Jager (2012) found semi-secular (40-60 yr) oscillations in LOD to be linearly related to cycles in solar orbital parameters, and that the semi-secular LOD oscillations presumably are exited by planetary orbital motions, especially Jupiter and Saturn. The above diagrams show that periods with relatively high planetary rotation velocity (and low LOD) tend to be associated with relatively warm periods, and vice versa. Good examples are the peak of LOD in the early 20th century, concurrent with the last cold spell of The Little Ice Age and the loss of Titanic. Also the cold period 1965-1977 was associated with long day length (high LOD) and low planetary angular velocity. The generally increasing rotation velocity of Earth (and decreasing LOD) since then has taken place along with the period of late 20th century warming. Variations in LOD has also been associated with the Atmospheric Circulation Index (ACI) and variations in commercial catches of different fish species. Some of these associations are thoroughly described and discussed by Klyashtorin and Lyubushin (2007). Click here to jump back to the list of contents.