Presentation on theme: "An analysis of a decadal prediction system"— Presentation transcript:
1An analysis of a decadal prediction system Jon RobsonRowan Sutton and Doug Smith (Met Office)Thanks also to Ed Hawkins, Alan Iwi and Andy Heaps
2Overview Background and motivation Introduction to DePreSys Analysis of DePreSys hindcastsHypothesis testing experimentsConclusions and Implications
3Projections of climate change The current rate of observed global mean warming is predicted to continue and may even increase over the coming decadeDecision makers will need the best information available on regional or local scales for adaptation decisions.Current regional climate projections are dominated by natural variability over the next decadeHow can we constrain the uncertainty in climate projections over the next decade?
4Uncertainty Uncertainty in climate forecasts arise from 3 sources. InternalUncertainty in climate forecasts arise from 3 sources.Model uncertaintyScenario uncertaintyInternal variabilityGlobal projections of climate change are dominated by model and scenario errorHowever for regional scales internal variability can be a very important source of uncertainty over the next two decadesCan we reduce the uncertainty caused by internal variability?ScenarioModelInternalScenarioModel(Hawkins and Sutton, 2009)
5Long-time scale variability and predictability “slower” parts of the earth system could be predictable for many years and could constrain uncertainty over the next decade.Depends on what you look at and where you lookBut there does seem to be some hint of potential predictability in the North AtlanticWhat is the cause of this predictability?(Boer, 2004)
6AMOC variabilityThe AMOC transports heat northward and warms the climate of Western Europe.Model studies show that the strength of the AMOC is naturally variable on multi- decadal timescales and modulates the northward heat transport“Perfect” model results suggest the AMOC could be potentially predictable for over a decade(Knight et al, 2005) 1 Sverdrup = 106 m3 s-1But we do not know how that translates into actual predictability
7Initialised forecasts - DePreSys Smith et al, Science, showed that initialising the ocean in a coupled climate model did improve the skill of global surface temperature forecasts over the next decade compared to forecasts that didn’t assimilate information.Surface temp113m heat content
8Motivation for my project Mean skill scores do not inform you of why the forecasts are performing better, or indeed why forecasts that assimilate information are performing worse in some areas.What are the mechanisms behind the improved predictability?Why do some forecasts fail?Evaluating the climate models against observations at the process level – A new handle on understanding model error.
10DePreSys Fully coupled decadal forecast system, based on HadCM3 Initialised from the observed climate state in order to constrain predictions over the next decadeForced by anthropogenic emissions (SRES B2 scenario), previous 11 year solar cycle and volcanic aerosol. Volcanic aerosol is reduced with an e-folding timescale of one year.There are no future volcanoes in the forecastsHindcast Set4 member ensemble DePreSys hindcasts initialised seasonally (March, June, Sept and December) over the yearsFor comparison a second similar ensemble is also initialised, that does NOT assimilate observations – this is called NoAssimOver 6000 model years
11Initialisation of DePreSys Seasonal forecasts typically assimilate the full fields of variables to initialise the model as close to the observed state as possible.However the model climate and the real climate are not the same, and so the forecast will drift back to the model’s preferred state over the course of the forecastDePreSys is Initialised close to the model attractor by assimilating anomalies on to the model climateTop 100m average Temperature+Climatology(Calculated form transient integrations)Observed anomaly
12Anomaly assimilationNoAssimObs anomaly2010196019792001Assimilation RunTransient Run’sDePreSysGlobal TemptimeAssimilation run is started from a transient run and integrated forward using historical forcing and is constantly relaxed (strongly) toward the model climatology plus the observed anomaliesOcean:- Relaxed to 3D T and S, anomalies calculated from Met Office Ocean analysis. Climatological period =Atmosphere:- Relaxed to 3D temp, 3D winds and surface pressure calculated from ERA-40. Climatological period =DePreSys also has a perturbed physics ensemble of 9 QUMP models
133. Analysis of DePreSys hindcasts What changes have occurred in the world oceans over the hindcast period?
14Rapid warming of the North Atlantic Inverted NAO in blackTemp anomaly of Subtropical gyre (60W-10W,50N-66N) from Levitus, ECMWF and Met OfficeThe rapid warming of the North Atlantic was largely a lagged response to the positive NAO forcing of the 80s and 90sEvidence that spin up of the AMOC and a surge in the heat transport causes the warming
15How skillful is DePreSys for the rapid warming? Top 500m average ocean temp for the subpolar gyre(60w-10w, 50n-66n)Black = ObservationRed = DePreSys hindcastDePreSys Exhibits remarkable levels of skill for the 1995 rapid warming of the subpolar gyre
16However it doesn’t get it right all the time…. After 1990 DePreSys hindcasts become very eager to warm rapidly in the subpolar gyre region.What is the cause of these early warmers?
17What’s happening in the initial conditions? Need to look at density in order to deduce changes in initialised circulationIn HadCM3 high density in the subpolar gyre due to NAO forcing leads to an increase in overturning, and hence increase the Northward heat transportCorrelation of m density anomaly leading the AMOC index by 5 years from HadCM3 control runNormalised m density anomalies
18Density errors occur in the assimilation run Large density errors occur across the whole ocean but occur frequently in the North AtlanticIn the early 90s large density errors occur in the deep convective regions of the North AtlanticHypothesis A:- The early warming hindcasts are caused by the presence of errors in the assimilated density anomalies that cause an increase in the AMOC that is too early or too large
19The Response of the AMOC All of the DePreSys hindcasts show a rapid and large collapse of the AMOC at 50N
20Drifts present in DePreSys Subpolar gyre densityMean Atlantic Stream function evolution as a function of time over all DePreSys hindcasts minus DePreSys climatology1980199020002010Mean 0-113m T bias in the Gulf Stream Extension0.0What is the cause of this Drift?0.4Forecast season
21Drift in the HadCM3 control run Antarctic Bottom Water overturning indexSverdrupsTempThe first transient run was initialised in yr 1859 from the control run (year 9)Each subsequent transient run was initialised 100 years after the one beforeThe DePreSys climatology comes from a transient run that was initialised from an unstable state in the control run and is driftingHypothesis B:- The background state for the assimilation is unstable and causes the DePreSys hindcasts to drift
22Can relaxation to just T and S cause further problems? The model is being relaxed strongly to the background state plus the observed anomaliesIf there are no observed anomalies the model will be stuck firm to the climatological state.However the background state for DePreSys isIt is not clear that this background state will be stable even if all the intervening states are
23Aside:- The effect of climatology error on mean skill scores The skill scores are calculated by evaluating forecast anomalies against the observed anomaliesThe NoAssim hindcasts are initialised from transient runs with a different climatology to DePreSysNoAssim (trans1) – DePreSys 113m RMSENoAssim (sep) – DePreSys 113m RMSE
25HypothesesA. The early warming hindcasts are caused by the presence of errors in the assimilated density anomalies that cause an increase in the AMOC that is too early or too largePerturb the assimilated density so that the density anomalies are the same as observed, by perturbing salinity anomaliesB. The back ground state for the assimilation run is unstable and causes the DePreSys hindcasts to drift?Use a new climatology calculated from an ensemble of 6 transient runs, initialised 1500 years into the control run.Thanks to Alan Iwi for supplying the Climatology!There have been a few changes to DePreSys since the original hindcast experiment. We re-run new unperturbed forecast first to compare with.Re-run the December 1991 hindcast
26The effect of density Errors Control – Perturbed Salinity overturning stream function as a fn of Latitude and timeSubpolar gyre 0-500m Temp2nd year SST forecast difference control – perturbed Salinity.
27The effect of a new climatology Subpolar gyre 0-500m Temp2nd year SST forecast difference control – new clim .
29ConclusionsMoving past mean skill scores to looking at individual hindcasts for case studies is an important route for improving decadal prediction systemsHindcasts can be very sensitive to the choice of climatology used for the anomaly assimilation.The non-linear equation of state means that some imbalance may be inevitable when climatologies are derived from time mean temperature and salinityNon-linearities also lead to errors in the assimilated density anomalies that can have a significant effect upon the hindcasts
30Future of decadal climate forecasting Decadal forecasting included in CMIP5 (includes HiGEM DPS)More work required on assimilation and initialisation strategiesBalanced initialisation techniquesAssimilate density directlyStrategies to minimise assimilated density anomaly errorEnsemble designUnderstanding the mechanisms that give rise to the improved predictionsAssessing the models against observations at the process level to tackle model error’sThank you!!