International efforts in Climate Modeling Projections, Predictions and Downscaling

Coordinated by the World Climate Research Program (WCRP)

CMIP5: The 5th Coupled Model Intercomparison ProjectCMIP5: The 5th Coupled Model Intercomparison Projecthttp://cmip-pcmdi.llnl.gov

CORDEX: A Coordinated Regional Downscaling ExperimentCORDEX: A Coordinated Regional Downscaling Experimenthttp://wcrp.ipsl.jussieu.fr/SF_RCMTerms.html

Colin JonesRossby Centre, SMHI

Thanks to: Karl Taylor (PCMDI), Filippo Giorgi (ICTP), Ghassam Asrar (WCRP)

Promotes a standard set of model simulations in order to : evaluate how realistic the models are in simulating the recent past provide projections of future climate change on two time scales understand factors responsible for model differences

Two timescales and two sets of science problems

An important input to IPCC AR5

Taylor et al. 2009, http://cmip-pcmdi.llnl.gov/cmip5/

Near-Term :(next 1-30 years)

decadal climate predictability

ocean initialization

aerosol impacts

regional climate change (high resol)

& climate extremes

air quality changes (aerosols, chemistry)

Long-Term :(1860 to 2100 & beyond)

evaluation of climate models

(e.g. new satellite data)

detection & attribution

climate change scenarios

climate sensitivity, radiativeforcing and physical

feedbacks (e.g. clouds)

biogeochemical feedbacks(e.g. carbon, chemistry)

CMIP5 : a framework for climate change modeling for the next 5+ years

CMIP5: Centennial Timescales: Earth System CMIP5: Centennial Timescales: Earth System ModelingModelingAims to improve our ability to simulate all processes that influence the response of the climate system to increasing greenhouse gases

• • Cloud FeedbacksCloud Feedbacks

• • Carbon-Climate Feedback (Ocean and Terrestrial)Carbon-Climate Feedback (Ocean and Terrestrial)

• • Aerosol FeedbacksAerosol Feedbacks

• • Sea-Ice/Snow FeedbacksSea-Ice/Snow Feedbacks

• • Ocean circulation changesOcean circulation changes

• • Ice Sheets/Glacier responseIce Sheets/Glacier response

• • Sea-level changesSea-level changes

• • Ocean acidification and ecosystem responseOcean acidification and ecosystem response

• • Permafrost and Methane ReleasePermafrost and Methane Release

To better constrain the lower and upper bounds of To better constrain the lower and upper bounds of anthropogenic climate change requires anthropogenic climate change requires (an accurate and (an accurate and complete)complete) representation representationof complex and interacting process in Earth System of complex and interacting process in Earth System ModelsModels

• Start from a pre-industrial spin-up run (>500 yrs)• The 20th century control run includes observed changes in GHG,

aerosol concentrations, volcanoes, and land-use from 1850-2005• 3 RCP scenarios for the 21th century

Possibly extend with more RCP scenarios, 1% CO2 increase, …

CMIP5: centennial projections

20th century control

1850 1900 1950 2000 2050 2100

RCP8.5

RCP4.5

Sp

in-u

p

RCP2.6

First CMIP5 projections results now becoming available

Decadal predictability and climate prediction

Predictability we are familiar with arises from an estimate

of future changes in GHG radiative forcing, and the climate

system response to those changes.

Predictability might also arise from information Predictability might also arise from information contained in the initial state of the systemcontained in the initial state of the system

- “committed warming” due to previous GHG “committed warming” due to previous GHG forcingforcing- natural variability of the systemnatural variability of the system

Tom Delworth GFDL

Assuming we can (i) observe this information (i) observe this information (ii) assimilate it assimilate it in our models,in our models, (iii) the variability has a predictable (iii) the variability has a predictable componentcomponentandand (iv) our models are good enough to simulate the subsequent evolution of the climate system

We may be able to provide useful information about the evolution of the climate system on a ~1-20 year timescale.

Climate Prediction as a mixed initial/boundary value Climate Prediction as a mixed initial/boundary value problemproblem

The Atlantic Meridional Oscillation indexThe Atlantic Meridional Oscillation indexA 10-yr moving average of annual North Atlantic SST A 10-yr moving average of annual North Atlantic SST

anomaliesanomalies

Linked to variability in the Atlantic Meridional Overturning CirculationLinked to variability in the Atlantic Meridional Overturning Circulationcrucial to simulate the time evolution of AMOC for decadal predictioncrucial to simulate the time evolution of AMOC for decadal prediction

Global annual Global annual mean surface mean surface

temp (Ttemp (TSS))

Global annual Global annual mean ocean mean ocean

heat content in heat content in upper 113m upper 113m

(H)(H)

There appears to be some increased skill (in a quantitative sense)There appears to be some increased skill (in a quantitative sense)when observations are included in coupled climate model predictionswhen observations are included in coupled climate model predictions

Results from the UK Met. Office DePreSys integrationsResults from the UK Met. Office DePreSys integrations

D. Smith etal. UKMO

CMIP5: decadal prediction experiments

1960 1970 1980 1990 2000 2010 2020

10 yrs

10 yrs

10 yrs

10 yrs

10 yrs

10 yrs

10 yrs

10 yrs

10 yrs

10 yrs

10 yrs

+20 yrs

+20 yrs

+20 yrs

• Start a 10-yr experiment every 5 years• Initialize from observation-based re-analysis of atmosphere and ocean• Extend a few runs to 30 yrs

Decadal prediction still a researchtopic: Targeted for ~1-20 yearTimescale : climate services ?climate services ?

• Hindcast simulations to assess skill & uncertainty

• Test ocean and sea-ice initialisation techniques

• Interpretation of results not easy (potential predictability)

It may be that much of the predictive skill for the comingdecade (and beyond) will result from the “forced” GHG response not the initialized climate state.

Results from “initialized” climate simulations often Results from “initialized” climate simulations often requirerequire(bias/drift) corrections: Application of these (bias/drift) corrections: Application of these corrections corrections is not trivial,is not trivial, there is danger of incorrect there is danger of incorrect interpretation.interpretation.

For non-experts it may be safer & perhaps as informative touse output of the first few decades of the ‘long-term’ CMIP5experiments (uncertainty issues will need to be (uncertainty issues will need to be addressed)addressed)

In both cases an ensemble approach is an absolute In both cases an ensemble approach is an absolute necessitynecessity

Decadal climate prediction is still in an exploratory stageDecadal climate prediction is still in an exploratory stage

CMIP5 output will be made available to everyone

Terms of use:

All output available for educational and research use

About half of all output available for unrestricted use.

Extensive documentation will be available describing the models and the experiment conditions.

Model data accessed via a federated Earth System Grid led by PCMDI connecting identical identical accessible/structuredaccessible/structured distributed archives across the world.

Actual location of model data invisible to the user

Data Providers (modeling groups)

Users (climate model analysts)

Node 1

Node 2

Node 3

Node 4

Node 5 Data Archive

ESG Gateway (PCMDI)

Copy of heavily-

used output

Model & expt. documentation

DOI catalog

How will users access CMIP5 model output? ESG

CORDEXCORDEX A Coordinated Regional Downscaling A Coordinated Regional Downscaling ExperimentExperiment Sponsored by the World Climate Research Sponsored by the World Climate Research ProgrammeProgramme

http://wcrp.ipsl.jussieu.fr/SF_RCMTerms.html

Generating an ensemble of high-resolution regional climate projections for the majority of land regions of the globe, based on a suitable sample of CMIP5 GCM projections.

Strong orientation towards user needs: impacts and impacts and adaptationadaptation

General Aims and Plans for CORDEXGeneral Aims and Plans for CORDEX

Provide an ensemble of coordinated Regional Climate Provide an ensemble of coordinated Regional Climate projections for 1950-2100 projections for 1950-2100 (core 1980-2050),(core 1980-2050), for most land- for most land-regions of the globe based on CMIP5 simulations following regions of the globe based on CMIP5 simulations following RCPs 4.5, 8.5 and 2.6RCPs 4.5, 8.5 and 2.6

Make this data available and useable to users, with a Make this data available and useable to users, with a common diagnostic set and format (following CMIP5) at common diagnostic set and format (following CMIP5) at CORDEX archivesCORDEX archives

Provide a framework for testing Regional Climate Models Provide a framework for testing Regional Climate Models and Downscaling techniques for the recent past and future and Downscaling techniques for the recent past and future scenarios.scenarios.

Foster coordination between downscaling efforts around Foster coordination between downscaling efforts around the world & encourage local participation in this process the world & encourage local participation in this process esp .developing nationsesp .developing nations

With CMIP5 provide climate simulation data to support With CMIP5 provide climate simulation data to support IPCC AR5 and impact-adaptation-vulnerability research on IPCC AR5 and impact-adaptation-vulnerability research on longer timescaleslonger timescales

International emphasis on African climate & impacts International emphasis on African climate & impacts coming 2 years: START/WCRP analysis, training & capacity coming 2 years: START/WCRP analysis, training & capacity building activity 2011-12 building activity 2011-12

Uncertainty inUncertainty inregional climateregional climate

projectionprojection

Emission/Emission/ConcentrationConcentration

ScenariosScenarios

AOGCM ConfigurationAOGCM Configuration(Multiple AOGCMs)(Multiple AOGCMs)

Internal variabilityInternal variability(Multiple realizations)(Multiple realizations)

RCD ConfigurationRCD Configuration(Multiple models)(Multiple models)

RCD approachRCD approach(Multiple RCD methods)(Multiple RCD methods)

RegionRegion

Sampling the sources of uncertainty in Sampling the sources of uncertainty in

RCD-based Regional climate projectionsRCD-based Regional climate projections

CORDEX Phase I experiment design CORDEX Phase I experiment design

Model Evaluation Model Evaluation FrameworkFramework

Climate ProjectionClimate ProjectionFrameworkFramework

ERA-Interim BC ERA-Interim BC 1989-20081989-2008

Multiple AOGCMsMultiple AOGCMs

RCP4.5, RCP8.5RCP4.5, RCP8.5some RCP 2.6 runssome RCP 2.6 runs

Regional Projections 1950-2100Regional Projections 1950-2100

Multiple regions (Initial focus on Africa)Multiple regions (Initial focus on Africa)50km resolution (higher in some regions, Europe: 10km)50km resolution (higher in some regions, Europe: 10km)

Regional AnalysisRegional AnalysisRegional DatabanksRegional DatabanksEurope, Korea, S.AfricaEurope, Korea, S.Africa

CORDEX DOMAINS (plus Arctic & Antarctica)

•12 domains with a resolution of 0.44° (approx. 50x50km²)•Focus on Africa : 11 groups committed to run Africa projections•High resolution ~0.11°x0.11° for Europe (~6 institutions)

What has been decided in CORDEXWhat has been decided in CORDEX

1.1. 6-hourly 3D model level fields will be saved by 6-hourly 3D model level fields will be saved by CMIP5 GCMs making climate projections as CMIP5 GCMs making climate projections as boundary forcing for RCMsboundary forcing for RCMs

AAt least 1 RCP4.5 and 1 RCP8.5 member (1950-2100) per t least 1 RCP4.5 and 1 RCP8.5 member (1950-2100) per GCM. Many GCMs will also save an RCP2.6, plus > 1 GCM. Many GCMs will also save an RCP2.6, plus > 1 RCP4.5 memberRCP4.5 member

This data will become available on the CMIP5 data nodes in This data will become available on the CMIP5 data nodes in May to October 2011May to October 2011

2.2. The standard resolution is 50kmThe standard resolution is 50km ((many groups plan to many groups plan to also runalso run

higher resolution for selected domains, e.g. ~10km Europe higher resolution for selected domains, e.g. ~10km Europe ensembleensemble))

50km base resolution to include as many groups as 50km base resolution to include as many groups as possiblepossible

3.Before GCM forced runs for a given region RCMs 3.Before GCM forced runs for a given region RCMs must be must be run with ERA-interim (1989-2008) for the same run with ERA-interim (1989-2008) for the same region region 4.An initial (international) focus for climate 4.An initial (international) focus for climate projections will beprojections will be AfricaAfrica with an aim to provide input to the IPCC AR5 with an aim to provide input to the IPCC AR5 processprocess

Seasonal Mean Precipitation JAS 1998-2008

Seasonal Mean Precipitation Bias: Land GPCC

Annual Cycle spatially averaged precipitation

Annual Cycle spatially averaged precipitation

Annual Cycle spatially averaged precipitation

Annual Cycle of West African Monsoon5-day mean rainfall averaged between 10W to 10E

Health impact examples: Malaria Incidence over Africa: 2000-2008

Mean annual malaria Incidence (%) based on the Liverpool Malaria Model (LMM) for the period 2000-2008.

The LMM has been driven by different observations (NCEP, ERAINTERIM and a hybrid run using GPCP rainfall and ERAINT temperatures) and one RCM from the CORDEX project (SMHI-RCA35, ERAINT control exp).

The RCM fairly well reproduces the mean annual distribution of malaria incidence with respect to the GPCP-ERAINT run..

A.MorseU. Liverpool

Health impact examples: Malaria Prevalence over Africa: 2000-2008

Mean annual malaria Prevalence (%) based on the Liverpool Malaria Model (LMM) for 2000-2008.

The LMM has been driven by different observations (NCEP, ERAINTERIM and a hybrid run using GPCP rainfall and ERAINT temperatures) and one RCM from the CORDEX project (SMHI-RCA35, ERAINT control exp).

The RCM reproduces well the mean annual distribution of malaria prevalence with respect to the GPCP-ERAINT run (best estimate)..

A.MorseU. Liverpool

Annual Cycle of Central African Rainfall Monthly mean rainfall averaged between 10E to 25E

Summary

CMIP5 & CORDEX will deliver an unprecedented set of coordinatedcoordinated Global and Regional climate simulations over the coming ~1-4 years

These data cover both the historical past, near-term predictions and a range of GHG/land-use scenario forced future projections

CORDEX data will provide 50km (higher in some regions) CORDEX data will provide 50km (higher in some regions) ensemblesensemblesof downscaled regional climate projections for most land of downscaled regional climate projections for most land regions ofregions ofthe world for use in impact-adaptation-vulnerability the world for use in impact-adaptation-vulnerability researchresearch

CORDEX has developed regionally-specific, locally-led CORDEX has developed regionally-specific, locally-led evaluation and analysis teams, with coupled capacity evaluation and analysis teams, with coupled capacity building and training activitiesbuilding and training activitiese.g. Africa CORDEX WCRP/START training and analysis e.g. Africa CORDEX WCRP/START training and analysis workshops.workshops.

Both CMIP5 and CORDEX can provide important Both CMIP5 and CORDEX can provide important input to the evolving Climate Service sector for input to the evolving Climate Service sector for regions worldwideregions worldwide