International efforts in Climate Modeling Projections, Predictions and Downscaling Coordinated by the World Climate Research Program (WCRP) CMIP5: The 5th Coupled Model Intercomparison Project CORDEX: A Coordinated Regional Downscaling Experiment Colin Jones Rossby 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, 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, radiative forcing 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 Modeling Aims to improve our ability to simulate all processes that influence the response of the climate system to increasing greenhouse gases Cloud Feedbacks Cloud Feedbacks Carbon-Climate Feedback (Ocean and Terrestrial) Carbon-Climate Feedback (Ocean and Terrestrial) Aerosol Feedbacks Aerosol Feedbacks Sea-Ice/Snow Feedbacks Sea-Ice/Snow Feedbacks Ocean circulation changes Ocean circulation changes Ice Sheets/Glacier response Ice Sheets/Glacier response Sea-level changes Sea-level changes Ocean acidification and ecosystem response Ocean acidification and ecosystem response Permafrost and Methane Release Permafrost and Methane Release To better constrain the lower and upper bounds of anthropogenic climate change requires (an accurate and complete) representation of complex and interacting process in Earth System Models

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 RCP scenarios for the 21th century Possibly extend with more RCP scenarios, 1% CO 2 increase, … CMIP5: centennial projections 20th century control RCP8.5 RCP4.5 Spin-up 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 contained in the initial state of the system committed warming due to previous GHG forcing - committed warming due to previous GHG forcing natural variability of the system - natural variability of the system Tom Delworth GFDL (i) observe this information assimilate it Assuming we can (i) observe this information (ii) assimilate it in our models,(iii) the variability has a predictable component in our models, (iii) the variability has a predictable component and and (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 problem

The Atlantic Meridional Oscillation index A 10-yr moving average of annual North Atlantic SST anomalies Linked to variability in the Atlantic Meridional Overturning Circulation crucial to simulate the time evolution of AMOC for decadal prediction

Global annual mean surface temp (T S ) Global annual mean ocean heat content in upper 113m (H) There appears to be some increased skill (in a quantitative sense) when observations are included in coupled climate model predictions Results from the UK Met. Office DePreSys integrations D. Smith etal. UKMO

CMIP5: decadal prediction experiments 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 research topic: Targeted for ~1-20 year climate services ? Timescale : 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 coming decade (and beyond) will result from the forced GHG response not the initialized climate state. Results from initialized climate simulations often require (bias/drift) corrections: Application of these corrections is not trivial,there is danger of incorrect interpretation. is not trivial, there is danger of incorrect interpretation. For non-experts it may be safer & perhaps as informative to use output of the first few decades of the long-term CMIP5 (uncertainty issues will need to be addressed) experiments (uncertainty issues will need to be addressed) In both cases an ensemble approach is an absolute necessity Decadal 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. identical accessible/structured Model data accessed via a federated Earth System Grid led by PCMDI connecting identical accessible/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

CORDEX A Coordinated Regional Downscaling Experiment A Coordinated Regional Downscaling Experiment Sponsored by the World Climate Research Programme Sponsored by the World Climate Research Programme 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. impacts and adaptation Strong orientation towards user needs: impacts and adaptation

General Aims and Plans for CORDEX Provide an ensemble of coordinated Regional Climate projections for (core ), for most land-regions of the globe based on CMIP5 simulations following RCPs 4.5, 8.5 and 2.6 Make this data available and useable to users, with a common diagnostic set and format (following CMIP5) at CORDEX archives Provide a framework for testing Regional Climate Models and Downscaling techniques for the recent past and future scenarios. Foster coordination between downscaling efforts around the world & encourage local participation in this process esp.developing nations With CMIP5 provide climate simulation data to support IPCC AR5 and impact-adaptation-vulnerability research on longer timescales International emphasis on African climate & impacts coming 2 years: START/WCRP analysis, training & capacity building activity

Uncertainty in regional climate projection Emission/ConcentrationScenarios AOGCM Configuration (Multiple AOGCMs) Internal variability (Multiple realizations) RCD Configuration (Multiple models) RCD approach (Multiple RCD methods) Region Sampling the sources of uncertainty in RCD-based Regional climate projections

CORDEX Phase I experiment design Model Evaluation Framework Climate Projection Framework ERA-Interim BC Multiple AOGCMs RCP4.5, RCP8.5 some RCP 2.6 runs Regional Projections Multiple regions (Initial focus on Africa) 50km resolution (higher in some regions, Europe: 10km) Regional Analysis Regional Databanks Europe, 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 CORDEX 1.6-hourly 3D model level fields will be saved by CMIP5 GCMs making climate projections as boundary forcing for RCMs A t least 1 RCP4.5 and 1 RCP8.5 member ( ) per GCM. Many GCMs will also save an RCP2.6, plus > 1 RCP4.5 member A t least 1 RCP4.5 and 1 RCP8.5 member ( ) per GCM. Many GCMs will also save an RCP2.6, plus > 1 RCP4.5 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 The standard resolution is 50km ( many groups plan to also run higher resolution for selected domains, e.g. ~10km Europe ensemble ) higher resolution for selected domains, e.g. ~10km Europe ensemble ) 50km base resolution to include as many groups as possible 50km base resolution to include as many groups as possible 3.Before GCM forced runs for a given region RCMs must be run with ERA-interim ( ) for the same region run with ERA-interim ( ) for the same region 4.An initial (international) focus for climate projections will be Africa with an aim to provide input to the IPCC AR5 process Africa with an aim to provide input to the IPCC AR5 process

Seasonal Mean Precipitation JAS

Seasonal Mean Precipitation Bias: Land GPCC

Annual Cycle spatially averaged precipitation

Annual Cycle of West African Monsoon 5-day mean rainfall averaged between 10W to 10E

Health impact examples: Malaria Incidence over Africa: Mean annual malaria Incidence (%) based on the Liverpool Malaria Model (LMM) for the period 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.Morse U. Liverpool

Health impact examples: Malaria Prevalence over Africa: Mean annual malaria Prevalence (%) based on the Liverpool Malaria Model (LMM) for 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.Morse U. Liverpool

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

Summary coordinated CMIP5 & CORDEX will deliver an unprecedented set of coordinated 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) ensembles of downscaled regional climate projections for most land regions of the world for use in impact-adaptation-vulnerability research CORDEX has developed regionally-specific, locally-led evaluation and analysis teams, with coupled capacity building and training activities e.g. Africa CORDEX WCRP/START training and analysis workshops. Both CMIP5 and CORDEX can provide important input to the evolving Climate Service sector for regions worldwide