Outline. Introduction to the downscaling approach GCM selection SST bias correction CCAM model features Climate Projections for Vietnam
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1 Outline Introduction to the downscaling approach GCM selection SST bias correction CCAM model features Climate Projections for Vietnam
2 Rationale: why do we need more detail? Understand the likely effects of climate change at the local level. Help identify the people and sectors at risk through more localised climate change projections Partnership between CSIRO, IMHEN and the Hanoi University of Science to help refine Vietnam s climate change projections Evidence based climate change information that can be understood by provincial and local decision makers
3 NEW INFORMATION: USING THE LATEST SCIENTIFIC APPROACHES New greenhouse gases (GHG) and aerosols (CMIP5) Latest global climate simulations (CMIP5) High-resolution projections (10 km) Seasonal analysis Regional sea-level assessment Improved data access
4 COMPARISON OF GREENHOUSE GAS SCENARIOS CO 2 concentration (ppmv) New Old RCP 8.5 RCP 4.5 (Higher) (Lower)
5 Dynamical Downscaling Start with Global Climate Model projections Select 6 global models and 2 scenarios lower: RCP4.5 and higher: RCP8.5 Drive regional models with bias-corrected sea surface temperatures (SST) and sea ice Two regional climate models (CCAM and RegCM4) Global model SST and sea ice Global CCAM 50 km Regional CCAM 10 km Correction applied Additional Downscaling
6 Terrain ACCESS 1.0 (global) RegCM4 (20km) (regional) CCAM (10km) (regional) Observations (1km) (Meters)
7 GCM Selection
8 GCM Selection Requirements Good performance in present climate Simulation of rainfall, air temperature etc. Reproduce observed trends Good SSTs ENSO pattern/frequency SST distribution Good spread of climate change signals 8
9 GCM Selection Evaluation studies 24 CMIP5 models > 20 evaluation studies 6 publications with rankings + evaluation used within the project Peer-reviewed or submitted ACCESS1.0 ACCESS1.3 CanESM2 CCSM4 CNRM-CMS CSIRO-Mk3-6-0 FGOALS-g2 FGOALS-s2 GFDL-CM3 GFDL-ESM2M GISS-E2-H HadCM3 HadGEM2-CC HadGEM2-ES inmcm4 IPSL-CM5A-LR IPSL-CM5A-MR MIROC4h MIROC5 MIROC-ESM MIROC-ESM-CHEM MPI-ESM-LR MRI-CGCM3 NorESM1-M 9
10 GCM Selection Rankings GCMs Bhend (pers. communication) Suppiah (2012, HRD VN) Z-score Temp trend RMSE Temp Watterson et al. (Aust) RMSE Prec PC Prec M-Score M-Score No. ENSO Watterson et al. (Kont) Grose et al. (2012, submitted) Kim and Yu (2012, GRL) RMSE N3.4 Corr N3.4 Std N3.4 Cor EP ENSO EOF1 Cor CP ENSO EOF1 ACCESS ACCESS CanESM CCSM CNRM-CMS CSIRO-Mk FGOALS-g FGOALS-s GFDL-CM GFDL-ESM2M GISS-E2-H HadCM HadGEM2-CC HadGEM2-ES Inmcm IPSL-CM5A-LR IPSL-CM5A-MR MIROC4h MIROC MIROC-ESM MIROC-ESM-CHEM MPI-ESM-LR MRI-CGCM NorESM1-M Kug et al. (2012, ERL) Cor N3 N4
11 GCM Selection Final ranking The rankings of the 6 individual studies are averaged to yield a final ranking of the models. Rank GCM Average Score 1 CNRM-CM CCSM ACCESS NorESM1-M ACCESS MPI-ESM-LR GFDL-CM HadGEM2-CC MIROC4h MIROC GFDL-ESM2M MRI-CGCM HadCM IPSL-CM5A-MR HadGEM2-ES FGOALS-g CSIRO-Mk inmcm CanESM MIROC-ESM-CHEM GISS-ES-H IPSL-CM5A-LR FGOALS-s MIROC-ESM
12 GCM Selection climate change signal JJA - good spread 12
13 Method SST correction Observations daily optimum interpolation SST & SIC (Reynolds et al., 2007) 1/4 resolution for Method adjust variance adjust mean OBS GCM frequency SST Modifications variance correction decreases linearly with latitude no variance correction North (South) of 50 N ( S) reduction of bias correction with sea ice concentration 13
14 SST bias correction Results: SST BIAS ACCESS1.0 JAN JUL original after correction (K) 14
15 SST bias correction Results: SST variance ACCESS1.0 (January) ACCESS1.0 Observed Bias & Variance corrected Mean SSTs SST Stdev 15
16 Conformal Cubic Atmospheric Model Developed at CSIRO for over 20 years First 3D cubic atmospheric model in the world CCAM is highly computationally efficient for comparable accuracy. CCAM can run on 25,000+ core supercomputers, or as a distributed system on laptops. New features Urban model Parallel IO and improved scaling New model: flux form on gnomic grid Global Climate Model (~200 km) or Analyses Bias and variance correct SST Global CCAM (~50 km) Additional downscaling with spectral filter Stretched CCAM (~10 km)
17 Thank you Jack Katzfey t e Jack.Katzfey@csiro.au w
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