The role of northern Arabian Sea surface temperature biases in CMIP5 model simulations and future projections of Indian summer monsoon rainfall Richard Levine Thanks to: Andy Turner, Deepthi Marathayil, Gill Martin
Table of Contents CMIP3 future monsoon projections Impact of Arabian Sea SST bias on (1) PD climate in HadGEM3 simulations and CMIP5 models (2) Future projections in time-slice experiments and CMIP5
Future monsoon projections
Indian monsoon in the future (1) from IPCC AR4, change for A1B scenario (Meehl et al, 2007) CMIP3: Small increase in summer Indian monsoon rainfall, but inter-model spread is larger than signal Large surface warming over Indian Ocean
Indian monsoon in the future (2) CMIP3 analysis (from Ueda et al 2006) Indian Ocean warming enhances moisture supply for monsoon rainfall, but balanced by (1) weakening of meridional tropospheric temperature gradient (2) enhanced SST warming in central and eastern Pacific (cf. El Nino)
Arabian Sea is important moisture source for monsoon rainfall from Gimeno et al (2000): relative contribution from major moisture sources (defined as areas with max vertically integrated moisture flux divergence) to JJA rainfall calculated using Lagrangian particle trajectories with ECMWF analyses from Levine and Turner (2011): strong monsoon years depend on additional moisture across Arabian Sea Composites of STRONG minus WEAK monsoon rainfall years (1958-2001): Vectors: anomaly of vertically integrated ERA40 MFL Colours: anomaly of rain-gauge rainfall
Northern Arabian Sea cold SST biases common in CMIP5 models Cold SST bias develops in winter, persists into summer monsoon season Cold bias may affect present day simulation, and weaken future moisture flux enhancement through non-linearity of Clausius-Clapeyron relationship
Impact of Arabian Sea SST bias on PD climate
Arabian Sea SST bias in recent development version of HadGEM3 from Levine and Turner, Clim Dyn, 2011
Impact of Arabian Sea SST bias in HadGEM3 precip (JJAS) AMIP control 850hPa winds (JJAS) ~30% reduction in summer monsoon rainfall in coupled model compared to equivalent AMIP run Inter-annual variability in observations is only ~10% coupled minus AMIP Idealised AMIP experiments decomposing elements of coupled model SST bias show this is mainly due to cold Arabian Sea SST bias AMIP forced by coupled SST minus AMIP from Levine and Turner, Clim Dyn, 2011
Impact of Arabian Sea SST bias in HadGEM3 (2) surface latent heat flux anomaly (W/m2) Idealised AMIP experiment Applying coupled model SST bias 1 & 2: rainfall (colours) and VINT moisture flux anoms coupled minus AMIP Impact in AMIP tests is direct and local effect of SST bias by weakening evaporation and moisture fluxes during monsoon season from Levine and Turner, Clim Dyn, 2011
CMIP5 models: historical rainfall bias JJAS Many models have large biases Dry bias over Indian land common
CMIP5 COLD and WARM composites comparison of historical simulations Composites created based on MAM magnitude of Arabian Sea SST bias in historical simulations (1986-2005) 5 models per composite,1 model per centre, no Hadley Centre models COLD composite WARM composite Historical SST bias- May COLD (large SST bias) composite: WARM (small SST bias) composite: NorESM1-M, inmcm4, IPSL-CM5ALR, MRI-CGCM3, CSIRO-mk3-6-0 MPI-ESM-LR, MIROC5, CCSM4, CanESM2, CNRM-CM5
CMIP5 COLD and WARM composites Monsoon rainfall (taken over wider monsoon region: 65-95 E, 10-30 N) limited in COLD models (particularly early monsoon) composite means
Development of bias during winter: consistent with mechanism in HadGEM3 (LT2011) and CMIP3 (Marathayil et al 2012) 1- continental cold surface temperature bias strengthens winter monsoon northerlies 2- excessive equatorial convection further draws in winds from over Arabian Sea Other factors influence COLD-WARM differences: COLD models have weaker ΔTT, consistent with mechanisms forcing SST bias T_cont T_ocean
Impact of bias in early monsoon: pattern and magnitude similar to HadGEM3 impact of Arabian Sea SST bias Arabian Sea SST bias strongly correlated with monsoon rainfall, ΔTT change may also contribute
Impact of Arabian Sea SST bias on future projections
HadGEM2 AMIP FUTURE time-slice experiments (27-year runs) cold Arabian Sea SST bias can limit future rainfall increases (1) ΔSST from HadGEM2-ES RCP8.5: SST = OBS + [FUT PD] (removes main effects of coupled model SST biases) (2) CO2 and trace gas concentrations from RCP8.5 run (~year 2100) (3) Additionally HadGEM2-ES climatological monthly SST bias applied over Arabian Sea and Bay of Bengal Arabian Sea SST forcing in 4 experiments 28% increase w/o bias 19% increase with bias
HadGEM2 AMIP FUTURE time-slice experiments Enhanced rainfall inhibited over C India, E Arabian Sea, Bay of Bengal, particularly during enhanced monsoon phase in August (change ~20% less with bias)
CMIP5 future RCP8.5 projections composite mean projected rainfall changes similar for COLD and WARM inter-model spread for future scenario more constrained for COLD composite in early monsoon, particularly negative changes
CMIP5 future RCP8.5 projections only small differences over Indian land (Himalayas) in mean rainfall changes in June between COLD and WARM composites
CMIP5 future RCP8.5 projections inter-annual variability of rainfall over India during early monsoon is enhanced in future (Clausius-Clapeyron), despite no change to mean (balanced by delay in ΔTT reversal, E/C Pacific warming) enhancement over C India is much weaker in COLD composite (cold base state), enhanced variability mainly over ocean/himalayas (weak mean state over India)
Conclusions
Conclusions Northern Arabian Sea cold SST biases are common in CMIP5 models Development of biases occurs in winter due to atmospheric/land processes, similar to CMIP3 analysis (Marathayil et al. 2012) CMIP5 models with large Arabian Sea SST biases underestimate monsoon rainfall, similar to direct impact of SST bias in HadGEM3 AMIP time-slice experiments suggest Arabian Sea cold SST bias can limit future rainfall increases (cold base state: starting lower down on Clausius-Clapeyron curve) Appears that such an impact on CMIP5 mean state future rainfall changes is limited However, SST bias, through cold base state and weak mean state over India, may constrain inter-model spread and mask large future enhancement in early monsoon rainfall variability over Indian land References: RC Levine, AG Turner, D Marathayil, GM Martin (2012), The role of northern Arabian Sea surface temperature biases in CMIP5 model simulations and future projections of Indian summer monsoon rainfall, submitted to Climate Dynamics RC Levine, AG Turner (2011), Dependence of Indian monsoon rainfall on moisture fluxes across the Arabian Sea and the impact of coupled model sea surface temperature biases, Climate Dynamics, in press, doi:10.1007/s00382-011-1096-z D Marathayil, L Shaffrey, A Turner, J Slingo, Examination of Arabian Sea SST biases in the HiGEM high resolution coupled climate Crown copyright Office model and the CMIP3Met multi-model dataset, in preparation
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