Alfredo Ruiz-Barradas Sumant Nigam North American Hydroclimate Variability in IPCC’s 20th Century Climate Simulations Alfredo Ruiz-Barradas Sumant Nigam Department of Atmospheric and Oceanic Science University of Maryland 2006 Joint Assembly Meeting Baltimore, Maryland May 23, 2006

Motivation To better know the structure and mechanisms of precipitation variability in state-of-the-art climate models At issue: Model validation Relative contributions of local (evaporation) and remote (moisture fluxes) water sources

Outline The data sets. Annual Cycle of Precipitation Precipitation variability over the Great Plains. Structure of hydroclimate fields and their relative contributions associated with precipitation anomalies. The surface temperature signature. Conclusions

Data Sets US-Mexico retrospective precipitation analysis:1951-1998. North American Regional Reanalysis (NARR): 1979-1998. Simulations of the Climate of the 20th Century: 1951-1998. Historical Forcing: Solar irradiance Volcanic and anthropogenic aerosols (optical depth) Ozone, Carbon Dioxide Other well mixed greenhouse gases Resolution: Horizontal: R30 (96x80) Gaussian grid Vertical: 17-pressure levels

MODELS

MODELS

Precipitation: Annual Cycle & Annual Mean (1979-1998) The annual cycle diminishes and occurs earlier in the summer months from tropical Mexico to central US Weak maximum over southern US in winter/spring months Maximum over northwestern US In January Models do well over US northwest in winter But seem to have some problems over southeastern and central US in spring and summer

JJA Precipitation Climatology

Precipitation: JJA STD What makes the observed and Simulated STD? Great Plains Precipitation Index is defined over the area of maximum STD in observations US-MEX 0.91 mm/day 0.63 mm/day 1.00 mm/day min 1.12 mm/day 0.92 mm/day Max 0.72 mm/day 0.78 mm/day

Histogram of Precipitation Events According to GPP Indices (1951-1998) 0.91 mm/day 76<0 68>0 1.00 mm/day 0.63 mm/day Small STD due to a concentration of small events 77<0 67>0 67<0 77>0 Large STD due to extreme events 1.12 mm/day 0.92 mm/day 75<0 69>0 72<0 72>0 0.72 mm/day 0.78 mm/day 73<0 71>0 73<0 71>0

Regressed Precipitation Anomalies on JJA GPP Indices 0.89 mm/day 1.04 mm/day 0.63 mm/day 1.13 mm/day 0.92 mm/day 0.73 mm/day 0.78 mm/day

Regressed Convective Precipitation on GPP Indices

Regressed Moisture Flux Anomalies on JJA GPP Indices 0.66 mm/day 0.45 mm/day 0.46 mm/day 0.40 mm/day 0.83 mm/day 0.91 mm/day 0.66 mm/day

Regressed Evaporation Anomalies on JJA GPP Indices 0.22 mm/day 0.69 mm/day 0.04 mm/day 0.59 mm/day 0.14 mm/day -0.04 mm/day 0.06 mm/day CI=1/3 of that in P & MFC

So far, we have the following picture regarding the relative controls of precipitation variability: Evaporation dominates over Moisture Flux Convergence: CCSM3, GFDL-CM2.1 Moisture Flux Convergence largely dominates over Evaporation: GISS-EH, MIROC3.2(hires) Moisture Flux Convergence dominates over Evaporation: NARR/US-MEX PCM,UKMO-HadCM3 Is precipitation recycling the same in CCSM3 and GFDL-CM2.1?

Autocorrelation of GPP Indices Standard Errors Significance at the 0.05 level CCSM3 & GFDL-CM2.1 do not recycle precipitation in the same way!!

Regressed Surface Temperature Anomalies on JJA GPP Indices Large evaporation anomalies have implications on the surface energy balance and so on surface temperature, the variable of choice when analyzing warming scenarios -0.8 K -2.4 K -0.3 K -1.9 K -0.9 K -0.0 K -0.7 K

Conclusions NARR/US-Mexico data sets suggest that remote water sources (moisture fluxes) dominate over local water sources (evaporation) in the generation of interannual rainfall variability over the Great Plains during the warm-season. Three different hierarchy of process in models: MFC >> E: MIROC3.2(hires), GISSEH, GISS-ER MFC > E: UKMO-HadCM3, PCM E > MFC: CCSM3, GFDL-CM2.1, GFDL-CM2.0, GISS-AOM Deficient simulation of moisture pathways feeding the Great Plains. In consequence: regional hydroclimate simulations and predictions remain challenging for global models, at least in the context of variability over the Great Plains.