P1.12
Pattern and trend analysis of temperature in a set of seasonal ensemble simulations
Mei Zhao, COLA, Calverton, MD; and P. Dirmeyer
Eighteen years of global climate model ensemble simulations have been performed with observed sea surface temperature (SST) to assess the ability of dynamical models to predict seasonal-interannual climate variations during boreal summer. In addition, test suites have been designed to assess the role in climate trends, predictability of land-surface initial conditions, systematic errors of precipitation and radiation fluxes at the land surface, and increasing CO2. The model reproduces a global warming trend in surface temperature similar to observed. This appears to be attributable to the influence of SST. However, flux replacement and atmospheric initialization can reduce this SST influence even though those changes can improve the spatial pattern of surface air temperature. The external factors (mainly due to downward longwave radiation) affect the temperature in different ways, e.g. spatial pattern, time scale, and the magnitude of warm trend. The results also show that land surface interaction not only impacts surface air temperature, but also has an effect on the higher levels of the troposphere.
Poster Session 1, Climate Modeling and Observed Climate Change (Hall 4AB)
Tuesday, 13 January 2004, 9:45 AM-11:00 AM, Hall 4AB
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