LOCAL TEMPERATURE ESTIMATION UNDER CLIMATE-CHANGE

A methodology to estimate the space-time distribution of daily mean te mperature under climate change is developed and applied to a central N ebraska case study. The approach is based on the analysis of the Marko v properties of atmospheric circulation pattern (CP) types, and a stoc hastic linkage between daily (here 500 hPa) CP types and daily mean te mperatures. Historical data and general circulation model (GCM) output of daily CP corresponding to 1 x CO2 and 2 x CO2 scenarios are consid ered. The relationship between spatially averaged geopotential height of the 500 hPa surface - within each CP type - and daily mean temperat ure is described by a nonparametric regression technique. Time series of daily mean temperatures corresponding to each of these cases are si mulated and their statistical properties are compared. Under the clima te of central Nebraska, the space-time response of daily mean temperat ure to global climate change is variable. In general, a warmer climate appears to cause about 5-degrees-C increase in the winter months, a s maller increase in other months with no change in July and August. The sensitivity of the results to the GCM utilized should be considered.