Estimating the urban bias of surface shelter temperatures using upper-air and satellite data. Part I: development of models predicting surface shelter temperatures

Abstract

Multiple regression techniques were used to predict surface shelter temperatures based on the time period 1986-89 using upper-air data from the European Centre for Medium-Range Weather Forecasts to represent the background climate and site-specific data to represent the local landscape. Initial correlation analyses revealed that data from 700 mb were sufficient to represent the upper-air or background climate. Three-, six-, and full-variable models were developed for comparative purposes. Inferences about the variables selected for the various models were easier for the GHCN models, which displayed month-to-month consistency in which variables were selected, than for the COOP models, which were assigned a different list of variables for nearly every month. These and other results suggest that global calibration is preferred because data from the global spectrum of physical processes that control surface temperatures are incorporated in a global model. -from Authors