ESTIMATING THE URBAN BIAS OF SURFACE SHELTER TEMPERATURES USING UPPER-AIR AND SATELLITE DATA .2. ESTIMATION OF THE URBAN BIAS

A methodology is presented for estimating the urban bias of surface sh elter temperatures due to the effect of the urban heat island. Multipl e regression techniques were used to predict surface shelter temperatu res based on the time period 1986-89 using upper-air data from the Eur opean Centre for Medium-Range Weather Forecasts to represent the backg round climate, site-specific data to represent the local landscape, an d satellite-derived data-the normalized difference vegetation index (N DVI) and the Defense Meteorological Satellite Program (DMSP) nighttime brightness data-to represent the urban and rural landscape. Local NDV I and DMSP values were calculated for each station using the mean NDVI and DMSP values from a 3 km X 3 km area centered over the given stati on. Regional NDVI and DMSP values were calculated to represent a typic al rural value for each station using the mean NDVI and DMSP values fr om a 1 degrees X 1 degrees latitude-longitude area in which the given station was located. Models for the United States were then developed for monthly maximum, mean, and minimum temperatures using data from ov er 1000 stations in the U.S. Cooperative Network and for monthly mean temperatures with data from over 1150 stations in the Global Historica l Climate Network. Local biases, or the differences between the model predictions using the observed NDVI and DMSP values, and the predictio ns using the background regional values were calculated and compared w ith the results of other research. The local or urban bias of U.S. tem peratures, as derived from all U.S. stations (urban and rural) used in the models, averaged near 0.40 degrees C for monthly minimum temperat ures, near 0.25 degrees C for monthly mean temperatures, and near 0.10 degrees C for monthly maximum temperatures. The biases of monthly min imum temperatures for individual stations ranged from near -1.1 degree s C for rural stations to 2.4 degrees C for stations from the largest urban areas. There are some regions of the United States where a regio nal NDVI value based on a 1 degrees X 1 degrees latitude-longitude are a will not represent a typical ''rural'' NDVI value for the given regi on. Thus, for some regions of the United States, the urban bias of thi s study may underestimate the actual current urban bias. The results o f this study indicate minimal problems for global application once glo bal NDVI and DMSP data become available. It is anticipated that result s from global application will provide insights into the urban bias of the global temperature record.