Abstract
Seasonal differences in the calibration of overland passive microwave rain retrieval are investigated using Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and precipitation radar (PR). Four geographic regions from southern Africa, South Asia, the Amazon basin, and the southeastern United States are selected. Three seasons are compared for each region. Two scenarios of algorithm calibration are considered. In the first, the parameter sets are derived by calibrating the TMI algorithm with PR in each season. In the second scenario, common parameter sets are derived from the combined dataset of all three seasons. The parameter sets from both scenarios are then applied to the validation dataset of each season to determine the effect of seasonal calibration. Furthermore, calibration parameters from one season are also applied to another season, and results are compared against those derived using the season’s own parameters. Appreciable seasonal differences are observed for the U.S. region, while there are no significant differences between using individual seasonal calibration and the all-season calibration for the other regions. However, using one season’s parameter set to retrieve rainfall for another season is associated with increased uncertainty. It is also shown that the performance of the retrieval varies by season.
Corresponding author address: Prof. Emmanouil N. Anagnostou, Civil and Environmental Engineering, U-37, University of Connecticut, Storrs, CT 06269. Email: manos@engr.uconn.edu
