Improvement of the Rain/No-Rain Classification Method for Microwave Radiometers Over the Tibetan Plateau.

This letter identifies causes of the deterioration of the Global Satellite Mapping of Precipitation rain detection over the Tibetan Plateau during the summer monsoon season. Using the rain/no-rain classification (RNC) method over the Plateau, observed brightness temperature (Tb) at 21 (23) GHz from the Tropical Rainfall Measuring Mission Microwave Imager (the Defense Meteorological Satellite Program Special Sensor Microwave Imager) [Tb(21 V) and Tb(23 V)], and surface emissivity ( $\varepsilon )$ was substituted for surface temperatures (Ts) to exclude areas of low Ts as snow cover because it is difficult to distinguish between the scattering signals of precipitation and snow cover. A case study demonstrates that rain systems are excluded because Ts is often below the threshold for snow cover due to the use of an inadequate value for $\varepsilon $ (constant value throughout the year), even though a rain scattering signal at high-frequency channels under no snow cover is evident. After $\varepsilon $ is replaced with values from a monthly mean satellite observation-based land surface emissivity database, rainfall detection is improved. In addition, it is suggested that a database of RNCs should also consider diurnal variations in Tb(21 V) and Tb(23 V) due to large diurnal differences over the Plateau. [ABSTRACT FROM PUBLISHER]