Combining GOES-R and GPM to improve GOES-R rainrate product

This study analyses relationships between lightning flash rate, radar reflectivity, and passive microwave brightness temperature (Tb) for convective and stratiform precipitation over land using multi-year data from the Tropical Rainfall Measuring Mission (TRMM) satellite. A new convective and stratiform index (CSI, an estimate of convective areal fraction) for the TRMM Microwave Imager (TMI) is developed from the analysis. Four years of TRMM TMI, Lightning Imaging Sensor (LIS), and Precipitation Radar (PR) data (2002-2005) are co-located and remapped to 0.1 and 0.05 degree grids for analysis. The scientific objective of this study is to understand the relationship between lightning and active and passive microwave observations, and explore ways of using lightning information to enhance the discrimination between convective and stratiform precipitation in TMI rain rate retrieval algorithm. PR provides the reference convective and stratiform classification, and is coincident with LIS which reports lightning parameters such as the occurrence (yes or no) and flash rates. Analysis of ~14 million coincident precipitating TRMM measurements over land (i.e., excluding oceans and coasts) reveals that 6% of rain data have lightning flash rates greater than zero. For all lightning data, 60% have 0-1 fl/min, 28% have 1-2 fl/min, and 12% have flash rates greater than 2 fl/min. Overall, 86.5 % (13.5%) of lightning occurred in convective (stratiform) precipitation. In other words, stratiform rainfall is predominant when LIS detects no lightning, and that the convective rain probability increases with increasing lightning frequency. For example, 34% of rainfall is convective for low flash rates (0-1 fl/min), whereas the convective probability increases to 99.7% for high flash rates (>= 2 fl/min). This study develops a simple method that incorporates lightning into the CSIto test if lightning can help passive microwave (PM) delineate convective and stratiform precipitation. LIS lightning occurrence and flash rates (i.e., no flash, 0-1 fl/min, 1-2 fl/min, and > 2 fl/min) are used to pre-classify TMI Tbs into four groups of increasing convective probability. Multi-variable linear regression is then applied to each group to derive the CSI. Results reveal that lightning information primarily improves the identification of highly convective rainfall by correctly shifting microwave observations previously identified as moderate to highly convective. Alternatively, the absence of lightning also helps PM to identify likely stratiform. Overall, including lightning information results in a decrease of bias error of 6% and a small increase in RMS error of 4.5% on the entire range of rainfall.