Using Space-Based Lightning Observations to Enhance Geostationary Satellite Rainfall Estimation

Lightning observations provide a wealth of information regarding the kinematic and microphysical characteristics of convection therefore it has great potential for improving the estimation of convective rainfall. The recent launches of the Global Lightning Mapper (GLM) onboard the GOES-16 and the Lightning Imaging Sensor (LIS) to the ISS provide an excellent opportunity to apply lightning observations for enhancing satellite rainfall estimation.

We have quantified the relationships between lightning, convective rain volume, cold cloud coverage, and bulk precipitation microphysics for both tropical and mid-latitude convection (warm season) based on observations from the Global Precipitation Mission (GPM) and GOES-16. The results are first applied to an IR-only technique, the Convective-Stratiform Technique (CST). The lightning-based statistical relationships are then used to develop/refine a lightning-enhanced IR rainfall estimation algorithm (called CST-L). The application of the CST-L algorithm to an independent GOES-16 IR and lightning database showed significant improvement compared to IR-only rainfall estimation when validated by GPM passive microwave and DPR precipitation radar rainfall estimates. The CST-L significantly improves the classification of convective rain areas, reduces false alarm of heavy precipitation, and better represents rainfall variability.

The CST-L algorithm will be further improved by including environmental variables such as wind shear between 850 and 200 hPa, CAPE, and total precipitable water (850-500 hPa) as derived from reanalysis data. Our updated lightning-enhanced rainfall estimation algorithm will be further validated against rain estimates from GPM, ground-based radar, and the operational GOES-16 rainfall product (SCaMPR). This effort will make the geosynchronous satellite precipitation information uniquely important, providing more accurate (and highly time resolved) precipitation estimates for supplementing ground-based and orbital satellite-based estimates, especially in remote mountainous areas and over the open oceans.