Intercomparison Between Polarimetric Radar and Satellite Indicators of Storm Severity in Supercells

Recent observational nowcasting of severe weather in supercells mainly has focused on the use of radar data, particularly in the WSR-88D dual-polarization era. However, the launch of GOES-R and the recent advent of GOES-16 high spatial and temporal resolution data collection, has introduced new possibilities for accurate real-time assessment of severe weather potential in supercells. Comparisons are made between derived products from radar and satellite data that act as indicators of storm severity and proxies for storm updraft strength in several supercell cases. The data that are analyzed include available satellite products developed to detect features like overshooting tops (OTs) and determine the amount of cloud-top cooling (CTC), and a polarimetric radar algorithm used to determine the heights of columns of enhanced differential radar reflectivity factor (Z_DR). Also, depending on the location of the specific storm and the availability of data, lightning data and corresponding derived products like “lightning jumps” also can be compared with remote sensing data. These products all can be used to infer changes in storm severity and previously have been shown to be diagnostic or prognostic indicators of severe weather.

The goal of this study is to establish direct relationships between available satellite, polarimetric radar, and lightning products that are all thought to be indicators or predictors of severe weather. Of particular interest is (i) how and when the combined suite of products provide complementary information vs. when a particular product alone provides unique indicators of impending severe weather and (ii) how indicators of storm severity change leading up to important storm processes, including tornado formation. Previous work by the authors on this topic used data from GOES-14 run in Super Rapid Scan Operations for GOES-R (SRSOR) mode, but GOES-R has since launched and several recent severe weather outbreaks have occurred during GOES-16 testing in 2017. The availability and accuracy of GOES-16 data and associated derived products while in ongoing testing mode will determine whether SRSOR or GOES-16 data are presented.