Cross-Evaluation of Reflectivity from NEXRAD and Global Precipitation Mission during Extreme Weather Events

During extreme events such as tropical cyclones, the precision of sensors used to sample the meteorological data is vital to feed weather and climate models for storm path forecasting, quantitative precipitation estimation, and other atmospheric parameters. For this reason, periodic data comparison between several sensors used to monitor these phenomena such as ground-based and satellite instruments, must maintain a high degree of correlation in order to issue alerts with an accuracy that allows for timely decision making. This study presents a cross-evaluation of the radar reflectivity from the dual-frequency precipitation radar (DPR) onboard the Global Precipitation Measurement Mission (GPM) and the U.S. National Weather Service (NWS) Next-Generation Radar (NEXRAD) ground-based instrument located in the Caribbean island of Puerto Rico, USA, to determine the correlation degree between these two sensors’ measurements during extreme weather events and normal precipitation events during 2015–2019. GPM at Ku-band and Ka-band and NEXRAD at S-band overlapping scanning regions data of normal precipitation events during 2015–2019, and the spiral rain bands of four extreme weather events, Irma (Category 5 Hurricane), Beryl (Tropical Storm), Dorian (Category 1 hurricane), and Karen (Tropical Storm), were processed using the GPM Ground Validation System (GVS). In both cases, data were classified and analyzed statistically, paying particular attention to variables such as elevation angle mode and precipitation type (stratiform and convective). Given that ground-based radar (GR) has better spatial and temporal resolution, the NEXRAD was used as ground-truth. The results revealed that the correlation coefficient between the data of both instruments during the analyzed extreme weather events was moderate to low; for normal precipitation events, the correlation is lower than that of studies that compared GPM and NEXRAD reflectivity located in other regions of the USA. Only Tropical Storm Karen obtained similar results to other comparative studies in terms of the correlation coefficient. Furthermore, the GR elevation angle and precipitation type have a substantial impact on how well the rain reflectivity correlates between the two sensors. It was found that the Ku-band channel possesses the least bias and variability when compared to the NEXRAD instrument’s reflectivity and should therefore be considered more reliable for future tropical storm tracking and tropical region precipitation estimates in regions with no NEXRAD coverage.