Contributions of Storm-Associated Precipitation and its Extreme using Observations

Precipitation extremes can cause socio-economic damage and are often associated with weather phenomena, such as tropical cyclone (TC), extratropical cyclone (ETC), atmospheric river (AR), and mesoscale convective systems (MCS). In this study, we use observational-based datasets with the TempestExtremes feature tracker to quantify the contributions of TC, ETC, AR, MCS to precipitation climatology and extremes. The global quantification is based on NOAA's Climate Prediction Center MORPHing technique product (CMORPH) and NASA's Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) and dynamic fields from ECMWF's ERA5 reanalysis. We also apply the feature tracking to E3SM seasonal hindcasts to better understanding biases in the Energy Exascale Earth System Model (E3SM) associated with these phenomena. This phenomenon-based analysis helps us better understand the characteristic of precipitation on sub-seasonal to seasonal (S2S) time scales and the underlying problems in model physics for precipitation predictions.

(This work is supported by Lawrence Livermore National Laboratory Laboratory Directed Research and Development project 22-ERD-013 and is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-838411)