A Diagnosis of Oceanic Precipitation in IMERG-GMI

Abstract

Diagnosing errors in spaceborne oceanic precipitation estimates is difficult due to complicated multisatellite algorithms and limited surface-based measurements. The Global Precipitation Measurement (GPM) mission helps to alleviate these challenges with NASA’s Integrated MultisatellitE Retrievals for GPM (IMERG) product, which is trans-parently designed to encourage community validation activities, and the GPM Validation Network, which collects observations across global precipitation regimes from over 100 ground-based weather radars to serve as reference datasets for the GPM precipitation products. This study uses the GPM Validation Network’s oceanic precipitation observations from 32 island and coastal radars to diagnose the performance of IMERG V06B and V07B Final Run products during GPM Microwave Imager (GMI) overpasses (i.e., IMERG-GMI) in the period June 2014–September 2021. Errors are traced from the input level 2 (satellite footprint) Goddard profiling algorithm climate (GPROF-CLIM) GMI product through the successive gridding, calibration, and precipitation distribution restoration steps of IMERG’s level 3 (gridded) algorithm. Results highlight that IMERG-GMI V07B outperforms V06B in detecting and quantifying oceanic precipitation, with a significant improvement over high-latitude ocean (V06B: 1143%; V07B: 150%). Furthermore, there is a clear oceanic latitudinal trend in the mean relative bias of IMERG-GMI V07B (high latitude: 150%; midlatitude: 110%; tropical: 241%), which largely traces back to GPROF-CLIM V07 (high latitude: 122%; midlatitude: 28%; tropical: 244%), with bias differences driven by IMERG’s passive microwave calibration scheme. This error tracing approach supports future IMERG algorithm developments by disentangling how algorithm steps enhance or mitigate errors.