H12E-06
Evaluating the Global Precipitation Measurement mission with NOAA/NSSL Multi-Radar Multisensor: current status and future directions.

Monday, 14 December 2015: 11:35
3022 (Moscone West)
Pierre-Emmanuel Kirstetter, University of Oklahoma Norman Campus, Norman, OK, United States
Abstract:
Accurate characterization of uncertainties in precipitation estimates derived from space-borne measurements is critical for many applications including water budget studies or prediction of natural hazards caused by extreme rainfall events. The GPM precipitation Level II (active and passive) and Level III (IMERG) estimates are compared to the NEXRAD-based precipitation estimates derived from NOAA/NSSL’s Multi-Radar, Multi-Sensor (MRMS) platform. The NEXRAD network has undergone an upgrade in technology with dual-polarization capabilities and the MRMS products, after having been adjusted by rain gauges and passing several quality controls and filtering procedures, are 1) accurate with known uncertainty bounds and 2) measured at a resolution below the pixel sizes any GPM estimates. They are used by a number of NASA investigators to evaluate Level II and Level III satellite precipitation algorithms.

A comparison framework was developed to examine the consistency of the ground and space-based sensors in term of precipitation detection, typology (e.g. convective, stratiform) and quantification. At the Level II precipitation features are introduced to analyze satellite estimates under various precipitation processes. Specific factors for passive (e.g. surface conditions for GMI) and active (e.g. attenuation of the radar signal, non uniform beam filling for DPR) sensors are investigated. Prognostic analysis directly provides feedback to algorithm developers on how to improve the satellite estimates. Comparison with TRMM products serves as a benchmark to evaluate GPM precipitation estimates. A the Level III the contribution of Level II is explicitly characterized and a rigorous characterization is performed to migrate across scales fully understanding the propagation of errors. This cross products characterization acts as a bridge to intercalibrate microwave measurements from the GPM constellation satellites and propagate to the combined and global precipitation estimates. Future perspectives are presented.