This document provides a basic set of documentation for the data products available from the GPM Ground Validation System (GVS) Validation Network (VN). In the GPM era the VN performs a direct match-up of GPM’s space-based Dual-frequency Precipitation Radar (DPR) data with ground radar data from the U.S. network of NOAA Weather Surveillance Radar-1988 Doppler (WSR-88D, or “NEXRAD”). Ground radar networks from international partners are also part of the VN.
This excerpt from the November 2014 edition of The Earth Observer provides a summary of the activities at the PMM Science Team Meeting which took place from August 4 - 7, 2014. The PMM program supports scientific research, algorithm development, and ground-based validation activities for the Tropical Rainfall Measuring Mission (TRMM) and the Global Precipitation Measurement (GPM) Core Observatory that launched on February 27, 2014.
HIWRAP is under the wing in the black compartment; the Cloud Radar System is under the other wing and is not visible; and the EXRAD radar is in the extended nose cone.
Rain, ice, hail, severe winds, thunderstorms, and heavy fog – the Appalachian Mountains in the southeast United States have it all. On May 1, NASA begins a campaign in western North Carolina to better understand the difficult-to-predict weather patterns of mountain regions. The field campaign serves as ground truth for measurements made by the Global Precipitation Measurement (GPM) mission's Core Observatory.
The Global Precipitation Measurement (GPM) Core Observatory, launched on Feb. 27, 2015, from Tanegashima Space Center in Japan, will help advance our understanding of Earth's water and energy cycles, improve the forecasting of extreme events that cause natural disasters, and extend current capabilities of using satellite precipitation information to directly benefit society.
Profile of Steve Nesbitt, a professor of Atmospheric Sciences at the University of Illinois and a mission scientist on GPM ground validation field campaigns. Nesbitt uses the data collected to improve the representation of cloud microphysical processes using radars, aircraft probes, and surface instrumentation in satellite precipitation algorithms to improve global precipitation estimates.