GHRC News

The NASA Global Hydrology Resource Center (GHRC) DAAC published the GPM Ground Validation Multi-Radar/Multi-Sensor (MRMS) Precipitation Reanalysis for Satellite Validation Product dataset. This dataset contains precipitation rate and type estimates, quality control products, and precipitation corrective factors products. These data products were created using the NOAA MRMS System which ingests Weather Surveillance Radar 88 Doppler (WSR-88D) radar data, Rapid Update Cycle (RAP) model analysis fields, and gauge data. It should be noted that these data products are not standard MRMS. Significant post-processing is applied to MRMS to generate products specifically adapted to satellite purposes and needs over North America. These data are available from March 2, 2014 through October 30, 2018 in ASCII format.

Leigh Sinclair and Ajinkya Kulkarni from the NASA Global Hydrology Resource Center (GHRC) DAAC attended the American Geophysical Union (AGU) Fall Meeting in Washington, D.C. where four posters were presented. Leigh conducted a lightning talk at the NASA Hyperwall titled “Application of ISS Lightning Data to Improve Hazardous Weather Preparation”, as well as chaired an oral session. Ajinkya conducted an oral presentation titled “Challenges Deploying Legacy Software in the Cloud”. You can find the posters presented at https://www.itsc.uah.edu/main/outreach/posters for a closer look. 

The NASA Global Hydrology Resource Center (GHRC) DAAC published the GPM Ground Validation Autonomous Parsivel Unit (APU) Wallops Flight Facility (WFF) dataset. This dataset consists of precipitation data including precipitation amount, precipitation rate, reflectivity in Rayleigh regime, liquid water content, drop diameter, and drop concentration obtained from six Autonomous Parsivel Units (APUs) positioned at the Wallops Flight Facility (WFF) in support of the Global Precipitation Mission (GPM). The APU is an optical laser-disdrometer based on single particle extinction that measures particle size and fall velocity. It consists of the Parsivel2 developed by OTT in Germany and supporting hardware developed by University of Alabama. Data are available in ASCII format for the period of May 6, 2013 through October 9, 2014.
The NASA Global Hydrology Resource Center (GHRC) DAAC published the GPM Ground Validation Weather Research and Forecasting (WRF) Images MC3E dataset. This data consists of browse only images showing radar reflectivity, radar echo top, convective available potential energy (CAPE), temperature, geopotential height, wind speed, relative humidity, rain water, snow, cloud water, cloud ice, and graupel. These data were simulated by the Weather Research and Forecasting (WRF) for the period of the GPM Ground Validation Mid-­latitude Continental Convective Cloud Experiment (MC3E) field campaign. The overarching goal of the MC3E field campaign was to provide the most complete characterization of convective cloud systems, precipitation, and the environment ever obtained and to provide new constraints for model cumulus parameterizations and space-­based rainfall retrieval algorithms over land. Browse imagery files in PNG and GIF formats are available for April 19, 2011 through June 6, 2011.

 

GHRC DAAC held its annual User Working Group meeting November 13-14 in Huntsville, AL.  The primary focus of this meeting was to present GHRC FY2018 successes and provide descriptions of FY2019 goals.  The DAAC also reported improvements and changes that directly responded to last year's UWG recommendations.  The GHRC DAAC UWG was led by chairs Michael Peterson (Los Alamos National Laboratory) and Pierre Kirstetter (University of Oklahoma).  We were also pleased to have several guests joining us, including Andy Mitchell, Drew Kittel and Steve Berrick from NASA's Earth Science Data and Information Systems (ESDIS) Project; Bruce Wilson (ORNL DAAC) and Chris Doescher (LP DAAC). A lively afternoon brainstorming session included topics on how to broaden the GHRC user base, improve field campaign data use, and future communication with our users. 

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