Climate Rainfall Data Center (CRDC)

- Visit the Climate Rainfall Data Center siteĀ 

Climate Rainfall Data Center (CRDC) is an experiment designed to assess if overall data access and usage from NASA data centers can be improved by adding a layer of service that is discipline specific (rainfall in our case). While the task of distributing standard rainfall products is left to the NASA data centers, CRDC is staffed by research personnel with knowledge of the products and the flexibility to address individual user needs. As such, CRDC can answer detailed questions about the products, direct users to the appropriate products for a specific application, create alternate products if necessary, and even create a quick image if needed. In short, the CRDC will do everything it can to accommodate any honest question or request as part of this experiment. In return, however, user feedback is needed to assess if the CRDC is a viable model for future NASA data systems.

The CRDC is most closely aligned with the Precipitation Processing System (PPS) at NASA Goddard Space Flight Center (GSFC). The PPS currently processes data from the Tropical Rainfall Measuring Mission (TRMM), but is evolving to handle multiple satellites for the planned Global Precipitation Mission (GPM). The TRMM satellite was launched in November of 1997 and rainfall products from the Precipitation Radar (PR) and TRMM Microwave Imager (TMI) have been available since December 1997. While the TRMM sensors and corresponding retrieval algorithms represent the state-of-the-art in satellite rainfall estimation, TRMM is a research satellite with a relatively short record for climate studies. Long-term merged global climate rainfall products such as GPCP and CMAP date back as far as 1979 providing over two decades of continuous global rainfall coverage. These merged products use observations from operational satellite systems, providing a much longer data record. Limitations of the sensors and techniques from the operational satellites, however, often result in regional and time-dependent biases. Because of these tradeoffs, the best rainfall dataset is highly dependent on the application.

Chris Kummerow - PI, Colorado State University

Page Last Updated: May 5, 2019 at 11:11 PM EDT