New Precipitation Climate Data Record

Precipitation Estimation from Remotely Sensed Information using an Artificial Neural Network (PERSIANN) Climate Data Record precipitation estimates for October 24, 2012

Precipitation Estimation from Remotely Sensed Information using an Artificial Neural Network (PERSIANN) Climate Data Record precipitation estimates for October 24, 2012

NCDC is announcing the release of the Precipitation Estimation from Remotely Sensed Information using an Artificial Neural Network (PERSIANN) Climate Data Record (CDR). Developed by NOAA funded work at the University of California–Irvine, this CDR consists of daily precipitation estimates derived from longwave infrared satellite data. The PERSIANN CDR provides valuable precipitation data beginning in 1983 at 0.25° resolution in a consistent long-term record of remotely sensed precipitation observations.

These CDR data are valuable to meteorologists, climate modelers, and researchers in a wide range of applications, including climate change detection and monitoring at finer resolutions than previously possible. Climatologists can also use PERSIANN to perform extreme event analyses, studying frequency and duration of both floods and droughts. Hydrologists studying rainfall and runoff modeling on regional and global scales may also find PERSIANN useful in their work. And this CDR can be an extremely valuable product for decision making in water resources systems planning and management.

As with all operational CDRs at NCDC, the PERSIANN CDR meets rigorous quality standards recommended by the National Academy of Sciences and other expert organizations to help ensure consistent and reliable products.