Coming soon…the most advanced, accurate gridded precipitation technology available.

Radar-estimated Precipitation

A fundamental requirement for high quality radar-estimated precipitation is a high quality radar mosaic, a seamless collection of concurrent weather radar data from individual radar sites covering the United States and southern Canada.  Our vendor of NEXRAD weather radar data is Weather Decision Technologies, Inc. (WDT), who accesses, mosaics, and quality-controls DualPol radar-estimated precipitation using cutting-edge technologies.

Satellite-estimated Precipitation

NOAA’s Hydro-Estimator (H-E) uses infrared (IR) data from Geostationary Operational Environmental Satellites (GOES) to estimate precipitation.  These estimates provide critical precipitation information in regions where data from gauges and/or radar are unavailable or unreliable. The H-E algorithm also uses data from numerical weather prediction models to correct for evaporation of raindrops, topography and other factors.

We are also exploring the use of the Integrated Multi-satellitE Retrievals for GPM (IMERG) satellite-estimated precipitation in our real-time QPEs. The IMERG algorithm integrates and merges all satellite microwave precipitation estimates, together with microwave-calibrated infrared (IR) satellite estimates, and precipitation gauge analyses.

Climatologically-aided Precipitation

A radar- and satellite-independent grid of 1-hour precipitation is computed using the measured precipitation data together with a climatological grid of mean monthly precipitation. This so-called climatologically-aided interpolation approach allows gauge data to dictate the magnitude of precipitation, while the spatial patterns are govern by the climatological grids. This approach incorporates important precipitation patterns resulting from terrain and other micro-climates. The climatologically-aided interpolation provides an important depiction of precipitation in areas where radar data is blocked or unavailable due to radar outages. This approach ensures the measured gauge precipitation is consistent with gridded precipitation. As a strategic partner of Synoptic Data Corp, the provider of the QC’d gauge data, the climatologically -aided interpolation algorithm leverages the gauge QC analytics for producing an accurate and representative grid of precipitation.


Unlike any other radar-based precipitation product, the QPE data from MetStat® achieves improved accuracy by leveraging gauge QC analytics through a data stream of QC’d 1-hour precipitation gauge amounts from Synoptic Data Corp, an affiliate of MetStat®.  Rain gauge data are collected from numerous networks, including local networks such as data provided by clients, and quality controlled using a multi-sensor approach.  Gauges can suffer from a number of different problems including freezing rain, windy conditions, gauge sighting (e.g., obstructions around the gauge), and under-measurement by tipping bucket gauges in high intensity rainfall, and gauge maintenance, therefore making QC an imperative step before utilizing the precipitation data.  The multi-sensor QC algorithm is based on surrounding gauges, radar reflectivity data, National Weather Service Stage IV gauge-adjusted radar-estimated rain data and satellite-estimated rain data. The MetStat®/Synoptic QC system repeatedly processes data for each hour in order to capture all available gauge data and leverage increasingly rich independent datasets that have varying latencies.  The complexities of gauge QC often prevent a binary (correct or not correct) decision to be made, therefore a QC confidence flag is computed for each measured value ranging from 0 to 1, 0 implying error and 1 a valid value.r areas not well covered by radar data, the precipitation gauge data are coupled with a climatological basemap to define the spatial patterns of precipitation.  Climatological basemaps are independent grids of spatially distributed weather or climate variables that are used to govern the spatial patterns of the hourly precipitation in the absence of radar data.  Sometimes referred to as “climatologically-aided” interpolation, the basemap and gauge precipitation are combined to produce grids of precipitation.

The 1-hour QPEs are based on state-of-the-art algorithms that couple the QC’d radar-estimated, gauge-corrected precipitation and the climatologically-aided basemap values into a seamless grid.  The resulting 1-hour QPEs are true to the measured precipitation at gauge locations, where/when the gauges have passed the QC tests.

  • The QPE output is available in a variety of formats, including GIS-compatable grids, shapefiles, map layers, png, images, text files, etc.
  • Leverages the largest, most comprehensive, real-time quality-controlled 1-hour precipitation gauge dataset in the North America.
  • The QPE algorithms have been optimized by a team of highly-experienced hydro-meteorologists.
  • The QPE product has a low latency.