Description

Reliable real-time acquisition protocols coupled with a multi-sensor QC algorithm produces a high-quality dataset of 1-hour rain gauge data.  The QC’d gauge data and QC statistics provide the foundation of various hydrometeorological applications, including gauge-adjusted radar-estimated rain algorithms, identification of gauge malfunctions, alert notifications of rainfall intensities that meet/exceed thresholds, detailed post-event analyses and climatological studies.  Gauges can suffer from a number of different problems including freezing rain, windy conditions, gauge siting (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 data.

The QC system repeatability processes data for each hour in order to capture all available gauge data and leverage increasingly rich independent datasets that have varying latencies.  The QC system accesses and processes both hourly-reporting and daily-reporting gauge amounts.  The daily-reported amounts are disaggregated into estimated hourly amounts based on the temporal distribution of rain from gauge-adjusted rain grids.  The daily-based hourly rain data combined with the hourly-reporting data provides a very high density of “ground truth” data.

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, the QC confidence flag provides an objective measure of how well the value compares to independent, multi-sensor datasets.  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.

Data Sources

Data from nearly 20,000 stations are accessed, QC’d and archived each hour.   Real-time rain gauge data are accessed from a variety of real-time sources, but largely from the Meteorological Assimilation Data Ingest System (MADIS) and MesoWest, both of which collect and integrate weather observations from government and non-government gauge networks.  Strategic alliances with other data providers allow unique and exclusive access to data sources otherwise difficult to attain.  Pooled data from the increasing number of sources makes this one of the largest known real-time, QC’d rain datasets available in the United States.  Currently, 1-hour rain data is acquired from the following sources:

• Meteorological Assimilation Data Ingest System (MADIS)
  • Meteorological Surface Network (see http://madis.noaa.gov/mesonet_providers.html for provider list)
  • Hydrological Surface Network (see http://madis.noaa.gov/hydro_providers.html for provider list)
• MesoWest (University of Utah)
• United States Geologic Survey (USGS) Rainfall Network
• NOAA’s California Nevada River Forecast Center
• Lower Colorado River Authority Hydromet
• Flood Control District of Maricopa County, Arizona ALERT network
• City of Portland, Oregon HYDRA Rainfall Network
• Arizona ALERT Systems
  • Yavapai County
  • Pima County
  • Navajo County
  • Maricopa County
  • Others
• Community Collaborative Rain, Hail and Snow Network (CoCoRaHS)*

* Daily data.

If you have rain gauge data you would like to share, please contact us!

Archive

We maintain an archive of the QC’d 1-hour rain gauge data dating back to 9/2011.

Spatial Extent

Continental United States, adjacent portions of Canada and Mexico, but adaptable to any location.  Below is a regularly updated map of rain gauge locations we are currently acquiring, quality controlling and using in a high-resolution, nationwide gauge-adjusted radar-estimated rainfall product.