AHPS Precipitation Analysis
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About the Precipitation Analysis Pages

These pages graphically show the short-term observed and climatic trends of precipitation across the lower 48 United States (CONUS) and Puerto Rico.

Observed Precipitation

"Observed" data is a byproduct of National Weather Service (NWS) operations at the 12 CONUS River Forecast Centers (RFCs), and is displayed as a gridded field with a spatial resolution of roughly 4x4 km. "Observed" data is expressed as a 24-hour total ending at 1200 Z (same as Greenwich Mean Time, or GMT), with longer periods simply being a summation of multiple 24-hour periods. 1200 GMT is used as the ending time for a 24-hour total, because it is the end of the "hydrologic day", a standard used in river modeling. Additionally, 1200 GMT closely coincides with the reporting time for most of the National Weather Service's cooperative observers, whose data are used as a quality control on the dataset. 1200 GMT coincides with 8 AM EDT, 7 AM EST, 7 AM CDT, 6 AM CST, etc.

When viewing "ALL RFC DATA" you may notice that "Observed" data extends well beyond the U.S. border, most notably north of Washington and Idaho and west of Texas. Several RFCs located in the CONUS have service areas that extend beyond the U.S. border, in order to model rivers that flow into the United States. Examples include the Columbia River in the Pacific Northwest and tributaries of the Rio Grande along the Texas-Mexico border. Although no forecasts are provided outside of U.S. boundaries, precipitation estimates are created over these areas in order to simulate streamflow along these rivers as they cross into the United States. When viewing "ALL RFC DATA" it may be helpful to turn on the "RFC Boundary" overlay as a geographic reference.

Normal Precipitation

"Normal" precipitation is derived from PRISM climate data, created at Oregon State University. The PRISM gridded climate maps are considered the most detailed, highest-quality spatial climate datasets currently available. The 30 year PRISM normal from 1981-2010 is used for precipitation analysis since 2004. Prior to 2004 the 30 year PRISM normal from 1961-1990 is used.

Puerto Rico PRISM data comes from a separate project by the International Institute of Tropical Forestry (Ref: Daly, C, E.H. Helmer and M. Quiñones. 2003. Mapping the climate of Puerto Rico, Vieques and Culebra. International Journal of Climatology 23:1353-1381.) PRISM data for Puerto Rico covers the time period 1963-1995.

The PRISM data is expressed as a monthly normal rainfall. For durations less than one month, the value for that month is divided by the total days in that month and multiplied by the number of days in the selected field. For example, a 7-day normal for January 10th (ending at 1200 GMT) would be 7/31 of the total normal rainfall for January, while a 14-day normal would be 9/31 of January's normal plus 5/31 of December's normal.

Derived Precipitation Products

"Departure from Normal" and "Percentage of Normal" graphics are generated by simple grid mathematics, where the "Normal" dataset is respectively subtracted from or divided into the "Observed" dataset.

Observation Methods

East of the Continental Divide, RFCs derive the "Observed" precipitation field using a multisensor approach. Hourly precipitation estimates from WSR-88D NEXRAD are compared to ground rainfall gauge reports, and a bias (correction factor) is calculated and applied to the radar field. The radar and gauge fields are combined into a "multisensor field", which is quality controlled on an hourly basis. In areas where there is limited or no radar coverage, satellite precipitation estimates (SPE) can be incorporated into this multisensor field. The SPE can also be biased against rain gauge reports.

The following links provide additional information about the programs used to derive these multisensor fields:

In mountainous areas west of the Continental Divide, a different method is used to derive the "Observed" data. Gauge reports are plotted against long term climatologic precipitation (PRISM data), and derived amounts are interpolated between gauge locations. The following link provides more information about the process and program used to derive observed precipitation for the western U.S.

Quality of Data

Studies have shown that algorithms which combine sensor inputs -- radar, gauge, satellite -- yield more accurate precipitation estimates than those which rely on a single sensor (i.e. radar-only, gauge-only, satellite-only). Although it is not perfect, this dataset is one of the best sources of timely, high resolution precipitation information available. Still, users should understand the inherent weaknesses of this dataset before using it in certain decision - making applications, especially those which require a high degree of accuracy.

Radar Data Errors.
These precipitation estimates are based substantially on radar which samples over a large area. Each grid value on the maps represents average precipitation over roughly 16 km2 (6ΒΌ mi2). Radar values may not be comparable with one or more rain gauges within that area. Radar sampling errors that can create inaccuracies in the data include freezing or frozen precipitation, low topped convection, bright banding, accuracy of the reflectivity - rainfall relationship in use, calibration of the radar, radar location and elevation, range degradation (i.e., larger sampling area and effect of intervening precipitation), and the radar's effective coverage (e.g., physical obstructions such as mountains).

Precipitation Gauge Errors.
A rain gauge measures approximately 12 in2. There are over 10,000 precipitation gauges scattered through the country. Gauge sampling problems could include freezing precipitation, windy conditions, gauge siting (e.g., obstructions around the gauge), under-measurement by tipping bucket gauges in high intensity rainfall, and gauge maintenance. In places where NWS quality control efforts fail to resolve persistent problems, significant sampling errors will be noticable in longer-duration products (e.g. 30 days or more).

Horizontal Accuracy.
Horizontal accuracy errors may reach up to 5 km (3 mi). In other words, "peaks" in the precipitation data may actually have occurred miles away.

This information is not certified and cannot be used in legal proceedings. Official, certified data is available exclusively through the National Climatic Data Center.

References:
Seo, D.-J., 1999: Real-time estimation of rainfall fields using radar rainfall and rain gauge data. J. Hydrol., 208, 37-52
Seo, D.-J., J. Breidenbach, and E. Johnson, 1999: Real-time estimation of mean field bias in radar rainfall data. J. Hydrol., 223, 131-147
Seo, D.-J. and J. Breidenbach, 2002: Real-time correction of spatially nonuniform bias in radar rainfall data using rain gauge measurements. J. Hydrometeor., 3, 93-111

Production / Update Times

The precipitation analysis pages are routinely updated six times per day, at approximately 10:00am, 12:00pm, 2:00pm, 4:00pm, 6:00pm and 8:00pm Eastern Standard Time. Data for the western U.S. are usually available by the second or third update. The data are preliminary and subject to change throughout the day and even on subsequent days. While the data in the final update are much less likely to change, they are neither official nor certified. Please contact the National Climatic Data Center for certified past weather information.

Data Formats

The precipitation fields are provided in PNG format for viewing, and shapefile and netCDF formats for download and use in other projects and research. More information about using netCDF files is available from the University Corporation for Atmospheric Research (UCAR).

Metadata

The following links provide more information about the observed precipitation, normal precipitation, and derived precipitation products:

   

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Page last modified: 25-Jun-2014 4:49 AM
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