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 1971-2000
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 update three times per day, at approximately 9:30am,
12:30pm and 4:30pm Eastern Standard Time. Data for the western U.S. are usually available by the second
update. The data for the first two updates are preliminary and subject to change. 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).
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