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Exponent Atmospheric Sciences News Release
Using NEXRAD Radar Data to Estimate RainfallBy Alfred M. Klausmann, Christopher DesAutels, and Jelena Popovic
IntroductionIntense or sudden rainfall can have a number of impacts on people and the built environment. Rain gauges represent a common source for information on rainfall rates and accumulation. However, information from gauges will not always be sufficient. Rainfall can vary significantly due to terrain with greater rain falling at higher elevations. There also can be significant spatial variability within severe weather systems, even over the distance of a few kilometers. Doppler radar can be useful in these circumstances to develop location specific rainfall information.
Radars have been used to estimate rainfall rates since the late 1980’s (Hunter, 1996). Doppler radars have coverage spanning most of the continental United States. There is a direct relationship between radar reflectivity and precipitation rate which allows for estimation at locations across a large area. Starting in approximately 2011, dual polarization radars have come into use, resulting in increased resolution and accuracy. Care must be taken to correctly interpret dual polarization radar fields, but they have the ability to provide important information on precipitation type (rain versus hail) along with precipitation rate on a time scale as fine as 5 minutes and horizontal resolutions on the order of 1–2 kilometers.
The West Virginia Historic Flood Event of June 2016During the period June 22–26, 2016, intense thunderstorm activity along a stationary frontal boundary resulted in rainfall amounts on the order of 8–10 inches over an area of southeastern West Virginia. The combination of topography and rainfall resulted in historic flooding with extensive property damage. Figure 1 shows a set of 4 composite radar reflectivity images. Radars send out a radio signal that travels outward from the radar antenna. That radio signal will bounce off particles in the atmosphere and the reflected radio signal, received by the radar, is then analyzed. The magnitude of the reflectivity is proportional to the precipitation intensity. Composite imagery means that the maximum radar reflectivity is shown based on scans from all radar beam elevation angles. This plot shows a series of intense thunderstorm cells moving through West Virginia. These cells had peak reflectivity values greater than 50 dBZ indicative of intense rainfall. The focus of these thunderstorms is over southeastern West Virginia from Charleston southeastward. Figure 2 shows a sample of the radar based one-hour precipitation for this event and the storm total precipitation for the event ending at 2358 UTC on June 24, 2016. The 1-hour rainfall total shows large
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1-hour rainfall rates on the order of 1–2 inches in a northwest-southeast band. The storm total rainfall shows peak rainfall totals along this same northwest to southeast band with rainfall amounts on the order of 10 inches across parts of Greenbrier County, WV. The plots in Figures 1 and 2 also show very large
FIGURE 1. Composite radar reflectivity from Charleston West Virginia Radar on June 23, 2016 at 1539, 1751, 1930, and 2050 UTC. Deep reds show intense rainfall. Note the very sharp spatial changes in rainfall intensity.
FIGURE 2. 1-hour rainfall totals for June 23, 2016 at hour ending at 1938 UTC (left) and storm total rainfall for the period June 23, 2016 at 0153 UTC through June 24, 2016 at 2358 UTC (right). Radar images from the Charleston, West Virginia NEXRAD radar site. (A band of grey in this figure (southwest of the maximum rainfall) represents interference with the radar signal and should be ignored.)
gradients in reflectivity and rainfall totals and show how rain gauge measurements can misrepresent total rainfall in a region depending on their position relative to these thunderstorms. Note to the southwest of the maximum rainfall in Figure 2 is a band of grey which shows interference with the radar signal.
Maximum 1-hour rainfall
Axis of maximum storm total rainfall across Greenbrier
County, WV
Radar interference
Charleston,WV radar
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Studies have suggested that radar rainfall estimates can have biases that are dependent on geographical region, the characteristics of the weather event, and season. For this reason, an essential component of a radar based precipitation analysis must involve calibrating the radar estimates against available rain-gauge measurements (Cunha et al., 2013). Available rain gauge measurements can be used to compare with radar derived rainfall estimates to assess any systematic bias and then impose a bias correction to the radar rainfall estimates.
Performing the Radar AnalysisRainfall estimates from radars are done using an empirical relationship between reflectivity and surface rainfall rate known as the Z-R relationship. The Z-R relationship is non-linear and there are variations in different geographical regions and seasons due to variations in cloud microphysics. The relationship depends on the droplet size distribution as well as the type of precipitation particles in the sampled volume. The droplet size distribution and characteristics of the precipitation particles are the result of the microphysical processes which can vary by individual event, season, and geographical region.
The quality of the measurements is also impacted by the effects of topography intersecting the radar beams as well as interference from other sources such as manmade obstacles or the effects of electromagnetic fields. Thus an analysis needs to be conducted to evaluate the quality of the radar data at a particular site. This may involve the use of data from multiple radars. Radar precipitation estimates can also be correlated with both infrared and visible satellite imagery to compare satellite image cloud signatures with the location of maximum rainfall.
Figure 3 shows an example of storm total precipitation from the Seattle, Washington radar from November 13-18, 2015, a period with flooding rains along the Cascade Mountains. There are several interesting features shown in Figure 3. One is the donut shaped pattern to the total rainfall. This pattern is the result of sinking air on the lee side of the Olympic Mountains in the Seattle region known as the Olympic rain-shadow. This lee side terrain induced sinking of air causes rainfall to diminish in this region. The area of maximum precipitation to the east and southeast of Seattle is due to higher topography and upslope flow on the windward side of the Cascades. Figure 3 also shows interference patterns in the radar data to the north of the radar and southwest of the radar. This interference is due to the radar beams intersecting the mountains, resulting in rainfall measurements which are not reliable.
FIGURE 3. NEXRAD Radar storm total rainfall using Seattle NEXRAD radar for the period beginning on November 13, 2015 at 1945 UTC and ending at November 14, 2015 0948 UTC (top) and November 18, 2015 at 2340 UTC (bottom).
Minimum rainfall due to Olympic Rain Shadow
Topographic interference
due to Olympic
Mountains
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For more information on Exponent capabilities, please visit our website, www.exponent.com.
Exponent ExpertiseExponent’s atmospheric science team specializes in applied meteorology, meteorological modeling and analysis, climatological studies, and air quality modeling. Clients benefit from our multidisciplinary approach, which includes the support of staff across multiple practice areas. Our atmospheric scientists work closely with building, structural and civil engineers to evaluate structural damage due to storm events. Exponent has powerful computational capabilities, including a dedicated 120-processor Linux cluster computer, which allow us to simulate at very high spatial resolution as well as run multiple scenarios and sensitivity studies.
Exponent scientists have used a variety of available observational data to perform analyses of meteorological conditions associated with such phenomena as tropical storms or flash flood events. These datasets include surface and upper air meteorological observations, radar data, satellite imagery, lightning data, buoy data, various analysis NOAA analyses, and high resolution terrain and land use data. Exponent’s atmospheric scientists have extensive experience with meteorological analysis including radar analysis and have done a number of radar studies of severe weather events including rainfall analysis for flash flooding and landslide events, wind events due to thunderstorm microbursts, and hurricanes.
ReferencesCunha, L.K., J.A. Smith, M.L. Baeck, and W. F. Krajewski, 2013, An Early Performance Evaluation of the NEXRAD Dual-Polarization Radar Rainfall Estimates for Urban Flood Applications. Weather and Forecasting, Volume 28, 1478–1479.
Hunter, S.M., 1996,”WSR-88D Radar Rainfall Estimation: Capabilities, Limitations, and Potential Improvements. National Weather Digest, Volume 20 (4), 26–38.
Contact InformationAlfred Klausmann, [email protected] | 978.461.4628
Christopher [email protected] | 978.461.4623
Jelena [email protected] | 978.461.4622
