Dual-polarized quantitative precipitation estimation as a function of range
Since the advent of dual-polarization radar technology, many studies have been conducted to determine the extent to which the differential reflectivity (ZDR) and specific differential phase shift (KDP) add benefits to estimating rain rates (<i>R</i>) compared to reflectivity (<i>...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2018-06-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | https://www.hydrol-earth-syst-sci.net/22/3375/2018/hess-22-3375-2018.pdf |
| _version_ | 1819298773887614976 |
|---|---|
| author | M. J. Simpson N. I. Fox |
| author_facet | M. J. Simpson N. I. Fox |
| author_sort | M. J. Simpson |
| collection | DOAJ |
| description | Since the advent of dual-polarization radar technology, many
studies have been conducted to determine the extent to which the
differential reflectivity (ZDR) and specific differential phase shift (KDP)
add benefits to estimating rain rates (<i>R</i>) compared to reflectivity (<i>Z</i>)
alone. It has been previously noted that this new technology provides
significant improvement to rain-rate estimation, primarily for ranges within
125 km of the radar. Beyond this range, it is unclear as to whether the
National Weather Service (NWS) conventional <i>R</i>(<i>Z</i>)-convective algorithm
is superior, as little research has investigated radar precipitation estimate performance
at larger ranges. The current study investigates the performance of three
radars – St. Louis (KLSX), Kansas City (KEAX), and Springfield (KSGF), MO –
with 15 tipping bucket gauges serving as ground truth to the radars. With
over 300 h of precipitation data being analyzed for the current study, it
was found that, in general, performance degraded with range beyond,
approximately, 150 km from each of the radars. Probability of detection (PoD) in
addition to bias values decreased, while the false alarm rates increased as
range increased. Bright-band contamination was observed to play a potential
role as large increases in the absolute bias and overall error values near
120 km for the cool season and 150 km in the warm season. Furthermore,
upwards of 60 % of the total error was due to precipitation being falsely
estimated, while 20 % of the total error was due to missed precipitation.
Correlation coefficient values increased by as much as 0.4 when these
instances were removed from the analyses (i.e., hits only). Overall, due to
the lowest normalized standard error (NSE) of less than 1.0, a National Severe
Storms Laboratory (NSSL) <i>R</i>(<i>Z</i>,ZDR) equation was determined to be the most
robust, while a <i>R</i>(ZDR,KDP) algorithm recorded NSE values as high as 5. The
addition of dual-polarized technology was shown to estimate
quantitative precipitation estimates (QPEs) better
than the conventional equation. The
analyses further our understanding of the strengths and limitations of the
Next Generation Radar (NEXRAD) system overall and from a seasonal perspective. |
| first_indexed | 2024-12-24T05:35:14Z |
| format | Article |
| id | doaj.art-92f460bea01a48769e6a482d18ab2823 |
| institution | Directory Open Access Journal |
| issn | 1027-5606 1607-7938 |
| language | English |
| last_indexed | 2024-12-24T05:35:14Z |
| publishDate | 2018-06-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Hydrology and Earth System Sciences |
| spelling | doaj.art-92f460bea01a48769e6a482d18ab28232022-12-21T17:13:02ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382018-06-01223375338910.5194/hess-22-3375-2018Dual-polarized quantitative precipitation estimation as a function of rangeM. J. Simpson0N. I. Fox1University of Missouri, School of Natural Resources, Water Resources Program, Department of Soil, Environmental, and Atmospheric Sciences, 332 ABNR Building, Columbia, Missouri 65211, USAUniversity of Missouri, School of Natural Resources, Water Resources Program, Department of Soil, Environmental, and Atmospheric Sciences, 332 ABNR Building, Columbia, Missouri 65211, USASince the advent of dual-polarization radar technology, many studies have been conducted to determine the extent to which the differential reflectivity (ZDR) and specific differential phase shift (KDP) add benefits to estimating rain rates (<i>R</i>) compared to reflectivity (<i>Z</i>) alone. It has been previously noted that this new technology provides significant improvement to rain-rate estimation, primarily for ranges within 125 km of the radar. Beyond this range, it is unclear as to whether the National Weather Service (NWS) conventional <i>R</i>(<i>Z</i>)-convective algorithm is superior, as little research has investigated radar precipitation estimate performance at larger ranges. The current study investigates the performance of three radars – St. Louis (KLSX), Kansas City (KEAX), and Springfield (KSGF), MO – with 15 tipping bucket gauges serving as ground truth to the radars. With over 300 h of precipitation data being analyzed for the current study, it was found that, in general, performance degraded with range beyond, approximately, 150 km from each of the radars. Probability of detection (PoD) in addition to bias values decreased, while the false alarm rates increased as range increased. Bright-band contamination was observed to play a potential role as large increases in the absolute bias and overall error values near 120 km for the cool season and 150 km in the warm season. Furthermore, upwards of 60 % of the total error was due to precipitation being falsely estimated, while 20 % of the total error was due to missed precipitation. Correlation coefficient values increased by as much as 0.4 when these instances were removed from the analyses (i.e., hits only). Overall, due to the lowest normalized standard error (NSE) of less than 1.0, a National Severe Storms Laboratory (NSSL) <i>R</i>(<i>Z</i>,ZDR) equation was determined to be the most robust, while a <i>R</i>(ZDR,KDP) algorithm recorded NSE values as high as 5. The addition of dual-polarized technology was shown to estimate quantitative precipitation estimates (QPEs) better than the conventional equation. The analyses further our understanding of the strengths and limitations of the Next Generation Radar (NEXRAD) system overall and from a seasonal perspective.https://www.hydrol-earth-syst-sci.net/22/3375/2018/hess-22-3375-2018.pdf |
| spellingShingle | M. J. Simpson N. I. Fox Dual-polarized quantitative precipitation estimation as a function of range Hydrology and Earth System Sciences |
| title | Dual-polarized quantitative precipitation estimation as a function of range |
| title_full | Dual-polarized quantitative precipitation estimation as a function of range |
| title_fullStr | Dual-polarized quantitative precipitation estimation as a function of range |
| title_full_unstemmed | Dual-polarized quantitative precipitation estimation as a function of range |
| title_short | Dual-polarized quantitative precipitation estimation as a function of range |
| title_sort | dual polarized quantitative precipitation estimation as a function of range |
| url | https://www.hydrol-earth-syst-sci.net/22/3375/2018/hess-22-3375-2018.pdf |
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