Evaluation of Multisensor Quantitative Precipitation Estimation in Russian River Basin

Willie, Delbert; Chen, Haonan; Chandrasekar, V.; Cifelli, Robert; Campbell, Carroll; Reynolds, David; Matrosov, Sergey; Zhang, Yu

doi:10.1061/(ASCE)HE.1943-5584.0001422

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Evaluation of Multisensor Quantitative Precipitation Estimation in Russian River Basin

2016
By Willie, Delbert ; Chen, Haonan ; Chandrasekar, V. ; ...
Source: J. Hydrol. Eng., 2017, 22(5): E5016002

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Journal Title:

Journal of Hydrologic Engineering
Personal Author:

Willie, Delbert ; Chen, Haonan ; Chandrasekar, V. ; Cifelli, Robert ; Campbell, Carroll ; ... More +

Willie, Delbert ; Chen, Haonan ; Chandrasekar, V. ; Cifelli, Robert ; Campbell, Carroll ; Reynolds, David ; Matrosov, Sergey ; Zhang, Yu Less -
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; PSL (Physical Sciences Laboratory) ; ESRL (Earth System Research Laboratory)

OAR (Oceanic and Atmospheric Research) ; PSL (Physical Sciences Laboratory) ; ESRL (Earth System Research Laboratory) Less -
Description:

An important goal of combining weather radar with rain gauge data is to provide reliable estimates of rainfall rate and accumulation and to further identify intense precipitation and issue flood warnings. Scanning radars provide the ability to observe precipitation over wider areas within shorter timeframes compared to rain gauges, leading to improved situational awareness and more accurate and reliable warnings of future precipitation and flooding events. The focus of this study is on evaluating the performance of the multi-radar multi-sensor (MRMS) system with and without the impact of a local gap filling radar. The challenge of using radar and rain gauges to provide accurate rainfall estimates in complex terrain is investigated. The area of interest is the Russian River basin north of San Francisco, CA, which lies within the National Oceanic and Atmospheric Administration (NOAA) Hydrometeorology Testbed (HMT). In this complex mountainous terrain, the challenge of obtaining reliable quantitative precipitation estimations (QPEs) is hindered by beam blockage and overshooting, as well as the enhancement of rainfall on the windward side of mountain ranges. The effectiveness of several local radars, which include four S-band National Weather Service (NWS) Weather Surveillance Radar–1988 Doppler (WSR-88DP) radars and a C-band gap filling TV station radar (i.e., KPIX), are considered for deriving QPE over this region. The precipitation estimation methodologies used the MRMS algorithms and an independent KPIX-only (Z−RZ−R) based QPE algorithm. In addition, a time series analysis is conducted in order to illustrate the radar-gauge rainfall difference caused by radar beam height. The sampling relative to precipitation vertical structure is also considered in regards to the depth of the precipitation and the height of the bright band. The quantitative evaluation of different QPE products is presented.
Source:

J. Hydrol. Eng., 2017, 22(5): E5016002
DOI:

https://doi.org/10.1061/(ASCE)HE.1943-5584.0001422
Document Type:

Journal Article
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CC BY
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urn:sha256:bfe401c9bbdebf79cc0b4ce39c28bb93a5240e0b1e432308aeb6363043b66964
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https://repository.library.noaa.gov/view/noaa/14632/noaa_14632_DS1.pdf
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