scholarly journals Polarimetric Radar Signatures and Performance of Various Radar Rainfall Estimators during an Extreme Precipitation Event over the Thousand-Island Lake Area in Eastern China

2019 ◽  
Vol 11 (20) ◽  
pp. 2335 ◽  
Author(s):  
Yabin Gou ◽  
Haonan Chen ◽  
Jiafeng Zheng
Keyword(s):  
Extreme Precipitation ◽  
Rapid Development ◽  
Eastern China ◽  
Rain Gauge ◽  
Extreme Precipitation Event ◽  
Precipitation Event ◽  
Distribution Data ◽  
Lake Area ◽  
Polarimetric Radar ◽  
Radar Rainfall

Polarimetric radar provides more choices and advantages for quantitative precipitation estimation (QPE) than single-polarization radar. Utilizing the C-band polarimetric radar in Hangzhou, China, six radar QPE estimators based on the horizontal reflectivity (ZH), specific attenuation (AH), specific differential phase (KDP), and double parameters that further integrate the differential reflectivity (ZDR), namely, R(ZH, ZDR), R(KDP, ZDR), and R(AH, ZDR), are investigated for an extreme precipitation event that occurred in Eastern China on 1 June 2016. These radar QPE estimators are respectively evaluated and compared with a local rain gauge network and drop size distribution data observed by two disdrometers. The results show that (i) although R(AH, ZDR) underestimates in the light rain scenario, it performs the best among all radar QPE estimators according to the normalized mean error; (ii) the optimal radar rainfall relationship and consistency between radar measurements aloft and their surface counterparts are both required to obtain accurate rainfall estimates close to the ground. The contamination from melting layer on AH and KDP can make R(AH), R(AH, ZDR), R(KDP), and R(KDP, ZDR) less effective than R(ZH) and R(ZH,ZDR). Instead, adjustments of the α coefficient can partly reduce such impact and hence render a superior AH–based rainfall estimator; (iii) each radar QPE estimator may outperform others during some time intervals featured by particular rainfall characteristics, but they all tend to underestimate rainfall if radar fails to capture the rapid development of rainstorms.

Polarimetric Radar Signatures and Performance of Various Radar Rainfall Estimators during an Extreme Precipitation Event over the Thousand-Island Lake Area in Eastern China

2020 ◽  
Author(s):  
Yabin Gou ◽  
Haonan Chen ◽  
Juan Zhou
Keyword(s):  
Extreme Precipitation ◽  
Eastern China ◽  
Rain Gauge ◽  
Extreme Precipitation Event ◽  
Precipitation Event ◽  
Lake Area ◽  
Polarimetric Radar ◽  
Radar Rainfall ◽  
Light Rain ◽  
Advantages And Disadvantages

<p>Polarimetric radar provides more choices and advantages for quantitative precipitation estimation (QPE). Utilizing the C-band polarimetric (CPOL) radar in Hangzhou, China, six radar QPE estimators based on the horizontal reflectivity (<em>Z</em><sub>H</sub>), the specific attenuation (<em>A</em><sub>H</sub>), the specific differential phase (<em>K</em><sub>DP</sub>), and their corresponding double-parameters that further integrate the differential reflectivity (<em>Z</em><sub>DR</sub>), namely <em>R</em>(<em>Z</em><sub>H</sub>, <em>Z</em><sub>DR</sub>), <em>R</em>(<em>K</em><sub>DP</sub>, <em>Z</em><sub>DR</sub>) and <em>R</em>(<em>A</em><sub>H</sub>, <em>Z</em><sub>DR</sub>), are investigated for an extreme precipitation event occurred in Eastern China on 1 June 2016. These radar QPE estimators are respectively evaluated and compared with a local rain gauge network and drop size distribution (DSD) data observed by two disdrometers. The results show that (i) Each radar QPE estimator has its own advantages and disadvantages depending on the specific rainfall patterns, and it can outperform other estimators at a certain period of time; (ii) although <em>R</em>(<em>A</em><sub>H</sub>, <em>Z</em><sub>DR</sub>) underestimates in the light rain pattern, it performs best of all radar QPE estimators according to statistical scores; (iii) Both the optimal radar rainfall relationship and the consistency between radar measurements aloft and surface observations are required to obtain accurate rainfall estimates close to the ground. The contamination of melting solid hydrometeors on <em>A</em><sub>H</sub> and/or <em>K</em><sub>DP </sub>may make them less effective than <em>Z</em><sub>H</sub>. In addition, appropriate α coefficient can eliminate the melting impact on the <em>A</em><sub>H</sub>-based rainfall estimator.</p>

scholarly journals Response of a mixed grass prairie to an extreme precipitation event

Ecosphere ◽  
2015 ◽  
Vol 6 (10) ◽  
pp. art172 ◽  
Author(s):  
Amy L. Concilio ◽  
Janet S. Prevéy ◽  
Peter Omasta ◽  
James O'Connor ◽  
Jesse B. Nippert ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Extreme Precipitation Event ◽  
Precipitation Event ◽  
Mixed Grass Prairie ◽  
Mixed Grass

Extreme precipitation event over the Yellow Sea western coast: Is there a trend?

2017 ◽  
Vol 441 ◽  
pp. 1-17 ◽  
Author(s):  
Huailiang Wang ◽  
Zhuhai Shao ◽  
Tao Gao ◽  
Tao Zou ◽  
Jie Liu ◽  
...  
Keyword(s):  
Yellow Sea ◽  
Extreme Precipitation ◽  
Extreme Precipitation Event ◽  
The Yellow Sea ◽  
Precipitation Event ◽  
Western Coast

Evaluating the skill of satellite data on the individuation of extreme precipitation events in Calabria (southern Italy)

2020 ◽  
Author(s):  
Tommaso Caloiero ◽  
Roberto Coscarelli ◽  
Giulio Nils Caroletti
Keyword(s):  
Satellite Data ◽  
Extreme Precipitation ◽  
Southern Italy ◽  
Hot Spot ◽  
Rain Gauge ◽  
Precipitation Event ◽  
The European Union ◽  
Extreme Precipitation Events ◽  
Daily Data ◽  
Precipitation Events

<p>In this study, the skill of TRMM Multi-Satellite Precipitation Analysis (TMPA) data to locate spatially and temporally extreme precipitation has been tested over Calabria, a region in southern Italy.</p><p>Calabria is a very challenging region for hydrometeorology studies, as i) it is a mainly mountainous region with complex orography; ii) it is surrounded by sea, providing  an abundance of available moisture; iii) it belongs to the Mediterranean region, a hot-spot for climate change.</p><p>TMPA, which provides daily data at a 0.25° resolution (i.e., about 25 km at southern Italy latitudes), was tested with regards to three extreme precipitation events that occurred between 1998 and 2019, i.e., the years of TMPA’s operational time frame. The first event, taking place on 07-12/09/2000, lasted for several days and involved most of Calabria. The second (01-04/07/2006) was a very localized midsummer event, which hit a very small area with destructive consequences. Finally, the 18-27/11/2013 event was a ten-day long heavy precipitation event that hit the region in spots.</p><p>TMPA daily data were compared against validated and homogenized rain gauge data from 79 stations managed by the Multi-Risk Functional Centre of the Regional Agency for Environmental Protection. TMPA was evaluated both in relative and absolute terms: i) the relative skill was tested by checking if TMPA evaluated correctly the presence of extreme precipitation, defined as daily precipitation passing the 99th percentile threshold; ii) the absolute skill was tested by checking if TMPA reproduced correctly the cumulated precipitation values during the events.</p><p>TMPA proved sufficiently able to locate areas subject to heavy cumulated precipitation during large spatially distributed events over the region. However, it showed difficulties in reproducing very localized events, as the 2006 case study was not detected at all, showing that 25-km spatial resolution and daily time resolution proved inadequate to resolve this type of rainfall event.</p><p>Results might give insights into the possibility of using satellite data for real-time monitoring of extreme precipitation, especially since the transition from the old TMPA to the new Integrated Multi-satellitE Retrievals for GPM (IMERG) set was completed in January 2020.</p><p> </p><p>Acknowledgments:</p><p>The Project INDECIS is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462).</p>

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