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Nathaporn Areerachakul, Sethakarn Prongnuch, Peeranat Longsomboon and Jaya Kandasamy
This study of the Quantitative Estimation Precipitation (QEP) of rainfall, detected by two Meteorology Radars over Chi Basin, North-east Thailand, used data from the Thai Meteorological Department (TMD). The rainfall data from 129 rain gauge stations in ...
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Andre D. L. Zanchetta, Paulin Coulibaly and Vincent Fortin
The use of machine learning (ML) for predicting high river flow events is gaining prominence and among its non-trivial design decisions is the definition of the quantitative precipitation estimate (QPE) product included in the input dataset. This study p...
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Thanh Thi Luong, Ivan Vorobevskii, Judith Pöschmann, Rico Kronenberg, Daniel Gliksman and Christian Bernhofer
Quality of water balance estimations are strongly dependent on the precipitation input. The key limitation here is typically a lack of spatial representation in precipitation data. Quantitative precipitation estimation (QPE) using radar is recognized as ...
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Dayal Wijayarathne, Paulin Coulibaly, Sudesh Boodoo and David Sills
Demand for radar Quantitative Precipitation Estimates (QPEs) as precipitation forcing to hydrological models in operational flood forecasting has increased in the recent past. It is practically impossible to get error-free QPEs due to the intrinsic limit...
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Merhala Thurai, Viswanathan Bringi, Patrick N. Gatlin, Walter A. Petersen and Matthew T. Wingo
The raindrop size distribution (DSD) is fundamental for quantitative precipitation estimation (QPE) and in numerical modeling of microphysical processes. Conventional disdrometers cannot capture the small drop end, in particular the drizzle mode which co...
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Zhigang Chu, Yingzhao Ma, Guifu Zhang, Zhenhui Wang, Jing Han, Leilei Kou and Nan Li
Reflectivity factor bias caused by radar calibration errors would influence the accuracy of Quantitative Precipitation Estimations (QPE), and further result in spatial discontinuity in Multiple Ground Radars QPE (MGR-QPE) products. Due to sampling differ...
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Ibrahim Seck and Joël Van Baelen
Optimal Quantitative Precipitation Estimation (QPE) of rainfall is crucial to the accuracy of hydrological models, especially over urban catchments. Small-to-medium size towns are often equipped with sparse rain gauge networks that struggle to capture th...
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Mario Montopoli, Nicoletta Roberto, Elisa Adirosi, Eugenio Gorgucci and Luca Baldini
Near surface quantitative precipitation estimation (QPE) from weather radar measurements is an important task for feeding hydrological models, limiting the impact of severe rain events at the ground as well as aiding validation studies of satellite-based...
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D. J. GOCHIS,S. W. NESBITT,W. YU,S. F. WILLIAMS
Satellite-based quantitative precipitation estimates (QPE) offer the potential for global, near real-time monitoring of precipitation. Provided their accuracy, in terms of frequency and intensity structures, can be verified, such products would prove...
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S. K. ROY BHOWMIK,S. SEN ROY
n this paper, Principal Component Analysis has been applied to investigate the spatial variability of errors in the INSAT derived quantitative precipitation estimates (QPE) over the Indian monsoon region, using daily rainfall ...
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