|
|
|
|
|
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 ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chiara Corbari, Giovanni Ravazzani, Alessandro Perotto, Giulio Lanzingher, Gabriele Lombardi, Matteo Quadrio, Marco Mancini and Raffaele Salerno
This paper presents a system for supporting hydropower production on mountainous areas. The system couples the outputs of a numerical weather prediction model and a snow melting and accumulation temperature-based model. Several procedures are presented f...
ver más
|
|
|
|
|
|
|
|
|
|
|
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 ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Lina Yuan, Long Li, Ting Zhang, Longqian Chen, Weiqiang Liu, Sai Hu and Longhua Yang
This study aims to integrate multisource data to model the relative soil moisture (RSM) over the Chinese Loess Plateau in 2017 by stepwise multilinear regression (SMLR) in order to improve the spatial coverage of our previously published RSM. First, 34 c...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jae-Kyoung Lee and Chang Geun Song
Several sources of bias are involved at each stage of a quantitative precipitation estimation process because weather radars measure precipitation amounts indirectly. Conventional methods compare the relative uncertainties between different stages of the...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
Roberto Cremonini and Renzo Bechini
Piemonte region, in the north-western Italy, is characterized by complex orography and Mediterranean influence that often causes extreme rainfall event, during the warm season. Although the region is monitored by a dense gauge network (more than one gaug...
ver más
|
|
|
|
|
|