D
Dongsoo Kim
Researcher at National Oceanic and Atmospheric Administration
Publications - 15
Citations - 1205
Dongsoo Kim is an academic researcher from National Oceanic and Atmospheric Administration. The author has contributed to research in topics: Quantitative precipitation estimation & Rapid update cycle. The author has an hindex of 10, co-authored 15 publications receiving 1124 citations.
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Journal ArticleDOI
An Hourly Assimilation–Forecast Cycle: The RUC
Stanley G. Benjamin,Dezso Devenyi,Stephen S. Weygandt,Kevin J. Brundage,John M. Brown,Georg Grell,Dongsoo Kim,Barry E. Schwartz,Tatiana G. Smirnova,Tracy Lorraine Smith,Geoffrey S. Manikin +10 more
TL;DR: The Rapid Update Cycle (RUC) as discussed by the authors is an operational regional analysis-forecast system among the suite of models at the National Centers for Environmental Prediction (NCEP), which is distinctive in two primary aspects: its hourly assimilation cycle and its use of a hybrid isentropic-sigma vertical coordinate.
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Parameterization of cold-season processes in the MAPS land-surface scheme
TL;DR: In this paper, the Mesoscale Analysis and Prediction System (MAPS) is improved to include a snow accumulation/melting scheme and also parameterization of processes in frozen soil.
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Multisensor Precipitation Reanalysis
TL;DR: In this paper, the authors have reengineered the multisensor precipitation estimator (MPE) algorithms of the NWS into the MPR package, which allows for the utilization of additional rain gauge data, more rigorous automatic quality control, and post factum correction of radar quantitative precipitation estimation (QPE).
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Characteristics of Reprocessed Hydrometeorological Automated Data System (HADS) Hourly Precipitation Data
TL;DR: In this paper, the quality of the reprocessed HADS hourly precipitation data from rain gauges is assessed by two objective metrics: the average fraction of missing values and the percentage of top-of-the-hour observations for a 3-yr period (2003-05).
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Evolving Multisensor Precipitation Estimation Methods: Their Impacts on Flow Prediction Using a Distributed Hydrologic Model
David Kitzmiller,Suzanne Van Cooten,Feng Ding,Kenneth W. Howard,Carrie Langston,Jian Zhang,Heather Moser,Yu Zhang,Jonathan J. Gourley,Dongsoo Kim,David Riley +10 more
TL;DR: In this paper, the authors investigated evolving methodologies for radar and merged gauge-radar quantitative precipitation estimation (QPE) to determine their influence on the flow predictions of a distributed hydrologic model.