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Dong Jun Seo
Researcher at University of Texas at Arlington
Publications - 140
Citations - 8790
Dong Jun Seo is an academic researcher from University of Texas at Arlington. The author has contributed to research in topics: Hydrological modelling & Quantitative precipitation estimation. The author has an hindex of 42, co-authored 138 publications receiving 8067 citations. Previous affiliations of Dong Jun Seo include National Oceanic and Atmospheric Administration & Silver Spring Networks.
Papers
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Journal ArticleDOI
The WSR-88D Rainfall Algorithm
TL;DR: In this paper, a detailed description of the operational WSR-88D rainfall estimation algorithm is presented, and the processing steps to quality control and compute the rainfall estimates are described, and current deficiencies and future plans for improvement are discussed.
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Overall distributed model intercomparison project results
Seann Reed,Victor Koren,Michael Smith,Ziya Zhang,Fekadu Moreda,Dong Jun Seo,and Dmip Participants +6 more
TL;DR: The results from the Distributed Model Intercomparison Project (DMIP) study as discussed by the authors show that some calibration strategies for distributed models are not as well defined as strategies for lumped models, but some calibration efforts applied to distributed models significantly improve simulation results.
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National Mosaic and Multi-Sensor QPE (NMQ) System: Description, Results, and Future Plans
Jian Zhang,Kenneth W. Howard,Carrie Langston,Steve Vasiloff,Brian Kaney,Ami Arthur,Suzanne Van Cooten,Kevin E. Kelleher,David Kitzmiller,Feng Ding,Dong Jun Seo,Ernie Wells,Chuck Dempsey +12 more
TL;DR: The National Mosaic and Multi-sensor Quantitative Precipitation Estimation (NMQ) system was initially developed from a joint initiative between the National Oceanic and Atmospheric Administration's National Severe Storms Laboratory, the Federal Aviation Administration's Aviation Weather Research Program, and the Salt River Project.
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The distributed model intercomparison project (DMIP): Motivation and experiment design
Michael B. Smith,Dong Jun Seo,Victor Koren,Seann Reed,Ziya Zhang,Qingyun Duan,Fekadu Moreda,Shuzheng Cong +7 more
TL;DR: The distributed model intercomparison project was formulated as a broad comparison of many distributed models amongst themselves and to a lumped model used for operational river forecasting in the US to address unresolved questions on the variability of rainfall and its effect on basin response.
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Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities
Yuqiong Liu,Yuqiong Liu,Albrecht Weerts,Martyn P. Clark,Harrie-Jan Hendricks Franssen,Sujay V. Kumar,Sujay V. Kumar,Hamid Moradkhani,Dong Jun Seo,Dirk Schwanenberg,Paul Smith,A. I. J. M. van Dijk,N. van Velzen,Minxue He,Haksu Lee,Haksu Lee,Seong Jin Noh,Oldrich Rakovec,P. Restrepo +18 more
TL;DR: It is recommended that cost-effective transition of hydrologic DA from research to operations should be helped by developing community-based, generic modeling and DA tools or frameworks, and through fostering collaborative efforts among hydrologics modellers, DA developers, and operational forecasters.