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Young Cheol Kwon

Korea Meteorological Administration

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Song‐You Hong

Cooperative Institute for Research in Environmental Sciences

Vijay Tallapragada

National Oceanic and Atmospheric Administration

In‐Hyuk Kwon

Korea Institute of Atmospheric Prediction Systems

William M. Frank

Pennsylvania State University

Junghan Kim

Korea Institute of Atmospheric Prediction Systems

Suk‐Jin Choi

Gangneung–Wonju National University

Myung‐Seo Koo

Korea Institute of Atmospheric Prediction Systems

In‐Jin Choi

Korea Institute of Atmospheric Prediction Systems

Jung-Eun Esther Kim

Korea Institute of Atmospheric Prediction Systems

TaeHun Kim

Korea Institute for Advanced Study

Cooperative Institutions

Korea Institute of Atmospheric Prediction Systems

National Oceanic and Atmospheric Administration

Korea Meteorological Administration

Seoul National University

Yonsei University

NOAA Environmental Modeling Center

NOAA National Centers for Environmental Prediction

NSF National Center for Atmospheric Research

National Institute of Meteorological Sciences

Kyungpook National University

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Tropical Cyclone Initialization for the Hurricane WRF Model

한국기상학회 학술대회 논문집 (2013)

In‐Hyuk Kwon Mingjing Tong Young Cheol Kwon Vijay Tallapragada

Atlantic hurricane

Tropical cyclone scales

Initialization

Typhoon

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Updates in the NCEP GFS Cumulus Convection Schemes with Scale and Aerosol Awareness

Weather and Forecasting (2017)

Jongil Han Weiguo Wang Young Cheol Kwon Song‐You Hong Vijay Tallapragada

Abstract The current operational NCEP Global Forecast System (GFS) cumulus convection schemes are updated with a scale-aware parameterization where the cloud mass flux decreases with increasing grid resolution. The ratio of advective time to convective turnover time is also taken into account for the scale-aware parameterization. In addition, the present deep cumulus convection closure using the quasi-equilibrium assumption is no longer used for grid sizes smaller than a threshold value. For the shallow cumulus convection scheme, the cloud-base mass flux is modified to be given by a function of mean updraft velocity. A simple aerosol-aware parameterization where rain conversion in the convective updraft is modified by aerosol number concentration is also included in the update. Along with the scale- and aerosol-aware parameterizations, more changes are made to the schemes. The cloud-base mass-flux computation in the deep convection scheme is modified to use convective turnover time as the convective adjustment time scale. The rain conversion rate is modified to decrease with decreasing air temperature above the freezing level. Convective inhibition in the subcloud layer is used as an additional trigger condition. Convective cloudiness is enhanced by considering suspended cloud condensate in the updraft. The lateral entrainment in the deep convection scheme is also enhanced to more strongly suppress convection in a drier environment. The updated NCEP GFS cumulus convection schemes display significant improvements especially in the summertime continental U.S. precipitation forecasts.

Convective inhibition

Entrainment (biomusicology)

Free convective layer

Mass flux

Cloud base

10.1175/waf-d-17-0046.1

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Improvement of Rain Rate Estimation using the GMS-5 IR Data and rainrate by radars over Japan

International Symposium on Remote Sensing (2000)

H. S. Park Young Cheol Kwon Myung-Hwan Ahn A. S. Suh

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<title>Improvement of rain rate estimation using the GMS-5 IR data and verification</title>

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (2000)

Hye S. Park Young Cheol Kwon Myoung‐Hwan Ahn K. L. Kim

Hourly rain rates are estimated operationally in Korea Meteorological Administration (KMA) since last year by the regression method (A_REG), which uses the GMS-5 IR and Automatic Weather Systems (AWS) gauges data over Korean Peninsula. As the results, A_REG method estimates rain rate better than other retrieval methods such as probability matching method and look up table method do. However, this equation can't represent on the whole area including oceans because a number of rain gauges are limited over Korean peninsula. In this study the A_REG method has been improved by using the radar rain rate over Japan instead of AWS over Korea Peninsula. As the statistical verification, the estimated rain rates by R_REG method are improved than existing method (A_REG). The mean errors of R_REG nearly don't appear though A_REG show positive bias. Root mean square errors of R_REG are 2-3 times smaller than A_REG. The correlation coefficients of two methods are similar.

Rain rate

Peninsula

Table (database)

10.1117/12.410621

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Community Support and Transition of Research to Operations for the Hurricane Weather Research and Forecasting Model

Bulletin of the American Meteorological Society (2014)

Lígia Bernardet Vijay Tallapragada Shaowu Bao S. Trahan Young Cheol Kwon

Abstract The Hurricane Weather Research and Forecasting Model (HWRF) is an operational model used to provide numerical guidance in support of tropical cyclone forecasting at the National Hurricane Center. HWRF is a complex multicomponent system, consisting of the Weather Research and Forecasting (WRF) atmospheric model coupled to the Princeton Ocean Model for Tropical Cyclones (POM-TC), a sophisticated initialization package including a data assimilation system and a set of postprocessing and vortex tracking tools. HWRF’s development is centralized at the Environmental Modeling Center of NOAA’s National Weather Service, but it incorporates contributions from a variety of scientists spread out over several governmental laboratories and academic institutions. This distributed development scenario poses significant challenges: a large number of scientists need to learn how to use the model, operational and research codes need to stay synchronized to avoid divergence, and promising new capabilities need to be tested for operational consideration. This article describes how the Developmental Testbed Center has engaged in the HWRF developmental cycle in the last three years and the services it provides to the community in using and developing HWRF.

Testbed

National weather service

Initialization

10.1175/bams-d-13-00093.1

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Study on the Thermal Bridge Reduction Method Between Windows and Walls

LHI journal of land, housing, and urban affairs (2021)

Woong Hoe Kim Kyoung Ha Kang Cheol Yong Park Young Cheol Kwon

Bridge (graph theory)

10.5804/lhij.2021.12.1.119

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Applications of Low-Emissivity Hybrid Insulation in South Korea

Journal of Power and Energy Engineering (2016)

Young Cheol Kwon

10.4236/jpee.2016.74002

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Evaluation of a Multi-Model Ensemble Prediction System 

Hyun-Cheol Shin Eun‐Jung Kim Sug-gyeong Yun Hyun‐Suk Kang Young Cheol Kwon

<p>A multi-model ensemble prediction system that integrates UM (Unified Model) global and ensemble models, ECMWF global and ensemble models, and KIM (Korean Integrated Model) global model was established and its performance was evaluated. KIM is KMA&#8217;s new generation model which is based on the cubed sphere grid system and has 12km horizontal resolution and 91 vertical levels. It was developed over 9 years from 2011 to 2019 and operationally launched in April 2020.<br>The optimal mean field was produced by weighted average of 5 models, where the weights were given inversely proportional to the error of each model.<br>As a result of comparing RMSE (Root Mean Square Error) of the multi-model ensemble with 5 member models, a multiple-model ensemble showed better performance than any other member model. It was better than ECMWF ensemble model which showed the best performance among member models. In RMSE score, Mean Surface pressure was improved by 3.1% and 500hPa geopotential height was improved by 2.1% against ECMWF ensemble model.&#160;<br>The performance of a multi-model ensemble by various weight calculation methods which are used for weighted averaging was compared. It was found that horizontally domain-averaged weight, having the different value for the forecast time gave the best performance. Giving the detailed and complex weights differently for each forecast time and each grid point rather degraded the performance of a multi-model ensemble.<br>In BIAS verification, it was found that the BIAS of the multi-model ensemble showed the value between the maximum BIAS and the minimum BIAS of member models. Therefore, it was found that when the BIAS of the member models was distributed in a balanced positive and negative directions without being biased in one direction, the multi-model ensemble showed the smallest BIAS.</p>

Ensemble forecasting

Root mean square

Geopotential height

Ensemble average

10.5194/ems2022-386

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Status and Plan of Standard Verification System for the NWP model in Korea Meteorological Administration

So Ra Park H.K. Park Hae-Jin Lee S. N. Song Jong-Chul Ha

The Korea Meteorological Administration (KMA) has established and operated a standard verification system of the operational NWP models to evaluate the predictive performance of NWP model and compare them with other NWP models operated by domestic and foreign organization. This secures the objectivity of the verification results by applying the verification standards (WMO-No.485) presented by World Meteorological Organization (WMO), and being able to compare the performance with the numerical forecasting models of other institutions under the same conditions. The NWP models to be verified is a global, a regional, very short-range, and an ensemble prediction system and verification against analyses and observations are performed twice a day (00 UTC, 12 UTC). In addition to standard verification, precipitation, typhoon and various verification indexes (CBS index, KMA index, jumpiness index) are verified and used to evaluate the utilization of NWP models. The Korea Integrated Model (KIM), which is developed for Korea’s own NWP model, has been in operation since April 2020. Since the start of operation, the RMSE of 500hPa geopotential height (in Northern Hemisphere) has decreased every year, showing that forecast performance is improving. In addition, it can be seen that the 72-hour prediction accuracy for 12-hour accumulated precipitation (1.0 mm or more) in the Korean Peninsula area (75 ASOS stations) is also improving. As such, this study intends to discuss the predictive performance of the numerical forecast model based on the standard verification system and plans to improve the verification system in the future. 

10.5194/egusphere-egu24-14541

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Impact of Turbulent Mixing in the Stratocumulus-Topped Boundary Layer on Numerical Weather Prediction

Asia-Pacific Journal of Atmospheric Sciences (2018)

Eunhee Lee Eunjung Lee Rae‐Seol Park Young Cheol Kwon Song‐You Hong

Entrainment (biomusicology)

Radiative Cooling

10.1007/s13143-018-0024-0

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Citations (14)

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