김현미

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이름 : 김현미
직함 : 정교수
이메일 : khm@yonsei.ac.kr
전화 : 02-2123-5683
연구실 : 대기예측성 및 자료동화 연구실 / 과학관 541호
웹페이지 : https://apdal.yonsei.ac.kr

연구분야

  • 자료동화, 예측가능성, 확률 예측
  • 대기질 모델링, 탄소 인버스 모델링
  • 최적관측, 관측망 디자인, 관측영향평가
  • 재분석/재예측과 기후 빅데이터
  • 종관규모 및 대규모역학

학력

  • Ph.D. (2002) Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, USA
  • M.S. (1992) Atmospheric Sciences, Yonsei University, Seoul, Korea
  • B.S. (1990) Atmospheric Sciences, Yonsei University, Seoul, Korea

연구 경력

  • 2014-current : Professor, Yonsei University
  • 2009-2014 : Associate professor, Yonsei University
  • 2005-2008 : Assistant professor, Yonsei University
  • 2003-2005 : Research Scientist, Korea Meteorological Administration
  • 2002-2003 : Research Associate, Dept. of Atmospheric and Oceanic Sciences, Univ. of Wisconsin-Madison
  • 1992-1997 : Research Scientist, Korea Meteorological Administration

담당과목

  • 자료동화
  • 대기예측
  • 기상재해
  • 환경과 대기
  • 대기역학 I, 대기역학 II
  • 예측가능성론

논문

  • Kim, D.-H., and H. M. Kim, 2024: Effect of microphysics scheme and data assimilation on hydrometer and radiative flux simulations in the Arctic. Royal Society Open Science, 11, 240594, https://doi.org/10.1098/rsos.240594.
  • Cho, Y., H. M. Kim, E.-G. Yang, Y. Lee, J.-B. Lee, and S. Ha, 2024: Effect of meteorological data assimilation on regional air quality forecasts over the Korean Peninsula. Journal of Meteorological Research, 38, 1-23. https://doi.org/10.1007/s13351-024-3152-8.
  • Ha, S., R. Kumar, G. G. Pfister, Y. Lee, D. Lee, H. M. Kim, and Y.-H. Ryu, 2024: Chemical data assimilation with aqueous chemistry in WRF-Chem coupled with WRFDA (V4.4.1). Journal of Advances in Modeling Earth Systems, 16, e2023MS003928, https://doi.org/10.1029/2023MS003928.
  • Seo, M.-G., H. M. Kim, and D.-H. Kim, 2024: Effect of atmospheric conditions and VPRM parameters on high-resolution regional CO2 simulations over East Asia. Theoretical and Applied Climatology, 155, 859-877, https://doi.org/10.1007/s00704-023-04663-2.
  • Kim, D.-H., and H. M. Kim, 2024: Design of buoy observation network over the Arctic Ocean. Cold Regions Science and Technology, 218, 104087, https://doi.org/10.1016/j.coldregions.2023.104087.
  • Kim, D.-H., and H. M. Kim, 2023: Evaluation of observation impact on the meteorological forecasts associated with heat wave in 2018 over East Asia using observing system experiments. Heliyon, 9, e23064, https://doi.org/10.1016/j.heliyon.2023.e23064.
  • Seo, M.-G., and H. M. Kim, 2023: Effect of meteorological data assimilation using 3DVAR on high-resolution simulations of atmospheric CO2 concentrations in East Asia. Atmospheric Pollution Research, 14, 101759, https://doi.org/10.1016/j.apr.2023.101759.
  • Terao T., S. Kanae, H. Fujinami, S. Das, A. P. Dimri, S. Dutta, K. Fujita, A. Fukushima, K.-J. Ha, M. Hirose, J. Hong, H. Kamimera, R. B. Kayastha, M. Kiguchi, K. Kikuchi, H. M. Kim, A. Kitoh, H. Kubota, W. Ma, Y. Ma, M. Mujumdar, M. I. Nodzu, T. Sato, Z. Su, S. Sugimoto, H. G. Takahashi, Y. Takaya, S. Wang, K. Yang, S. Yokoi, and J. Matsumoto, 2023: AsiaPEX: Challenges and Prospects in Asian Precipitation Research. Bulletin of the American Meteorological Society.
  • Kim, D.-H., and H. M. Kim, 2022: Deep learning for downward longwave radiative flux forecasts in the Arctic. Expert Systems With Applications, 210, 118547, https://doi.org/10.1016/j.eswa.2022.118547.
  • Yang, E.-G., H. M. Kim, and D.-H. Kim, 2022: Development of East Asia Regional Reanalysis based on advanced hybrid gain data assimilation method and evaluation with E3DVAR, ERA-5, and ERA-Interim reanalysis. Earth System Science Data, 14, 2109-2127, https://doi.org/10.5194/essd-14-2109-2022.
  • Kim, D.-H., and H. M. Kim, 2022: Effect of data assimilation in the Polar WRF with 3DVAR on the prediction of radiation, heat flux, cloud, and near surface atmospheric variables over Svalbard. Atmospheric Research, 272, 106155, https://doi.org/10.1016/j.atmosres.2022.106155.
  • Cho, M., and H. M. Kim, 2022: Effect of assimilating CO2 observations in the Korean Peninsula on the inverse modeling to estimate surface CO2 flux over Asia. PLoS ONE, 17, e0263925. https://doi.org/10.1371/journal.pone.0263925.
  • Kim, H. M., and D.-H. Kim, 2021: Effect of boundary conditions on adjoint-based forecast sensitivity observation impact in a regional model. Journal of Atmospheric and Oceanic Technology, 38, 1233-1247, doi:10.1175/JTECH-D-20-0040.1.
  • Yang, E.-G., and H. M. Kim, 2021: A comparison of variational, ensemble-based, and hybrid data assimilation methods over East Asia for two one-month periods, Atmospheric Research, 249,105257, https://doi.org/10.1016/j.atmosres.2020.105257.
  • Park, J., and H. M. Kim, 2020: Design and evaluation of CO₂ observation network to optimize surface CO₂ fluxes in Asia using observation system simulation experiments, Atmospheric Chemistry and Physics, 20, 5175-5195, https://doi.org/10.5194/acp-20-5175-2020.
  • Kim, D.-H., H. M. Kim, and J. Hong, 2019: Evaluation of wind forecasts over Svalbard using the high-resolution Polar WRF with 3DVAR, Arctic, Antarctic, and Alpine Research, 51, 471-489, doi:10.1080/ 15230430.2019.1676939.
  • He, J., F. Zhang, X. Chen, X. Bao, D. Chen, H. M. Kim, H.-W. Lai, L. R. Leung, X. Ma, Z. Meng, T. Ou, Z. Xiao, E.-G. Yang, and K. Yang, 2019: Development and evaluation of an ensemble-based data assimilation system for regional reanalysis over the Tibetan Plateau and surrounging regions, Journal of Advances in Modeling Earth Systems, 11, 2503-2522, doi:10.1029/2019MS001665.
  • Kim, S.-M., and H. M. Kim, 2019: Forecast sensitivity observation impact in the 4DVAR and Hybrid-4DVAR data assimilation systems, Journal of Atmospheric and Oceanic Technology, 36, 1563-1575, doi:10.1175/JTECH-D-18-0240.1.
  • Hwang, S.-O., J. Park,and H. M. Kim, 2019: Effect of hydrometeor species on very-short-range simulations of precipitation using ERA5, Atmospheric Research, 218, 245-256, doi:10.1016/j.atmosres.2018.12.008.
  • On, N., H. M. Kim, and S. Kim, 2018: Effects of resolution, cumulus parameterization scheme, and probability forecasting on precipitation forecasts in a high-resolution limited-area ensemble prediction system, Asia-Pacific Journal of Atmospheric Sciences, 54, 623-637, doi:10.1007/s13143-018-0081-4.
  • Kim, S.-M., and H. M. Kim, 2018: Effect of observation error variance adjustment on numerical weather prediction using forecast sensitivity to error covariance parameters, Tellus A, 70, 1-16, doi:10.1080 /16000870.2018.1492839
  • Kim, D.-H., and H. M. Kim, 2018: Effect of assimilating Himawari-8 atmospheric motion vectors on forecast errors over East Asia, Journal of Atmospheric and Oceanic Technology, 35, 1737-1752, doi:10.1175/JTECH-D-17-0093.1.
  • Kim, H., H. M. Kim, M. K. Cho, J. Park, and D.-H. Kim, 2018: Development of the aircraft CO₂ measurement data assimilation system to improve the estimation of surface CO₂ fluxes using an inverse modeling system, Atmosphere, 28(2), 1-9, doi:10.14191/Atmos.2018.28.2.113. (in Korean with English abstract)
  • Noh, K., H. M. Kim, and D.-H. Kim, 2018: Development of the three-dimensional variational data assimilation system for the Republic of Korea Air Force operational numerical weather prediction system, Journal of the Korea Institute of Military Science and Technology, 21(3), 403-412, doi:10.9766/KIMST.2018.21.3.403. (in Korean with English abstract)
  • Kim, H., H. M. Kim, J. Kim, and C.-H. Cho, 2018: Effect of data assimilation parameters on the optimized surface CO₂ flux in Asia, Asia-Pacific Journal of Atmospheric Sciences, 54, 1-17, doi:10.1007/s13143-017-0049-9.
  • Yang, E.-G., and H. M. Kim, 2017: Evaluation of a regional reanalysis and ERA-Interim over East Asia using in situ observations during 2013-14, Journal of Applied Meteorology and Climatology, 56, 2821-2844, doi: 10.1175/JAMC-D-16-0227.1.
  • Kim, S., and H. M. Kim, 2017: Effect of considering sub-grid scale uncertainties on the forecasts of a high-resolution limited area ensemble prediction system, Pure and Applied Geophysics, 174(5), 2021-2037, doi: 10.1007/s00024-017-1513-2.
  • Kim, S.-M., and H. M. Kim, 2017: Adjoint-based observation impact of Advanced Microwave Sounding Unit-A (AMSU-A) on the short-range forecast in East Asia, Atmosphere, 27(1), 93-104, doi:10.14191/Atmos.2017.27.1.093. (in Korean with English abstract)
  • Kim, M., H. M. Kim, J. Kim, S.-M. Kim, C. Velden, and B. Hoover, 2017: Effect of enhanced satellite-derived atmospheric motion vectors on numerical weather prediction in East Asia using an adjoint-based observation impact method, Weather and Forecasting, 32, 579-594, doi:10.1175/WAF-D-16-0061.1.
  • Kim, J., H. M. Kim, C.-H. Cho, K.-O. Boo, A. R. Jacobson, M. Sasakawa, T. Machida, M. Arshinov, and N. Fedoseev, 2017: Impact of Siberian observations on the optimization of surface CO₂flux, Atmospheric Chemistry and Physics, 17, 2881-2899, doi:10.5194/acp-17-2881-2017.
  • Kim, H. J., H. M. Kim, J. Kim, and C.-H. Cho, 2016: A Comparison of the Atmospheric CO₂ Concentrations Obtained by an Inverse Modeling System and Passenger Aircraft Based Measurement, Atmosphere, 26(3), 387-400. (in Korean with English abstract)
  • Kim, S., H. M. Kim, J. K. Kay, and S.-W. Lee, 2015: Development and evaluation of high resolution limited area ensemble prediction system in KMA, Atmosphere, 25(1), 67-83. (in Korean with English abstract)
  • Kim, J., H. M. Kim, and C.-H. Cho, 2014: Influence of CO₂ observations on the optimized CO₂ flux in an ensemble Kalman filter, Atmospheric Chemistry and Physics, 14, 13515-13530, doi:10.5194/acp-14-13515-2014.
  • Yang, E.-G., H. M. Kim, J. Kim, and J. K. Kay, 2014: Effect of observation network design on meteorological forecasts of Asian dust events, Monthly Weather Review, 142, 4679-4695, doi:10.1175/MWR-D-14-00080.1.
  • Kim, S.-M., and H. M. Kim, 2014: Sampling error of observation impact statistics, Tellus A, 66, 25435, http://dx.doi.org/10.3402/tellusa.v66.25435.
  • Kay, J. K., and H. M. Kim, 2014: Characteristics of initial perturbations in the ensemble prediction system of the Korea Meteorological Administration, Weather and Forecasting, 29, 563-581, doi: 10.1175/WAF-D-13-00097.1.
  • Kim, J., H. M. Kim, and C.-H. Cho, 2014: The effect of optimization and the nesting domain on carbon flux analyses in Asia using a carbon tracking system based on the ensemble Kalman filter, Asia-Pacific Journal of Atmospheric Sciences, 50, 327-344, doi:10.1007/s13143-014-0020-y.
  • Jung, B.-J., H. M. Kim, T. Auligne, X. Zhang, X. Zhang, and X.-Y. Huang, 2013: Adjoint-derived observation impact using WRF in the western North Pacific, Monthly Weather Review, 141, 4080-4097.
  • Kim, H. M., J. K. Kay, E.-G. Yang, S. Kim, M. Lee, 2013: Statistical adjoint sensitivity distributions for meteorological forecast errors of Asian dust transport events in Korea, Tellus B, 65, 20554, http://dx.doi.org/10/3402/tellusb.v65i0.20554.
  • Kay, J. K., H. M. Kim, Y.-Y. Park, and J. Son, 2013: Effect of doubling ensemble size on the performance of ensemble prediction in warm season using MOGREPS implemented in KMA, Advances in Atmospheric Sciences, 30(5), 1287-1302, doi:10.1007/s00376-012-2083-y.
  • Kim, S., H. M. Kim, E.-J. Kim, and H.-C. Shin, 2013: Forecast sensitivity to observations for high-impact weather events in the Korean Peninsula, Atmosphere, 23(2), 171-186. (in Korean with English abstract)
  • Park, S.-Y., H. M. Kim, T.-Y. Lee, and M. Morgan, 2013: Statistical distributions of singular vectors for tropical cyclones affecting Korea over a 10-year period, Meteorology and Atmospheric Physics, 120, 107-122, doi: 10.1007/s00703-013-0247-7.
  • Kim, J., H. M. Kim, and C.-H. Cho, 2012: Application of Carbon Tracking System based on ensemble Kalman filter on the diagnosis of Carbon Cycle in Asia, Atmosphere, 22(4), 415-427. (in Korean with English abstract)
  • Jung, B.-J., H. M. Kim, F. Zhang, and C.-C. Wu, 2012: Effect of targeted dropsonde observations and best track data on the track forecasts of Typhoon Sinlaku (2008) using an Ensemble Kalman Filter, Tellus A, 64, 14984, doi: 10.3402/tellusa.v64i0.14984.
  • Kim, H. M., S.-M. Kim, and B.-J. Jung, 2011: Real-time adaptive observation guidance using singular vectors for typhoon Jangmi (200815) in T-PARC 2008, Weather and Forecasting, 26, 634-649, doi: 10.1175/WAF-D-10-05013.1.
  • Kim, S.-M., H. M. Kim, S.-W. Joo, H.-C. Shin, and D. Won, 2011: Development of tools for calculating forecast sensitivities to the initial condition in the Korea Meteorological Administration (KMA) Unified Model (UM), Atmosphere, 21(2), 163-172. (in Korean with English abstract)
  • Kim, H. M., and R. J. Beare, 2011: Characteristics of adjoint sensitivity to potential vorticity. Meteorology and Atmospheric Physics, 111, 91-102, doi: 10.1007/s00703-010-0119-3.
  • Hong, S.-Y., H. M. Kim, J.-E. Kim, S.-O. Hwang, and H. Park, 2011: The impact of model uncertainties on analyzed data in a global data assimilation system, Terrestrial, Atmospheric and Oceanic Sciences, 22(1),41-47.
  • Kim, H. M., and J. K. Kay, 2010: Forecast sensitivity analysis of an Asian dust event occurred on 6-8 May 2007 in Korea, Atmosphere, 20(4), 399-414. (in Korean with English abstract)
  • Park, J. I., and H. M. Kim, 2010: Typhoon Wukong (200610) prediction based on the Ensemble Kalman Filter and ensemble sensitivity analysis, Atmosphere, 20(3), 287-306. (in Korean with English abstract)
  • Jung, B.-J., H. M. Kim, Y.-H. Kim, E.-H. Jeon, and K.-H. Kim, 2010: Observation system experiments for Typhoon Jangmi (200815) observed during T-PARC, Asia-Pacific J. Atmos. Sci., 46, 305-316.
  • Jung, B.-J. and H. M. Kim, 2009: Moist-adjoint based forecast sensitivities for a heavy snowfall event over the Korean peninsula on 4-5 March 2004, J. Geophys. Res., 114, D15104, DOI:10.1029/2008JD011370.
  • Kim, H. M., and B.-J. Jung, 2009: Influence of moist physics and norms on singular vectors for a tropical cyclone. Mon. Wea. Rev., 137, 525-543.
  • Kim, H. M., and B.-J. Jung, 2009: Singular vector structure and evolution of a recurving tropical cyclone. Mon. Wea. Rev., 137, 505-524.
  • Kim, H. M., B.-J. Jung, Y. -H. Kim, and H.-S. Lee, 2008: Adaptive observation guidance applied to Typhoon Rusa: Implications for THORPEX-PARC 2008. Asia-Pacific J. Atmos. Sci., 44, 297-312.
  • Kim, H. M., J. K. Kay, and B.-J. Jung, 2008: Application of adjoint-based forecast sensitivities to Asian dust transport events in Korea. Water, Air, and Soil Pollution, 195, 335-343, DOI:10.1007/s11270-008-9750-8.
  • Kim, H. M., and B.-J. Jung, 2006: Adjoint-based forecast sensitivities of Typhoon Rusa. Geophys. Res. Lett., 33, L21813, DOI:10.1029/2006GL027289.
  • Kim, H. M., Y. H. Youn, and H. S. Chung, 2004: Potential vorticity thinking as an aid to understanding midlatitude weather systems. Journal of the Korean Meteorological Society, 40(6), 633-647.
  • Kim, H. M., M. Morgan, and R. E. Morss, 2004: Evolution of analysis error and adjoint-based sensitivities: Implications for adaptive observations. J. Atmos. Sci., 61, 795-812.
  • Kim, H. M., 2003: A computation of adjoint-based sensitivities in a quasigeostrophic model. Korean Journal of the Atmospheric Sciences, 6(2), 71-83.
  • Kim, H. M. and M. Morgan, 2002: Dependence of singular vector structure and evolution on the choice of norm. J. Atmos. Sci., 59, 3099-3116.