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Korean Meteorological Society (한국기상학회)
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Numerical Weather Prediction and Forecast Application

수치모델링과 예보

  • Woo-Jin Lee (Korea Institute of Atmospheric Prediction Systems) ;
  • Rae-Seol Park (Korea Institute of Atmospheric Prediction Systems) ;
  • In-Hyuk Kwon (Korea Institute of Atmospheric Prediction Systems) ;
  • Junghan Kim (Korea Institute of Atmospheric Prediction Systems)
  • 이우진 ((재) 차세대수치예보모델개발사업단) ;
  • 박래설 ((재) 차세대수치예보모델개발사업단) ;
  • 권인혁 ((재) 차세대수치예보모델개발사업단) ;
  • 김정한 ((재) 차세대수치예보모델개발사업단)
  • Received : 2022.10.23
  • Accepted : 2022.12.26
  • Published : 2023.03.31
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Abstract

Over the past 60 years, Korean numerical weather prediction (NWP) has advanced rapidly with the collaborative effort between the science community and the operational modelling center. With an improved scientific understanding and the growth of information technology infrastructure, Korea is able to provide reliable and seamless weather forecast service, which can predict beyond a 10 days period. The application of NWP has expanded to support decision making in weather-sensitive sectors of society, exploiting both storm-scale high-impact weather forecasts in a very short range, and sub-seasonal climate predictions in an extended range. This article gives an approximate chronological account of the NWP over three periods separated by breakpoints in 1990 and 2005, in terms of dynamical core, physics, data assimilation, operational system, and forecast application. Challenges for future development of NWP are briefly discussed.

Keywords

Acknowledgement

본 논문의 개선을 위해 좋은 의견을 제시해 주신 두분의 심사위원께 감사를 드립니다. 본 연구는 기상청출연사업인 (재)차세대수치예보모델개발사업단의 가변격자체계 기반 통합형수치예보모델 개발(KMA2020-02212) 과제의 지원을 받아 수행되었습니다.

References

  1. Ahn, J.-B., J. Hur, and A-Y. Lim, 2014: Estimation of finescale daily temperature with 30m-resolution using PRISM. Atmosphere. Korean Meteor. Soc., 24, 101-110, doi: 10.14191/Atmos.2014.24.1.101. 
  2. Ahn, J.-B., and J. Lee, 2015: Comparative study on the seasonal predictability dependency of boreal winter 2 m temperature and sea surface temperature on CGCM initial conditions. Atmosphere. Korean Meteor. Soc., 25, 353-366, doi: 10.14191/Atmos.2015.25.2.353. 
  3. Ahn, M.-H., J. Kim, G.-W. Lee, and S.-W. Kim, 2023: A progress status of remote sensing in the Korean Meteorological Society. Atmosphere. Korean Meteor. Soc., 33, 197-222, doi: 10.14191/Atmos.2023.33.2.197. 
  4. Bae, S. Y., and R.-S. Park, 2019: Consistency between the cloud and radiation processes in a numerical forecasting model. Meteor. Atmos. Phys., 131, 1429-1436, doi: 10.1007/s00703-018-0647-9. 
  5. Bae, S. Y., S.-Y. Hong, and K.-S. Lim, 2016: Coupling WRF double-moment 6-class microphysics schemes to RRTMG radiation scheme in weather research forecasting model. Adv. Meteor., doi: 10.1155/5070154. 
  6. Baek, S. H., 2017: A revised radiation package of G-packed McICA and two-stream approximation: Performance evaluation in a global weather forecasting model. J. Adv. Model. Earth Syst., 9, doi: 10.1002/2017MS000994. 
  7. Byun, U.-Y., and Coauthors, 2011: WRF-based short-range forecast system of the Korea Air Force: verification of prediction skill in 2009 summer. Atmosphere. Korean Meteor. Soc., 21, 197-208, doi: 10.14191/Atmos.2011.21.2.197. 
  8. Byun, Y.-H., and S.-Y. Hong, 2007: Improvements in the subgrid-scale representation of moist convection in a cumulus parameterization scheme: the single-column test and its impact on seasonal prediction. Mon. Wea. Rev., 135, 2135-2154.  https://doi.org/10.1175/MWR3397.1
  9. Chang, D.-E., and D.-K. Lee, 1989: A simulation study of the tropical cyclone Vera using a mesoscale numerical model. J. Korean Meteor. Soc., 25, 148-167. 
  10. Chang, E.-C., and K. Yoshimura, 2015: A semi-Lagrangian advection scheme for radioactive tracers in the NCEP regional spectral model (RSM). Geosci. Model Dev., 8, 3247-3255, doi: 10.5194/gmd-8-3247-2015. 
  11. Chang, P.-H., and Coauthors, 2021: Global ocean data assimilation and prediction system in KMA: description and assessment. Atmosphere. Korean Meteor. Soc., 31, 229-240, doi: 10.14191/Atmos.2021.31.2.229. 
  12. Cheong, H.-B., 1999a: Solution of elliptic equation on a sphere using double Fourier series. J. Korean Meteor. Soc., 35, 247-253. 
  13. Cheong, H.-B., 1999b: A spectral method using double Fourier series on a sphere: application of spherical harmonics filter to the vorticity equation. J. Korean Meteor. Soc., 35, 254-262. 
  14. Cheong, H.-B., 2001: Solution of elliptic equations on a sphere using double Fourier series. J. Korean Meteor. Soc., 35, 247-253. 
  15. Cheong, H.-B., 2005: Spectral Galerkin-finite difference combined method for reduced grid system on the sphere. J. Korean Meteor. Soc., 41, 481-494. 
  16. Cheong, H.-B., 2006: A dynamical core with double Fourier series: comparison with the spherical harmonics method. Mon. Wea. Rev., 134, 1299-1315.  https://doi.org/10.1175/mwr3121.1
  17. Cheong, H.-B., and H.-G. Kang, 2015: Eigensolutions of the spherical Laplacian for the cubed-sphere and icosahedral-hexagonal grids. Quart. J. Roy. Meteor. Soc., 141, 3383-3398, doi: 10.1002/qj.2620. 
  18. Cheong, H.-B., and I.-H. Kwon, 2007: Use of aliased DFS spectral method for the shallow water equations on the sphere. J. Korean Meteor. Soc., 43, 429-447. 
  19. Cheong, H.-B., Y.-J. Nam, C.-H. Lee, and J.-J. Kim, 2021: Isotropic high-order filter for a local domain on the sphere. Asia-Pac. J. Atmos. Sci., 57, 149-160, doi: 10.1007/s13143-020-00177-3. 
  20. Cho, J.-Y., and J.-W. Kim, 1 983: A synoptic structure of the vertical P-velocity: I. adiabatic calculation. J. Korean Meteor. Soc., 19, 51-58. 
  21. Choi, H.-J., and Coauthors, 2018: Effects of non-orographic gravity wave drag on seasonal and medium-range predictions in a global forecast model. Asia-Pac. J. Atmos. Sci., 54, 385-402, doi: 10.1007/s13143-018-0023-1. 
  22. Choi, H.-J., and H.-Y. Chun, 2011: Momentum flux spectrum of convective gravity waves. Part I: an update of a parameterization using mesoscale simulations. J. Atmos. Sci., 68, 739-759, doi: 10.1175/2010JAS3552.1. 
  23. Choi, H.-J., and S.-Y. Hong, 2015: An updated subgrid orographic parameterization for global atmospheric forecast models. J. Geophys. Res. Atmos., 120, 12445-12457, doi: 10.1002/2015JD024230. 
  24. Choi, J.-T., and J.-Y. Cho, 2001: Prediction of Max/Min temperatures using PPM. J. Korean Meteor. Soc., 37, 465-474. 
  25. Choi, J.-T., and J.-Y. Cho, 2002: The objective prediction of probability of precipitation (PoP) based on PPM. J. Korean Meteor. Soc., 38, 119-127. 
  26. Choi, J.-T., and T.-Y. Lee, 2000: Capability of observing systems over the Korean Peninsula for the observation of mesoscale atmospheric structure- a study using observing system simulation experiments. J. Korean Meteor. Soc., 36, 619-630. 
  27. Choi, S.-J., 2018: Structure of eigenvalues in the advectiondiffusion equation by the spectral element method on a cubed sphere. Asia-Pac. J. Atmos. Sci., 54, 293-301, doi: 10.1007/s13143-018-0020-4. 
  28. Choi, S.-J., F. X. Giraldo, J. Kim, and S. Shin, 2014: Verification of non-hydrostatic dynamical core using the horizontal spectral element method and vertical finite difference method. Geosci. Model Dev., 7, 2717-2731, doi: 10.5194/gmd-7-2717-2014. 
  29. Choi, S.-J., and J. B. Klemp, 2021: A new hybrid sigma-pressure vertical coordinate with smoothed coordinate surfaces. Mon. Wea. Rev., 149, 4077-4089, doi: 10.1175/MWR-D-21-0086.1. 
  30. Choi, S.-J., and S.-Y. Hong, 2016: A global non-hydrostatic dynamical core using the spectral element method on a cubed-sphere grid. Asia-Pac. J. Atmos. Sci., 52, 291-307, doi: 10.1007/s13143-016-0005-0. 
  31. Choi, Y.-W., and J.-B. Ahn, 2017: Impact of cumulus parameterization schemes on the regional climate simulation for the domain of CORDEX-East Asia phase 2 using WRF model. Atmosphere. Korean Meteor. Soc., 27, 105-118, doi: 10.14191/Atmos.2017.27.1.105. 
  32. Choo, S.-H., P.-H. Chang, S.-O. Hwang, H.-J. Jo, J. Lee, S.-M. Lee, Y.-K. Hyun, and J.-H. Moon, 2021: Assessment of assimilation impact of Argo float observations in marginal seas around Korean peninsula through observing system experiments. Atmosphere, 31, 283-294, doi: 10.14191/Atmos.2021.31.3.283. 
  33. Chun, H.-Y., H.-J. Choi, and I.-S. Song, 2008: Effects of nonlinearity on convectively forced internal gravity waves: application to gravity wave drag parameterization. J. Atmos. Sci., 65, 557-575.  https://doi.org/10.1175/2007JAS2255.1
  34. Chun, H.-Y., and J.-J. Baik, 1998: Momentum flux by thermally induced internal gravity waves and its approximation for large-scale models. J. Atmos. Sci., 55, 3299-3310.  https://doi.org/10.1175/1520-0469(1998)055<3299:MFBTII>2.0.CO;2
  35. Chun, H.-Y., and S.-B. Kim, 1997: Sensitivity of the biosphereatmosphere transfer scheme (BATS) to the parameter values for Suwon province. J. Korean Meteor. Soc., 33, 521-534. 
  36. Chun, J.-M., S.-Y. Lee, K.-R. Kim, and Y.-J. Choi, 2014: A study of the urban heat island in Seoul using local analysis system. J. KOSAE, 30, 119-127, doi: 10.5572/KOSAE.2012.28.2.119. 
  37. Chung, K.-Y., D. Barker, S.-O. Moon, E.-H. Jeon, and H.-S. Lee, 2007: Comparison of ensemble perturbations using Lorenz-95 model: bred vectors, orthogonal bred vectors and ensemble transform Kalman filter (ETKF). Atmosphere. Korean Meteor. Soc., 17, 217-230. 
  38. Chung, K.-Y., and S.-U. Park, 1997: Numerical simulations of Yellow Sand events observed in Korea: I. an aerosol modelling and preliminary results. Korean J. Atmos. Sci., 33, 179-199. 
  39. Chung, S.-K., and S.-S. Kim, 1983: Linear baroclinic instability on the Changma front. J. Korean Meteor. Soc., 19, 37-46.  https://doi.org/10.3348/jkrs.1983.19.1.156
  40. Dudhia, J., S.-Y. Hong, and K.-S. S. Lim, 2008: A new method for representing mixed- phase particle fall speeds in bulk microphysics parameterizations. J. Meteor. Soc. Japan, 86A, 33-44.  https://doi.org/10.2151/jmsj.86A.33
  41. Gates, W. L., and Coauthors, 1999: An overview of the results of the atmospheric model intercomparison project (AMIP I). Bull. Amer. Meteor. Soc., 80, 29-55.  https://doi.org/10.1175/1520-0477(1999)080<0029:AOOTRO>2.0.CO;2
  42. Glahn, H. R., and D. P. Ruth, 2003: The new digital forecast database of the national weather service. Bull. Amer. Meteor. Soc., 84, 195-201.  https://doi.org/10.1175/BAMS-84-2-195
  43. Ha, J.-C., D.-E. Chang, and C.-H. Cho, 2007: The assimilation of SSM/I rain rates into a mesoscale model with latent heat nudging method. J. Korean Meteor. Soc., 43, 285-298. 
  44. Ha, J.-H., J.-H. Kang, and S.-J. Choi, 2018: The impact of vertical resolution in the assimilation of GPS radio occultation data. Wea. Forecasting, 33, 1033-1044, doi: 10.1175/WAF-D-17-0061.1. 
  45. Ha, K.-J., and J.-W. Kim, 1987: A quasi-geostrophic model for sea level pressure forecast. J. Korean Meteor. Soc., 23, 91-102. 
  46. Ha, K.-J.,J.-W. Kim, K.-Y. Kim, and J.-Y. Moon, 1998: Sensitivity experiments of an atmospheric general circulation model to coupling of a multi-layer land surface model. J. Korean Meteor. Soc., 34, 630-642. 
  47. Ha, W.-S., and J.-G Lee, 2011: WRF sensitivity experiments on the choice of Land Cover Data an event of sea breeze over the Yeongdong region. Atmosphere. Korean Meteor. Soc., 21, 373-389, doi: 10.14191/Atmos.2011.21.4.373. 
  48. Ham, S., and S.-Y. Hong, 2013: Sensitivity of simulated intraseasonal oscillation to four convective parameterization schemes in a coupled climate model. AsiaPac. J. Atmos. Sci., 49, 483-496, doi: 10.1007/s13143-013-0043-9. 
  49. Han, J., and C. S. Bretherton, 2019: TKE-based Moist Eddy-Diffusivity Mass-Flux (EDMF) Parameterization for Vertical Turbulent Mixing. Wea. Forecasting, 34, 869-886, doi: 10.1175/WAF-D-18-0146.1. 
  50. Han, J., and H.-L. Pan, 2011: Revision of Convection and Vertical Diffusion Schemes in the NCEP Global Forecast System. Wea. Forecasting, 26, 520-533, doi:10.1175/WAF-D-10-05038.1. 
  51. Han, J., W. Wang, Y.-C. Kwon, S.-Y. Hong, V. Tallapragada, and F. Yang, 2017: Updates in the NCEP GFS cumulus convection schemes with scale and aerosol awareness. Wea. Forecasting, 32, 2005-2017, doi: 10.1175/WAF-D-17-0046.1. 
  52. Han, J.-Y., S.-Y. Hong, K.-S. S. Lim, and J. Han, 2016: Sensitivity of a cumulus parameterization scheme to precipitation production representation and its impact on a heavy rain event over Korea. Mon. Wea. Rev., 144, 2125-2135, doi: 10.1175/MWR-D-15-0255.1. 
  53. Han, J.-Y., S.-Y. Hong, and Y.-C. Kwon, 2020: The performance of a revised simplified Arakawa-Schubert (SAS) convection scheme in the medium-range forecasts of the Korean Integrated Model (KIM). Mon. Wea. Rev., 35, 1113-1128, doi: 10.1175/WAF-D-19-0219.1. 
  54. Han, J.-Y., S.-Y. Kim, I.-J. Choi, and E. K. Jin, 2019: Effects of the convective triggering process in a cumulus parameterization scheme on the diurnal variation of precipitation over East Asia. Atmosphere. Korean Meteor. Soc., 10, doi: 10.3390/atmos10010028. 
  55. Han, K., J.-T. Choi, and C, Kim, 2018: Comparison of statistical post-processing methods for probabilistic wind speed forecasting. Asia-Pac. J. Atmos. Sci., 54, 91-101, doi: 10.1007/s13143-017-0062-z. 
  56. Ho, C.-H., B.-G. Kim, B.-M. Kim, D.-S. Park, C.-K. Park, S.-W. Son, J.-H. Jeong, and D.-H. Cha, 2023: Review of the weather hazard research: focused on typhoon, heavy rain, drought, heat wave, cold surge, heavy snow, and strong wind. Atmosphere. Korean Meteor. Soc., 33, 223-246, doi: 10.14191/Atmos.2023.33.2.223. 
  57. S.-W. Son, and I.-S. Kang, 1996: A parameterization of the terrestrial radiation suitable for a climate model: absorption bands of water vapor. J. Korean Meteor. Soc., 32, 29-39. 
  58. Hong, K.-O., M. S. Suh, D.-K. Rha, D.-H. Chang, C. Kim, and M.-K. Kim, 2007: Estimation of high-resolution gridded temperature using GIS and PRISM. Atmosphere. Korean Meteor. Soc., 17, 255-268. 
  59. Hong, K.-O., M. S. Suh, J.-H. Kang, and C. Kim, 2010: Development of updateable model output statistics (UMOS) system for the daily maximum and minimum temperature. Atmosphere. Korean Meteor. Soc., 20, 73-89, doi: 10.1007/s13143-011-0009-8. 
  60. Hong, S.-Y., 2010: A new stable boundary-layer mixing scheme and its impacts on the simulated East Asian summer monsoon. Quart. J. Roy. Meteor. Soc., 136, 1481-1496, doi: 10.1002/qj.665. 
  61. Hong, S.-Y., and Coauthors, 2013a: The Global/Regional Integrated Model system (GRIMs). Asia-Pac. J. Atmos. Sci., 49, 219-243, doi: 10.1007/s13143-013-0023-0. 
  62. Hong, S.-Y., and Coauthors, 2013b: An evaluation of the software system dependency of a global atmospheric model. Mon. Wea. Rev., 141, 4165-4172, doi: 10.1175/MWR-D-12-00352.1. 
  63. Hong, S.-Y., and D.-K. Lee, 1987: A numerical simulation of the winter cyclone in a mesoscale model. J. Korean Meteor. Soc., 23, 35-55. 
  64. Hong, S.-Y., and E.-C. Chang, 2012: Spectral nudging sensitivity experiments in a regional climate model. Asia-Pac. J. Atmos. Sci., 48, 345-355, doi: 10.1007/s13143-012-0033-3. 
  65. Hong, S.-Y., and H.-L. Pan, 1996: Nonlocal boundary layer vertical diffusion in a medium-range forecast model. Mon. Wea. Rev., 124, 2322-2339.  https://doi.org/10.1175/1520-0493(1996)124<2322:NBLVDI>2.0.CO;2
  66. Hong, S.-Y., and H.-L. Pan, 1998: Convective trigger function for a mass-flux cumulus parameterization scheme. Mon. Wea. Rev., 126, 2599-2620.  https://doi.org/10.1175/1520-0493(1998)126<2599:CTFFAM>2.0.CO;2
  67. Hong, S.-Y., and J. Choi, 2006: Sensitivity of the simulated regional climate circulations over East Asia in 1997 and 1998 summers to three convective parameterization schemes. Asia-Pac. J. Atmos. Sci., 42, 361-378. 
  68. Hong, S.-Y., J. Choi, E.-C. Chang, H. Park, and Y.-J. Kim, 2008: Lower tropospheric enhancement of gravity wave drag in a global spectral atmospheric forecast model. Wea. Forecasting, 23, 523-531.  https://doi.org/10.1175/2007WAF2007030.1
  69. Hong, S.-Y., J. Duhdia, and S.-H. Chen, 2004: A revised approach to ice microphysical processes for the bulk parameterization of cloud and precipitation. Mon. Wea. Rev., 132, 103-120.  https://doi.org/10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2
  70. Hong, S.-Y., and J. Jang, 2018: Impacts of shallow convection processes on a simulated boreal summer climatology in a global atmospheric model. Asia-Pac. J. Atmos. Sci., 54, 361-370, doi: 10.1007/s13143-018-0013-3. 
  71. Hong, S.-Y., and M. Kanamitsu, 2014: Dynamic downscaling: fundamental issues from an NWP point of view and recommendation. Asia-Pac. J. Atmos. Sci., 50, 83-104, doi: 10.1007/s13143-014-0029-2. 
  72. Hong, S.-Y., S. Ham, Y.-H. Byun, and J. Kim, 2009: Investigation of ice-cloud radiation interaction in a general circulation model. Asia-Pac. J. Atmos. Sci., 45, 391-409. 
  73. Hong, S.-Y., and Y. Noh, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 2318-2341.  https://doi.org/10.1175/mwr3199.1
  74. Hong, S.-Y., and Coauthors, 2018: The Korean integrated model (KIM) system for global weather forecasting. Asia-Pac. J. Atmos. Sci., 54, 267-292, doi: 10.1007/s13143-018-0028-9. 
  75. Hwang, Y.-J., and Coauthors, 2012: Predictability for heavy rainfall over the Korean Peninsula during the summer using TIGGE model. Atmosphere. Korean Meteor. Soc., 22, 287-298, doi: 10.14191/Atmos.2012.22.3.287. 
  76. Hyun, J.-H., and D.-K. Lee, 1990: Simulation of sea-land breeze over Jeju Island on a three-dimensional mesoscale model. J. Korean Meteor. Soc., 26, 121-136. 
  77. Hyun, S.-H., S.-O. Hwang, S.-M. Lee, S.-H. Choo, 2022: Verification of the KMA ocean model NEMO against Argo floats and drift buoys: a comparison with the up-to-date US navy HYCOM. Atmosphere. Korean Meteor. Soc., 32, 71-84, doi: 10.14191/Atmos.2022.32.1.071. 
  78. In, H. J., and S. U. Park, 2002: A simulation of long-range transport of Yellow Sand observed on April 1998 in Korea. Atmos. Environ., 36, 4173-4187.  https://doi.org/10.1016/S1352-2310(02)00361-8
  79. In, H. J., and S. U. Park, 2003: Estimation of dust deposition for the yellow Sand event observed in April 1998 in Korea. Korean J. Atmos. Sci., 6, 13-25. 
  80. Jang, J., and S.-Y. Hong, 2016: Comparison of simulated precipitation over East Asia in two regional models with hydrostatic and nonhydrostatic dynami.cal cores. Mon. Wea. Rev., 144, 3579-3590, doi: 10.1175/MWRD-15-0428.1. 
  81. Jee, J.-B., and Coauthors, 2016: Sensitivity analysis of the high-resolution WISE-WRF model with the use of surface roughness length in Seoul metropolitan areas. Atmosphere. Korean Meteor. Soc., 26, 111-126, doi:10.14191/Atmos.2016.26.1.111. 
  82. Jee, J.-B., J.-S. Min, M. Jang, Y.-B. Kim, I.-S. Zo, and K.-T. Lee, 2017: Sensitivity Analysis of Numerical Weather Prediction Model with Topographic Effect in the Radiative Transfer Process. Atmosphere, 27, 385-398, doi:10.14191/Atmos.2017.27.4.385. 
  83. Jee, J.-B., and K.-T. Lee, 2013: Parameterization for Longwave Scattering Properties of Ice Clouds with Various Habits and Size Distribution for Use in Atmospheric Models. Atmosphere, 23, 39-45, doi: 10.14191/Atmos.2013.23.1.039. 
  84. Jee, J.-B., and S. Kim, 2016: Sensitivity study on high-resolution numerical modeling of static topographic data. Atmosphere. Korean Meteor. Soc., 7, doi: 10.3390/atmos7070086. 
  85. Jeong, G.-R., B. M. Monge-Sanz, E.-H. Lee, and J. R. Ziemke, 2016: Simulation of stratospheric ozone in global forecast model using linear photochemistry parameterization. Asia-Pac. J. Atmos. Sci., 52, 479-494, doi: 10.1007/s13143-016-0032-x. 
  86. Jeong, H.-B., H.-W. Chun, and S. Lee, 2019a: A Study of Iterative QC-BC Method for AMSU-A in the KIAPS Data Assimilation System. Atmosphere. Korean Meteor. Soc., 29, 241-255, doi: 10.14191/Atmos.2019.29.3.241. 
  87. Jeong, J.-H., and Coauthors, 2017: The status and prospect of seasonal climate prediction of climate over Korea and east Asia: a review. Asia-Pac. J. Atmos. Sci., 53, 149-173.  https://doi.org/10.1007/s13143-017-0008-5
  88. Jeong, Y.-C., S.-W. Yeh, S. Lee, and R. J. Park, 2019b: A global/regional integrated model system-chemistry climate model: I. simulation characteristics. Earth and Space Sci., 6, 2016-2030, doi: 10.1029/2019EA000727. 
  89. Jin, H.-G., H. Lee, and J.-J. Baik, 2019: A new parameterization of the accretion of cloud water by graupel and its evaluation through cloud and precipitation simulations. J. Atmos. Sci., 76, 381-400, doi: 10.1175/JASD-18-0245.1. 
  90. Jin, H.-G., and J.-J. Baik, 2020: A new parameterization of the accretion of cloud water by snow and its evaluation through simulations of mesoscale convective systems. J. Atmos. Sci., 77, 2885-2903, doi: 10.1175/JASD-19-0326.1. 
  91. Jin, H.-G., J.-J. Baik, H. Lee, and T. Ahmed, 2022: A new warm-cloud collection and breakup parameterization scheme for weather and climate models. Atmos. Res., 272, 106145, doi: 10.1016/j.atmosres.2022.106145. 
  92. Jo, Y., J.-S. Kang, and H. Kwon, 2015: Optimization of the vertical localization scale for GPS-RO data assimilation within KIAPS-LETKF system. Atmosphere, 25, 529-541, doi: 10.14191/Atmos.2015.25.3.529. 
  93. Joo, S.-W., and D.-K. Lee, 2007: The Impact of Statistically Calculated Observation Error of ATOVS Radiances on a Global Data Assimilation System. AsiaPac. J. Atmos. Sci., 43, 17-29. 
  94. Juang, H.-M., and S.-Y. Hong, 2010: Forward semi-Lagrangian advection with mass conservation and positive definiteness for falling hydrometeors. Mon. Wea. Rev., 138, 1778-1791, doi: 10.1175/2009MWR3109.1. 
  95. Jun, S., J.-H. Park, H.-J. Choi, Y.-H. Lee, Y.-J. Lim, K.-O. Boo, and H.-S. Kang, 2021: Impact of Soil Moisture Data Assimilation on Analysis and Medium-Range Forecasts in an Operational Global Data Assimilation and Prediction System. Atmosphere, 12, 1089, doi:10.3390/atmos12091089. 
  96. 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. Mon. Wea. Rev., 141, 4080-4097, doi: 10.1175/MWR-D12-00197.1. 
  97. 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-Pac. J. Atmos. Sci., 46, 305-316, doi: 10.1007/s13143-010-1007-y. 
  98. Jung, B.-J., S. Kim, and Y. Jo, 2014: Representer-based variational data assimilation in a spectral element shallow water model on the cubed-sphere grid. Tellus A, 66, 24493, doi: 10.3402/tellusa.v66.24493. 
  99. Kang, H.-S., and S.-Y. Hong, 2008: An assessment of the land surface parameters on the simulated regional climate circulations: the 1997 and 1998 east Asian summer monsoon cases. J. Geophys. Res., 113, D15121. 
  100. Kang, J.-H., and Coauthors, 2018: Development of an observation processing package for data assimilation in KIAPS. Asia-Pac. J. Atmos. Sci., 54, 303-318, doi:10.1007/s13143-018-0030-2. 
  101. Kang, J.-H., M.-S. Suh, and C.-H. Kwak, 2007: Comparison of the land cover data sets over Asian region: USGS, IGBP, and UMD. Atmosphere. Korean Meteor. Soc., 17, 159-169. 
  102. Kang, J.-Y., S.-Y. Bae, R.-S. Park, and J.-Y. Han, 2019: Aerosol indirect effects on the predicted precipitation in a global weather forecasting model. Atmosphere, 10, 392, doi: 10.3390/atmos10070392. 
  103. Kang, M.-J., H.-Y. Chun, and Y.-H. Kim, 2017: Momentum flux of convective gravity waves derived from an offline gravity wave parameterization. Part I: spatiotemporal variations at source level. J. Atmos. Sci., 74, 3167-3189, doi: 10.1175/JAS-D-17-0053.1. 
  104. Kang, M.-S., M. Belorid, and K.-R. Kim, 2020: Development of impact-based heat health warning system based on ensemble forecasts of perceived temperature and its evaluation using heat-related patients in 2019. Atmosphere. Korean Meteor. Soc., 30, 195-207, doi: 10.14191/Atmos.2020.30.2.195. 
  105. Kay, J.-K., and H.-M. Kim, 2014: Characteristics of initial perturbations in the ensemble prediction system of the Korea Meteorological Administration. Wea. Forecasting, 29, 563-581, doi: 10.1175/WAF-D-13-00097.1. 
  106. Kay, J.-K., H.-M. Kim, Y.-Y. Park, and J. Son, 2013: Effect of doubling the ensemble size on the performance of ensemble prediction in the warm season using MOGREPS implemented at the KMA. Adv. Atmos. Sci., 30, 1287-1302, doi: 10.1007/s00376-012-2083-y. 
  107. Kelly, J. F., and F. X. Geraldo, 2012: Continuous and discontinuous Galerkin methods for a scalable threedimensional nonhydrostatic atmosphere model: limited area mode. J. Comput. Phys., 231, 7988-8008, doi: 10.1016/j.jcp.2012.04.042. 
  108. KIAPS, 2011: History of operational numerical weather prediction in Korea. Korea Institute of Atmospheric Prediction Systems, 436pp (in Korean). 
  109. Kim, C.-H., R. Park, S.-H. Lee, S.-W. Kim, and C.-K. Song, 2023: 60-year research history and future prospects in environment field in Korean Meteorological Society. Atmosphere. Korean Meteor. Soc., 33, 173-195, doi: 10.14191/Atmos.2023.33.2.173. 
  110. Kim, H., J. Lee, Y.-K. Hyun, and S.-O. Hwang, 2021: The KMA global seasonal forecasting system (GloSea6) - Part I: operational system and improvements. Atmosphere. Korean Meteor. Soc., 31, 341-359, doi: 10.14191/Atmos.2021.31.3.341. 
  111. Kim, H.-J., I.-U. Chung, and K.-T. Lee, 2009: Effects of an advanced radiation parameterization on a troposphere-stratosphere AGCM simulation. Asia-Pac. J. Atmos. Sci., 45, 439-462. 
  112. Kim, H.-J., I.-U. Chung, and M.-S. Joh, 2005: On the coupling of a land surface model to an atmospheric general circulation model. J. Korean Meteor. Soc., 41, 1137-1149. 
  113. Kim, H.-J., and J.-B. Ahn, 2015: Improvement in prediction of the artic oscillation with a realistic ocean initial condition. J. Climate, 28, 8951-8967, doi: 10.1175/JCLI-D-14-00457.1. 
  114. Kim, H.-J., and Y. Noh, 1999: Simulation of convective boundary layer using a new large eddy simulation model with the analysis on the effects of subgrid parameterization. J. Korean Meteor. Soc., 35, 587-598. 
  115. Kim, H.-M., and B.-J. Jung, 2006: Adjoint-based forecast sensitivities of Typhoon Rusa. Geophys. Res. Lett., 33, L21813, doi: 10.1029/2006GL027289. 
  116. Kim, H.-M., B.-J. Jung, Y.-H. Kim, and H.-S. Lee, 2008a: Adaptive observation guidance applied to typhoon Rusa: implications for THORPEX-PARC 2008. Asia-Pac. J. Atmos. Sci., 44, 297-312. 
  117. Kim, J., N. Miller, J. Oh, J. Chung, and D. Rha, 1998: Eastern Asian hydrometeorology simulation using the regional climate system model. Global Planet. Change, 18, 225-240.  https://doi.org/10.1016/S0921-8181(98)00049-6
  118. Kim, J., and Coauthors, 2014a: Evaluation of the CORDEX-Africa multi-RCM hindcast: systematic model errors. Climate Dyn., 42, 1189-1202, doi: 10.1007/s00382-013-1751-7. 
  119. Kim, J., Y. C. Kwon, and T.-H. Kim, 2018: A scalable high-performance I/O System for a numerical weather forecast model on the cubed-sphere grid (in press). Asia-Pac. J. Atmos. Sci., 54, doi: 10.1007/s13143-018-0021-3. 
  120. Kim, J.-E., and S.-Y. Hong, 2007: Impact of soil moisture anomalies on summer rainfall over east Asia: a regional climate model study. J. Climate, 20, 5732-5734.  https://doi.org/10.1175/2006JCLI1358.1
  121. Kim, J.-U., and Coauthors, 2020: Evaluation of performance and uncertainty for multi-RCM over CORDEX-East phase 2 region. Atmosphere. Korean Meteor. Soc., 30, 361-376, doi: 10.14191/Atmos.2020.30.4.361. 
  122. Kim, J.-W., 1983: A numerical model of weather prediction over Korea. J. Korean Meteor. Soc., 19, 33-50. 
  123. Kim, J.-W., and J.-T. Wang, 1981: The January and July het balance simulated by the OSU two-level atmospheric general circulation model. Report. No. 28, Climatic Res. Institute, Oregon State University, Corvallis, 55pp. 
  124. Kim, J.-Y., J.-H. Oh, D.-Y. Kim, and P. Sen, 2008b: Prediction of rainfall with high-resolution model using public-resource distributed computing. Asia-Pac. J. Atmos. Sci., 44, 287-296. 
  125. Kim, M.-K., and Coauthors, 2016: Statistical downscaling for daily precipitation in Korea using combined PRISM, RCM, and quantile mapping: part I, methodology and evaluation in historical simulation. Asia.- Pac. J. Atmos. Sci., 52, 79-89, doi: 10.1007/s13143-016-0010-3. 
  126. Kim, M.-K., D.-H. Lee, and J. Kim, 2013a: Production and validation of daily grid data with 1km resolution in South Korea. J. Climate Res., 8, 13-25. 
  127. Kim, M.-K., M.-S. Han, D.-H. Jang, S.-G. Baek, W.-S. Lee, Y.-H. Kim, and S. Kim, 2012: Production technique of observation Grid data of 1km resolution. J. Climate Res., 7, 55-68. 
  128. Kim, O.-Y., and J.-H. Oh, 2010: Verification of the performance of the high resolution QPF model for heavy rainfall event over the Korean Peninsula. Asia-Pac. J. Atmos. Sci., 46, 119-133, doi: 10.1007/s13143-010-0012-5. 
  129. Kim, S., B.-J. Jung, and Y. Jo, 2014b: Development of a tangent linear model (version 1.0) for the High-Order Method Modeling Environment dynamical core. Geosci. Model Dev., 7, 1175-1182, doi: 10.5194/gmd-7-1175-2014. 
  130. Kim, S., H.-M. Kim, E. J. Kim, and H.-C. Shin, 201 3b: Forecast sensitivity to observations for high-impact weather events in the Korean Peninsula. Atmosphere. Korean Meteor. Soc., 23, 171-186, doi: 10.14191/Atmos.2013.23.2.171. 
  131. Kim, S.-H., H.-Y. Chun, R. D. Sharman, and S. B. Trier, 2019a: Development of near-cloud turbulence diagnostics based on a convective gravity-wave drag parameterization. J. Appl. Meteor. Climatol., 58, 1725-1750, doi: 10.1175/JAMC-D-18-0300.1. 
  132. 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. Korean Meteor. Soc., 27, 93-104, doi:10.14191/Atmos.2017.27.1.093. 
  133. 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. Korean Meteor. Soc., 21, 163-172. 
  134. Kim, S.-Y., J.-Y. Han, I.-J. Choi, and S.-Y. Bae, 2014c: Evaluation of cloud and precipitation parameterization using a single-column model: a TWP-ICE case study. Asia-Pac. J. Atmos. Sci., 50, 469-480, doi: 10.1007/s13143-014-0037-2. 
  135. Kim, S.-Y., and S.-Y. Hong, 2018: The Use of Partial Cloudiness in a Bulk Cloud Microphysics Scheme: Concept and 2D Results. J. Atmos. Sci., 75, 2711-2719, doi: 10.1175/JAS-D-17-0234.1. 
  136. Kim, S.-Y., S.-Y. Hong, Y.-C. Kwon, Y.-H. Lee, and D.-E. Kim, 2019b: Effects of Modified Surface Roughness Length over Shallow Waters in a Regional Model Simulation. Atmosphere, 10, 818, doi: 10.3390/atmos10120818. 
  137. Kim, Y.-H., E.-H. Jeon, D.-E. Chang, H.-S. Lee, and J.-I. Park, 2010: The impact of T-PARC 2008 dropsonde observations on typhoon track forecasting. Asia-Pac. J. Atmos. Sci., 46, 287-303, doi: 10.1007/s13143-010-1011-2. 
  138. Kim, Y.-J., 1996: Representation of subgrid-scale orographic effects in a general circulation model: part I. impacts on the dynamics of a simulated January climate. J. Climate, 9, 2698-2717.  https://doi.org/10.1175/1520-0442(1996)009<2698:ROSSOE>2.0.CO;2
  139. Kim, Y.-J., and A. Arakawa, 1995: Improvement of orographic gravity wave parameterization using a mesoscale gravity wave model. J. Atmos. Sci., 52, 1875-1902.  https://doi.org/10.1175/1520-0469(1995)052<1875:IOOGWP>2.0.CO;2
  140. Kim, Y.-J., and J. D. Doyle, 2005: Extension of an orographic-drag parameterization scheme to incorporate orographic anisotropy and flow blocking. Quart. J. Roy. Meteorl. Soc., 131, 1893-1921.  https://doi.org/10.1256/qj.04.160
  141. Kim, Y.-J., S. D. Eckermann, and H.-Y. Chun, 2003: An overview of the past, present, and future of gravity-wave drag parameterization for numerical climate and weather prediction models. Atmos.-Ocean, 41, 65-98.  https://doi.org/10.3137/ao.410105
  142. Kim, Y.-S., C.-H. Cho, and O.-R. Park, 2004: A threedimensional cloud analysis for diabatic initialization of mesoscale model and its impact study. J. Korean Meteor. Soc., 40, 497-509. 
  143. Kim, Y.-S., O.-R. Park, and S.-O. Hwang, 2002a: Realtime operation of the Korea local analysis and prediction system at METRI. J. Korean Meteor. Soc., 38, 1-10. 
  144. Kim, Y.-T., 2003: Parallel implementation of the MAS (mesoscale atmospheric simulation) model for distributed memory computers. Korean J. Atmos. Sci., 6, 63-69. 
  145. Kim, Y.-T., Y.-H. Lee, J.-T. Choi, and J.-H. Oh, 2002b: Implementation and performance analysis of PC clusters using fast PCs and high-speed networks. Journal of KIISE: System and Theory, 29, 57-64. 
  146. Kim, Y.-T., Y.-H. Lee, and K.-Y. Chung, 2013c: WRF physics models using GP-GPUs with CUDA Fortran. Atmosphere. Korean Meteor. Soc., 23, 231-235, doi: 10.14191/Atmos.2013.23.2.231. 
  147. Klemp, J. B., W. C. Skamarock, and S.-H. Park, 2015: Idealized Global Nonhydrostatic Test Case on a Reduced Radius Sphere. J. Adv. Model. Earth Sys., 7, 1155-1177, doi: 10.1002/2015MS000435. 
  148. KMA, 2019: A study on the diagnosis and development direction of the forecasting system. Korea Meteorological Administration, 107pp. 
  149. Ko, E.-B., I.-J. Moon, Y.-Y. Jeong, and P.-H. Chang, 2018: A Comparison of accuracy of the ocean thermal environments using the daily analysis data of the KMA NEMO/NEMOVAR and the US Navy HYCOM/NCODA. Atmosphere. Korean Meteor. Soc., 28, 99-112, doi: 10.14191/Atmos.2018.28.1.099. 
  150. Koo, M.-S., H.-J. Choi, and J.-Y. Han, 2018: A parameterization of turbulent-scale and mesoscale orographic drag in a global atmospheric model. J. Geophys. Res., 123, 8400-8417, doi: 10.1029/2017JD028176. 
  151. Koo, M.-S., S.-H. Baek, K.-H. Seol, and K. Cho, 2017: Advances in land modeling of KIAPS based on the Noah land surface model. Asia-Pac. J. Atmos. Sci., 53, 361-373, doi: 10.1007/s13143-017-0043-2. 
  152. Koo, M.-S., and S.-Y. Hong, 2012: Double Fourier series (DFS) dynamical core with hybrid sigma-pressure vertical coordinates and semi-Lagrangian moisture advection. Proceedings of the Autumn Meeting, Korean Meteor. Soc., 152-153, doi: 10.3402/tellusa.v65i0.19851. 
  153. Koo, T.-Y., S.-O. Moon, H.-B. Cheong, and W.-J. Lee, 2001: A study on ensemble prediction with breeding method. Proceedings of the Autumn Meeting, Korean Meteor. Soc., 139-142. 
  154. Kurihara, Y., M. A. Bender, R. E. Tuleya, and R. J. Ross, 1995: Improvements in the GFDL hurricane prediction system. Mon. Wea. Rev., 123, 2791-2801.  https://doi.org/10.1175/1520-0493(1995)123<2791:IITGHP>2.0.CO;2
  155. Kwon, H.-J., and Coauthors, 2007: Performance of MTM in 2006 typhoon forecast. Atmosphere. Korean Meteor. Soc., 17, 207-216. 
  156. Kwon, H.-J., S.-H. Han, and K.-S. Shin, 2001: Operational prediction of typhoon track at KMA using barotropic adaptive-grid typhoon simulation (BATS) model. J. Meteor. Soc. Japan, 79, 1157-1168.  https://doi.org/10.2151/jmsj.79.1157
  157. Kwon, H.-J., and S.-H. Won, 2002: GFDL-type typhoon initialization in MM5. Mon. Wea. Rev., 130, 2966-2974.  https://doi.org/10.1175/1520-0493(2002)130<2966:gttiim>2.0.co;2
  158. Kwon, I.-H., and Coauthors, 2018a: Development of an operational hybrid data assimilation system at KIAPS. Asia-Pac. J. Atmos. Sci., 54, 319-335, doi: 10.1007/s13143-018-0029-8. 
  159. Kwon, I.-H., S. English, W. Bell, R. Potthast, A. Collard, and B. Ruston, 2018b: Assessment of progress and status of data assimilation in numerical weather prediction. Bull. Amer. Meteor. Soc., 99, ES75-ES79, doi: 10.1175/BAMS-D-17-0266.1. 
  160. Kwon, T.-Y., and Coauthors, 2006: Development of Yeongdong heavy snowfall forecast supporting system. Atmosphere. Korean Meteor. Soc., 16, 247-257. 
  161. Kwon, Y. C., and S.-Y. Hong, 2017: A mass-flux cumulus parameterization scheme across gray-zone resolutions. Mon. Wea. Rev., 145, 583-598, doi: 10.1175/MWR-D-16-0034.1. 
  162. Laprise, R., 1992: The Euler equations of motion with hydrostatic pressure as an independent variable. Mon. Wea. Rev., 120, 197-207.  https://doi.org/10.1175/1520-0493(1992)120<0197:TEEOMW>2.0.CO;2
  163. Lee, D.-B., and H.-Y. Chun, 2018: Development of the global-Korean aviation turbulence guidance (globalKTG) system using the global data assimilation and prediction system (GDAPS) of the Korea Meteorological Administration (KMA). Atmosphere. Korean Meteor. Soc., 28, 223-232, doi: 10.14191/Atmos.2018.28.2.223. 
  164. Lee, D.-B., H.-Y. Chun, S.-H. Kim, R. D. Sharman, and J.-H. Kim, 2022a: Development and evaluation of global Korean aviation turbulence forecast systems based on an operational numerical weather prediction model and in situ flight turbulence observation data, Wea. Forecasting, 37, 371-392, doi: 10.1175/WAF-D-21-0095.1. 
  165. Lee, D.-K., C.-H. Joung, S.-U. Park, S.-C. Yoon, and C.-W. Lee, 1991a: Numerical simulation of an explosive cyclogenesis near the East Asian coast. J. Korean Meteor. Soc., 27, 1-21. 
  166. Lee, D.-K., and Coauthors, 1987: A study on numerical simulation of winter cyclone development in the East Asian coast area. J. Korean Meteor. Soc., 23, 1-22. 
  167. Lee, D.-K., and D.-E. Chang, 1997: Sensitivity of cyclone development to initial data using an adjoint model. J. Korean Meteor. Soc., 33, 364-384. 
  168. Lee, D.-K., D.-Y. Eom, J.-W. Kim, and J.-B. Lee, 2010: Highresolution summer rainfall prediction in the JHWC real-time WRF system. Asia-Pac. J. Atmos. Sci., 46, 341-353, doi: 10.1007/s13143-010-1003-2. 
  169. Lee, D.-K., J.-G. Jhun, S.-Y. Hong, and H.-R. Kim, 1993: Numerical simulations of a heavy rainfall case occurred over central Korea during 10-12 September 1990. J. Korean Meteor. Soc., 29, 147-169. 
  170. Lee, D.-K., and J.-G. Park, 2002: A comparison study of moist physics schemes in a simulation of East Asian heavy rainfall. J. Korean Meteor. Soc., 38, 581-592. 
  171. Lee, D.-K., and K.-H. Lee, 2006: Sensitivity study of integration time-step size in simulations of heavy rainfall. J. Korean Meteor. Soc., 42, 379-388. 
  172. Lee, D.-K., and S.-Y. Hong, 1989: A case study of the sensitivity of sea surface temperature on the mesoscale model simulation of winter cyclone development. J. Korean Meteor. Soc., 25, 1-14. 
  173. Lee, D.-K., and S.-Y. Hong, 1991: Initialization experiments on a mesoscale numerical model for heavy rainfall simulation. J. Korean Meteor. Soc., 27, 144-164. 
  174. Lee, D.-K., S.-Y. Hong, J.-H. Bong, C.-W. Lee, and H.-S. Lee, 1994a: An operational regional-scale weather prediction model system for Korea. J. Korean Meteor. Soc., 30, 413-422. 
  175. Lee, D.-K., Y.-C. Kwon, and T.-K. Wee, 1992a: Typhoons approaching Korea, 1960~1989 Part II: prediction experiments on a mesoscale numerical model. J. Korean Meteor. Soc., 28, 149-163. 
  176. Lee, E.-J., and J.-G. Jhun, 1996: Development of normal mode initialization scheme in the tropics. J. Korean Meteor. Soc., 32, 169-188. 
  177. Lee, E.-H., E. Lee, R.-S. Park, Y. C. Kwon, and S.-Y. Hong, 2018a: Impact of Turbulent Mixing in the Stratocumulus-Topped Boundary Layer on Numerical Weather Prediction. Asia-Pac. J. Atmos. Sci., 54, 371-384, doi: 10.1007/s13143-018-0024-0. 
  178. Lee, E.-H., J.-C. Ha, S.-S. Lee, and Y. Chun, 2013a: PM10 data assimilation over South Korea to Asian dust forecasting model with the optimal interpolation method. Asia-Pac. J. Atmos. Sci., 49, 73-85, doi: 10.1007/s13143-013-0009-y. 
  179. Lee, H., and Coauthors, 2021: Development of the UKESMTOPAZ earth system model (version 1.0) and preliminary evaluation of its biochemical simulations. AsiaPac. J. Atmos. Sci., 58, 379-400, doi: 10.1007/s13143-021-00263-0. 
  180. Lee, H., and J.-J. Baik, 2017: A physically based autoconversion parameterization. J. Atmos. Sci., 74, 1599-1616, doi.org/10.1175/JAS-D-16-0207.1. 
  181. Lee, J., and Coauthors, 2020a: Evaluation of the Korea Meteorological Administration advanced earth-system model (K-ACE). Asia-Pac. J. Atmos. Sci., 56, 381-395, doi: 10.1007/s13143-019-00144-7. 
  182. Lee, J., J.-B. Ahn, and H.-G. Jeong, 2016a: A study on the method for estimating the 30m-resolution daily temperature extreme value using PRISM and GEV method. Atmosphere. Korean Meteor. Soc., 26, 697-709, doi: 10.14191/Atmos.2016.26.4.697. 
  183. Lee, J., S.-W. Lee, S.-O. Han, S. J. Lee, and D.-E. Jang, 2011: The impact of satellite observations on the UM-4DVar analysis and prediction system at KMA. Atmosphere. Korean Meteor. Soc., 21, 85-93, doi:10.14191/Atmos.2011.21.1.085. 
  184. Lee, J.-W., K.-H. Min, and K.-S. S. Lim, 2022b: Comparing 3DVAR and hybrid radar data assimilation methods for heavy rain forecast. Atmos. Res., 270, 106062, doi: 10.1016/j.atmosres.2022.106062. 
  185. Lee, J.-W., K.-H. Min, Y.-H. Lee, and G. Lee, 2020b: X-NetBased radar data assimilation study over the Seoul metropolitan area. Remote Sens. Environ., 12, 893, doi: 10.3390/rs12050893. 
  186. Lee, J.-B., and D.-K. Lee, 2011: Impact of cumulus parameterization schemes with different horizontal grid sizes on prediction of heavy rainfall. Atmosphere. Korean Meteor. Soc., 21, 391-404, doi: 10.14191/Atmos.2011.21.4.391. 
  187. Lee, J.-G., and J.-S. Lee, 2003: A numerical study of Yeongdong heavy snowfall events associated with easterly. Atmosphere. Korean Meteor. Soc., 39, 475-490. 
  188. Lee, J.-W., and S.-Y. Hong, 2014: Potential for added value to downscale climate extremes over Korea by increased resolution of a regional climate model. Theor. Appl. Climatol., 117, 667-677, doi: 10.1007/s00704-013-1034-6. 
  189. Lee, K.-T., 1998: Parameterizations of radiation process for numerical climate models. J. Korean Meteor. Soc., 34, 548-559. 
  190. Lee, K.-T., and J.-B. Jee, 2002: Parameterizations of infrared radiative transfer using correlated k-distribution method. J. Korean Meteor. Soc., 38, 141-153. 
  191. Lee, K.-T., J.-W. Kim, S.-M. Lee, T.-Y. Lee, and K.-H. Lee, 1994b: Research on the parameterization processes in climate models: IV. A parameterization of radiation for a climate model. J. Korean Meteor. Soc., 30, 363-376. 
  192. Lee, M.-J., and D.-K. Lee, 2006: Effects of trigger function in the Kain-Fritsch cumulus parameterization scheme on heavy rainfall simulation. J. Korean Meteor. Soc., 42, 397-410. 
  193. Lee, M.-S., 2005: Preliminary tests of first guess at appropriate time (FGAT) with WRF 3dVar and WRF model. J. Korean Meteor. Soc., 41, 495-505. 
  194. Lee, M.-S., and D.-K. Lee, 2000: Characteristic of the propagation of observational information and its dynamical interactions produced by MM5 4dVar in different synoptic environments. J. Korean Meteor. Soc., 36, 601-618.  https://doi.org/10.3348/jkrs.1997.36.4.601
  195. Lee, M.-Y., D.-I. Lee, and W.-J. Lee, 1999: The forecasting the maximum/minimum temperature using the Kalman filter. J. Korean Meteor. Soc., 35, 283-289. 
  196. Lee, S., and H.-J. Song, 2018: Impacts of LEOGEO Atmospheric Motion Vectors on East Asian weather forecasts. Quart. J. Roy. Meteorl. Soc., 144, 1914-1925, doi: 10.1002/qj.3392. 
  197. Lee, S., H.-J. Song, H.-W. Chun, I.-H. Kwon, J.-H. Kang, and S. Lim, 2020c: All-sky microwave humidity sounder assimilation in the Korean Integrated Model forecast system. Quart. J. Roy. Meteorl. Soc., 146, 3570-3586, doi: 10.1002/qj.3862. 
  198. Lee, S., H.-W. Chun, and H.-J. Song, 2018b: Impact of SAPHIR data assimilation in the KIAPS global numerical weather prediction system. Atmosphere. Korean Meteor. Soc., 28, 141-151, doi: 10.14191/Atmos.2018.28.2.141. 
  199. Lee, S., I.-H. Kwon, J.-H. Kang, H.-W. Chun, K.-H. Seol, H.-B. Jeong, and W.-H. Kim, 2022c: Data Assimilation of Aeolus/ALADIN Horizontal Line-Of-Sight Wind in the Korean Integrated Model Forecast System. Atmosphere. Korean Meteor. Soc., 32, 27-37, doi: 10.14191/Atmos.2022.32.1.027. 
  200. Lee, S., J.-H. Kim, J.-H. Kang, and H.-W. Chun, 2013b: Development of pre-processing and bias correction modules for AMSU-A satellite data in the KIAPS observation processing system. Atmosphere. Korean Meteor. Soc., 23, 453-470, doi: 10.14191/Atmos.2013.23.4.453. 
  201. Lee, S., R.-J. Park, S.-Y. Hong, M.-S. Koo, J. I. Jeong, S.-W. Yeh, and S.-W. Son, 2022d: A new chemistryclimate model GRIMs-CCM: Model evaluation of interactive chemistry-meteorology simulations, AsiaPac. J. Atmos. Sci., 58, 647-666, doi: 10.1007/s13143-022-00281-6. 
  202. Lee, S.-M., and Coauthors, 2014: Predictability study of snowfall case over South Korea using TIGGE data on 28 December 2012. Atmosphere. Korean Meteor. Soc., 24, doi: 10.14191/Atmos.2014.24.1.001. 
  203. Lee, S.-M., H.-S. Kang, Y.-H. Kim, Y.-H. Byun, and C.-H. Cho, 2016b: Verification and comparison of forecast skill between global seasonal forecast system version 5 and unified model during 2014. Atmosphere. Korean Meteor. Soc., 26, 59-72, doi: 10.14191/Atmos.2016.26.1.059. 
  204. Lee, S.-M., J.-W. Kim, H.-K. Cho, T.-Y. Lee, and K.-H. Lee, 1991b: Research on the parameterized processes in climate models: I. the change of surrounding by a transient shallow cumulus. J. Korean Meteor. Soc., 27, 257-266. 
  205. Lee, S.-S., and Coauthors, 2017: Improved dust forecast by assimilating MODIS IR-based nighttime AOT in the ADAM2 model. SOLA, 13, 192-198, doi: 10.2151/sola.2017-035. 
  206. Lee, T.-Y., J.-W. Kim, H.-K. Cho, S.-M. Lee, and K.-H. Lee, 1992b: Research on the parameterized processes in climate models: II. Diurnal variation of stratocumulus-topped marine boundary layer. J. Korean Meteor. Soc., 28, 9-28. 
  207. Lee, T.-Y., and S.-Y. Hong, 2005: Physical parameterization in next-generation NWP models. Bull. Amer. Meteor. Soc., 86, 1615-1618.  https://doi.org/10.1175/BAMS-86-11-1619
  208. Lee, W.-H., and K.-T. Jee, 2003: Thermal infrared radiation parameterization for gaseous absorption in YONU GCM. J. Korean Meteor. Soc., 39, 415-429. 
  209. Lee, W.-J., C.-W. Lee, and H.-J. Seong, 1984: A study on the 4-level quasi-geostrophic numerical model. J. Korea Water Resour. Assoc., 17, 211-219. 
  210. Lee, W.-J., and M. Mak, 1995: Dynamics of stormtracks: a linear instability perspective. J. Atmos. Sci., 52, 697-723.  https://doi.org/10.1175/1520-0469(1995)052<0697:DOSTAL>2.0.CO;2
  211. Lee, W.-J., and M. Mak, 1996: Role of orography in the dynamics of storm tracks. J. Atmos. Sci., 53, 1737-1750.  https://doi.org/10.1175/1520-0469(1996)053<1737:TROOIT>2.0.CO;2
  212. Lee, Y.-H., and Coauthors, 2005: Development of Mongolian numerical weather prediction system (MNWPS) based on cluster system. J. Korean Meteor. Soc., 15, 35-46. 
  213. Lee, Y.-H., D.-H. Cha, and D.-K. Lee, 2008: Impact of horizontal resolution of regional climate model on precipitation simulation over the Korean Peninsula. Atmosphere. Korean Meteor. Soc., 18, 387-395. 
  214. Lee, Y., S. Shin, and J. Kim, 2020d: A monitoring system of ensemble forecast sensitivity to observation based on the LETKF framework implemented to global NWP model. Atmosphere. Korean Meteor. Soc., 30, 103-113, doi: 10.14191/Atmos.2020.30.2.103. 
  215. Lim, H.-C., Y.-H. Byun, S. Park, and W.-T. Kwon, 2009: Changes in the characteristics of wintertime climatology simulation for METRI AGCM using the improved radiation parameterization. Atmosphere. Korean Meteor. Soc., 19, 127-143. 
  216. Lim, K.-S., 2019: Bulk-type cloud microphysics parameterization in atmospheric models. Atmosphere. Korean Meteor. Soc., 29, 227-239, doi: 10.14191/Atmos.2019.29.2.227. 
  217. Lim, K.-S., and Coauthors, 2011: Aerosol effects on the development of a supercell storm in a double-moment bulk-cloud microphysics scheme. J. Geophys. Res., 116, D02204, doi: 10.1029/2010JD014128. 
  218. Lim, K.-S., and S.-Y. Hong, 201 0: Development of an effective double-moment cloud microphysics scheme with a prognostic cloud condensation nuclei (CCN) for weather and climate models. Mon. Wea. Rev., 138, 1587-1612, doi: 10.1175/2009MWR2968.1. 
  219. Link, J., H. Tolman, and K. Robinson, 2017: NOAA's strategy for unified modelling. Nature, 549, doi: 10.1038/549458b. 
  220. Michalakes, J., S. Chen, J. Dudhia, L. Hart, J. Klemp, J. Middlecoff, and W. Skamarock, 2001: Development of a next-generation regional weather research and forecast model. Developments in Teracomputing: Proceedings of the 9th ECMWF workshop on the use of high-performance computing in meteorology, 269-276. 
  221. Miller, R. G., 1984: Very short-range statistical forecasting of automated weather observations. NOAA, DOT/FAA/PM-84/31, 25pp. 
  222. Min, J.-S., J.-B. Jee, M. Jang, and J.-G. Park, 2017: A study on improvement of high-resolution regional NWP by applying ocean mixed layer model. Atmosphere. Korean Meteor. Soc., 27, 317-329, doi: 10.14191/Atmos.2017.27.3.317. 
  223. Min, K.-H., K.-S. Chung, J.-W. Lee, C.-R. You, and G. Lee, 2022: Intercomparing radar data assimilation systems for ICE-POP 2018 snowfall cases. Geosci. Model Dev. Discuss., 1-32, doi: 10.5194/gmd-2022-18. 
  224. Nair, R. D., H.-W. Choi, and H. M. Tufo, 2009: Computational aspect of a scalable high-order discontinuous Galerkin atmospheric dynamical core. Comput. Fluids, 38, 309-319.  https://doi.org/10.1016/j.compfluid.2008.04.006
  225. Niekerk, A. V., and Coauthors, 2020: Constraining Orographic Drag Effects (COORDE): a model comparison of resolved and parameterized orographic drag. J. Adv. Modeling Earth Sys., 12, e2020MS002160, doi:10.1029/2020MS002160. 
  226. Noh, Y., W.-G. Cheon, S.-Y. Hong, and S. Raasch, 2003: Improvement of the K-profile model for the planetary boundary layer based on large eddy simulation data. Bound.-Layer Meteor., 107, 401-427.  https://doi.org/10.1023/A:1022146015946
  227. NSF, 1988: A study on statistical forecasting method in Korea. NSF, 228pp (in Korean). 
  228. Oh, J.-H., J.-H. Jung, and J.-W. Kim, 1994: Radiative transfer model for climate studies: 1. solar radiation parameterization and validation. J. Korean Meteor. Soc., 30, 315-333. 
  229. Oh, J.-H., 1996: Radiative transfer model for climate studies: 2. longwave radiation parameterization for a clear sky. J. Korean Meteor. Soc., 32, 471-484. 
  230. Oh, S.-G., and M.-S. Suh, 2019: Effects of irrigated cropland on the local and regional climate over northeast Asia in a regional climate model. Asia-Pac. J. Atmos. Sci., 55, 351-371, doi: 10.1007/s13143-018-0092-1. 
  231. Oh, S.-G., M.-S. Suh, and D.-H. Cha, 2013: Impacts of lateral boundary conditions on precipitation and temperature extremes over South Korea in the CORDEX regional climate simulation using RegCM4. Asia-Pac. J. Atmos. Sci., 49, 497-509, doi: 10.1007/s13143-013-0044-8. 
  232. Oh, W.-T., 2003: History of meteorological activities at Korea Meteorological Administration. Atmosphere. Korean Meteor. Soc., 13, 16-27. 
  233. Park, H., and S.-Y. Hong, 2007: An evaluation of a massflux cumulus parameterization scheme in the KMA global forecast system. J. Meteor. Soc. Japan, 85, 151-169.  https://doi.org/10.2151/jmsj.85.151
  234. Park, J.-R., H.-B. Cheong, and H.-G. Gang, 2011: High-order filter for the spherical surface limited area. Mon. Wea. Rev., 139, 1256-1278, doi: 10.1175/2010MWR3440.1. 
  235. Park, R.-S., J.-H. Chae, and S.-Y. Hong, 2016: A revised prognostic cloud fraction scheme in a global forecasting system. Mon. Wea. Rev., 114, 1219-1229, doi:10.1175/MWR-D-15-0273.1. 
  236. Park, R.-S., and Y. C. Kwon, 2018: The Implications for radiative cloud forcing via the link between shallow convection and planetary boundary layer mixing, J. Geophys. Res., 123, doi: 10.1029/2018JD028678. 
  237. Park, S., 2014a: A unified convection scheme (UNICON). Part I: formulation. J. Atmos. Sci., 71, 3902-3930, doi: 10.1175/JAS-D-13-0233.1. 
  238. Park, S., 2014b: A Unified Convection Scheme (UNICON). Part II: Simulation. J. Atmos. Sci., 71, 3931-3973, doi: 10.1175/JAS-D-13-0234.1. 
  239. Park, S., 2017: A heuristic parameterization for the integrated vertical overlap of cumulus and stratus. J. Adv. Model. Earth Syst., 9, 2437-2465, doi: 10.1002/2017MS001055. 
  240. Park, S., S.-Y. Hong, and Y.-H. Byun, 2010: Precipitation in boreal summer simulated by a GCM with two convective parameterizations schemes: implications of the intraseasonal oscillation for dynamic seasonal prediction. J. Climate, 23, 2801-2816, doi: 10.1175/2010JCLI3283.1. 
  241. Park, S.-H., J.-B. Jee, and C. Yi, 2015: Sensitivity test of the numerical simulation with high resolution topography and landuse over Seoul metropolitan and surrounding area. Atmosphere. Korean Meteor. Soc., 25, 309-322, doi: 10.14191/Atmos.2015.25.2.309. 
  242. Park, S.-H., J. B. Klemp, and W. C Skamarock, 2014: A comparison of mesh refinement in the global MPAS-A and WRF models using an idealized normal-mode baroclinic wave simulation. Mon. Wea. Rev., 142, 3614-3634, doi: 10.1175/MWR-D-14-00004.1. 
  243. Park, S.-H., and T.-Y. Lee, 2009: Accuracy tests for two-timelevel split-explicit scheme. Asia-Pac. J. Atmos. Sci., 45, 347-355. 
  244. Park, S.-K., 2002: The observing system research and predictability experiment (THORpex) and potential benefit for Korea. Atmosphere. Korean Meteor. Soc., 12, 463-467. 
  245. Park, S.-H., D.-L., Zhang, and H.-M., Lee, 2008: Impact of dropwindsonde data on the track forecasts of a tropical cyclone: an observing-systems simulation experiment study. Asia-Pac. J. Atmos. Sci., 44, 85-92. 
  246. Park, S.-H., and E.-H. Lee, 2005; Characteristics on Land-Surface and Soil Models Coupled in Mesoscale Meteorological Models. Atmosphere, 15, 1-16. 
  247. Park, S.-H., and E. Kalnay, 2004: Inverse three-dimensional variational data assimilation for an advection-diffusion problem: impact of diffusion and hybrid application. Geophys. Res. Lett., 31, L04102, doi: 10.1029/2003GL018830. 
  248. Park, S.-H., S. O, and C. Cassardo, 2017: Soil temperature response in Korea to a changing climate using a land surface model. Asia-Pac. J. Atmos. Sci., 53, 457-470, doi: 10.1007/s13143-017-0048-x. 
  249. Park, S.-K., and Coauthors, 2005: Development of graphic editing module (GEM) for digital forecast. Proceedings of the Autumn Meeting, Korean Meteor. Soc., 418-419. 
  250. Park, S.-Y., and T.-Y. Lee, 2003: A case study on the dependence of simulated cumulus convection on horizontal grid size. J. Korean Meteor. Soc., 39, 379-396. 
  251. Park, Y.-J., and Y.-D. Han, 2021: Analysis on the Yeongdong downslope windstorms generation condition verified by observation cases. Atmosphere. Korean Meteor. Soc., 31, 405-420, doi: 10.14191/Atmos.2021.31.4.405. 
  252. Parsons, D. B., and Coauthors, 2017: THORPEX research and the science prediction. Bull. Amer. Meteor. Soc., 98, 807-830, doi: 10.1175/BAMS-D-14-00025.1. 
  253. Randall, D. A., and Coauthors, 2019: 100 years of Earth system model development. A Century of Progress in Atmospheric and Related Sciences: Celebrating the American Meteorological Society Centennial. Meteor. Monogr., 59, doi: 10.1175/AMSMONOGRAPHS-D18-0018.1. 
  254. Rha, D.-K., M.-S. Suh, and C.-H. Kwak, 2005: Impacts of Land Cover Changes on the Simulation of Heavy Rainfall over South Korea. J. Korean Meteor. Soc., 41, 809-824. 
  255. Roberts, B., I. L. Jirak, A. J. Clark, S. J. Weiss, and J. S. Kain, 2019: Postprocessing and visualization techniques for convection-allowing ensembles. Bull. Amer. Meteor. Soc., 100, 1245-1258, doi: 10.1175/BAMSD-18-0041.1. 
  256. Schar, C., D. Leuenberger, O. Fuhrer, D. Luthi, and C. Girard, 2002: A new terrain-following vertical coordinate formulation for atmospheric prediction models. Mon. Wea. Rev., 130, 2459-2480.  https://doi.org/10.1175/1520-0493(2002)130<2459:antfvc>2.0.co;2
  257. Seo, E., and Coauthors, 2016: Improvement of soil moisture initialization for a global seasonal forecast system. Atmosphere. Korean Meteor. Soc., 26, 35-45, doi: 10.14191/Atmos.2016.26.1.035. 
  258. Shim, J.-K., and S.-Y. Hong, 2006: A study on the sensitivity of the simulations of typhoon Saomai (2000) to the cumulus parameterization and planetary boundary layer schemes in MM5. J. Korean Meteor. Soc., 42, 75-85. 
  259. Shim, T.-H., and Coauthors, 2015: Development and assessment of dynamical seasonal forecast system using the cryospheric variables. Atmosphere. Korean Meteor. Soc., 25, 155-167, doi: 10.14191/Atmos.2015.25.1.155. 
  260. Shin, D.-H., and T.-Y. Lee, 1997: Turbulence structure of the stratocumulus-topped marine boundary layer revealed by large eddy simulations. J. Korean Meteor. Soc., 33, 75-91. 
  261. Shin, H.-H., and S.-Y. Hong, 2014: Representation of the subgrid-scale turbulent transport in convective boundary layers at gray-zone resolutions. Mon. Wea. Rev., 143, 250-271, doi: 10.1175/MWR-D-14-00116.1. 
  262. Shin, S., and Coauthors, 2018: Real data assimilation using the local ensemble transform Kalman filter (LETKF) system for a global non-hydrostatic NWP model on the cubed-sphere. Asia-Pac. J. Atmos. Sci., 54, 351-360, doi: 10.1007/s13143-018-0022-2. 
  263. Shin, S., J.-S. Kang, and Y. Jo, 2016: The local ensemble transform Kalman filter (LETKF) with a global NWP model on the cubed sphere. Pure Appl. Geophys., 173, 2555-2570, doi: 10.1007/s00024-016-1269-0. 
  264. Shin, S.-C., M.-K. Kim, M.-S. Suh, D.-H. Jang, C.-S. Kim, W.-S. Lee, and Y.-H. Kim, 2008: Estimation of highresolution gridded precipitation using GIS and PRISM. Atmosphere. Korean Meteor. Soc., 18, 71-81. 
  265. Shin, S.-H., T.-Y. Lee, and S.-M. Lee, 1998: Interaction between the cumulus convection and surrounding atmosphere. J. Korean Meteor. Soc., 34, 376-389. 
  266. Skamarock, W. C., and Coauthors, 2008: A description of the Advanced Research WRF version 3. NCAR Tech. Note NCAR/TN- 4751STR, 113 pp. 
  267. Skamarock, W. C., and J. B. Klemp, 2008: A time-split nonhydrostatic atmospheric model for weather research and forecasting applications. J. Comput. Phys., 227, 3465-3485.  https://doi.org/10.1016/j.jcp.2007.01.037
  268. Skamarock, W. C., J. B. Klemp, M. G. Duda, L. D. Fowler, and S.-H. Park, 2012: A multiscale nonhydrostatic atmospheric model using centroidal Voronoi tessellations and Cgrid staggering. Mon. Wea. Rev., 140, 3090-3105.  https://doi.org/10.1175/mwr-d-11-00215.1
  269. Sohn, K.-T., and S.-D. Kim, 2001: Mid-term prediction of the daily maximum/minimum temperature in Seoul area using GDAPS outputs and dynamic linear models. J. Korean Meteor. Soc., 37, 13-20. 
  270. Song, H.-J., and I.-H. Kwon, 2015: Spectral transformation using a cubed-sphere grid for a three-dimensional variational data assimilation system. Mon. Wea. Rev., 143, 2581-2599, doi: 10.1175/MWR-D-14-00089.1. 
  271. Song, H.-J., I.-H. Kwon, and J. Kim, 2017a: Characteristics of a spectral inverse of the Laplacian using spherical harmonic functions on a cubed-sphere grid for background error covariance modeling. Mon. Wea. Rev., 145, 307-322, doi: 10.1175/MWR-D-16-0134.1. 
  272. Song, H.-J., J.-H. Ha, I.-H. Kwon, J. Kim, and J. Kwun, 2018: Multi-resolution Hybrid Data Assimilation Core on a Cubed-sphere Grid (HybDA), Asia-Pac. J. Atmos. Sci., 54, 337-350, doi: 10.1007/s13143-018-0018-y. 
  273. Song, H.-J., J. Kwun, I.-H. Kwon, J.-H. Ha, J.-H. Kang, S. Lee, H.-W. Chun, and S. Lim, 2017b: The impact of the nonlinear balance equation on a 3D-Var cycle during an Australian-winter month as compared with the regressed wind-mass balance. Quart. J. Roy. Meteorl. Soc., 143, 2036-2049, doi: 10.1002/qj.3065. 
  274. Song, H.-J., S. Shin, J.-H. Ha, and S. Lim, 2017c: The advantages of hybrid 4dEnVar in the context of the forecast sensitivity to initial conditions. J. Geophys. Res., 122, doi: 10.1002/2017JD027598. 
  275. Song, I.-S., and H.-Y. Chun, 2005: Momentum flux spectrum of convectively forced internal gravity waves and its application to gravity wave drag parameterization. Part I: theory. J. Atmos. Sci., 62, 107-124.  https://doi.org/10.1175/JAS-3363.1
  276. Song, I.-S., and H.-Y. Chun, 2008: A Lagrangian spectral parameterization of gravity wave drag induced by cumulus convection. J. Atmos. Sci., 65, 1204-1224.  https://doi.org/10.1175/2007JAS2369.1
  277. Suh, M.-S., and D.-K. Lee, 2004: Impacts of land use/cover changes on surface climate over east Asia for extreme climate cases using RegCM2, J. Geophys. Res., 109, D02108. 
  278. Swinbank, R., and Coauthors, 2016: The TIGGE project and its achievements. Bull. Amer. Meteor. Soc., 97, 49-67, doi: 10.1175/BAMS-D-13-00191.1. 
  279. Tang, S., and Coauthors, 2021: Long-term single column model intercomparison of diurnal cycle of precipitation over midlatitude and tropical land. Quart. J. Roy. Meteorl. Soc., 148, 641-669, doi: 10.1002/qj.4222. 
  280. Ukkonen, P., 2022: Exploring pathways to more accurate machine learning emulation of atmospheric radiative transfer. J. Adv. Modeling Earth Sys., 14, e2021MS002875, doi: 10.1029/2021MS002875. 
  281. Wee, T.-K., and D.-K. Lee, 1994: Semiprognostic tests of Fritsch-Chappell water-cycle process for numerical simulation of heavy rainfalls in Korean Peninsula. J. Korean Meteor. Soc., 30, 537-563. 
  282. Wilson, L. J., and M. Vallee, 2003: The Canadian updateable model output statistics (UMOS) system: validation against prefect prog. Wea. Forecasting, 18, 288-302.  https://doi.org/10.1175/1520-0434(2003)018<0288:TCUMOS>2.0.CO;2
  283. Wu, S.-M., J.-H. Oh, and D, Majewski, 2009: High-resolution numerical simulation with 10km global icosahedral hexagonal gridpoint model. Proceedings of the Spring Meeting, Korean Meteor. Soc., 224-225. 
  284. Xue, Y., and Coauthors, 2021: Impact of initialized land surface temperature and snowpack on subseasonal to seasonal prediction project, phase I (LS4P-I): organization and experimental design. Geosci. Model. Dev., 14, 4465-4494, doi: 10.5194/gmd-14-4465-2021. 
  285. Yang, E.-K., and H.-M. Kim, 2021: A comparison of variational, ensemble-based, and hybrid data assimilation methods over East Asia for two one-month periods. Atmos. Res., 249, 105257, doi: 10.1016/j.atmosres.2020.105257. 
  286. Yhang, Y.-B., and S.-Y. Hong, 2011: A study on large-scale nudging effects in regional climate model simulation. Asia-Pac. J. Atmos. Sci., 47, 235-243.  https://doi.org/10.1007/s13143-011-0012-0
  287. Zeng, X., and Coauthors, 2018: Future community efforts in understanding and modelling atmospheric processes. Bull. Amer. Meteor. Soc., 99, 159-162, doi: 10.1175/BAMS-D-18-0139.1. 
  288. Zo, I.-S., J.-B. Jee, and K.-T. Lee, 2014: Development of GWNU (Gangneung-Wonju National University) One-Layer Transfer Model for Calculation of Solar Radiation Distribution of the Korean Peninsula. AsiaPac. J. Atmos. Sci., 50, 23-32, doi: 10.1007/s13143-014-0047-0.