Skip to main content
Log in

The Korean Integrated Model (KIM) System for Global Weather Forecasting

  • Published:
Asia-Pacific Journal of Atmospheric Sciences Aims and scope Submit manuscript

Abstract

The Korea Institute of Atmospheric Prediction Systems (KIAPS) began a national project to develop a new global atmospheric model system in 2011. The ultimate goal of this 9-year project is to replace the current operational model at the Korea Meteorological Administration (KMA), which was adopted from the United Kingdom’s Meteorological Office’s unified model (UM) in 2010. The 12-km Korean Integrated Model (KIM) system, consisting of a spectral-element non-hydrostatic dynamical core on a cubed sphere grid and a state-of-the-art physics parameterization package, has been launched in a real-time forecast framework, with initial conditions obtained via the advanced hybrid four-dimensional ensemble variational data assimilation (4DEnVar) over its native grid. A development strategy for KIM and the evolution of its performance in medium-range forecasts toward a world-class global forecast system are described. Outstanding issues in KIM 3.1 as of February 2018 are discussed, along with a future plan for operational deployment in 2020.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • ACEC (Advanced Computing Evaluation Committee), 2016: NGGPS phase-2 Benchmarks and Software Evaluation. AVEC Rep., 13 pp.

    Google Scholar 

  • Alpert, J. C., M. Kanamitsu, P. M. Caplan, J. G. Sela, G. H. White, and E. Kalnay, 1988: Mountain induced gravity wave drag parameterization in the NMC medium-range forecast model. Proc. Eighth Conference on Numerical Weather Prediction, Baltimore, USA, Amer. Meteor. Soc. 726-733.

    Google Scholar 

  • Bae, S.-Y., S.-Y. Hong, and K.-S. Lim, 2016: Coupling WRF doublemoment 6-class microphysics schemes to RRTMG radiation scheme in weather research and forecasting Model. Adv. Meteor., 2016, 5070154, doi:10.1155/2016/5070154.

    Article  Google Scholar 

  • Baek, S., 2017: A revised radiation package of G-packed McICA and twostream approximation: Performance evaluation in a global weather forecasting model. J. Adv. Model. Earth Syst., 9, 1628-1640, doi:10. 1002/2017MS000994.

    Article  Google Scholar 

  • Bonavita, M., L. Isaksen, and E. Hólm, 2012: On the use of EDA background error variances in the ECMWF 4D-Var. Quart. J. Roy. Meteor. Soc., 138, 1540-1559, doi:10.1002/qj.1899.

    Article  Google Scholar 

  • Buehner, M., and Coauthors, 2015: Implementation of deterministic weather forecasting systems based on ensemble-variational data assimilation at Environment Canada. Part I: The global system. Mon. Wea. Rev., 143, 2532-2559, doi:10.1175/MWR-D-14-00354.1.

    Google Scholar 

  • Chen, F., and J. Dudhia, 2001: Coupling an advanced land surfacehydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model Implementation and Sensitivity. Mon. Wea. Rev., 129, 569-585, doi:10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2.

    Google Scholar 

  • Cheong, H.-B., 2006: A dynamical core with double Fourier series: Comparison with the spherical harmonics method. Mon. Wea. Rev., 134, 1299-1315.

    Article  Google Scholar 

  • 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:10.1175/2010-JAS3552.1.

    Google Scholar 

  • Choi, H.-J., and S.-Y. Hong, 2015: An updated subgrid orographic parameterization for global atmospheric forecast. J. Geophys. Res., 120, 12445-12457, doi:10.1002/2015JD024230.

    Google Scholar 

  • Choi, H.-J., S.-J. Choi, M.-S. Koo, J.-E. Kim, Y. C. Kwon, and S.-Y. Hong, 2017: Effects of parameterized orographic drag on weather forecasting and simulated climatology over East Asia during boreal summer. J. Geophys. Res., 122, 10669-10678, doi:10.1002/2017JD026696.

    Article  Google Scholar 

  • Choi, H.-J., J.-Y. Han, M.-S. Koo, H.-Y. Chun, Y.-H. Kim, and S.-Y. Hong, 2018: Effects of non-orographic gravity wave drag on seasonal and medium-range predictions in a global model (in press). Asia-Pac. J. Atmos. Sci., 54, doi:10.1007/s13143-018-0023-1.

  • Choi, S.-J., 2018: Structure of Eigenvalues in the advection-diffusion equation by the spectral element method on a cubed-sphere grid (in press). Asia-Pac. J. Atmos. Sci., 54, doi:10.1007/s13143-018-0020-4.

  • 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.

    Article  Google Scholar 

  • Choi, S.-J., F. X. Giraldo, J. Kim, and S. Shin, 2014: Verification of a nonhydrostatic dynamical core using horizontally spectral element vertically finite difference method: 2-D aspects. Geosci. Model Dev., 7, 2717-2731, doi:10.5194/gmd-7-2717-2014.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Clayton, A. M., A. C. Lorenc, and D. M. Barker, 2013: Operational implementation of a hybrid ensemble/4D-Var global data assimilation system at the Met Office. Quart. J. Roy. Meteor. Soc., 139, 1445-1461, doi:10.1002/qj.2054.

    Article  Google Scholar 

  • Dennis, J., J. Edwards, K. J. Evans, O. N. Guba, P. H. Lauritzen, A. A. Mirin, A. St-Cyr, M. A. Taylor, and P. H. Worly, 2011: CAM-SE: a scalable spectral element dynamical core for the community atmosphere model. Int. J. High Perform Comput. Appl., 26, 74-89, doi: 10.1177/1094342011428142, doi:10.1177/1094342011428142.

    Article  Google Scholar 

  • Ek, M. B., K. E. Mitchell, Y. Lin, E. Rogers, P. Grunmann, V. Koren, G. Gayno, and J. D. Tarpley, 2003: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta Model. J. Geophys. Res., 108, D22, doi: 10.1029/2002JD003296.

    Article  Google Scholar 

  • Giraldo, F. X., J. F. Kelly, and E. M. Constantinescu, 2013: Implicit-Explicit Formulations for a 3D Nonhydrostatic Unified Model of the Atmosphere (NUMA). SIAM J. Sci. Comput., 35, B1162-B1194, doi: 10.1137/120876034.

    Article  Google Scholar 

  • Govett, M., and Coauthors, 2017: Parallelization and performance of the NIM weather model on CPU, GPU, and MIC processors. Bull. Amer. Meteor. Soc., 98, 2201-2213, doi:10.1175/BAMS-D-15-00278.1.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Haywood, J., 2009: The strategy for aerosols and dust in climate, weather and air quality forecasting. MOSAC-14, Paper No. 14.11, 15 pp.

    Google Scholar 

  • Hong, S.-Y., 2010: A new stable boundary-layer mixing scheme and its impact on the simulated East Asian summer monsoon. Quart. J. Roy. Meteor. Soc., 136, 1481-1496, doi:10.1002/qj.665.

    Article  Google Scholar 

  • Hong, S.-Y., and J.-O. J. Lim, 2006: The WRF Single-Moment 6-Class Microphysics Scheme (WSM6). J. Korean Meteor. Soc., 42, 129-151.

    Google Scholar 

  • Hong, S.-Y., and J. Dudhia, 2012: Next-generation numerical weather prediction: Bridging parameterization, explicit clouds, and large eddies. Bull. Amer. Meteor. Soc., 93, ES6-ES9, doi:10.1175/2011BAMS3224.1.

    Article  Google Scholar 

  • Hong, S.-Y., and M. Kanamitsu, 2014: Dynamical downscaling: Fundamental issues from an NWP point of view and recommendations. Asia-Pac. J. Atmos. Sci., 50, 83-104, doi:10.1007/s13143-014-0029-2.

    Article  Google Scholar 

  • Hong, S.-Y., and J. Jang, 2018: Impacts of shallow convection processes on a simulated boreal summer climatology in a global atmospheric model (in press). Asia-Pac. J. Atmos. Sci., 54, doi:10.1007/s13143-018-0013-3.

  • Hong, S.-Y., J. Duhdia, and S.-H. Chen, 2004: A revised approach to icemicrophysical processes for the bulk parameterization of cloud and precipitation. Mon. Wea. Rev., 132, 103-120.

    Article  Google Scholar 

  • Hong, S.-Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 2318-2341.

    Article  Google Scholar 

  • Hong, S.-Y., J. Choi, E.-C. Chang, H. Park, and Y.-J. Kim, 2008: Lowertropospheric enhancement of gravity wave drag in a global spectral atmospheric forecast model. Wea. Forecasting, 23, 523-531.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Hong, S.-Y., M. Koo, J. Jang, J. Esther Kim, H. Park, M. Joh, J. Kang, and T. Oh, 2013b: An evaluation of the system software dependency of a global spectral model. Mon. Wea. Rev., 141, 4165-4172, doi:10.1175/MWR-D-12-00352.1.

    Article  Google Scholar 

  • Iacono, M.-J., J. S. Delamere, E. J. Mlawer, M. W. Shepherd, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by long-lived greenhouse gases: Calculation with the AER radiative transfer models. J. Geophys. Res., 113, D13103, doi:10.1029/2008JD009944.

    Article  Google Scholar 

  • Kalnay, E., 2003: Atmospheric Modeling, Data Assimilation and Predictability. Cambridge Univsersity Press, 341 pp.

    Google Scholar 

  • Kanamitsu, M., 1989: Description of the NMC Global Data Assimilation and Forecast System. Wea. Forecasting, 4, 335-342, https://doi.org/10.1175/1520-0434(1989)004<0335:DOTNGD>2.0.CO;2.

    Article  Google Scholar 

  • Kanamitsu, M., K. Tada, T. Kuo, N. Sato and S. Isa, 1983: Description of the JMA operational spectral model. J. Meteor. Soc. Japan, 61, 812-828.

    Article  Google Scholar 

  • Kang, H.-G., and H.-B. Cheong, 2017: An efficient implementation of a high-order filter for a cubed-sphere spectral element model. J. Comput. Phys., 332, 66-82, doi:10.1016/j.jcp.2016.12.001.

    Article  Google Scholar 

  • Kang, J.-H., and Coauthors, 2018: Development of an observation processing package for data assimilation in KIAPS (in press). Asia-Pac. J. Atmos. Sci., 54, doi:10.1007/s13143-018-0030-2.

  • Kim, E.-J., and S.-Y. Hong, 2010: Impact of air-sea interaction on East Asian summer monsoon climate in WRF. J. Geophys. Res., 115, D19118, doi:10.1029/2009JD013253.

    Article  Google Scholar 

  • Kim, J, Y. C. Kwon, and T.-H. Kim, 2018a: 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.

    Google Scholar 

  • Kim, K.-H., P.-S. Shim, S. Shin, and J. Kim, 2018b: A simple method to find a neighboring grid point on the cubed-sphere (in press). Asia-Pac. J. Atmos. Sci., 54, doi:10.1007/s13143-018-0027-x.

  • Kim, S.-Y., and S.-Y. Hong, 2018: The use of partial cloudiness in a bulk cloud microphysics scheme: Concept and 2D results (in press). J. Atmos. Sci., doi:10.1175/JAS-D-17-0234.1.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • Koo, M.-S., and S.-Y. Hong, 2014: Stochastic representation of dynamic model tendency: Formulation and preliminary results. Asia-Pac. J. Atmos. Sci., 50, 497-506, doi:10.1007/s13143-014-0039-0.

    Article  Google Scholar 

  • Koo, M.-S., S. Baek, K.-H. Seol, and K. Cho, 2017: Advances in land surface 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.

    Article  Google Scholar 

  • Koo, M.-S., H.-J. Choi, and J.-Y. Han, 2018: A parameterization of turbulentscale orographic form drag in a global atmospheric model. AOGS 15th Annual Meeting, Honolulu, Hawaii, United States, AS20-A039 [Available online at http://www.asiaoceania.org/aogs2018/doc/AOGS2018_prgbook.pdf].

    Google Scholar 

  • Kwon, I.-H., S. English, W. Bell, R. Potthast, A. Collard, and B. Ruston, 2018: Assessment of progress and status of data assimilation in numerical weather prediction. Bull. Amer. Soc., 99, ES75-ES79, doi:10.1175/BAMS-D-17-0266.1.

    Article  Google Scholar 

  • Kwon, I.-H., and Coauthors, 2018: Development of operational hybrid data assimilation system at KIAPS (in press). Asia-Pac. J. Atmos. Sci., 54, doi:10.1007/s13143-018-0029-8.

  • 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.

    Article  Google Scholar 

  • Lee, E.-H., E. Lee, R. Park, Y.-C. Kwon, and S.-Y. Hong, 2018: Impact of turbulent Mmixing in the stratocumulus-topped boundary layer on numerical weather prediction (in press). Asia-Pac. J. Atmos. Sci., 54, doi:10.1007/s13143-018-0024-0.

    Google Scholar 

  • Lim, K.-S., S.-Y. Hong, J.-H. Yoon, and J. Han, 2014: Simulation of the summer monsoon rainfall over East Asia using the NCEP GFS cumulus parameterization at different horizontal resolution. Wea. Forecasting, 29, 1143-1154, doi:10.1175/WAF-D-13-00143.1.

    Article  Google Scholar 

  • Lin, S.-J., L. Harris, X. Chen. W. Yao, and J. Chai, 2017: Colliding modons: A nonlinear test for the evaluation of global dynamical cores. J. Adv. Model. Earth Syst., 9, 2483-2492, doi:10.1002/2017MS000965.

    Article  Google Scholar 

  • Long, P. E., 1984: A general unified similarity theory for the calculation of turbulent fluxes in numerical weather prediction models for unstable conditions. NCEP Office Note 302, 30 pp.

  • Long, P. E., 1986: An economical and compatible scheme for parameterizing the stable surface layer in the medium range forecast model. NCEP Office Note 321, 24 pp.

  • Lorenc, A. C., N. E. Bowler, A. M. Clayton, S. R. Pring, and D. Fairbairn, 2015: Comparison of hybrid-4DEnVar and hybrid-4DVar data assimilation methods for global NWP. Mon. Wea. Rev., 143, 212-229, doi:10.1175/MWR-D-14-00195.1.

    Article  Google Scholar 

  • Mahrt, L., 2008: Bulk formulation of surface fluxes extended to weakwind stable conditions. Quart. J. Roy. Meteorol. Soc., 134, 1-10.

    Article  Google Scholar 

  • Majewski, D., D. Liermann, P. Prohl, B. Ritter, M. Buchhold, T. Hanisch, G. Paul, W. Wergen, and J. Baumgardner, 2002: The operational global icosahedral-hexagonal gridpoint model GME: Description and highresolution tests. Mon. Wea. Rev., 130, 319-338.

    Article  Google Scholar 

  • McFarlane, N. A., 1987: The Effect of Orographically Excited Gravity Wave Drag on the General Circulation of the Lower Stratosphere and Troposphere. J. Atmos. Sci., 44, 1775-1800.

    Article  Google Scholar 

  • McNally, T., M. Bonvita, and J.-N. The ìpaut, 2014: The role of satellite data in the forecasting of Hurricane Sandy. Mon. Wea. Rev., 142, 634-646, doi:10.1175/MWR-D-13-00170.1.

    Article  Google Scholar 

  • Park, H., S.-Y. Hong, H.-B. Cheong, and M.-S. Koo, 2013: A double Fourier series (DFS) dynamic core in a global atmospheric model with full physics. Mon. Wea. Rev., 141, 3052-3061, doi:10.1175/MWR-D-12-00270.1.

    Article  Google Scholar 

  • 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., 144, 1219-1229, doi:10.1175/MWR-D-15-0273.1.

    Article  Google Scholar 

  • Rabier, F., 2005: Overview of global data assimilation developments in numerical weather prediction centres. Quart. J. Roy. Meteor. Soc., 131, 3215-3233, doi:10.1256/qj.05.129.

    Article  Google Scholar 

  • Randall, D. A., R. Heikes, and T. Ringer, 2000: General Circulation Model Development. Academic Press, 416 pp.

    Google Scholar 

  • Sela, J. G., 1980: Spectral modeling at the National Meteorological Center. Mon. Wea. Rev., 108, 1279-1292.

    Article  Google Scholar 

  • Sadourny, R., 1972: Conservative finite-difference approximations of the primitive equations on quasi-uniform spherical grids. Mon. Wea. Rev., 100, 136-144.

    Article  Google Scholar 

  • Shin, H. H., and S.-Y. Hong, 2013: Analysis on resolved and parameterized vertical transport in convective boundary layers at gray-zone resolution. J. Atmos. Sci., 70, 3248-3261, doi:10.1175/JAS-D-12-0290.1.

    Article  Google Scholar 

  • Shin, H. H., and S.-Y. Hong, 2015: 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.

    Article  Google Scholar 

  • Shin, S., and Coauthors, 2018: Real data assimilation using the Local Ensemble Transform Kalman Filter (LETKF) system for a global nonhydrostatic NWP model on the cubed-sphere (in press). Asia-Pac. J. Atmos. Sci., 54, doi: 10.1007/s13143-018-0022-2.

  • Song, H.-J., and I.-H. Kwon, 2015: Spectral transformation using a cubedsphere grid for a three-dimensional variational data assimilation system. Mon. Wea. Rev., 143, 2581-2599, doi:10.1175/MWR-D-14-00089.1.

    Article  Google Scholar 

  • Song, H.-J., S. Shin, J.-H. Ha, and S. Lim, 2017: The advantages of hybrid 4DEnVar in the context of the forecast sensitivity to initial conditions. J. Geophys. Res., 122, 12226-12244, doi:10.1002/2017JD027598.

    Google Scholar 

  • Song, H.-J., J.-H. Ha, I.-H. Kwon, J. Kim, and J. Kwun, 2018: Multiresolution Hybrid Data Assimilation Core on a Cubed-sphere Grid (HybDA). Asia-Pac. J. Atmos. Sci., 54, doi:10.1007/s13143-018-0018-y.

    Google Scholar 

  • Skamarock, W. C., 2004: Evaluating mesoscale NWP models using kinetic energy spectra. Mon. Wea. Rev., 132, 3019-3032.

    Article  Google Scholar 

  • Song, H.-J., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, M. G. Duda, X.-Y. Huang, W. Wang, and J. G. Powers, 2008: A description of the advanced research WRF version 3. NCAR Tech. Note NCAR/TN-475+STR, 113 pp.

    Google Scholar 

  • Song, H.-J., J. B. Klemp, M.G. Duda, L.D. Fowler, S. Park, and T.D. Ringler, 2012: A multi-scale nonhydrostatic atmospheric model using centroidal voronoi tesselations and c-grid staggering. Mon. Wea. Rev., 140, 3090-3105, doi:10.1175/MWR-D-11-00215.1.

    Article  Google Scholar 

  • Taylor, M. A., J. Tribbia, and M. Iskandarani, 1997: The spectral element method for the shallow water equations on the sphere. J. Comput. Phys., 130, 92-108.

    Article  Google Scholar 

  • Tiedtke, M., 1989: A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon. Wea. Rev., 117, 1779-1800.

    Article  Google Scholar 

  • Tiedtke, M., 1993: Representation of clouds in large-scale models, Mon. Wea. Rev., 121, 3040-3061.

    Article  Google Scholar 

  • Tomita, H., and M. Satoh, 2004: A new dynamical framework of nonhydrostatic global model using the icosahedral grid. Fluid Dyn. Res., 34, 357-400.

    Article  Google Scholar 

  • Viterbo, P., A. Beljaars, J.-F. Mahfouf, and J. Teixeira, 1999: The representation of soil moisture freezing and its impact on the stable boundary layer. Quart. J. Roy. Meteorol. Soc., 125, 2401-2426.

    Article  Google Scholar 

  • Warner, C. D. and M. E. McIntyre, 2001: An ultrasimple spectral parameterization for nonorographic gravity waves. J. Atmos. Sci., 58, 1837-1857.

    Article  Google Scholar 

  • Wedi, N. P., M. Hamrud, and G. Mozdzynski, 2013: A fast spherical harmonics transform for global NWP and climate models. Mon. Wea. Rev., 141, 3450-3461, doi:10.1175/MWR-D-13-00016.1.

    Article  Google Scholar 

  • Wilson, D. R. and D. Gregory, 2003: The behaviour of large-scale model cloud schemes under idealized forcing scenarios. Quart. J. Roy. Meteorol. Soc., 129, 967-986.

    Article  Google Scholar 

  • Winton, M., 2000: A Reformulated Three-Layer Sea Ice Model. J. Atmos.Oceanic Technol., 17, 525-531.

    Article  Google Scholar 

  • Zängl, G., D. Reinert, M.-P. Ripodas, and M. Baldauf, 2014: The ICON (ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M: Description of the non-hydrostatic dynamical core. Quart. J. Roy. Meteor. Soc., 141, 563-579, doi:10.1002/qj.2378.

    Article  Google Scholar 

  • Zeng, X., Z. Wang, and A. Wang, 2012: Surface skin temperature and the interplay between sensible and ground heat fluxes over arid regions. J. Hydrometeor., 13, 1359-1370, doi:10.1175/JHM-D-11-0117.1.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Song-You Hong.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hong, SY., Kwon, Y.C., Kim, TH. et al. The Korean Integrated Model (KIM) System for Global Weather Forecasting. Asia-Pacific J Atmos Sci 54 (Suppl 1), 267–292 (2018). https://doi.org/10.1007/s13143-018-0028-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13143-018-0028-9

Key words

Navigation