References
- ACEC (Advanced Computing Evaluation Committee), 2016: NGGPS phase-2 Benchmarks and Software Evaluation. AVEC Rep., 13 pp.
- 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.
- 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.
- 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.
- Bonavita, M., L. Isaksen, and E. Holm, 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.
- 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.
- 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.
- 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
- 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.
- 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.
- 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.
- 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.
- 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.
- 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
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- Haywood, J., 2009: The strategy for aerosols and dust in climate, weather and air quality forecasting. MOSAC-14, Paper No. 14.11, 15 pp.
- 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.
- 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.
- 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.
- 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.
- 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. https://doi.org/10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2
- 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. https://doi.org/10.1175/MWR3199.1
- 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. https://doi.org/10.1175/2007WAF2007030.1
- 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.
- 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.
- 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.
- Kalnay, E., 2003: Atmospheric Modeling, Data Assimilation and Predictability. Cambridge Univsersity Press, 341 pp.
- 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.
- 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. https://doi.org/10.2151/jmsj1965.61.6_812
- 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.
- 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.
- 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.
- 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.
- 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
- 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.
- 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.
- 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].
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- Mahrt, L., 2008: Bulk formulation of surface fluxes extended to weakwind stable conditions. Quart. J. Roy. Meteorol. Soc., 134, 1-10. https://doi.org/10.1002/qj.197
- 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. https://doi.org/10.1175/1520-0493(2002)130<0319:TOGIHG>2.0.CO;2
- 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. https://doi.org/10.1175/1520-0469(1987)044<1775:TEOOEG>2.0.CO;2
- McNally, T., M. Bonvita, and J.-N. The ipaut, 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.
- 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.
- 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.
- 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.
- Randall, D. A., R. Heikes, and T. Ringer, 2000: General Circulation Model Development. Academic Press, 416 pp.
- Sela, J. G., 1980: Spectral modeling at the National Meteorological Center. Mon. Wea. Rev., 108, 1279-1292. https://doi.org/10.1175/1520-0493(1980)108<1279:SMATNM>2.0.CO;2
- Sadourny, R., 1972: Conservative finite-difference approximations of the primitive equations on quasi-uniform spherical grids. Mon. Wea. Rev., 100, 136-144. https://doi.org/10.1175/1520-0493(1972)100<0136:CFAOTP>2.3.CO;2
- 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.
- 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.
- 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.
- 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.
- 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.
- Skamarock, W. C., 2004: Evaluating mesoscale NWP models using kinetic energy spectra. Mon. Wea. Rev., 132, 3019-3032. https://doi.org/10.1175/MWR2830.1
- Skamarock, W. C., 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.
- Skamarock, W. C., 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.
- 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. https://doi.org/10.1006/jcph.1996.5554
- Tiedtke, M., 1989: A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon. Wea. Rev., 117, 1779-1800. https://doi.org/10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2
- Tiedtke, M., 1993: Representation of clouds in large-scale models, Mon. Wea. Rev., 121, 3040-3061. https://doi.org/10.1175/1520-0493(1993)121<3040:ROCILS>2.0.CO;2
- Tomita, H., and M. Satoh, 2004: A new dynamical framework of nonhydrostatic global model using the icosahedral grid. Fluid Dyn. Res., 34, 357-400. https://doi.org/10.1016/j.fluiddyn.2004.03.003
- 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. https://doi.org/10.1002/qj.49712555904
- Warner, C. D. and M. E. McIntyre, 2001: An ultrasimple spectral parameterization for nonorographic gravity waves. J. Atmos. Sci., 58, 1837-1857. https://doi.org/10.1175/1520-0469(2001)058<1837:AUSPFN>2.0.CO;2
- 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.
- 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. https://doi.org/10.1256/qj.02.74
- Winton, M., 2000: A Reformulated Three-Layer Sea Ice Model. J. Atmos. Oceanic Technol., 17, 525-531. https://doi.org/10.1175/1520-0426(2000)017<0525:ARTLSI>2.0.CO;2
- Zangl, 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.
- 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.
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- Impact of Different Nesting Methods on the Simulation of a Severe Convective Event Over South Korea Using the Weather Research and Forecasting Model vol.126, pp.5, 2018, https://doi.org/10.1029/2020jd033084
- WRF 모형에서 한반도 여름철 강수 예측에 모의영역이 미치는 영향 vol.31, pp.1, 2018, https://doi.org/10.14191/atmos.2021.31.1.017
- Seasonal Performance of a Nonhydrostatic Global Atmospheric Model on a Cubed‐Sphere Grid vol.8, pp.4, 2018, https://doi.org/10.1029/2021ea001643
- Origin, Variability, and Pathways of East Sea Intermediate Water in a High‐Resolution Ocean Reanalysis vol.126, pp.6, 2021, https://doi.org/10.1029/2020jc017158
- Impact of Soil Moisture Data Assimilation on Analysis and Medium-Range Forecasts in an Operational Global Data Assimilation and Prediction System vol.12, pp.9, 2018, https://doi.org/10.3390/atmos12091089
- Suppressing Grid-Point Storms in a Numerical Forecasting Model vol.12, pp.9, 2018, https://doi.org/10.3390/atmos12091194
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- AMIP Simulations of a Global Model for Unified Weather‐Climate Forecast: Understanding Precipitation Characteristics and Sensitivity Over East Asia vol.13, pp.11, 2018, https://doi.org/10.1029/2021ms002592
- A New Hybrid Sigma-Pressure Vertical Coordinate with Smoothed Coordinate Surfaces vol.149, pp.12, 2021, https://doi.org/10.1175/mwr-d-21-0086.1
- A New Hybrid Sigma-Pressure Vertical Coordinate with Smoothed Coordinate Surfaces vol.149, pp.12, 2021, https://doi.org/10.1175/mwr-d-21-0086.1