Au-Yeung, A. Y. M., and J. C. L. Chan, 2012: Potential use of a regional climate model in seasonal tropical cyclone activity predictions in the western North Pacific. Climate Dyn., 39, 783−794, https://doi.org/10.1007/s00382-011-1268-x.
Bengtsson, L., H. Böttger, and M. Kanamitsu, 1982: Simulation of hurricane-type vortices in a general circulation model. Tellus, 34, 440−457, https://doi.org/10.3402/tellusa.v34i5.10830.
Bengtsson, L., M. Botzet, and M. Esch, 1995: Hurricane-type vortices in a general circulation model. Tellus A, 47, 175−196, https://doi.org/10.3402/tellusa.v47i2.11500.
Bentsen, M., and Coauthors, 2013: The Norwegian Earth System Model, NorESM1-M−Part 1: Description and basic evaluation of the physical climate. Geoscientific Model Development, 6, 687−720, https://doi.org/10.5194/gmd-6-687-2013.
Broccoli, A. J., and S. Manabe, 1990: Can existing climate models be used to study anthropogenic changes in tropical cyclone climate? Geophys Res. Lett., 17, 1917−1920, https://doi.org/10.1029/GL017i011p01917.
Camargo, S. J., 2013: Global and regional aspects of tropical cyclone activity in the CMIP5 models. J. Climate, 26, 9880−9902, https://doi.org/10.1175/jcli-d-12-00549.1.
Camargo, S. J., and S. E. Zebiak, 2002: Improving the detection and tracking of tropical cyclones in atmospheric general circulation models. Wea. Forecasting, 17, 1152−1162, https://doi.org/10.1175/1520-0434(2002)017<1152:itdato>2.0.co;2.
Chan, J. C. L., 2005: The physics of tropical cyclone motion. Annual Review of Fluid Mechanics, 37, 99−128, https://doi.org/10.1146/annurev.fluid.37.061903.175702.
Chan, J. C. L., and M. Xu, 2009: Inter-annual and inter-decadal variations of landfalling tropical cyclones in East Asia. Part I: Time series analysis. International Journal of Climatology, 29, 1285−1293, https://doi.org/10.1002/joc.1782.
Collins, W. J., and Coauthors, 2011: Development and evaluation of an Earth-System model-HadGEM2. Geoscientific Model Development, 4, 1051−1075, https://doi.org/10.5194/gmd-4-1051-2011.
Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553−597, https://doi.org/10.1002/qj.828.
Diro, G. T., F. Giorgi, R. Fuentes-Franco, K. J. E. Walsh, G. Giuliani, and E. Coppola, 2014: Tropical cyclones in a regional climate change projection with RegCM4 over the CORDEX Central America domain. Climatic Change, 125, 79−94, https://doi.org/10.1007/s10584-014-1155-7.
Emanuel, K. A., 1991: A scheme for representing cumulus convection in large-scale models. J. Atmos. Sci., 48, 2313−2335, https://doi.org/10.1175/1520-0469(1991)048<2313:asfrcc>2.0.co;2.
Emanuel, K. A., 2013: Downscaling CMIP5 climate models shows increased tropical cyclone activity over the 21st century. Proceedings of the National Academy of Sciences of the United States of America, 110, 12219−12224, https://doi.org/10.1073/pnas.1301293110.
Emanuel, K. A., 2021: Response of global tropical cyclone activity to increasing CO2: Results from downscaling CMIP6 models. J. Climate, 34, 57−70, https://doi.org/10.1175/JCLI-D-20-0367.1.
Emanuel, K. A., and M. Živković-Rothman, 1999: Development and evaluation of a convection scheme for use in climate models. J. Atmos. Sci., 56, 1766−1782, https://doi.org/10.1175/1520-0469(1999)056<1766:daeoac>2.0.co;2.
Eyring, V., S. Bony, G. A. Meehl, C. A. Senior, B. Stevens, R. J. Stouffer, and K. E. Taylor, 2016: Overview of the Coupled Model Intercomparison Project Phase 6(CMIP6) experimental design and organization. Geoscientific Model Development, 9, 1937−1958, https://doi.org/10.5194/gmd-9-1937-2016.
Flato, G., and Coauthors, 2013: Evaluation of climate models. Climate Change 2013: The physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Stocker et al., Eds., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 741−866.
Fuentes-Franco, R., F. Giorgi, E. Coppola, and K. Zimmermann, 2017: Sensitivity of tropical cyclones to resolution, convection scheme and ocean flux parameterization over Eastern Tropical Pacific and Tropical North Atlantic Oceans in the RegCM4 model. Climate Dyn., 49, 547−561, https://doi.org/10.1007/s00382-016-3357-3.
Gao, X. J., Y. Shi, and F. Giorgi, 2016: Comparison of convective parameterizations in RegCM4 experiments over China with CLM as the land surface model. Atmos. Ocean. Sci. Lett., 9, 246−254, https://doi.org/10.1080/16742834.2016.1172938.
Gao, X. J., and Coauthors, 2017: Performance of RegCM4 over major river basins in China. Adv. Atmos. Sci., 34, 441−455, https://doi.org/10.1007/s00376-016-6179-7.
Gao, X. J., and Coauthors, 2018: Future changes in thermal comfort conditions over China based on multi-RegCM4 simulations. Atmos. Ocean. Sci. Lett., 11, 291−299, https://doi.org/10.1080/16742834.2018.1471578.
Gentry, M. S., and G. M. Lackmann, 2010: Sensitivity of simulated tropical cyclone structure and intensity to horizontal resolution. Mon. Wea. Res., 138, 688−704, https://doi.org/10.1175/2009MWR2976.1.
Giorgi, F., 2019: Thirty years of regional climate modeling: Where are we and where are we going next? J Geophys. Res. Atmos., 124, 5696−5723, https://doi.org/10.1029/2018jd030094.
Giorgi, F., M. R. Marinucci, G. T. Bates, and G. De Canio, 1993: Development of a second-generation regional climate model (REGCM2). Part II: Convective processes and assimilation of lateral boundary conditions. Mon. Wea. Rev., 121, 2814−2832, https://doi.org/10.1175/1520-0493(1993)121<2814:DOASGR>2.0.CO;2.
Giorgi, F., C. Jones, and G. R. Asrar, 2009: Addressing climate information needs at the regional level: The CORDEX framework. WMO Bull., 58, 175−183.
Giorgi, F., and Coauthors, 2012: RegCM4: Model description and preliminary tests over multiple CORDEX domains. Climate Research, 52, 7−29, https://doi.org/10.3354/cr01018.
Gray, W. M., 1979: Meteorology over the tropical oceans. Hurricanes: Their Formation, Structure and Likely Role in the Tropical Circulation, D. B. Shaw, Eds., Royal Meteorological Society, 155−218.
Gutowski, W. J. Jr., and Coauthors, 2016: WCRP COordinated Regional Downscaling EXperiment (CORDEX): A diagnostic MIP for CMIP6. Geoscientific Model Development, 9, 4087−4095, https://doi.org/10.5194/gmd-9-4087-2016.
Haarsma, R. J., J. F. B. Mitchell, and C. A. Senior, 1993: Tropical disturbances in a GCM. Climate Dyn., 8, 247−257, https://doi.org/10.1007/bf00198619.
Han, Z. Y., X. J. Gao, Y. Shi, J. Wu, M. L. Wang, and F. Giorgi, 2015: Development of Chinese high resolution land cover data for the RegCM4/CLM and its impact on regional climate simulation. Journal of Glaciology and Geocryology, 37, 857−866, https://doi.org/10.7522/j.issn.1000-0240.2015.0095. (in Chinese with English abstract
Hazeleger, W., and Coauthors, 2010: EC-Earth: A seamless earth-system prediction approach in action. Bull. Amer. Meteor. Soc., 91, 1357−1363, https://doi.org/10.1175/2010bams2877.1.
He, F., and D. J. Posselt, 2015: Impact of parameterized physical processes on simulated tropical cyclone characteristics in the community atmosphere model. J. Climate, 28, 9857−9872, https://doi.org/10.1175/jcli-d-15-0255.1.
Holtslag, A. A. M., E. I. F. De Bruijn, and H. L. Pan, 1990: A high resolution air mass transformation model for short-range weather forecastiong. Mon. Wea. Rev., 118, 1561−1575, https://doi.org/10.1175/1520-0493(1990)118<1561:ahramt>2.0.co;2.
Huang, W.-R., and J. C. L. Chan, 2014: Dynamical downscaling forecasts of Western North Pacific tropical cyclone genesis and landfall. Climate Dyn., 42, 2227−2237, https://doi.org/10.1007/s00382-013-1747-3.
Iversen, T., and Coauthors, 2013: The Norwegian Earth System Model, NorESM1-M−Part 2: Climate response and scenario projections. Geoscientific Model Development, 6, 389−415, https://doi.org/10.5194/gmd-6-389-2013.
Jiang, D. B., Z. P. Tian, and X. M. Liang, 2016: Reliability of climate models for China through the IPCC Third to Fifth Assessment Reports. International Journal of Climatology, 36, 1114−1133, https://doi.org/10.1002/joc.4406.
Jin, C.-S., D.-H. Cha, D.-K. Lee, M.-S. Suh, S.-Y. Hong, H.-S. Kang, and C.-H. Ho, 2016: Evaluation of climatological tropical cyclone activity over the western North Pacific in the CORDEX-East Asia multi-RCM simulations. Climate Dyn., 47, 765−778, https://doi.org/10.1007/s00382-015-2869-6.
Jungclaus, J. H., and Coauthors, 2013: Characteristics of the ocean simulations in the Max Planck Institute Ocean Model (MPIOM) the ocean component of the MPI-Earth system model. Journal of Advances in Modeling Earth Systems, 5, 422−446, https://doi.org/10.1002/jame.20023.
Kiehl, J. T., J. J. Hack, G. B. Bonan, B. A. Boville, D. L. Williamson, and P. J. Rasch, 1998: The National Center for Atmospheric Research community climate model: CCM3. J. Climate, 11, 1131−1149, https://doi.org/10.1175/1520-0442(1998)011<1131:tncfar>2.0.co;2.
Knapp, K. R., M. C. Kruk, D. H. Levinson, H. J. Diamond, and C. J. Neumann, 2010: The International Best Track Archive for Climate Stewardship (IBTrACS): Unifying tropical cyclone data. Bull. Amer. Meteor. Soc., 91, 363−376, https://doi.org/10.1175/2009bams2755.1.
Kruk, M. C., K. R. Knapp, and D. H. Levinson, 2010: A technique for combining global tropical cyclone best track data. J. Atmos. Ocean. Technol., 27, 680−692, https://doi.org/10.1175/2009jtecha1267.1.
Lee, H., C. S. Jin, D. H. Cha, M. Lee, D. K. Lee, M. S. Suh, S. Y. Hong, and H. S. Kang, 2019: Future change in tropical cyclone activity over the Western North Pacific in CORDEX-East Asia multi-RCMs forced by HadGEM2-AO. J. Climate, 32, 5053−5067, https://doi.org/10.1175/jcli-d-18-0575.1.
Li, R. C. Y., W. Zhou, C. M. Shun, and T. C. Lee, 2017: Change in destructiveness of landfalling tropical cyclones over China in recent decades. J. Climate, 30, 3367−3379, https://doi.org/10.1175/jcli-d-16-0258.1.
Liang, J., C. G. Wang, and K. I. Hodges, 2017: Evaluation of tropical cyclones over the South China Sea simulated by the 12 km MetUM regional climate model. Quart. J. Roy. Meteor. Soc., 143, 1641−1656, https://doi.org/10.1002/qj.3035.
Lok, C. C. F., and J. C. L. Chan, 2018a: Changes of tropical cyclone landfalls in South China throughout the twenty-first century. Climate Dyn., 51, 2467−2483, https://doi.org/10.1007/s00382-017-4023-0.
Lok, C. C. F., and J. C. L. Chan, 2018b: Simulating seasonal tropical cyclone intensities at landfall along the South China coast. Climate Dyn., 50, 2661−2672, https://doi.org/10.1007/s00382-017-3762-2.
Manabe, S., J. L. Holloway Jr., and H. M. Stone, 1970: Tropical circulation in a time-integration of a global model of the atmosphere. J. Atmos. Sci., 27, 580−613, https://doi.org/10.1175/1520-0469(1970)027<0580:tciati>2.0.co;2.
Moss, R. H., and Coauthors, 2010: The next generation of scenarios for climate change research and assessment. Nature, 463, 747−756, https://doi.org/10.1038/nature08823.
Murakami, H., and M. Sugi, 2010: Effect of model resolution on tropical cyclone climate projections. SOLA, 6, 73−76, https://doi.org/10.2151/sola.2010-019.
Murakami, H., B. Wang, and A. Kitoh, 2011: Future change of western North Pacific typhoons: Projections by a 20-km-mesh global atmospheric model. J. Climate, 24, 1154−1169, https://doi.org/10.1175/2010jcli3723.1.
Murakami, H., R. Mizuta, and E. Shindo, 2012a: Future changes in tropical cyclone activity projected by multi-physics and multi-SST ensemble experiments using the 60-km-mesh MRI-AGCM. Climate Dyn., 39, 2569−2584, https://doi.org/10.1007/s00382-011-1223-x.
Murakami, H., and Coauthors, 2012b: Future changes in tropical cyclone activity projected by the new high-resolution MRI-AGCM. J. Climate, 25, 3237−3260, https://doi.org/10.1175/jcli-d-11-00415.1.
Murakami, H., M. Sugi, and A. Kitoh, 2013a: Future changes in tropical cyclone activity in the North Indian Ocean projected by high-resolution MRI-AGCMs. Climate Dyn., 40, 1949−1968, https://doi.org/10.1007/s00382-012-1407-z.
Murakami, H., B. Wang, T. Li, and A. Kitoh, 2013b: Projected increase in tropical cyclones near Hawaii. Nature Climate Change, 3, 749−754, https://doi.org/10.1038/nclimate1890.
Oleson, K. W., and Coauthors, 2008: Improvements to the Community Land Model and their impact on the hydrological cycle. J. Geophys. Res. Biogeosci., 113, https://doi.org/10.1029/2007jg000563.
Oouchi, K., J. Yoshimura, H. Yoshimura, R. Mizuta, S. Kusunoki, and A. Noda, 2006: Tropical cyclone climatology in a global-warming climate as simulated in a 20 km-mesh global atmospheric model: Frequency and wind intensity analyses. J. Meteor. Soc. Japan, 84, 259−276, https://doi.org/10.2151/jmsj.84.259.
Pal, J. S., E. E. Small, and E. A. B. Eltahir, 2000: Simulation of regional-scale water and energy budgets: Representation of subgrid cloud and precipitation processes within RegCM. J. Geophys. Res. Atmos., 105, 29579−29594, https://doi.org/10.1029/2000jd900415.
Pal, J. S., and Coauthors, 2007: Regional climate modeling for the developing world: The ICTP RegCM3 and RegCNET. Bull. Amer. Meteor. Soc., 88, 1395−1410, https://doi.org/10.1175/bams-88-9-1395.
Phan-Van, T., L. Trinh-Tuan, H. Bui-Hoang, and C. Kieu, 2015: Seasonal forecasting of tropical cyclone activity in the coastal region of Vietnam using RegCM4.2. Climate Researc, 62, 115−129, https://doi.org/10.3354/cr01267.
Reed, K. A., and C. Jablonowski, 2011: Assessing the uncertainty in tropical cyclone simulations in NCAR's Community Atmosphere Model. Journal of Advances in Modeling Earth Systems, 3, M08002, https://doi.org/10.1029/2011ms000076.
Reed, K. A., J. T. Bacmeister, N. A. Rosenbloom, M. F. Wehner, S. C. Bates, P. H. Lauritzen, J. E. Truesdale, and C. Hannay, 2015: Impact of the dynamical core on the direct simulation of tropical cyclones in a high-resolution global model. Geophys. Res. Lett., 42, 3603−3608, https://doi.org/10.1002/2015gl063974.
Rotstayn, L. D., and Coauthors, 2010: Improved simulation of Australian climate and ENSO-related rainfall variability in a global climate model with an interactive aerosol treatment. International Journal of Climatology, 30, 1067−1088, https://doi.org/10.1002/joc.1952.
Seneviratne, S. I., and Coauthors, 2012: Changes in climate extremes and their impacts on the natural physical environment. Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC), Field et al., Eds., Cambridge University Press, Cambridge, UK, and New York, NY, USA, 109−230.
Shen, W. Q., J. P. Tang, Y. Wang, S. Y. Wang, and X. R. Niu, 2017: Evaluation of WRF model simulations of tropical cyclones in the western North Pacific over the CORDEX East Asia domain. Climate Dyn., 48, 2419−2435, https://doi.org/10.1007/s00382-016-3213-5.
Stevens, B., and Coauthors, 2013: Atmospheric component of the MPI-M Earth System Model: ECHAM6. Journal of Advances in Modeling Earth Systems, 5, 146−172, https://doi.org/10.1002/jame.20015.
Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485−498, https://doi.org/10.1175/bams-d-11-00094.1.
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.
Vecchi, G. A., and Coauthors, 2019: Tropical cyclone sensitivities to CO2 doubling: Roles of atmospheric resolution, synoptic variability and background climate changes. Clim. Dyn., 53, 5999−6033, https://doi.org/10.1007/s00382-019-04913-y.
Walsh, K. J. E., M. Fiorino, C. W. Landsea, and K. L. McInnes, 2007: Objectively determined resolution-dependent threshold criteria for the detection of tropical cyclones in climate models and reanalyses. J. Climate, 20, 2307−2314, https://doi.org/10.1175/jcli4074.1.
Wang, C. G., J. Liang, and K. I. Hodges, 2017: Projections of tropical cyclones affecting Vietnam under climate change: Downscaled HadGEM2-ES using PRECIS 2.1. Quart. J. Roy. Meteor. Soc., 143, 1844−1859, https://doi.org/10.1002/qj.3046.
Wang, Y. J., S. S. Wen, X. C. Li, F. Thomas, B. D. Su, R. Wang, and T. Jiang, 2016: Spatiotemporal distributions of influential tropical cyclones and associated economic losses in China in 1984-2015. Natural Hazards, 84, 2009−2030, https://doi.org/10.1007/s11069-016-2531-6.
Wu, J., and X. J. Gao, 2020: Present day bias and future change signal of temperature over China in a series of multi-GCM driven RCM simulations. Climate Dyn., 54, 1113−1130, https://doi.org/10.1007/s00382-019-05047-x.
Wu, L., and Coauthors, 2014: Simulations of the present and late-twenty-first-century western North Pacific tropical cyclone activity using a regional model. J. Climate, 27, 3405−3424, https://doi.org/10.1175/jcli-d-12-00830.1.
Wu, L. G., B. Wang, and S. Q. Geng, 2005: Growing typhoon influence on East Asia. Geophys. Res. Lett., 32, L18703, https://doi.org/10.1029/2005gl022937.
Yokoi, S., Y. N. Takayabu, and H. Murakami, 2013: Attribution of projected future changes in tropical cyclone passage frequency over the western North Pacific. J. Climate, 26, 4096−4111, https://doi.org/10.1175/jcli-d-12-00218.1.
Zeng, X. B., and A. Beljaars, 2005: A prognostic scheme of sea surface skin temperature for modeling and data assimilation. Geophys. Res. Lett., 32, L14605, https://doi.org/10.1029/2005GL023030.
Zhang, C. X., and Y. Q. Wang, 2017: Projected future changes of tropical cyclone activity over the western North and South Pacific in a 20-km-mesh regional climate model. J. Climate, 30, 5923−5941, https://doi.org/10.1175/jcli-d-16-0597.1.
Zhang, C. X., and Y. Q. Wang, 2018: Why is the simulated climatology of tropical cyclones so sensitive to the choice of cumulus parameterization scheme in the WRF model? Climate Dyn., 51, 3613−3633, https://doi.org/10.1007/s00382-018-4099-1.
Zhang, Q., L. G. Wu, and Q. G. Liu, 2009: Tropical cyclone damages in China 1983-2006. Bull. Amer. Meteor. Soc., 90, 489−496, https://doi.org/10.1175/2008bams2631.1.
Zhao, M., I. M. Held, S.-J. Lin, and G. A. Vecchi, 2009: Simulations of global hurricane climatology, interannual variability, and response to global warming using a 50-km resolution GCM. J. Climate, 22, 6653−6678, https://doi.org/10.1175/2009jcli3049.1.
Zhao, M., I. M. Held, and S.-J. Lin, 2012: Some counterintuitive dependencies of tropical cyclone frequency on parameters in a GCM. J. Atmos. Sci., 69, 2272−2283, https://doi.org/10.1175/jas-d-11-0238.1.