Effects of Background Synoptic Environment in Controlling South China Sea Tropical Cyclone Intensity and Size Changes in Pseudo–Global Warming Experiments

Tsun Ngai Chow aEarth and Atmospheric Science Program, The Chinese University of Hong Kong, Hong Kong, China

Search for other papers by Tsun Ngai Chow in
Current site
Google Scholar
PubMed
Close
,
Chi Yung Tam aEarth and Atmospheric Science Program, The Chinese University of Hong Kong, Hong Kong, China
bShenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China

Search for other papers by Chi Yung Tam in
Current site
Google Scholar
PubMed
Close
,
Jilong Chen cGuangdong-Hong Kong-Macao Greater Bay Area Weather Research Center for Monitoring Warning and Forecasting (Shenzhen Institute of Meteorological Innovation), Shenzhen, China

Search for other papers by Jilong Chen in
Current site
Google Scholar
PubMed
Close
, and
Chenxi Hu aEarth and Atmospheric Science Program, The Chinese University of Hong Kong, Hong Kong, China

Search for other papers by Chenxi Hu in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Assessing how global warming affects tropical cyclones (TC) is immensely important for climate change adaptation and hazard mitigation. However, projected intensity and size change can vary greatly among different individual storms, even under the same forcing in pseudo–global warming (PGW) experiments. Here we hypothesize that these variations are related to the historical environment in which each TC was embedded. Twenty-five TCs in the South China Sea (SCS) region were simulated using the Weather Research and Forecasting (WRF) Model. Their changes in the near (2036–65) and far future (2075–99) following the representative concentration pathways 8.5 (RCP8.5) and 4.5 (RCP4.5) under phase 5 of the Coupled Model Intercomparison Project (CMIP5) were investigated by the PGW technique. The mean changes in TC intensity and gale-force wind radius (R17) in the SCS were +6.4% and +1.5% for a 2°C warming, respectively. Multiple linear regression and stepwise regression analysis revealed that storm intensity variations were positively correlated with historical sea surface temperature and negatively with outer (i.e., outside the TC’s R17) atmospheric instability, while the R17 variations correlated positively with outer midtropospheric relative humidity (RH) and surface outer wind speed (OWS). Ertel potential vorticity (EPV) diagnostics further showed a moister SCS background can cause stronger diabatic heating and EPV production at the spiral rainbands under PGW, which increases R17. Additionally, stronger background absolute angular momentum (AAM) promoted stronger AAM influx, leading to larger R17. Implications were drawn to explain the uncertainties in projected TC intensity and size due to natural variability.

Significance Statement

Changes in the intensity and size of individual tropical cyclones in future climates are highly variable. This study aims to understand the environmental factors influencing these variations. We selected 25 storms that entered the South China Sea region and modeled them in both present and future climates. The mean intensity and size were projected to increase by 6.4% and 1.5% for a 2°C warming, respectively. We found that tropical cyclones embedded in historically warmer oceans and more stable atmospheres intensified more than the others, while historically wetter and windier environments promoted larger size growth. Our results suggest that certain tropical cyclones can exhibit a greater increase in intensity and size in a warmer climate under favorable environmental conditions.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Francis Tam, francis.tam@cuhk.edu.hk

Abstract

Assessing how global warming affects tropical cyclones (TC) is immensely important for climate change adaptation and hazard mitigation. However, projected intensity and size change can vary greatly among different individual storms, even under the same forcing in pseudo–global warming (PGW) experiments. Here we hypothesize that these variations are related to the historical environment in which each TC was embedded. Twenty-five TCs in the South China Sea (SCS) region were simulated using the Weather Research and Forecasting (WRF) Model. Their changes in the near (2036–65) and far future (2075–99) following the representative concentration pathways 8.5 (RCP8.5) and 4.5 (RCP4.5) under phase 5 of the Coupled Model Intercomparison Project (CMIP5) were investigated by the PGW technique. The mean changes in TC intensity and gale-force wind radius (R17) in the SCS were +6.4% and +1.5% for a 2°C warming, respectively. Multiple linear regression and stepwise regression analysis revealed that storm intensity variations were positively correlated with historical sea surface temperature and negatively with outer (i.e., outside the TC’s R17) atmospheric instability, while the R17 variations correlated positively with outer midtropospheric relative humidity (RH) and surface outer wind speed (OWS). Ertel potential vorticity (EPV) diagnostics further showed a moister SCS background can cause stronger diabatic heating and EPV production at the spiral rainbands under PGW, which increases R17. Additionally, stronger background absolute angular momentum (AAM) promoted stronger AAM influx, leading to larger R17. Implications were drawn to explain the uncertainties in projected TC intensity and size due to natural variability.

Significance Statement

Changes in the intensity and size of individual tropical cyclones in future climates are highly variable. This study aims to understand the environmental factors influencing these variations. We selected 25 storms that entered the South China Sea region and modeled them in both present and future climates. The mean intensity and size were projected to increase by 6.4% and 1.5% for a 2°C warming, respectively. We found that tropical cyclones embedded in historically warmer oceans and more stable atmospheres intensified more than the others, while historically wetter and windier environments promoted larger size growth. Our results suggest that certain tropical cyclones can exhibit a greater increase in intensity and size in a warmer climate under favorable environmental conditions.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Francis Tam, francis.tam@cuhk.edu.hk

Supplementary Materials

    • Supplemental Materials (PDF 6.1318 MB)
Save
  • Bister, M., and K. A. Emanuel, 1998: Dissipative heating and hurricane intensity. Meteor. Atmos. Phys., 65, 233240, https://doi.org/10.1007/BF01030791.

    • Search Google Scholar
    • Export Citation
  • Camargo, S. J., and A. H. Sobel, 2005: Western North Pacific tropical cyclone intensity and ENSO. J. Climate, 18, 29963006, https://doi.org/10.1175/JCLI3457.1.

    • Search Google Scholar
    • Export Citation
  • Camargo, S. J., and A. A. Wing, 2016: Tropical cyclones in climate models. Wiley Interdiscip. Rev.: Climate Change, 7, 211237, https://doi.org/10.1002/wcc.373.

    • Search Google Scholar
    • Export Citation
  • Chan, K. T. F., and J. C. L. Chan, 2013: Angular momentum transports and synoptic flow patterns associated with tropical cyclone size change. Mon. Wea. Rev., 141, 39854007, https://doi.org/10.1175/MWR-D-12-00204.1.

    • Search Google Scholar
    • Export Citation
  • Chan, K. T. F., and J. C. L. Chan, 2014: Impacts of initial vortex size and planetary vorticity on tropical cyclone size. Quart. J. Roy. Meteor. Soc., 140, 22352248, https://doi.org/10.1002/qj.2292.

    • Search Google Scholar
    • Export Citation
  • Chan, K. T. F., and J. C. L. Chan, 2015: Impacts of vortex intensity and outer winds on tropical cyclone size. Quart. J. Roy. Meteor. Soc., 141, 525537, https://doi.org/10.1002/qj.2374.

    • Search Google Scholar
    • Export Citation
  • Chen, J., Z. Wang, C. Y. Tam, N. C. Lau, D. S. D. Lau, and H. Y. Mok, 2020: Impacts of climate change on tropical cyclones and induced storm surges in the Pearl River Delta region using pseudo-global-warming method. Sci. Rep., 10, 1965, https://doi.org/10.1038/s41598-020-58824-8.

    • Search Google Scholar
    • Export Citation
  • Chen, J., C. Y. Tam, Z. Wang, K. Cheung, Y. Li, N. C. Lau, and D. S. D. Lau, 2022: Future thermodynamic impacts of global warming on landfalling typhoons and their induced storm surges to the Pearl River Delta region as inferred from high-resolution regional models. J. Climate, 35, 49054926, https://doi.org/10.1175/JCLI-D-21-0436.1.

    • Search Google Scholar
    • Export Citation
  • C3S, 2018a: CMIP5 monthly data on pressure levels. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), accessed 15 June 2023, https://doi.org/10.24381/cds.3b4b5bc9.

  • C3S, 2018b: CMIP5 monthly data on single levels. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), accessed 15 June 2023, https://doi.org/10.24381/cds.9d44a987.

  • Del Genio, A. D., 2012: Representing the sensitivity of convective cloud systems to tropospheric humidity in general circulation models. Surv. Geophys., 33, 637656, https://doi.org/10.1007/s10712-011-9148-9.

    • Search Google Scholar
    • Export Citation
  • Derbyshire, S. H., I. Beau, P. Bechtold, J. Y. Grandpeix, J. M. Piriou, J. L. Redelsperger, and P. M. M. Soares, 2004: Sensitivity of moist convection to environmental humidity. Quart. J. Roy. Meteor. Soc., 130, 30553079, https://doi.org/10.1256/qj.03.130.

    • Search Google Scholar
    • Export Citation
  • Dudhia, J., 1989: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, 30773107, https://doi.org/10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • ECMWF, 2014: ERA-20C Project (ECMWF Atmospheric Reanalysis of the 20th Century). Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, accessed 15 June 2023, https://doi.org/10.5065/D6VQ30QG.

  • Emanuel, K., 2000: A statistical analysis of tropical cyclone intensity. Mon. Wea. Rev., 128, 11391152, https://doi.org/10.1175/1520-0493(2000)128<1139:ASAOTC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Evans, J. L., 1993: Sensitivity of tropical cyclone intensity to sea surface temperature. J. Climate, 6, 11331140, https://doi.org/10.1175/1520-0442(1993)006<1133:SOTCIT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Frank, W. M., and E. A. Ritchie, 2001: Effects of vertical wind shear on the intensity and structure of numerically simulated hurricanes. Mon. Wea. Rev., 129, 22492269, https://doi.org/10.1175/1520-0493(2001)129<2249:EOVWSO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Gentry, M. S., and G. M. Lackmann, 2010: Sensitivity of simulated tropical cyclone structure and intensity to horizontal resolution. Mon. Wea. Rev., 138, 688704, https://doi.org/10.1175/2009MWR2976.1.

    • Search Google Scholar
    • Export Citation
  • Gutmann, E. D., and Coauthors, 2018: Changes in hurricanes from a 13-yr convection-permitting pseudo–global warming simulation. J. Climate, 31, 36433657, https://doi.org/10.1175/JCLI-D-17-0391.1.

    • Search Google Scholar
    • Export Citation
  • Hersbach, H., and Coauthors, 2023a: ERA5 hourly data on pressure levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), accessed 15 June 2023, https://doi.org/10.24381/cds.bd0915c6.

  • Hersbach, H., and Coauthors, 2023b: ERA5 hourly data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), accessed 15 June 2023, https://doi.org/10.24381/cds.adbb2d47.

  • Hill, K. A., and G. M. Lackmann, 2009a: Analysis of idealized tropical cyclone simulations using the Weather Research and Forecasting model: Sensitivity to turbulence parameterization and grid spacing. Mon. Wea. Rev., 137, 745765, https://doi.org/10.1175/2008MWR2220.1.

    • Search Google Scholar
    • Export Citation
  • Hill, K. A., and G. M. Lackmann, 2009b: Influence of environmental humidity on tropical cyclone size. Mon. Wea. Rev., 137, 32943315, https://doi.org/10.1175/2009MWR2679.1.

    • Search Google Scholar
    • Export Citation
  • Holland, G. J., 1983: Tropical cyclone motion: Environmental interaction plus a beta effect. J. Atmos. Sci., 40, 328342, https://doi.org/10.1175/1520-0469(1983)040<0328:TCMEIP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Holland, G. J., and R. T. Merrill, 1984: On the dynamics of tropical cyclone structural changes. Quart. J. Roy. Meteor. Soc., 110, 723745, https://doi.org/10.1002/qj.49711046510.

    • Search Google Scholar
    • Export Citation
  • 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, 23182341, https://doi.org/10.1175/MWR3199.1.

    • Search Google Scholar
    • Export Citation
  • Jiménez, P. A., J. Dudhia, J. F. González-Rouco, J. Navarro, J. P. Montávez, and E. García-Bustamante, 2012: A revised scheme for the WRF surface layer formulation. Mon. Wea. Rev., 140, 898918, https://doi.org/10.1175/MWR-D-11-00056.1.

    • Search Google Scholar
    • Export Citation
  • Kain, J. S., 2004: The Kain–Fritsch convective parameterization: An update. J. Appl. Meteor. Climatol., 43, 170181, https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kim, H. S., G. A. Vecchi, T. R. Knutson, W. G. Anderson, T. L. Delworth, A. Rosati, F. Zeng, and M. Zhao, 2014: Tropical cyclone simulation and response to CO2 doubling in the GFDL CM2.5 high-resolution coupled climate model. J. Climate, 27, 80348054, https://doi.org/10.1175/JCLI-D-13-00475.1.

    • Search Google Scholar
    • Export Citation
  • 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, 363376, https://doi.org/10.1175/2009BAMS2755.1.

    • Search Google Scholar
    • Export Citation
  • Knapp, K. R., H. J. Diamond, J. P. Kossin, M. C. Kruk, and C. J. Schreck, 2018: International Best Track Archive for Climate Stewardship (IBTrACS) Project, version 4. WP. NOAA National Centers for Environmental Information, accessed 15 June 2023, https://doi.org/10.25921/82ty-9e16.

  • Knutson, T. R., and Coauthors, 2013: Dynamical downscaling projections of twenty-first-century Atlantic hurricane activity: CMIP3 and CMIP5 model-based scenarios. J. Climate, 26, 65916617, https://doi.org/10.1175/JCLI-D-12-00539.1.

    • Search Google Scholar
    • Export Citation
  • Knutson, T. R., J. J. Sirutis, M. Zhao, R. E. Tuleya, M. Bender, G. A. Vecchi, G. Villarini, and D. Chavas, 2015: Global projections of intense tropical cyclone activity for the late twenty-first century from dynamical downscaling of CMIP5/RCP4.5 scenarios. J. Climate, 28, 72037224, https://doi.org/10.1175/JCLI-D-15-0129.1.

    • Search Google Scholar
    • Export Citation
  • Knutson, T. R., and Coauthors, 2020: Tropical cyclones and climate change assessment: Part II: Projected response to anthropogenic warming. Bull. Amer. Meteor. Soc., 101, E303E322, https://doi.org/10.1175/BAMS-D-18-0194.1.

    • Search Google Scholar
    • Export Citation
  • Lackmann, G. M., 2002: Cold-frontal potential vorticity maxima, the low-level jet, and moisture transport in extratropical cyclones. Mon. Wea. Rev., 130, 5974, https://doi.org/10.1175/1520-0493(2002)130<0059:CFPVMT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Lavers, D. A., A. Simmons, F. Vamborg, and M. J. Rodwell, 2022: An evaluation of ERA5 precipitation for climate monitoring. Quart. J. Roy. Meteor. Soc., 148, 31523165, https://doi.org/10.1002/qj.4351.

    • Search Google Scholar
    • Export Citation
  • Leroux, M. D., and Coauthors, 2018: Recent advances in research and forecasting of tropical cyclone track, intensity, and structure at landfall. Trop. Cyclone Res. Rev., 7, 85105, https://doi.org/10.6057/2018TCRR02.02.

    • Search Google Scholar
    • Export Citation
  • Li, H., and R. L. Sriver, 2018: Tropical cyclone activity in the high‐resolution Community Earth System Model and the impact of ocean coupling. J. Adv. Model. Earth Syst., 10, 165186, https://doi.org/10.1002/2017MS001199.

    • Search Google Scholar
    • Export Citation
  • Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated‐k model for the longwave. J. Geophys. Res., 102, 16 66316 682, https://doi.org/10.1029/97JD00237.

    • Search Google Scholar
    • Export Citation
  • Montgomery, M. T., and R. K. Smith, 2014: Paradigms for tropical cyclone intensification. Aust. Meteor. Oceanogr. J., 64, 3766, https://doi.org/10.22499/2.6401.005.

    • Search Google Scholar
    • Export Citation
  • Muller, C. J., P. A. O’Gorman, and L. E. Back, 2011: Intensification of precipitation extremes with warming in a cloud-resolving model. J. Climate, 24, 27842800, https://doi.org/10.1175/2011JCLI3876.1.

    • Search Google Scholar
    • Export Citation
  • Persing, J., M. T. Montgomery, J. C. McWilliams, and R. K. Smith, 2013: Asymmetric and axisymmetric dynamics of tropical cyclones. Atmos. Chem. Phys., 13, 12 29912 341, https://doi.org/10.5194/acp-13-12299-2013.

    • Search Google Scholar
    • Export Citation
  • Poli, P., and Coauthors, 2016: ERA-20C: An atmospheric reanalysis of the twentieth century. J. Climate, 29, 40834097, https://doi.org/10.1175/JCLI-D-15-0556.1.

    • Search Google Scholar
    • Export Citation
  • Ramsay, H. A., and A. H. Sobel, 2011: Effects of relative and absolute sea surface temperature on tropical cyclone potential intensity using a single-column model. J. Climate, 24, 183193, https://doi.org/10.1175/2010JCLI3690.1.

    • Search Google Scholar
    • Export Citation
  • 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, 36033608, https://doi.org/10.1002/2015GL063974.

    • Search Google Scholar
    • Export Citation
  • Roberts, M. J., and Coauthors, 2020: Impact of model resolution on tropical cyclone simulation using the HighResMIP–PRIMAVERA multimodel ensemble. J. Climate, 33, 25572583, https://doi.org/10.1175/JCLI-D-19-0639.1.

    • Search Google Scholar
    • Export Citation
  • Rogers, E., T. Black, B. Ferrier, Y. Lin, D. Parrish, and G. DiMego, 2001: National oceanic and atmospheric administration changes to the NCEP Meso eta analysis and forecast system: Increase in resolution, new cloud microphysics, modified precipitation assimilation, modified 3DVAR analysis. NWS Tech. Proc. Bull. 488, 15 pp.

  • Rotunno, R., and K. A. Emanuel, 1987: An air–sea interaction theory for tropical cyclones. Part II: Evolutionary study using a nonhydrostatic axisymmetric numerical model. J. Atmos. Sci., 44, 542561, https://doi.org/10.1175/1520-0469(1987)044<0542:AAITFT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Schenkel, B. A., D. Chavas, N. Lin, T. Knutson, G. Vecchi, and A. Brammer, 2023: North Atlantic tropical cyclone outer size and structure remain unchanged by the late twenty-first century. J. Climate, 36, 359382, https://doi.org/10.1175/JCLI-D-22-0066.1.

    • Search Google Scholar
    • Export Citation
  • Seeley, J. T., and D. M. Romps, 2015: Why does tropical convective available potential energy (CAPE) increase with warming? Geophys. Res. Lett., 42, 10  42910 437, https://doi.org/10.1002/2015GL066199.

    • Search Google Scholar
    • Export Citation
  • Shapiro, L. J., and H. E. Willoughby, 1982: The response of balanced hurricanes to local sources of heat and momentum. J. Atmos. Sci., 39, 378394, https://doi.org/10.1175/1520-0469(1982)039<0378:TROBHT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Singh, M. S., and P. A. O’Gorman, 2013: Influence of entrainment on the thermal stratification in simulations of radiative‐convective equilibrium. Geophys. Res. Lett., 40, 43984403, https://doi.org/10.1002/grl.50796.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., and Coauthors, 2008: A description of the Advanced Research WRF version 3. NCAR Tech. Note NCAR/TN-475+STR, 113 pp., https://doi.org/10.5065/D68S4MVH.

  • Srinivas, D., and D. V. Bhaskar Rao, 2014: Implications of vortex initialization and model spin-up in tropical cyclone prediction using Advanced Research Weather Research and forecasting model. Nat. Hazards, 73, 10431062, https://doi.org/10.1007/s11069-014-1125-4.

    • Search Google Scholar
    • Export Citation
  • Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485498, https://doi.org/10.1175/BAMS-D-11-00094.1.

    • Search Google Scholar
    • Export Citation
  • Tewari, M., and Coauthors, 2004: Implementation and verification of the unified NOAH land surface model in the WRF Model. 20th Conf. on Weather Analysis and Forecasting/16th Conf. on Numerical Weather Prediction, Seattle, WA, Amer. Meteor. Soc., 14.2a, https://ams.confex.com/ams/pdfpapers/69061.pdf.

  • Tuleya, R. E., M. Bender, T. R. Knutson, J. J. Sirutis, B. Thomas, and I. Ginis, 2016: Impact of upper-tropospheric temperature anomalies and vertical wind shear on tropical cyclone evolution using an idealized version of the operational GFDL hurricane model. J. Atmos. Sci., 73, 38033820, https://doi.org/10.1175/JAS-D-16-0045.1.

    • Search Google Scholar
    • Export Citation
  • Wang, S., and R. Toumi, 2018: Reduced sensitivity of tropical cyclone intensity and size to sea surface temperature in a radiative-convective equilibrium environment. Adv. Atmos. Sci., 35, 981993, https://doi.org/10.1007/s00376-018-7277-5.

    • Search Google Scholar
    • Export Citation
  • Wang, S., and R. Toumi, 2019: Impact of dry midlevel air on the tropical cyclone outer circulation. J. Atmos. Sci., 76, 18091826, https://doi.org/10.1175/JAS-D-18-0302.1.

    • Search Google Scholar
    • Export Citation
  • Wang, Y., 2009: How do outer spiral rainbands affect tropical cyclone structure and intensity? J. Atmos. Sci., 66, 12501273, https://doi.org/10.1175/2008JAS2737.1.

    • Search Google Scholar
    • Export Citation
  • Weatherford, C. L., and W. M. Gray, 1988: Typhoon structure as revealed by aircraft reconnaissance. Part II: Structural variability. Mon. Wea. Rev., 116, 10441056, https://doi.org/10.1175/1520-0493(1988)116<1044:TSARBA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wilks, D. S., 2011: Statistical Methods in the Atmospheric Sciences. Academic Press, 657 pp.

  • Wu, L., and Coauthors, 2012: Relationship of environmental relative humidity with North Atlantic tropical cyclone intensity and intensification rate. Geophys. Res. Lett., 39, L20809, https://doi.org/10.1029/2012GL053546.

    • Search Google Scholar
    • Export Citation
  • Yamada, Y., M. Satoh, M. Sugi, C. Kodama, A. T. Noda, M. Nakano, and T. Nasuno, 2017: Response of tropical cyclone activity and structure to global warming in a high-resolution global nonhydrostatic model. J. Climate, 30, 97039724, https://doi.org/10.1175/JCLI-D-17-0068.1.

    • Search Google Scholar
    • Export Citation
  • Ying, Y., and Q. Zhang, 2012: A modeling study on tropical cyclone structural changes in response to ambient moisture variations. J. Meteor. Soc. Japan, 90, 755770, https://doi.org/10.2151/jmsj.2012-512.

    • Search Google Scholar
    • Export Citation
  • Zeng, Z., Y. Wang, and C.-C. Wu, 2007: Environmental dynamical control of tropical cyclone intensity—An observational study. Mon. Wea. Rev., 135, 3859, https://doi.org/10.1175/MWR3278.1.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 767 767 33
Full Text Views 174 174 11
PDF Downloads 206 206 16