Role of the Convection Scheme in Modeling Initiation and Intensification of Tropical Depressions over the North Atlantic

J.-P. Duvel Laboratoire de Météorologie Dynamique, CNRS, École Normale Supérieure, Paris, France

Search for other papers by J.-P. Duvel in
Current site
Google Scholar
PubMed
Close
,
S. J. Camargo Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York

Search for other papers by S. J. Camargo in
Current site
Google Scholar
PubMed
Close
, and
A. H. Sobel Lamont-Doherty Earth Observatory, Palisades, and Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York

Search for other papers by A. H. Sobel in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

The authors analyze how modifications of the convective scheme modify the initiation of tropical depression vortices (TDVs) and their intensification into stronger warm-cored tropical cyclone–like vortices (TCs) in global climate model (GCM) simulations. The model’s original convection scheme has entrainment and cloud-base mass flux closures based on moisture convergence. Two modifications are considered: one in which entrainment is dependent on relative humidity and another in which the closure is based on the convective available potential energy (CAPE).

Compared to reanalysis, TDVs are more numerous and intense in all three simulations, probably as a result of excessive parameterized deep convection at the expense of convection detraining at midlevel. The relative humidity–dependent entrainment rate increases both TDV initiation and intensification relative to the control. This is because this entrainment rate is reduced in the moist center of the TDVs, giving more intense convective precipitation, and also because it generates a moister environment that may favor the development of early stage TDVs. The CAPE closure inhibits the parameterized convection in strong TDVs, thus limiting their development despite a slight increase in the resolved convection. However, the maximum intensity reached by TC-like TDVs is similar in the three simulations, showing the statistical character of these tendencies.

The simulated TCs develop from TDVs with different dynamical origins than those observed. For instance, too many TDVs and TCs initiate near or over southern West Africa in the GCM, collocated with the maximum in easterly wave activity, whose characteristics are also dependent on the convection scheme considered.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: J.-P. Duvel, jpduvel@lmd.ens.fr

Abstract

The authors analyze how modifications of the convective scheme modify the initiation of tropical depression vortices (TDVs) and their intensification into stronger warm-cored tropical cyclone–like vortices (TCs) in global climate model (GCM) simulations. The model’s original convection scheme has entrainment and cloud-base mass flux closures based on moisture convergence. Two modifications are considered: one in which entrainment is dependent on relative humidity and another in which the closure is based on the convective available potential energy (CAPE).

Compared to reanalysis, TDVs are more numerous and intense in all three simulations, probably as a result of excessive parameterized deep convection at the expense of convection detraining at midlevel. The relative humidity–dependent entrainment rate increases both TDV initiation and intensification relative to the control. This is because this entrainment rate is reduced in the moist center of the TDVs, giving more intense convective precipitation, and also because it generates a moister environment that may favor the development of early stage TDVs. The CAPE closure inhibits the parameterized convection in strong TDVs, thus limiting their development despite a slight increase in the resolved convection. However, the maximum intensity reached by TC-like TDVs is similar in the three simulations, showing the statistical character of these tendencies.

The simulated TCs develop from TDVs with different dynamical origins than those observed. For instance, too many TDVs and TCs initiate near or over southern West Africa in the GCM, collocated with the maximum in easterly wave activity, whose characteristics are also dependent on the convection scheme considered.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: J.-P. Duvel, jpduvel@lmd.ens.fr
Save
  • Bechtold, P., M. Köhler, T. Jung, F. Doblas-Reyes, M. Leutbecher, M. Rodwell, F. Vitart, and G. Balsamo, 2008: Advances in simulating atmospheric variability with the ECMWF model: From synoptic to decadal time-scales. Quart. J. Roy. Meteor. Soc., 134, 13371351, doi:10.1002/qj.289.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bechtold, P., N. Semane, P. Lopez, J. P. Chaboureau, A. Beljaars, and N. Bormann, 2014: Representing equilibrium and nonequilibrium convection in large-scale models. J. Atmos. Sci., 71, 734753, doi:10.1175/JAS-D-13-0163.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bell, G. D., and Coauthors, 2000: Climate assessment for 1999. Bull. Amer. Meteor. Soc., 81, S1S50, doi:10.1175/1520-0477(2000)81[s1:CAF]2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Burpee, R. W., 1972: The origin and structure of easterly waves in the lower troposphere of North Africa. J. Atmos. Sci., 29, 7790, doi:10.1175/1520-0469(1972)029<0077:TOASOE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Burpee, R. W., 1975: Some features of synoptic-scale waves based on a compositing analysis of GATE data. Mon. Wea. Rev., 103, 921925, doi:10.1175/1520-0493(1975)103<0921:SFOSWB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Camargo, S. J., 2013: Global and regional aspects of tropical cyclone activity in the CMIP5 models. J. Climate, 26, 98809902, doi:10.1175/JCLI-D-12-00549.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Camargo, S. J., and S. E. Zebiak, 2002: Improving the detection and tracking of tropical cyclones in atmospheric general circulation models. Wea. Forecasting, 17, 11521162, doi:10.1175/1520-0434(2002)017<1152:ITDATO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Camargo, S. J., and A. H. Sobel, 2004: Formation of tropical storms in an atmospheric general circulation model. Tellus, 56A, 5667, doi:10.1111/j.1600-0870.2004.00033.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Camargo, S. J., and A. G. Barnston, 2009: Experimental seasonal dynamical forecasts of tropical cyclone activity at IRI. Wea. Forecasting, 24, 472491, doi:10.1175/2008WAF2007099.1.

    • Crossref
    • 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, doi:10.1002/wcc.373.

    • Search Google Scholar
    • Export Citation
  • Camargo, S. J., A. G. Barnston, and S. E. Zebiak, 2005: A statistical assessment of tropical cyclone activity in atmospheric general circulation models. Tellus, 57A, 589604, doi:10.1111/j.1600-0870.2005.00117.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Camargo, S. J., H. Li, and L. Sun, 2007a: Feasibility study for downscaling seasonal tropical cyclone activity using the NCEP regional spectral model. Int. J. Climatol., 27, 311325, doi:10.1002/joc.1400.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Camargo, S. J., A. H. Sobel, A. Barnston, and K. A. Emanuel, 2007b: Tropical cyclone genesis potential in climate models. Tellus, 59A, 428443, doi:10.1111/j.1600-0870.2007.00238.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Carlson, T. N., 1969: Synoptic histories of three African disturbances that developed into Atlantic hurricanes. Mon. Wea. Rev., 97, 256276, doi:10.1175/1520-0493(1969)097<0256:SHOTAD>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Caron, L. P., and C. Jones, 2012: Understanding and simulating the link between African easterly waves and Atlantic tropical cyclones using a regional climate model: The role of domain size and lateral boundary conditions. Climate Dyn., 39, 113135, doi:10.1007/s00382-011-1160-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Daloz, A. S., F. Chauvin, K. Walsh, S. Lavender, D. Abbs, and F. Roux, 2012: The ability of general circulation models to simulate tropical cyclones and their precursors over the North Atlantic main development region. Climate Dyn., 39, 15591576, doi:10.1007/s00382-012-1290-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davis, C., C. Snyder, and A. C. Didlake Jr., 2008: A vortex-based perspective of eastern Pacific tropical cyclone formation. Mon. Wea. Rev., 136, 24612477, doi:10.1175/2007MWR2317.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, doi:10.1002/qj.828.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dunkerton, T. J., M. T. Montgomery, and Z. Wang, 2009: Tropical cyclogenesis in a tropical wave critical layer: Easterly waves. Atmos. Chem. Phys., 9, 55875646, doi:10.5194/acp-9-5587-2009.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Duvel, J.-P., 2015: Initiation and intensification of tropical depressions over the southern Indian Ocean: Influence of the MJO. Mon. Wea. Rev., 143, 21702191, doi:10.1175/MWR-D-14-00318.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Duvel, J.-P., and J. Vialard, 2007: Indo-Pacific sea surface temperature perturbations associated with intraseasonal oscillations of the tropical convection. J. Climate, 20, 30563082, doi:10.1175/JCLI4144.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 1991: A scheme for representing cumulus convection in large-scale models. J. Atmos. Sci., 48, 23132329, doi:10.1175/1520-0469(1991)048<2313:ASFRCC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Goulet, L., and J.-P. Duvel, 2000: A new approach to detect and characterize intermittent atmospheric oscillations: Application on the intraseasonal oscillation. J. Atmos. Sci., 57, 23972416, doi:10.1175/1520-0469(2000)057<2397:ANATDA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 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, 98579872, doi:10.1175/JCLI-D-15-0255.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hourdin, F., and Coauthors, 2006: The LMDZ4 general circulation model: Climate performance and sensitivity to parametrized physics with emphasis on tropical convection. Climate Dyn., 27, 787813, doi:10.1007/s00382-006-0158-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kim, D., and Coauthors, 2012: The tropical subseasonal variability simulated in the NASA GISS general circulation model. J. Climate, 25, 46414659, doi:10.1175/JCLI-D-11-00447.1.

    • Crossref
    • 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, doi:10.1175/2009BAMS2755.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Landman, W. A., A. Seth, and S. J. Camargo, 2005: The effect of regional climate model domain choice on the simulation of tropical cyclone–like vortices in the southwestern Indian Ocean. J. Climate, 18, 12631274, doi:10.1175/JCLI3324.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Landsea, C. W., 1993: A climatology of intense (or major) Atlantic hurricanes. Mon. Wea. Rev., 121, 17031713, doi:10.1175/1520-0493(1993)121<1703:ACOIMA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liebmann, B., H. H. Hendon, and J. D. Glick, 1994: The relationship between tropical cyclones of the western Pacific and Indian Oceans and the Madden–Julian oscillation. J. Meteor. Soc. Japan, 72, 401411.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Martin, E. R., and C. Thorncroft, 2015: Representation of African easterly waves in CMIP5 models. J. Climate, 28, 77027715, doi:10.1175/JCLI-D-15-0145.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Maue, R. N., 2009: Northern Hemisphere tropical cyclone activity. Geophys. Res. Lett., 36, L05805, doi:10.1029/2008GL035946.

  • Mozer, J. B., and J. A. Zehnder, 1996: Lee vorticity production by large-scale tropical mountain ranges. Part I: Eastern North Pacific tropical cyclogenesis. J. Atmos. Sci., 53, 521538, doi:10.1175/1520-0469(1996)053<0521:LVPBLS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Murakami, H., and Coauthors, 2012a: Future changes in tropical cyclone activity projected by the new high-resolution MRI-AGCM. J. Climate, 25, 32373260, doi:10.1175/JCLI-D-11-00415.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Murakami, H., R. Mizuta, and E. Shindo, 2012b: Future changes in tropical cyclone activity project by multi-physics and multi-SST ensemble experiments using 60-km-mesh MRI-AGCM. Climate Dyn., 39, 25692584, doi:10.1007/s00382-011-1223-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reed, K. A., and C. Jablownowski, 2011: Impact of physical parametrization on idealized tropical cyclones in the Community Atmosphere Model. Geophys. Res. Lett., 38, L048045, doi:10.1029/2010GL046297.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reed, R., D. Norquist, and E. Recker, 1977: The structure and properties of African wave disturbances as observed during Phase III of GATE12. Mon. Wea. Rev., 105, 317333, doi:10.1175/1520-0493(1977)105<0317:TSAPOA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roberts, M., and Coauthors, 2015: Tropical cyclones in the UPSCALE ensemble of high-resolution global climate models. J. Climate, 28, 57459, doi:10.1175/JCLI-D-14-00131.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shaevitz, D. A., and Coauthors, 2014: Characteristics of tropical cyclones in high-resolution models of the present climate. J. Adv. Model. Earth Syst., 6, 11541172, doi:10.1002/2014MS000372.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, R. B., 1993: A hurricane beta-drift law. J. Atmos. Sci., 50, 32133215, doi:10.1175/1520-0469(1993)050<3213:AHBDL>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stan, C., 2012: Is cumulus convection the concertmaster of tropical cyclone activity in the Atlantic? Geophys. Res. Lett., 39, L19716, doi:10.1029/2012GL053449.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tiedtke, M., 1989: A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon. Wea. Rev., 117, 17791800, doi:10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vitart, F., J. L. Anderson, J. Sirutis, and R. E. Tuleya, 2001: Sensitivity of tropical storms simulated by a general circulation model to changes in cumulus parametrization. Quart. J. Roy. Meteor. Soc., 127, 2551, doi:10.1002/qj.49712757103.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Walsh, K. J. E., and Coauthors, 2016: Tropical cyclones and climate change. Wiley Interdiscip. Rev.: Climate Change, 7, 6589, doi:10.1002/wcc.371.

    • Search Google Scholar
    • Export Citation
  • Yang, H., Z. Jiang, and L. Li, 2016: Biases and improvements in three dynamical downscaling climate simulations over China. Climate Dyn., 47, 32353251, doi:10.1007/s00382-016-3023-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 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, 22722283, doi:10.1175/JAS-D-11-0238.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1699 1439 71
PDF Downloads 222 39 5