Life Cycle–Resolved Observation of Radiative Properties of Mesoscale Convective Systems

Dominique Bouniol aCNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France

Search for other papers by Dominique Bouniol in
Current site
Google Scholar
PubMed
Close
,
Rémy Roca bLaboratoire d’Études en Géophysique et Océanographie Spatiales, Université de Toulouse III, CNRS, CNES, IRD, Toulouse, France

Search for other papers by Rémy Roca in
Current site
Google Scholar
PubMed
Close
,
Thomas Fiolleau bLaboratoire d’Études en Géophysique et Océanographie Spatiales, Université de Toulouse III, CNRS, CNES, IRD, Toulouse, France

Search for other papers by Thomas Fiolleau in
Current site
Google Scholar
PubMed
Close
, and
Patrick Raberanto cLaboratoire de Météorologie Dynamique, Palaiseau, France

Search for other papers by Patrick Raberanto in
Current site
Google Scholar
PubMed
Close
Restricted access

We are aware of a technical issue preventing figures and tables from showing in some newly published articles in the full-text HTML view.
While we are resolving the problem, please use the online PDF version of these articles to view figures and tables.

Abstract

The evolution of radiative properties [outgoing longwave radiation (OLR) and albedo at the top of the atmosphere] over a mesoscale convective system (MCS) life cycle is assessed using five years of Scanner for Radiation Budget (ScaRaB) radiometer on board the Megha-Tropiques satellite merged with geostationary infrared images. The MCS life cycle is documented using a tracking algorithm. A composite approach is then implemented to document the evolution of radiative properties at each life stage at the scale of the tropical belt, in continental and oceanic regions and in specific regions. Independently of the considered region, the composites share similarities with a unique maximum in albedo and a unique minimum in OLR, values of which differ depending on the environment as well as the amplitude of both parameters over the life cycle. The unique precessing orbit of the Megha-Tropiques satellite allows a consideration of the albedo as a function of the local time of observation showing that the magnitude of the albedo signal is mainly controlled by the solar zenithal angle. Sensitivity tests make possible the quantification of the impact of an error in radiative properties showing that even small errors lead to substantial increment on the instantaneous cloud radiative effect. All together, these elements point toward the subtle balance between life cycle, cloud radiative properties, and phasing within the diurnal cycle to build the atmospheric radiative budget in oceanic or continental regions.

© 2021 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: Dominique Bouniol, dominique.bouniol@meteo.fr

Abstract

The evolution of radiative properties [outgoing longwave radiation (OLR) and albedo at the top of the atmosphere] over a mesoscale convective system (MCS) life cycle is assessed using five years of Scanner for Radiation Budget (ScaRaB) radiometer on board the Megha-Tropiques satellite merged with geostationary infrared images. The MCS life cycle is documented using a tracking algorithm. A composite approach is then implemented to document the evolution of radiative properties at each life stage at the scale of the tropical belt, in continental and oceanic regions and in specific regions. Independently of the considered region, the composites share similarities with a unique maximum in albedo and a unique minimum in OLR, values of which differ depending on the environment as well as the amplitude of both parameters over the life cycle. The unique precessing orbit of the Megha-Tropiques satellite allows a consideration of the albedo as a function of the local time of observation showing that the magnitude of the albedo signal is mainly controlled by the solar zenithal angle. Sensitivity tests make possible the quantification of the impact of an error in radiative properties showing that even small errors lead to substantial increment on the instantaneous cloud radiative effect. All together, these elements point toward the subtle balance between life cycle, cloud radiative properties, and phasing within the diurnal cycle to build the atmospheric radiative budget in oceanic or continental regions.

© 2021 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: Dominique Bouniol, dominique.bouniol@meteo.fr
Save
  • Bony, S., and Coauthors, 2015: Clouds, circulation and climate sensitivity. Nat. Geosci., 8, 261268, https://doi.org/10.1038/ngeo2398.

  • Bony, S., B. Stevens, D. Coppin, T. Becker, K. A. Reed, A. Voigt, and B. Medeiros, 2016: Thermodynamic control of anvil cloud amount. Proc. Natl. Acad. Sci. USA, 113, 89278932, https://doi.org/10.1073/pnas.1601472113.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bouniol, D., J. Delanoë, C. Duroure, A. Protat, V. Giraud, and G. Penide, 2010: Microphysical characterisation of West African MCS anvils. Quart. J. Roy. Meteor. Soc., 136, 323344, https://doi.org/10.1002/qj.557.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bouniol, D., R. Roca, T. Fiolleau, and E. Poan, 2016: Macrophysical, microphysical, and radiative properties of tropical mesoscale convective systems along their life cycle. J. Climate, 29, 33533371, https://doi.org/10.1175/JCLI-D-15-0551.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Del Genio, A. D., and W. Kovari, 2002: Climatic properties of tropical precipitating convection under varying environmental conditions. J. Climate, 15, 25972615, https://doi.org/10.1175/1520-0442(2002)015<2597:CPOTPC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Del Genio, A. D., W. Kovari, M. S. Yao, and J. Jonas, 2005: Cumulus microphysics and climate sensitivity. J. Climate, 18, 23762387, https://doi.org/10.1175/JCLI3413.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Del Genio, A. D., J. Wu, and Y. Chen, 2012: Characteristics of mesoscale organization in WRF simulations of convection during TWP-ICE. J. Climate, 25, 56665688, https://doi.org/10.1175/JCLI-D-11-00422.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Donner, L. J., C. J. Seman, and R. S. Hemler, 2001: A cumulus parameterization including mass fluxes, convective vertical velocities, and mesoscale effects: Thermodynamic and hydrological aspects in a general circulation model. J. Climate, 14, 34443463, https://doi.org/10.1175/1520-0442(2001)014<3444:ACPIMF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Duvel, J. P. M., P. Viollier, R. Raberanto, M. Kandel, L. A. Haeffelin, V. A. Pakhomov, J. Golovko, and R. Mueller, 2001: The ScaRaB-Resurs Earth Radiation Budget dataset and first results. Bull. Amer. Meteor. Soc., 82, 13971408, https://doi.org/10.1175/1520-0477(2001)082<1397:TSRERB>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Eitzen, Z. A., K.-M. Xu, and T. Wong, 2009: Cloud and radiative characteristics of tropical deep convective systems in extended cloud objects from CERES observations. J. Climate, 22, 59836000, https://doi.org/10.1175/2009JCLI3038.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Elsaesser, G. S., A. D. Del Genio, J. H. Jiang, and M. van Lier-Walqui, 2017: 2016: An improved convective ice parameterization for the NASA GISS global climate model and impacts on cloud ice simulation. J. Climate, 30, 317336, https://doi.org/10.1175/JCLI-D-16-0346.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Feng, Z., X. Dong, B. Xi, C. Schumacher, P. Minnis, and M. Khaiyer, 2011: Top-of-atmosphere radiation budget of convective core/stratiform rain and anvil clouds from deep convective systems. J. Geophys. Res., 116, D23202, https://doi.org/10.1029/2011JD016451.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fiolleau, T., and R. Roca, 2013a: An algorithm for the detection and tracking of tropical mesoscale convective systems using infrared images from geostationary satellite. IEEE Trans. Geosci. Remote Sens., 51, 43024315, https://doi.org/10.1109/TGRS.2012.2227762.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fiolleau, T., and R. Roca, 2013b: Composite life cycle of tropical mesoscale convective systems from geostationary and low Earth orbit satellite observations: method and sampling considerations. Quart. J. Roy. Meteor. Soc., 139, 941953, https://doi.org/10.1002/qj.2174.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fiolleau, T., R. Roca, S. Cloché, D. Bouniol, and P. Raberanto, 2020: Homogenization of geostationary infrared imager channels for cold cloud studies using Megha-Tropiques/ScaRaB. IEEE Trans. Geosci. Remote Sens., 58, 66096622, https://doi.org/10.1109/TGRS.2020.2978171.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Futyan, J. M., and A. D. Del Genio, 2007: Deep convective system evolution over Africa and the tropical Atlantic. J. Climate, 20, 50415060, https://doi.org/10.1175/JCLI4297.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gif, N., O. Chomette, and P. Raberanto, 2011: Co-location algorithms: Geophysical data projection using pixel point spread function. Megha-Tropiques Tech. Memo. 2, 28 pp., https://meghatropiques.ipsl.fr/download/megha-tropiques-technical-memorandum-n2/#.

  • Hartmann, D. L., 2002: An important constraint on tropical cloud–climate feedback. Geophys. Res. Lett., 29, 1951, https://doi.org/10.1029/2002GL015835.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hartmann, D. L., B. Gasparini, S. E. Berry, and P. N. Blossey, 2018: The life cycle and net radiative effect of tropical anvil clouds. J. Adv. Model. Earth Syst., 10, 30123029, https://doi.org/10.1029/2018MS001484.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hohenegger, C., and B. Stevens, 2016: Coupled radiative convective equilibrium simulations with explicit and parameterized convection. J. Adv. Model. Earth Syst., 8, 14681482, https://doi.org/10.1002/2016MS000666.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Houze, R. A., Jr., 2004: Mesoscale convective systems. Rev. Geophys., 42, RG4003, https://doi.org/10.1029/2004RG000150.

  • Kandel, R., J.-L. Monge, M. Viollier, L. A. Pakhomov, V. I. Adasco, R. G. Reitenbach, R. G. Raschke, and R. Stuhlmann, 1994: The ScaRaB project: Earth radiation budget observations from the meteor satellites. Adv. Space Res., 14, 4754, https://doi.org/10.1016/0273-1177(94)90346-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kooperman, G. J., M. S. Pritchard, M. A. Burt, M. D. Branson, and D. A. Randall, 2016: Robust effects of cloud superparameterization on simulated daily rainfall intensity statistics across multiple versions of the Community Earth System Model. J. Adv. Model. Earth Syst., 8, 140165, https://doi.org/10.1002/2015MS000574.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liou, K. N., 2002: An Introduction to Atmospheric Radiation. 2nd ed. International Geophysics Series, Vol. 84, Academic Press, 583 pp.

  • Loeb, N. G., S. Kato, K. Loukachine, N. Manalo-Smith, and D. R. Doelling, 2007: Angular distribution models for top-of-atmosphere radiative flux estimation from the Clouds and the Earth’s Radiant Energy System instrument on the Terra satellite. Part II: validation. J. Atmos. Oceanic Technol., 24, 564584, https://doi.org/10.1175/JTECH1983.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nesbitt, S. W., E. J. Zipser, and D. J. Cecil, 2000: A census of precipitation features in the tropics using TRMM: Radar, ice scattering, and lightning observations. J. Climate, 13, 40874106, https://doi.org/10.1175/1520-0442(2000)013<4087:ACOPFI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Palmer, T., and B. Stevens, 2019: The scientific challenge of understanding and estimating climate change. Proc. Natl. Acad. Sci. USA, 116, 242390–242395, https://doi.org/10.1073/pnas.1906691116.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ramanathan, V., 1987: The role of Earth radiation budget studies in climate and general circulation research. J. Geophys. Res., 92, 40754095, https://doi.org/10.1029/JD092iD04p04075.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ramanathan, V., and W. Collins, 1991: Thermodynamic regulation of ocean warming by cirrus clouds deduced from observations of the 1987 El Niño. Nature, 351, 2732, https://doi.org/10.1038/351027a0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roca, R., and V. Ramanathan, 2000: Scale dependence of monsoonal convective systems over the Indian Ocean. J. Climate, 13, 12861298, https://doi.org/10.1175/1520-0442(2000)013<1286:SDOMCS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roca, R., M. Viollier, L. Picon, and M. Desbois, 2002: A multisatellite analysis of deep convection and its moist environment over the Indian Ocean during the winter monsoon. J. Geophys. Res., 107, 8012, https://doi.org/10.1029/2000JD000040.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roca, R., S. Louvet, L. Picon, and M. Desbois, 2005: A study of convective systems, water vapor and top of the atmosphere cloud radiative forcing over the Indian Ocean using INSAT-1B and ERBE data. Meteor. Atmos. Phys., 90, 4965, https://doi.org/10.1007/s00703-004-0098-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roca, R., and Coauthors, 2015: The Megha-Tropiques mission: A review after three years in orbit. Front. Earth Sci., 3, 17, https://doi.org/10.3389/feart.2015.00017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roca, R., T. Fiolleau, and D. Bouniol, 2017: A simple model of the life cycle of mesoscale convective systems cloud shield in the tropics. J. Climate, 30, 42834298, https://doi.org/10.1175/JCLI-D-16-0556.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rutan, D., G. L. Smith, and T. Wong, 2014: Diurnal variations of albedo retrieved from Earth Radiation Budget Experiment measurements. J. Appl. Meteor. Climatol., 53, 27472760, https://doi.org/10.1175/JAMC-D-13-0119.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, G. L., and D. A. Rutan, 2003: The diurnal cycle of outgoing longwave radiation from Earth Radiation Budget Experiment measurements. J. Atmos. Sci., 60, 15291542, https://doi.org/10.1175/2997.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sohn, B.-J., M.-J. Choi, and J. Ryu, 2015: Explaining darker deep convective cloud over the western Pacific than over tropical continental convective regions. Atmos. Meas. Tech., 8, 45734583, https://doi.org/10.5194/amt-8-4573-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sokol, A. B., and D. L. Hartmann, 2020: Tropical anvil clouds: Radiative driving toward a preferred state. J. Geophys. Res. Atmos., 125, e2020JD033107, https://doi.org/10.1029/2020JD033107.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Trémas, T. L., O. Aznay, and O. Chomette, 2015: ScaRaB: First results of absolute and cross calibration. Proc. SPIE, 9643, 964304, https://doi.org/10.1117/12.2194866.

    • Search Google Scholar
    • Export Citation
  • Vaillant de Guélis, T., H. Chepfer, V. Noël, R. Guzman, P. Dubuisson, D. M. Winker, and S. Kato, 2017: The link between outgoing longwave radiation and the altitude at which a spaceborne lidar beam is fully attenuated. Atmos. Meas. Tech., 10, 46594685, https://doi.org/10.5194/amt-10-4659-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Viollier, M., C. Standfuss, O. Chomette, and A. Quesney, 2009: Top-of-atmosphere radiance-to-flux conversion in the SW domain for the ScaRaB-3 instrument on Megha-Tropiques. J. Atmos. Oceanic Technol., 26, 21612171, https://doi.org/10.1175/2009JTECHA1264.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wall, C. J., D. Hartmann, M. M. Thieman, W. L. Smith Jr., and P. Minnis, 2018: The Life cycle of anvil clouds and the top-of-atmosphere radiation balance over the tropical west Pacific. J. Climate, 31, 10 05910 080, https://doi.org/10.1175/JCLI-D-18-0154.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wall, C. J., J. R. Norris, B. Gasparini, W. L. Smith Jr., M. M. Thieman, and O. Sourdeval, 2020: Observational evidence that radiative heating modifies the life cycle of tropical anvil clouds. J. Climate, 33, 86218640, https://doi.org/10.1175/JCLI-D-20-0204.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Webster, P. J., and G. L. Stephens, 1980: Tropical upper-tropospheric extended clouds: inferences from winter MONEX. J. Atmos. Sci., 37, 15211541, https://doi.org/10.1175/1520-0469-37.7.1521.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wing, A. A., 2019: Self-aggregation of deep convection and its implications for climate. Curr. Climate Change Rep., 5, 111, https://doi.org/10.1007/s40641-019-00120-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xu, K.-M., T. Wong, B. A. Wiekicki, L. Parker, and Z. A. Eitzen, 2005: Statistical analyses of satellite cloud object data from CERES. Part I: Methodology and preliminary results of the 1998 El Niño/2000 La Niña. J. Climate, 18, 24972514, https://doi.org/10.1175/JCLI3418.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, G.-Y., and J. Slingo, 2001: The diurnal cycle in the tropics. Mon. Wea. Rev., 129, 784801, https://doi.org/10.1175/1520-0493(2001)129<0784:TDCITT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zelinka, M. D., and D. L. Hartmann, 2010: Why is longwave cloud feedback positive? J. Geophys. Res., 115, D16117, https://doi.org/10.1029/2010JD013817.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zelinka, M. D., S. A. Klein, and D. L. Hartmann, 2012: Computing and partitioning cloud feedbacks using cloud property histograms. Part II: Attribution to changes in cloud amount, altitude, and optical depth. J. Climate, 25, 37363754, https://doi.org/10.1175/JCLI-D-11-00249.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 191 0 0
Full Text Views 2007 1551 649
PDF Downloads 584 154 8