Object-Based Evaluation of MERRA Cloud Physical Properties and Radiative Fluxes during the 1998 El Niño–La Niña Transition

Derek J. Posselt University of Michigan, Ann Arbor, Michigan

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Andrew R. Jongeward University of Maryland, College Park, College Park, Maryland

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Chuan-Yuan Hsu University of Michigan, Ann Arbor, Michigan

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Gerald L. Potter University of Michigan, Ann Arbor, Michigan

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Abstract

The Modern-Era Retrospective Analysis for Research and Application (MERRA) is a reanalysis designed to produce an improved representation of the Earth’s hydrologic cycle. This study examines the representation of deep convective clouds in MERRA, comparing analyzed liquid and ice clouds with deep convective cloud objects observed by instruments on the Tropical Rainfall Measuring Mission satellite. Results show that MERRA contains deep convective cloud in 98.1% of the observed cases. MERRA-derived probability density functions (PDFs) of cloud properties have a similar form as the observed PDFs and exhibit a similar trend with changes in object size. Total water path, optical depth, and outgoing shortwave radiation (OSR) in MERRA are found to match the cloud object observations quite well; however, there appears to be a bias toward higher-than-observed cloud tops in the MERRA. The reanalysis fits the observations most closely for the largest class of convective systems, with performance generally decreasing with a transition to smaller convective systems. Comparisons of simulated total water path, optical depth, and OSR are found to be highly sensitive to the assumed subgrid distribution of condensate and indicate the need for caution when interpreting model-data comparisons that require disaggregation of grid-scale cloud to satellite pixel scales.

Corresponding author address: Derek J. Posselt, Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, 2455 Hayward Street, Ann Arbor, MI 48109-2143. E-mail: dposselt@umich.edu

This article is included in the Modern Era Retrospective-Analysis for Research and Applications (MERRA) special collection.

Abstract

The Modern-Era Retrospective Analysis for Research and Application (MERRA) is a reanalysis designed to produce an improved representation of the Earth’s hydrologic cycle. This study examines the representation of deep convective clouds in MERRA, comparing analyzed liquid and ice clouds with deep convective cloud objects observed by instruments on the Tropical Rainfall Measuring Mission satellite. Results show that MERRA contains deep convective cloud in 98.1% of the observed cases. MERRA-derived probability density functions (PDFs) of cloud properties have a similar form as the observed PDFs and exhibit a similar trend with changes in object size. Total water path, optical depth, and outgoing shortwave radiation (OSR) in MERRA are found to match the cloud object observations quite well; however, there appears to be a bias toward higher-than-observed cloud tops in the MERRA. The reanalysis fits the observations most closely for the largest class of convective systems, with performance generally decreasing with a transition to smaller convective systems. Comparisons of simulated total water path, optical depth, and OSR are found to be highly sensitive to the assumed subgrid distribution of condensate and indicate the need for caution when interpreting model-data comparisons that require disaggregation of grid-scale cloud to satellite pixel scales.

Corresponding author address: Derek J. Posselt, Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, 2455 Hayward Street, Ann Arbor, MI 48109-2143. E-mail: dposselt@umich.edu

This article is included in the Modern Era Retrospective-Analysis for Research and Applications (MERRA) special collection.

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  • Bell, G. D., M. S. Halpert, C. F. Ropelewski, V. E. Kousky, A. V. Douglas, R. C. Schnell, and M. E. Gelman, 1999: Climate assessment for 1998. Bull. Amer. Meteor. Soc., 80, S1S48.

    • Search Google Scholar
    • Export Citation
  • Bodas-Salcedo, A., M. J. Webb, M. E. Brooks, M. A. Ringer, K. D. Williams, S. F. Milton, and D. R. Wilson, 2008: Evaluating cloud systems in the Met Office global forecast model using simulated CloudSat radar reflectivities. J. Geophys. Res., 113, D00A13, doi:10.1029/2007JD009620.

    • Search Google Scholar
    • Export Citation
  • Bosilovich, M. G., F. R. Robertson, and J. Chen, 2011: Global energy and water budgets in MERRA. J. Climate, 24, 57215739.

  • 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.

    • Search Google Scholar
    • Export Citation
  • Fu, Q., and K.-N. Liou, 1992: On the correlated k-distribution method for radiative transfer in nonhomogeneous atmospheres. J. Atmos. Sci., 49, 21392156.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., S. Matrosov, and B. Baum, 2003: Ice water path–optical depth relationships for cirrus and deep stratiform ice cloud layers. J. Appl. Meteor., 42, 13691390.

    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437471.

  • Kummerow, C., W. Barnes, T. Kozu, J. Shiue, and J. Simpson, 1998: The Tropical Rainfall Measuring Mission (TRMM) sensor package. J. Atmos. Oceanic Technol., 15, 809817.

    • Search Google Scholar
    • Export Citation
  • Larson, V. E., 2007: From cloud overlap to PDF overlap. Quart. J. Roy. Meteor. Soc., 133, 18771891.

  • Manton, M. J., and W. R. Cotton, 1977: Formulation of approximate equations for modeling moist deep convection on the mesoscale. Colorado State University Atmospheric Science Paper 266, 62 pp.

  • Minnis, P., and Coauthors, 1997: Cloud optical property retrieval (subsystem 4.3). Clouds and the Earth’s Radiant Energy System (CERES) algorithm theoretical basis document, 60 pp. [Available online at http://ceres.larc.nasa.gov/atbd.php.]

  • Minnis, P., and Coauthors, 2011a: CERES edition-2 cloud property retrievals using TRMM VIRS and Terra and Aqua MODIS data—Part I: Algorithms. IEEE Trans. Geosci. Remote Sens., 49, 43744400.

    • Search Google Scholar
    • Export Citation
  • Minnis, P., and Coauthors, 2011b: CERES edition-2 cloud property retrievals using TRMM VIRS and Terra and Aqua MODIS data—Part II: Examples of average results and comparisons with other data. IEEE Trans. Geosci. Remote Sens., 49, 44014430.

    • Search Google Scholar
    • Export Citation
  • Moorthi, S., and M. J. Suarez, 1992: Relaxed Arakawa–Schubert, a parameterization of moist convection for general circulation models. Mon. Wea. Rev., 120, 9781002.

    • Search Google Scholar
    • Export Citation
  • Norris, P. M., L. Oreopoulos, A. Y. Hou, W.-K. Tao, and X. Zeng, 2008: Representation of 3D heterogeneous cloud fields using copulas: Theory for water clouds. Quart. J. Roy. Meteor. Soc., 134, 18431864.

    • Search Google Scholar
    • Export Citation
  • Onogi, K., and Coauthors, 2005: JRA-25: Japanese 25-Year Re-Analysis Project—Progress and status. Quart. J. Roy. Meteor. Soc., 131, 32593268.

    • Search Google Scholar
    • Export Citation
  • Posselt, D. J., S. C. van den Heever, G. L. Stephens, and M. R. Igel, 2012: Changes in the interaction between tropical convection, radiation, and the large-scale circulation in a warming environment. J. Climate, 25, 557571.

    • Search Google Scholar
    • Export Citation
  • Raisanen, P., H. W. Barker, M. F. Khairoutdinov, J. Li, and D. A. Randall, 2004: Stochastic generation of subgrid-scale cloudy columns for large-scale models. Quart. J. Roy. Meteor. Soc., 130, 20472067.

    • Search Google Scholar
    • Export Citation
  • Rienecker, M. M., and Coauthors, 2008: The GEOS-5 Data Assimilation System—Documentation of versions 5.0.1 and 5.1.0, and 5.2.0. NASA Technical Report Series on Global Modeling and Data Assimilation, Vol. 27, NASA Tech Memo. NASA/TM-2008-104606, 101 pp.

  • Rienecker, M. M., and Coauthors, 2011: MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications. J. Climate, 24, 36243648.

    • Search Google Scholar
    • Export Citation
  • Robertson, F. R., M. G. Bosilovich, J. Chen, and T. L. Miller, 2011: The effect of satellite observing system changes on MERRA water and energy fluxes. J. Climate, 24, 51975217.

    • Search Google Scholar
    • Export Citation
  • Stephens, G. L., 2005: Cloud feedbacks in the climate system: A critical review. J. Climate, 18, 237273.

  • Trenberth, K. E., J. T. Fasullo, and J. Kiehl, 2009: Earth’s global energy budget. Bull. Amer. Meteor. Soc., 90, 311323.

  • Uppala, S. M., and Coauthors, 2005: The ERA-40 Re-Analysis. Quart. J. Roy. Meteor. Soc., 131, 29613012.

  • Wielicki, B. A., B. R. Barkstrom, E. F. Harrison, R. B. Lee III, G. L. Smith, and J. E. Cooper, 1996: Clouds and the Earth’s Radiant Energy System (CERES): An Earth Observing System experiment. Bull. Amer. Meteor. Soc., 77, 853868.

    • Search Google Scholar
    • Export Citation
  • Xu, K.-M., 2006: Using the bootstrap method for a statistical significance test of differences between summary histograms. Mon. Wea. Rev., 134, 14421453.

    • Search Google Scholar
    • Export Citation
  • Xu, K.-M., 2009: Evaluation of cloud physical properties of ECMWF analysis and re-analysis (ERA) against CERES tropical deep convective cloud object observations. Mon. Wea. Rev., 137, 207223.

    • Search Google Scholar
    • Export Citation
  • Xu, K.-M., T. Wong, B. A. Wielicki, 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.

    • Search Google Scholar
    • Export Citation
  • Xu, K.-M., T. Wong, B. A. Wielicki, L. Parker, B. Lin, Z. A. Eitzen, and M. Branson, 2007: Statistical analyses of satellite cloud object data from CERES. Part II: Tropical convective cloud objects during 1998 El Niño and evidence for supporting the fixed anvil temperature hypothesis. J. Climate, 20, 819842.

    • Search Google Scholar
    • Export Citation
  • Xu, K.-M., T. Wong, B. A. Wielicki, and L. Parker, 2008: Statistical analyses of satellite cloud object data from CERES. Part IV: Boundary layer cloud objects during 1998 El Niño. J. Climate, 21, 15001522.

    • Search Google Scholar
    • Export Citation
  • Yeh, S.-W., J.-S. Kug, B. Dewitte, M.-H. Kwon, B. P. Kirtman, and F.-F. Jin, 2009: El Niño in a changing climate. Nature, 461, 511515.

    • Search Google Scholar
    • Export Citation
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