Statistical analyses of satellite cloud object data from ceres. Part III: Comparison with cloud-resolving model simulations of tropical convective clouds

• Published in: Journal of the atmospheric sciences Vol. 64; no. 3; pp. 762 - 785
• Main Authors: YALI LUO, XU, Kuan-Man, WIELICKI, Bruce A, WONG, Takmeng, EITZEN, Zachary A
• Format: Journal Article
• Language: English
• Published: Boston, MA American Meteorological Society 01.03.2007
• Subjects: Albedo; Clouds; Earth, ocean, space; El Nino; Exact sciences and technology; External geophysics; La Nina; Meteorology; Optical analysis; Physical properties; Physics of the high neutral atmosphere; Prediction models; Research centers; Statistical analysis; Weather forecasting; Southern Europe; Italy; Marches Italy; physical properties; Uncertainty; Weather forecast; Europe; Convective cloud; digital simulation; Forecast model; Parameterization; Ice cloud; Probability density; La Niña; El Nino; Cloud physics; Outgoing longwave radiation; Height; Numerical forecast; Optical thickness; Forcing; statistical analysis; Cloud top; albedo; Retrieval algorithm
• DOI: 10.1175/JAS3871.1
• ISSN: 0022-4928

The present study evaluates the ability of a cloud-resolving model (CRM) to simulate the physical properties of tropical deep convective cloud objects identified from a Clouds and the Earth's Radiant Energy System (CERES) data product. The emphasis of this study is the comparisons among the small-, medium-, and large-size categories of cloud objects observed during March 1998 and between the large-size categories of cloud objects observed during March 1998 (strong El Nino) and March 2000 (weak La Nina). Results from the CRM simulations are analyzed in a way that is consistent with the CERES retrieval algorithm and they are averaged to match the scale of the CERES satellite footprints. Cloud physical properties are analyzed in terms of their summary histograms for each category. It is found that there is a general agreement in the overall shapes of all cloud physical properties between the simulated and observed distributions. Each cloud physical property produced by the CRM also exhibits different degrees of disagreement with observations over different ranges of the property. The simulated cloud tops are generally too high and cloud-top temperatures are too low except for the large-size category of March 1998. The probability densities of the simulated top-of-the-atmosphere (TOA) albedos for all four categories are underestimated for high albedos, while those of cloud optical depth are overestimated at its lowest bin. These disagreements are mainly related to uncertainties in the cloud microphysics parameterization and inputs such as cloud ice effective size to the radiation calculation. Summary histograms of cloud optical depth and TOA albedo from the CRM simulations of the large-size category of cloud objects do not differ significantly between the March 1998 and 2000 periods, consistent with the CERES observations. However, the CRM is unable to reproduce the significant differences in the observed cloud-top height while it overestimates the differences in the observed outgoing longwave radiation and cloud-top temperature between the two periods. Comparisons between the CRM results and the observations for most parameters in March 1998 consistently show that both the simulations and observations have larger differences between the large- and small-size categories than between the large- and medium-size, or between the medium- and small-size categories. However, the simulated cloud properties do not change as much with size as observed. These disagreements are likely related to the spatial averaging of the forcing data and the mismatch in time and space between the numerical weather prediction model from which the forcing data are produced and the CERES observed cloud systems. [PUBLICATION ABSTRACT]