On the diurnal cycle of deep convection, high-level cloud, and upper...

Zhang, Y., S. A. Klein, C. Liu, B. Tian, R. Marchand, J. Haynes, R. B. McCoy, Y. Zhang, and T. P. Ackerman (2008), On the diurnal cycle of deep convection, high-level cloud, and upper troposphere water vapor in the Multiscale Modeling Framework, J. Geophys. Res., 113, D16105, doi:10.1029/2008JD009905.

The Multiscale Modeling Framework (MMF), also called ‘‘superparameterization’’, embeds a cloud-resolving model (CRM) at each grid column of a general circulation model to replace traditional parameterizations of moist convection and large-scale condensation. This study evaluates the diurnal cycle of deep convection, high-level clouds, and upper troposphere water vapor by applying an infrared (IR) brightness temperature (Tb) and a precipitation radar (PR) simulator to the CRM column data. Simulator results are then compared with IR radiances from geostationary satellites and PR reflectivities from the Tropical Rainfall Measuring Mission (TRMM). While the actual surface precipitation rate in the MMF has a reasonable diurnal phase and amplitude when compared with TRMM observations, the IR simulator results indicate an inconsistency in the diurnal anomalies of high-level clouds between the model and the geostationary satellite data. Primarily because of its excessive high-level clouds, the MMF overestimates the simulated precipitation index (PI) and fails to reproduce the observed diurnal cycle phase relationships among PI, high-level clouds, and upper troposphere relative humidity. The PR simulator results show that over the tropical oceans, the occurrence fraction of reflectivity in excess of 20 dBZ is almost 1 order of magnitude larger than the TRMM data especially at altitudes above 6 km. Both results suggest that the MMF oceanic convection is overactive and possible reasons for this bias are discussed. However, the joint distribution of simulated IR Tb and PR reflectivity indicates that the most intense deep convection is found more often over tropical land than ocean, in agreement with previous observational studies.

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Modeling Analysis and Prediction Program (MAP)
Climate Variability and Change Program
Atmospheric Dynamics and Precipitation Program (ADP)