Diagnosis of stratocumulus and deep convective clouds simulated by the NCEP/GFS using satellite and ground-based measurements

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Description

Cloud properties, cloud vertical structure, and deep convective clouds are important for meteorological studies due to their impact on both the Earth’s radiation budget and adiabatic heating. The objectives of this study are to diagnose the performance of the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model cloud simulations, to identify possible causes of the discrepancies in cloud fields, and to examine individual factors that affect the development of deep convective clouds using different types of observational data sets.

Mistreatment of such marine stratocumulus clouds in the GFS model leads to an overestimation of upward longwave flux and an underestimation of upward shortwave flux at the top-of-atmosphere. With respect to input data biases, the temperature field from the GFS is comparable to that obtained from both satellite retrievals and ground-based measurements, but the GFS relative humidity field shows a moist bias in lower atmosphere. To improve simulations of low-level clouds, two experiments are performed by using the GFS model's original atmospheric fields with a different cloud parameterization scheme. The new approach generates a large quantity of marine stratocumulus clouds over the eastern tropical oceans as well as low cloud amounts in the other regions around the world. The other experiment is use of the exponential random overlap assumption, and this method leads to an improvement for high-level clouds, a neutral impact for middle-level clouds, and deterioration for low-level clouds. Comparison of distributions and characteristics of deep convective clouds between the model simulations and satellite retrievals is made, and overall, their gross features look similar in terms of locations and spatial patterns, although a weak convection strength is seen on cloud top of deep convection in the GFS model simulations.