| Summary: | Marine boundary layer clouds account for a significant amount of uncertainty in future climate change projections from general circulation models (GCMs). To reduce the uncertainty of the role of clouds in GCMs, improved cloud parameterizations and evaluations of these parameterizations are often sought using satellite data. Several studies have shown that marine stratus cloud fraction is strongly correlated with stability of the lower troposphere. These results are verified using data from the Multiangle Imaging Spectroradiometer (MISR). The MISR data allow for improved cloud top height and cloud cover retrievals for low clouds compared to all other passive sensors. From MISR daily data, two-dimensional histograms of cloud fraction and cloud top height at 500 m vertical resolution are explored for the first time. The daily data are also used to study cloud fraction on sub-monthly time scales in order to better understand the processes affecting cloud cover on the order of days. Average values of stability and low cloud fraction are compared at varying time scales to determine if known seasonal correlation holds for shorter time scales; as in previous work, no significant correlation was shown to exist on daily time scales based on an Eulerian view. To elucidate why this lack of correlation exists at shorter time scales, a Lagrangian view was examined by performing back trajectory analyses to determine if any time lag-correlation exists between the stability of the marine boundary layer and the cloud fraction at a given point for time lags up to 72 hours – no significant correlation was found. Using the MISR data, seasonal mean cloud fraction and various measures of stability had correlation coefficients on the order of 0.6 to 0.7. At monthly timescales, correlation coefficients are in the 0.7 to 0.8 range. At daily timescales, however, the correlation coefficients are nearly zero. The monthly analysis is also extended beyond marine stratus regions to other marine regions with low clouds, revealing areas of good correlation between low cloud and lower tropospheric stability where it was not expected, such as over the Gulf Stream in the western North Atlantic and east of China in the North Pacific. These results can then be compared with results from model-simulated cloud cover and stability to evaluate and improve model parameterizations of cloud cover on a global scale.
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