资源环境科技发展态势分析平台

We examine the sensitivity of cloud heterogeneity to large-scale meteorology in the marine midlatitudes using satellite observations from the Multiangle Imaging Spectroradiometer and Moderate Resolution Imaging Spectroradiometer instruments aboard the Terra satellite and nudged simulations from the UK Met Office's Global Atmosphere 7.0 (GA7) for the year 2007. Using Multiangle Imaging Spectroradiometer observations, we quantify several sources of observational uncertainty due to cloud heterogeneity such as finite-resolution cloud fraction biases and subpixel heterogeneity. With a simple measure of cloud geometry, we show that these sources of observational uncertainty are maximized in post-cold-frontal conditions, where scattered subpixel clouds are frequent, and are minimized in the warm sector, where subpixel clouds are infrequent. These results demonstrate the greater difficulty in interpreting remote sensing measurements in post-cold-frontal conditions compared to quiescent or warm-sector conditions. We show that the neglect of this observational uncertainty can qualitatively alter the interpretation of how cloud properties respond to large-scale meteorology in GA7 and general circulation models in general. However, conservative application of the satellite data still allows robust evaluation of the simulated clouds. For overcast domains, Moderate Resolution Imaging Spectroradiometer observations show that overcast cloud heterogeneity is independent of large-scale meteorology. However, heterogeneity increases when moving from warm sector to post-cold-frontal conditions in GA7. GA7 overestimates the heterogeneity of the low-topped clouds that populate these regimes. For overcast domains, this bias is equivalent to a 15% underestimation in the mean cloud optical depth. These results suggest a systematic error in the subgrid-scale variability parameterization, which, when corrected, will improve the simulation of the midlatitudes in GA7.