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首页> 外文期刊>Journal of Geophysical Research, D. Atmospheres: JGR >Cloud Heterogeneity in the Marine Midlatitudes: Dependence on Large-Scale Meteorology and Implications for General Circulation Models
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Cloud Heterogeneity in the Marine Midlatitudes: Dependence on Large-Scale Meteorology and Implications for General Circulation Models

机译:云在海洋中间体中的云异质性:依赖大规模气象学和对一般循环模型的影响

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摘要

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.
机译:我们使用来自多端成像光谱仪和中度分辨率的成像光谱仪器仪器的卫星观测来研究云异质性对大规模气象的敏感性。 2007年。利用多聚成像光谱辐射计观察,我们由于云异质性而定量了几个观测性不确定性的来源,例如有限分辨率云分数偏置和亚像素异质性。通过简单的云几何测量,我们表明这些观测性不确定性的源极化在冷的后额度条件下最大化,其中散射的亚像素云频繁,并且在温暖的扇区中最小化,亚像素云很少。与静态或热门扇区条件相比,这些结果表明,在冷却后额度条件下解释遥感测量的难度越难。我们表明,忽视这种观察性不确定性可以定性地改变云属性如何在GA7和一般循环模型中响应大规模气象的解释。然而,卫星数据的保守应用仍然允许对模拟云的鲁棒评估。对于阴云域,中度分辨率的成像光谱仪观察表明,阴云密布云异质性与大规模气象无关。然而,当从温暖的扇区移动到GA7中的冷冻前部条件时,异质性增加。 Ga7高估填充这些制度的低顶云的异质性。对于阴云域,这种偏差相当于平均云光学深度的低估了15%。这些结果表明底片级变化参数化中的系统误差,当校正时,将改善GA7中的中间位的模拟。

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