Evaluating Convective Initiation in High-Resolution Numerical Weather Prediction Models Using GOES-16 Infrared Brightness Temperatures
Evaluating Convective Initiation in High-Resolution Numerical Weather Prediction Models Using GOES-16 Infrared Brightness Temperatures
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DOI：
10.1175/mwr-d-20-0272.1
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发表时间：
2021-02
影响因子：
3.2
通讯作者：
David S. Henderson;J. Otkin;J. Mecikalski
中科院分区：
文献类型：
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作者：
David S. Henderson;J. Otkin;J. Mecikalski
基于模式的云顶亮度温度（BT）的演变与对流的启动（CI）进行了评估的天气研究和预报模式中的三个大块云微物理方案。使用基于复合的分析，云对象来自高分辨率（500米）模型模拟相比，5分钟的GOES-16图像的案例研究日位于密西西比州附近的边界。观测和模拟云的云特性达到CI利用红外BT通常用于基于卫星的CI临近预报方法进行检查。结果表明，基于对象的验证方法与卫星观测，以评估模型云特性的演变的能力，和BT比较提供了一个已知的问题模型模拟产生太多的对流细胞达到CI的洞察力。CI从不同的微物理方案的时间是依赖于生产的冰在上层的云，这通常发生在最大的云增长的时间附近。特别是，降水形成的巨大差异驱动了能够到达云层上层的云水数量的差异，这影响了云顶冰川作用。在云的持续增长中发现了更大的云混合比，导致更多的云水上升到云的上层并形成冰。无法维持增长的云缺乏形成冰和成长为积雨云所需的云水。增长速度较慢的云显示类似的BT趋势的云表现出增长，这表明，预测CI使用地球静止卫星可能需要额外的信息以外的云顶部。
The evolution of model-based cloud-top brightness temperatures (BT) associated with convective initiation (CI) is assessed for three bulk cloud microphysics schemes in the Weather Research and Forecasting Model. Using a composite-based analysis, cloud objects derived from high-resolution (500 m) model simulations are compared to 5-min GOES-16 imagery for a case study day located near the Alabama–Mississippi border. Observed and simulated cloud characteristics for clouds reaching CI are examined by utilizing infrared BTs commonly used in satellite-based CI nowcasting methods. The results demonstrate the ability of object-based verification methods with satellite observations to evaluate the evolution of model cloud characteristics, and the BT comparison provides insight into a known issue of model simulations producing too many convective cells reaching CI. The timing of CI from the different microphysical schemes is dependent on the production of ice in the upper levels of the cloud, which typically occurs near the time of maximum cloud growth. In particular, large differences in precipitation formation drive differences in the amount of cloud water able to reach upper layers of the cloud, which impacts cloud-top glaciation. Larger cloud mixing ratios are found in clouds with sustained growth leading to more cloud water lofted to the upper levels of the cloud and the formation of ice. Clouds unable to sustain growth lack the necessary cloud water needed to form ice and grow into cumulonimbus. Clouds with slower growth rates display similar BT trends as clouds exhibiting growth, which suggests that forecasting CI using geostationary satellites might require additional information beyond those derived at cloud top.