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首页> 外文期刊>Journal of Geophysical Research, D. Atmospheres: JGR >Impacts of Observation Errors on Hurricane Forecasts When Assimilating Hyperspectral Infrared Sounder Radiances in Partially Cloudy Skies
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Impacts of Observation Errors on Hurricane Forecasts When Assimilating Hyperspectral Infrared Sounder Radiances in Partially Cloudy Skies

机译：在部分多云天空中吸收高光谱红外发声器时，观察误差对飓风预报的影响

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摘要

Hyperspectral infrared (IR) sounders provide high vertical resolution atmospheric sounding information that can improve the forecast accuracy of numerical weather prediction (NWP) models. Due to the challenges of assimilating cloudy radiances, NWP centers usually assimilate only radiances that are not affected by clouds. An imager based cloud-clearing technique provides an alternative and effective way to remove the cloud effects from a partially cloudy field-of-view and derive the equivalent clear sky radiances or the cloud-cleared radiances (CCRs) for assimilation in NWP. Since the observation error is amplified in the cloud-clearing, or noise amplification process, it is necessary to inflate the observation errors appropriately in order to achieve the optimal value-added impact from assimilating CCRs. The estimation of observation error inflation is established and discussed. Hurricane Harvey (2017) and Hurricane Maria (2017) are used to simulate and understand the impacts of observation error inflation on the assimilation of Cross-track Infrared Sounder CCRs for hurricane forecast improvement. Both the precipitation location and intensity forecasts are improved when assimilating CCRs with an inflated observation error for Hurricane Harvey (2017). Assimilating CCRs with an inflated observation error adjusts the temperature and geopotential height fields and further affects the hurricane structures to improve the hurricane track forecasts, thereby demonstrating the importance of using hyperspectral IR measurements in partially cloudy skies for simulating the hurricane structure and improving its forecast. This method can be applied to other imager/sounder combined observations for improving sounder radiance assimilation in cloudy skies and has potential for operational applications.
机译：高光谱红外（IR）发声器提供高垂直分辨率的大气探测信息，可以提高数字天气预报（NWP）模型的预测精度。由于吸收多云的辐射的挑战，NWP中心通常仅吸收不受云层影响的无线。基于成像仪的云清算技术提供了一种替代和有效的方法来从部分多云的视野中删除云效应，并导出等效的清晰天空辐射或云清除的广场（CCR）在NWP中同化。由于观察误差在云清零或噪声放大过程中被放大，因此必须适当地膨胀观察误差，以便实现来自同化CCR的最佳增值冲击。建立并讨论了观察误差通胀的估计。 Hurricane Harvey（2017）和飓风玛丽亚（2017年）用于模拟和理解观察误差通胀对飓风预测改进的交叉轨道红外发声CCR的同化的影响。当使用飓风哈维（2017）时，在吸收CCR时，改善了降水位置和强度预测。通过膨胀的观测误差同化CCR调节温度和地理调位高度场，并进一步影响飓风结构以改善飓风轨道预测，从而展示在部分多云的天空中使用高光谱IR测量来模拟飓风结构并改善预测。该方法可以应用于其他成像器/探测器的组合观察，以改善多云的天空中的发声器辐射同化，并且具有运行应用的可能性。

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