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Spatial verification of rainfall forecasts for very severe cyclonic storm 'Phailin'

机译:极强气旋风暴“ Phailin”的降雨预报的空间验证

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The current study demonstrates the utilisation of a tool for the comprehensive evaluation of model forecasts using both traditional and spatial diagnostic techniques. The fundamental idea is to provide additional and meaningful insight into the model weaknesses and strengths in terms of underlying physical processes especially for very high resolution models and observations. The traditional scores also suffer from the so called "double penalty" issue and hence alone cannot provide a measure of spatial and temporal match between the forecast and observed rainfall patterns. Method for Object-based Diagnostics Evaluation is a spatial verification technique in the category of displacement methods while wavelet analysis comes into filtering type of spatial verification. Former is a features based verification technique while the latter is based on scale-separation principle. The case of Very Severe Tropical Cyclone 'Phailin' is taken up for the study and the rainfall forecasts from Global Forecast System and Unified Model run at National Centre for Medium Range Weather Forecasting are verified against g-ridded satellite-cum-raingauge-merged rainfall analysis. The traditional verification scores were computed using categorical and continuous measures and the spatial verification scores were computed against various thresholds. The results are presented to summarise the overall performance of both the global models with respect to the rainfall prediction.
机译:当前的研究证明了利用传统和空间诊断技术对模型预测进行综合评估的工具的利用。基本思想是提供有关基础物理过程方面的模型弱点和优势的更多且有意义的见解,尤其是对于非常高分辨率的模型和观测而言。传统分数也遭受所谓的“双重惩罚”问题,因此仅凭其本身无法提供预报和观测到的降雨模式之间的时空匹配程度。基于对象的诊断评估方法是位移方法类别中的一种空间验证技术,而小波分析已成为空间验证的过滤类型。前者是基于特征的验证技术,而后者是基于比例分离原理的。以非常强的热带气旋“ Phailin”为例进行了研究,并验证了全球预报系统和在美国国家中型天气预报中心运行的统一模型的降雨预报是否受到g卫星和雨量计合并的降雨的影响分析。传统的验证分数是使用分类和连续度量计算的,而空间验证分数是针对各种阈值计算的。给出结果以总结关于降雨预测的两个全球模型的整体性能。

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