Just What is “Good”? Musings on Hail Forecast Verification Through Evaluation of FV3-HAILCAST Hail Forecasts
Just What is “Good”? Musings on Hail Forecast Verification Through Evaluation of FV3-HAILCAST Hail Forecasts
复制标题
到底什么是“好”？
DOI：
10.1175/waf-d-22-0087.1
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发表时间：
2022
影响因子：
2.9
通讯作者：
Clark, Adam J.
中科院分区：
文献类型：
--
作者：
Adams-Selin, Rebecca D.;Kalb, Christina;Jensen, Tara;Henderson, John;Supinie, Tim;Harris, Lucas;Wang, Yunheng;Gallo, Burkely T.;Clark, Adam J.
在2019年，2020年和2021年NOAA危险天气试验台（HWT）春季预报实验（SFE）期间，对CAM-HAILCAST伪拉格朗日冰雹大小预报模型产生的冰雹预报进行了评估。作为评估的一部分，HWT SFE参与者被问及他们对"良好"冰雹预报的定义。与会者提出了两种不同的验证方法进行了三个不同的时空尺度，然后被要求主观评价冰雹预报以及不同的验证方法本身。结果建议使用多种验证方法，根据最终用户解释和应用预测所期望的预测类型量身定制。在此期间评估的冰雹预报包括在有限体积3（FV3）动力核心的统一预报系统的有限区域模型中实施CAM-HAILCAST。FV3-HAILCAST在1小时和24小时期间的评估发现，从2019年到2021年持续改善。这一改善主要是由于FV3集合成员之间的广泛互变性，2019年不同的微物理参数化在2020年和2021年显著减少。到2021年，整个昼夜周期的过度预测也有所减少。为了理解这种改进，需要结合尺度放大邻域验证和基于对象的技术（只保留匹配的对流对象），这与HWT SFE参与者对多种验证方法的建议相一致。重要性声明"良好"的冰雹预报可以通过多种方式确定，并且必须取决于制导性能和最终用户的观点。这项工作着眼于不同的验证策略，以捕捉在三年的春季预报实验（SFE）在不同的父模型的CAM-HAILCAST冰雹预报模型的性能。通过调查，SFE参与者的输入告知验证策略。与之前的SFE相比，SFE 2021中模型之间的技能差异有所下降。与2019年相比，2021年的FV3模型对对流分布和38毫米（1.5英寸）的预测都有所改进。冰雹的大小，以及从1900到2300 UTC对流的过度预测。
Hail forecasts produced by the CAM-HAILCAST pseudo-Lagrangian hail size forecasting model were evaluated during the 2019, 2020, and 2021 NOAA Hazardous Weather Testbed (HWT) Spring Forecasting Experiments (SFEs). As part of this evaluation, HWT SFE participants were polled about their definition of a “good” hail forecast. Participants were presented with two different verification methods conducted over three different spatiotemporal scales, and were then asked to subjectively evaluate the hail forecast as well as the different verification methods themselves. Results recommended use of multiple verification methods tailored to the type of forecast expected by the end-user interpreting and applying the forecast. The hail forecasts evaluated during this period included an implementation of CAM-HAILCAST in the Limited Area Model of the Unified Forecast System with the Finite Volume 3 (FV3) dynamical core. Evaluation of FV3-HAILCAST over both 1- and 24-h periods found continued improvement from 2019 to 2021. The improvement was largely a result of wide intervariability among FV3 ensemble members with different microphysics parameterizations in 2019 lessening significantly during 2020 and 2021. Overprediction throughout the diurnal cycle also lessened by 2021. A combination of both upscaling neighborhood verification and an object-based technique that only retained matched convective objects was necessary to understand the improvement, agreeing with the HWT SFE participants’ recommendations for multiple verification methods.Significance Statement“Good” forecasts of hail can be determined in multiple ways and must depend on both the performance of the guidance and the perspective of the end-user. This work looks at different verification strategies to capture the performance of the CAM-HAILCAST hail forecasting model across three years of the Spring Forecasting Experiment (SFE) in different parent models. Verification strategies were informed by SFE participant input via a survey. Skill variability among models decreased in SFE 2021 relative to prior SFEs. The FV3 model in 2021, compared to 2019, provided improved forecasts of both convective distribution and 38-mm (1.5 in.) hail size, as well as less overforecasting of convection from 1900 to 2300 UTC.