Deterministic Rapid Intensity Forecast Guidance for the Joint Typhoon Warning Center’s Area of Responsibility

IF 3 3区地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES

Weather and Forecasting Pub Date : 2023-09-29 DOI:10.1175/waf-d-23-0084.1

C. R. Sampson, J. A. Knaff, C. J. Slocum, M. J. Onderlinde, A. Brammer, M. Frost, B. Strahl

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Abstract

Abstract Intensity consensus forecasts can provide skillful overall guidance for intensity forecasting at the Joint Typhoon Warning Center as they provide among the lowest mean absolute errors; however, these forecasts are far less useful for periods of rapid intensification (RI) as guidance provided is generally low biased. One way to address this issue is to construct a consensus that also includes deterministic RI forecast guidance in order to increase intensification rates during RI. While this approach increases skill and eliminates some bias, consensus forecasts from this approach generally remain low biased during RI events. Another approach is to construct a consensus forecast using an equally-weighted average of deterministic RI forecasts. This yields a forecast that is generally among the top performing RI guidance, but suffers from false alarms and a high bias due to those false alarms. Neither approach described here is a prescription for forecast success, but both have qualities that merit consideration for operational centers tasked with the difficult task of RI prediction.

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联合台风预警中心责任区确定性快速强度预报指南

强度共识预报提供了最低的平均绝对误差，可以为台风联合预警中心的强度预报提供较好的总体指导;然而，这些预测对快速强化时期的用处要小得多，因为所提供的指导通常是低偏差的。解决这一问题的一种方法是建立一个共识，其中也包括确定性的国际扶轮预测指导，以增加国际扶轮期间的强化率。虽然这种方法提高了技能并消除了一些偏差，但在国际扶轮活动期间，这种方法的共识预测通常保持低偏差。另一种方法是使用确定性RI预测的等加权平均值构建共识预测。这产生的预测通常是表现最好的RI指导之一，但由于这些假警报而受到假警报和高偏差的影响。这里描述的两种方法都不是预测成功的处方，但它们都具有值得承担RI预测这一艰巨任务的运营中心考虑的品质。

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来源期刊

Weather and Forecasting 地学-气象与大气科学

CiteScore

5.20

自引率

17.20%

发文量

131

审稿时长

6-12 weeks

期刊介绍： Weather and Forecasting (WAF) (ISSN: 0882-8156; eISSN: 1520-0434) publishes research that is relevant to operational forecasting. This includes papers on significant weather events, forecasting techniques, forecast verification, model parameterizations, data assimilation, model ensembles, statistical postprocessing techniques, the transfer of research results to the forecasting community, and the societal use and value of forecasts. The scope of WAF includes research relevant to forecast lead times ranging from short-term “nowcasts” through seasonal time scales out to approximately two years.