S2S模式下热带气旋降水的气候学

IF 3 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Weather and Forecasting Pub Date : 2023-07-28 DOI:10.1175/waf-d-23-0029.1
J. L. García-Franco, Chia-ying Lee, S. Camargo, M. Tippett, Daehyun Kim, A. Molod, Y. Lim
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引用次数: 1

摘要

本研究评估了热带气旋降水(TCP)在海底到季节(S2S)项目中的代表性。S2S模型中的全球降水分布显示出多模式平均系综中的相关偏差,其特征是总降水量(P)和TCP中的湿偏差,大西洋除外。在南印度洋和南太平洋等盆地,TCP偏差可占总P偏差的50%以上。这些偏差的大小和空间模式随交付周期变化很小。TCP偏差的起源可归因于热带气旋发生频率的偏差。S2S模型模拟大西洋和北太平洋西部的TC太少,而南半球和北太平洋东部的TC太多。在风暴尺度上,由于弱TC的比例过高,模型中风暴中心附近的平均峰值降水量低于观测值。然而,在一些模型中,这种偏差被更大半径(300-500公里)下高于观测到的降水率所抵消。对每个网格点每个TC的平均TCP的分析表明,TCP速率估计过高,尤其是在近赤道的印度洋和西太平洋。这些发现表明,TC发生和风暴级降水的模拟需要更好的表示,以减少TCP偏差,提高平均和极端总P的亚季节预测能力。
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Climatology of tropical cyclone precipitation in the S2S models
This study evaluates the representation of tropical cyclone precipitation (TCP) in reforecasts from the Subseasonal-to-Seasonal (S2S) Project. The global distribution of precipitation in S2S models shows relevant biases in the multi-model mean ensemble which are characterized by wet biases in total precipitation (P) and TCP, except for the Atlantic. The TCP biases can contribute more than 50% of total P biases in basins such as the Southern Indian Ocean and South Pacific. The magnitude and spatial pattern of these biases exhibit little variation with lead time. The origins of TCP biases can be attributed to biases in the frequency of tropical cyclone occurrence (TCF). The S2S models simulate too few TCs in the Atlantic and Western North Pacific and too many TCs in the Southern Hemisphere and Eastern North Pacific. At the storm-scale, the average peak precipitation near the storm center is lower in the models than observations due to a too high proportion of weak TCs. However, this bias is offset in some models by higher than observed precipitation rates at larger radii (300-500 km). An analysis of the mean TCP for each TC at each grid-point reveals an overestimation of TCP rates, particularly in the near-equatorial Indian and Western Pacific Oceans. These findings suggest that the simulation of TC occurrence and the storm-scale precipitation require better representation in order to reduce TCP biases and enhance the subseasonal prediction skill of mean and extreme total P.
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来源期刊
Weather and Forecasting
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.
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