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Comparing the S2S hindcast skills to forecast Iran’s precipitation and capturing climate drivers signals over the Middle East
Theoretical and Applied Climatology ( IF 3.4 ) Pub Date : 2024-03-15 , DOI: 10.1007/s00704-024-04922-w
Habib Allah Ghaedamini , Mohammad Jafar Nazemosadat , Saeed Morid , Sedighe Mehravar

Abstract

To enhance the capabilities of the Subseasonal to Seasonal (S2S) database for forecasting Iran’s southwest precipitation from 1 to 4 weeks ahead, we compared observed precipitation and atmospheric variables with the corresponding hindcasts generated by the KMA, UKMO, ECWMF, and Meteo-France (MF) research centers. This analysis involved several deterministic and probabilistic metrics. Our reference datasets included daily precipitation data from 176 rain gauge stations and the NOAA-based atmospheric circulations data for Dec-April 1995–2014. Most hindcasts underestimated wet events in southern and eastern districts but overestimated them in the western and northern regions. Additionally, all hindcasts overforecasted the frequency of wet events across all lead times. The correlation scores were highest in the first week and declined as lead times increased. The ECMWF had the best correlation in all regions, showing superior deterministic and probabilistic forecast skills in western districts. The UKMO hindcasts, whose accuracy has the highest dependancy on precipitation amount, effectively captured signals of the El-Niño Southern Oscillation (ENSO) and Madden Julian Oscillation (MJO) over the study area and the Middle East. They accurately forecasted the 850 hPa moisture transport and 500 hPa vertical velocity features in these regions, particularly during the rainy phases of MJO. These findings offer valuable insights to enhance the accuracy of operational S2S precipitation forecasts for planning and decision-making in Iran and the Middle East.



中文翻译:

比较 S2S 后报技能以预测伊朗降水并捕获中东气候驱动信号

摘要

为了增强次季节到季节 (S2S) 数据库预测伊朗西南部 1 至 4 周降水的能力,我们将观测到的降水和大气变量与 KMA、UKMO、ECWMF 和 Meteo-France 生成的相应后报进行了比较( MF)研究中心。该分析涉及几个确定性和概率性指标。我们的参考数据集包括来自 176 个雨量站的每日降水量数据以及基于 NOAA 的 1995 年 12 月至 2014 年 4 月的大气环流数据。大多数后报低估了南部和东部地区的降雨事件,但高估了西部和北部地区的降雨事件。此外,所有事后预测都高估了所有交付周期内潮湿事件的频率。相关性得分在第一周最高,并随着交付时间的增加而下降。ECMWF 在所有地区中具有最好的相关性,在西部地区表现出优越的确定性和概率预测能力。UKMO 后报的准确性对降水量的依赖性最高,有效捕获了研究区域和中东上空的厄尔尼诺南方涛动 (ENSO) 和马登朱利安涛动 (MJO) 的信号。他们准确地预测了这些地区的 850 hPa 水汽输送和 500 hPa 垂直速度特征,特别是在 MJO 的雨相期间。这些发现为提高伊朗和中东规划和决策的业务 S2S 降水预报的准确性提供了宝贵的见解。

更新日期:2024-03-15
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