当前位置: X-MOL 学术J. Earth Syst. Sci. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Evaluation of sub-seasonal to seasonal rainfall forecast over Zambia
Journal of Earth System Science ( IF 1.9 ) Pub Date : 2021-02-19 , DOI: 10.1007/s12040-020-01548-0
Bathsheba Musonda , Yuanshu Jing , Matthews Nyasulu , Lucia Mumo

Highlights

  • Monthly S2S reforecast for 20 years obtained from the European Centre for Medium-Range Weather Forecast (ECMWF) were evaluated against the in-situ rainfall data over Zambia using 1-month lead time forecast.

  • The two datasets agree with the rainfall pattern throughout the year thereby, the S2S ECMWF realistically simulates the mean annual cycle skillfully by identifying the wet season from November to March (NDJFM), and the driest season as June to September (JJAS), in agreement with the observations.

  • The S2S ECMWF exhibits a better performance during wet months compared to dry months though depicted a slight wet bias in estimating the observed variation during the wet season.

  • The lowest spatial average value of RMSE and MAE during the wet season (NDJFM) was observed in March while the highest RMSE and MAE were recorded in December.

  • The CRPSS in most of the stations during the wet season (NDJFM) had positive values, while during dry months the results show most of the stations having negative CRPSS values.

Abstract

In this study, monthly S2S reforecast for 20 years obtained from the European Centre for Medium-Range Weather Forecast (ECMWF) were evaluated against the in-situ data. The spatial results show that the two datasets agree with the rainfall pattern throughout the year. The S2S ECMWF realistically simulates the mean annual cycle skillfully by identifying the wet season from November to March (NDJFM), and the driest season as June to September (JJAS), in agreement with the observations. However, the depicted slight wet bias in estimating the observed variation during the wet season. Nevertheless, the ECMWF S2S exhibits a better performance during wet months compared to dry months. This study provides insights into the performance of S2S forecasts and their potential application over Zambia. Future studies need to focus on explaining the observed discrepancies and improvement of S2S forecasts in the region, particularly by the modelling centers.



中文翻译:

赞比亚次季节至季节性降雨预报的评估

强调

  • 使用1个月的提前期预测,对欧洲中距离天气预报中心(ECMWF)获得的20年每月S2S预报值与赞比亚的原地降雨数据进行了评估。

  • 这两个数据集与全年的降雨模式一致,因此,S2S ECMWF通过识别11月至3月的湿季(NDJFM)和最干旱的6月至9月(JJAS)来熟练地模拟平均年周期。与观察。

  • 与干旱月份相比,S2S ECMWF在潮湿月份表现出更好的性能,尽管在估算潮湿季节观察到的变化方面略有潮湿偏差。

  • 在3月的湿季(NDJFM)的RMSE和MAE的空间平均值最低,而在12月则达到最高的RMSE和MAE。

  • 在雨季(NDJFM)期间,大多数气象站的CRPSS值为正,而在干旱月份,结果表明大多数气象站的CRPSS值为负。

抽象的

在这项研究中,对从欧洲中距离天气预报中心(ECMWF)获得的20年每月S2S进行了预测,并进行了现场评估。数据。空间结果表明,这两个数据集与全年的降雨模式一致。与观察结果一致,S2S ECMWF通过识别11月至3月的湿季(NDJFM)和最干旱的6月至9月(JJAS)来熟练地模拟平均年周期。然而,在估计雨季期间观察到的变化时,描绘了轻微的湿偏。但是,与干旱月份相比,ECMWF S2S在潮湿月份表现出更好的性能。这项研究提供了对S2S预测的性能及其在赞比亚的潜在应用的见解。未来的研究需要专注于解释该地区观察到的差异和S2S预测的改进,尤其是通过建模中心。

更新日期:2021-02-19
down
wechat
bug