Seasonal Prediction of Summer Precipitation over East Africa Using NUIST-CFS1.0

Abstract

East Africa is particularly vulnerable to precipitation variability, as the livelihood of much of the population depends on rainfed agriculture. Seasonal forecasts of the precipitation anomalies, when skillful, can therefore improve implementation of coping mechanisms with respect to food security and water management. This study assesses the performance of Nanjing University of Information Science and Technology Climate Forecast System version 1.0 (NUIST-CFS1.0) on forecasting June–September (JJAS) seasonal precipitation anomalies over East Africa. The skill in predicting the JJAS mean precipitation initiated from 1 May for the period of 1982–2019 is evaluated using both deterministic and probabilistic verification metrics on grid cell and over six distinct clusters. The results show that NUIST-CFS1.0 captures the spatial pattern of observed seasonal precipitation climatology, albeit with dry and wet biases in a few parts of the region. The model has positive skill across a majority of Ethiopia, Kenya, Uganda, and Tanzania, whereas it doesn’t exceed the skill of climatological forecasts in parts of Sudan and southeastern Ethiopia. Positive forecast skill is found over regions where the model shows better performance in reproducing teleconnections related to oceanic SST. The prediction performance of NUIST-CFS1.0 is found to be on a level that is potentially useful over a majority of East Africa.

摘要

在东非,大部分人口的生计依赖于旱作农业,故其特别容易受到降水变化的影响。因此,降水异常的季节性预测技巧的提高能够改进与粮食安全和水资源管理相关的应对机制的实施。本研究评估了南京信息工程大学气候预报系统1.0版本(NUIST-CFS1.0)对东非地区6–9月(JJAS)季节性降水异常的预报性能。即在六个不同的格点区域对1982–2019年期间,模式从5月1日起报的JJAS平均降水进行了确定性和概率性技巧预测的评估。结果表明,尽管在东非的一些区域存在干湿偏差,但是NUIST-CFS1.0能够再现观测到的夏季降水气候态的空间分布特征。该模式在埃塞俄比亚、肯尼亚、乌干达和坦桑尼亚的大部分地区预测技巧都为正,而在苏丹和埃塞俄比亚东南部的部分地区预测性能较差。模式在与海温具有遥相关的区域有较好的预测性。NUIST-CFS1.0的预测性能在东非大部分地区是有潜在用途的。

Electronic Supplementary Material to

Seasonal Prediction of Summer Precipitation over East Africa Using NUIST-CFS1.0