Rainstorm-scale predictions of climate impacts on the water balance in East African drylands

气候变化给旱地地区带来了巨大的挑战，特别是在社会经济生计与季节性降雨的持续性联系在一起的社区，如东非旱地地区。旱地的一个关键气候特征是极端降水持续时间短，风暴的时空变异性大。然而，世界上大多数干旱地区往往只有稀疏的降水测量数据，因此使用粗分辨率（每日，每周或每月）网格数据集，即使它们可能无法保留单个事件期间的风暴特征。降雨的时间分辨率已被证明对旱地土壤湿度的预测有重大影响（Kipkemoi等人，2021年）。此外，用于评估未来降雨量变化的气候模式通常分辨率较低（10- 100公里），无法捕捉短时间降雨特征。因此，现有降雨量数据的分辨率与旱地降水的特点之间的这种脱节，给预测气候对易发生干旱的旱地的区域水和粮食安全的影响带来了挑战。

Climate change presents great challenges for dryland regions, especially in communities where socioeconomic livelihoods are tied to the consistency of seasonal rainfall such as in the dryland regions of East Africa. A key climatic feature of drylands is short-duration precipitation extremes and high spatio-temporal variability of storms. However, most dryland regions around the world tend to have sparse precipitation gauge data, so coarse-resolution (daily, weekly, or monthly) gridded datasets are used even though they may not preserve the storm characteristics during individual events. The temporal resolution of rainfall has been shown to significantly impact predicted soil moisture in drylands (Kipkemoi et al., 2021). Additionally, climate models used to assess future changes in rainfall are also typically coarse resolution (10-100km) and unable to capture short-duration rainfall characteristics. This disconnect between the resolution of available rainfall data and the characteristics of dryland precipitation, therefore, creates challenges in predicting climate impacts on regional water and food security in drought-prone drylands.