There is a large agreement that global warming induces changes of precipitation regimes of different nature and amplitude depending on the timescale considered. This question is of special concern regarding extreme rainfall that might have critical socio-environmental consequences. A unified framework is proposed here for detecting trends in extreme rainfall. It is based on the GEV distribution, whose parameters depend both on a simple scaling formulation to account for multiple time durations of rainfall and on time to account for the non-stationarity deriving from climatic trends. The implementation of the model is illustrated in the Sahel region by analyzing 30 in situ rainfall series of 28 years measured at time-steps from 2 to 24 h. While the separate analysis of the point series proves inconclusive for detecting trends at any of the time-steps considered, the inclusion of all the series and time-steps into the proposed unified model allows trends to be detected at a high level of confidence (p-value < 1%). This trend essentially appears in the scale parameter of the regional GEV distribution, involving a 15 to 20% increase of the 10-year rainfall in 28 years, and a 23 to 30% increase of the 100-year rainfall. The main advantages of the proposed framework are (i) its parsimony, allowing for reducing the uncertainty associated with the model inference; (ii) its capacity for detecting trends either in the mean and/or in the variability of the extreme events; and (iii) its ability for producing non-stationary Intensity-Duration-Frequency curves that are coherent over a range of durations of accumulation.

人们一致认为，全球变暖会根据所考虑的时间尺度导致不同性质和幅度的降水状况发生变化。这个问题特别关注可能具有严重社会环境后果的极端降雨。这里提出了一个统一的框架来检测极端降雨的趋势。它基于 GEV 分布，其参数取决于一个简单的比例公式，以说明降雨的多个持续时间，并及时说明源自气候趋势的非平稳性。通过分析在 2 到 24 小时的时间步长测量的 28 年的 30 个原位降雨系列，说明了该模型在萨赫勒地区的实施。p值 < 1%）。这一趋势主要体现在区域GEV分布的尺度参数上，其中28年10年降雨量增加15%～20%，100年降雨量增加23%～30%。所提出框架的主要优点是（i）它的简洁性，允许减少与模型推理相关的不确定性；(ii) 检测极端事件的平均值和/或变异性趋势的能力；(iii) 其产生非平稳强度-持续时间-频率曲线的能力，这些曲线在一定范围的累积持续时间上是一致的。