广东地处东南沿海，常常受到台风侵袭，极端降水事件多发。在全球变暖趋势下，水循环加剧，降水时空分配格局被改变，并且在未来会随气候变化进一步改变，为区域带来更多极端降水灾害。对广东省的极端降水时空变化规律进行探索，有助于为理解区域水循环过程提供理论参考，以及为广东省防灾减灾政策的制定提供依据。本文利用高时间分辨率的小时降水资料，通过数据处理划分次降水，结合地学统计分析方法，依据极端降水指标分析广东省小时尺度和次尺度的极端降水时空分异规律。结果表明，从小时尺度上：（1）广东省25百分位的小时降水阈值基本一致，为0.2mm；50、75和95百分位的整体由南向北递减，取值范围分别为0.55-0.9mm、1.8-3.4mm和7.5-16.5mm，并且站点间小时降水阈值的差异随极端程度的增加而逐渐增大。（2）2年、5年和10年重现期的最大小时雨量分别在30-60mm、40-75mm和45-90mm之间，总体表现为由沿海向内陆递减；20年、50年和100年重现期的小时降水极值则分别在50-100mm、60-120mm和60-140mm之间，表现出高值中心特征，形成三个高值中心。（3）对于小时降水均值，在95%信度水平上小于25百分位的主要表现为下降趋势，大于50、75和95百分位的则主要为上升趋势，后者上升和显著上升趋势比例分别为95.38%和30.77%、93.85%和29.23%、63.08%和4.62%，下降趋势比例分别为4.62%、6.15%和36.92%，没有站点呈现显著的下降趋势；对于小时降水时数，在0.05的显著性水平上小于25百分位、大于50百分位的主要表现为下降趋势，大于75和95百分位的则为上升趋势。历时较短时各站点小时降水时数变化趋势具有更明显的差异。从次降水事件尺度上：（1）次降雨量、次降雨动能、最大小时雨强、次降雨侵蚀力以及暖季降雨侵蚀力南高北低，次降雨历时整体东高西低。与其他指标相比，站点间次降雨侵蚀力以及暖季降雨侵蚀力差别更为明显。（2）从站点比例看，六个次降水指标在0.05的显著性水平上主要表现为上升趋势。对于上升趋势和显著上升趋势，次降雨量为76.92%和13.85%，次降雨历时为75.38%和10.77%，次降雨动能为81.54%和23.08%，最大小时雨强为95.38%和43.08%，次降雨侵蚀力为76.92%和23.08%，暖季降雨侵蚀力为63.08%和13.85%；对于下降趋势，次降雨量为23.08%，次降雨历时为24.62%，次降雨动能为18.46%，最大小时雨强为4.62%，次降雨侵蚀力为23.08%，暖季降雨侵蚀力为36.92%，没有表现为显著下降趋势的站点。关于逐年变化，次降水指标均表现为上升趋势，次降雨动能、最大小时雨强、次降雨侵蚀力线性回归方程通过了0.05水平的显著性检验。总而言之，广东省不同站点的极端降水情况存在差异，并且随极端程度的不同而有所变化；时间尺度上，广东省极端降水的降雨强度趋于增加。极端降水增强导致城市内涝、土壤侵蚀等次生灾害的风险也随之增长，需要提升针对极端降水的防灾减灾和应急处置能力，以应对极端降水增加趋势带来的挑战。

Guangdong is located in the southeast coast, often hit by typhoons, and extreme precipitation events occur frequently. Under the trend of global warming, the water cycle intensifies, and the spatiotemporal distribution pattern of precipitation is changed, which will further change with climate change in the future, bringing more extreme precipitation disasters to the region. Exploring the spatiotemporal variation of extreme precipitation in Guangdong Province can provide theoretical reference for understanding the regional water cycle process and provide a basis for formulating disaster prevention and mitigation policies in Guangdong Province. This paper uses high-resolution hourly precipitation data, divides precipitation events through data processing, and combines geoscientific statistical analysis methods to analyze the temporal and spatial variability of extreme precipitation on both hourly and precipitation event scales in Guangdong Province based on extreme precipitation indicators. The results show that on an hourly scale: (1) The hourly precipitation thresholds for the 25th percentile in Guangdong Province are basically the same, at 0.2mm; The values of the 50th, 75th, and 95th percentiles decrease from south to north overall, with values ranging from 0.55-0.9mm, 1.8-3.4mm, and 7.5-16.5mm, respectively. The difference in hourly precipitation thresholds between stations gradually increases with the increase of extreme degrees. (2) The maximum hourly rainfall for 2-year, 5-year, and 10-year return periods is between 30-60mm, 40-75mm, and 45-90mm, respectively, with an overall decrease from coastal to inland; The hourly precipitation extremes for 20-year, 50-year, and 100-year return periods are between 50-100mm, 60-120mm, and 60-140mm, respectively, exhibiting the characteristics of high value centers, forming three high value centers.  (3) For the average hourly precipitation, at the 95% confidence level, those below the 25 percentile show a downward trend, while those above the 50, 75, and 95 percentiles show an upward trend. The proportion of the latter's upward and significant upward trends is 95.38% and 30.77%, 93.85% and 29.23%, 63.08% and 4.62%, respectively, and the proportion of downward trends is 4.62%, 6.15%, and 36.92%, respectively. No station shows a significant downward trend; For hourly precipitation hours, at a significance level of 0.05, those below the 25th percentile and above the 50th percentile show a downward trend, while those above the 75th and 95th percentile show an upward trend. The variation trend of hourly precipitation hours at each station has a more significant difference when the duration is relatively short. On the scale of precipitation events: (1) Rainfall, rainfall kinetic energy, maximum hourly rainfall intensity, rainfall erosivity, and rainfall erosivity in the warm season are higher in the south and lower in the north, while rainfall duration is generally higher in the east and lower in the west. Compared with other indicators, rainfall erosivity or warm season rainfall erosivity between stations is more significant. (2) From the perspective of station proportion, the six precipitation indicators mainly show an upward trend at the significance level of 0.05. For the upward trend and significant upward trend, the rainfall is 76.92% and 13.85%, the rainfall duration is 75.38% and 10.77%, the rainfall kinetic energy is 81.54% and 23.08%, the maximum hourly rainfall intensity is 95.38% and 43.08%, the rainfall erosivity is 76.92% and 23.08%, and the warm season rainfall erosivity is 63.08% and 13.85%; For the downward trend, the rainfall is 23.08%, the rainfall duration is 24.62%, the rainfall kinetic energy is 18.46%, the maximum hourly rainfall intensity is 4.62%, the rainfall erosivity is 23.08%, and the warm season rainfall erosivity is 36.92%. There are no stations showing a significant downward trend. Regarding the annual changes, the indicators of precipitation events have shown an upward trend, and the linear regression equations for the kinetic energy, maximum hourly rainfall intensity and rainfall erosivity have passed the significance test at the 0.05 level. In summary, there are differences in extreme precipitation conditions at different stations in Guangdong Province, and they vary with the degree of extremes; On the time scale, the rainfall intensity of extreme precipitation in Guangdong Province tends to increase. The risk of secondary disasters such as urban waterlogging and soil erosion caused by increased extreme precipitation also increases. It is necessary to enhance disaster prevention, reduction, and emergency response capabilities for extreme precipitation to address the challenges posed by the increasing trend of extreme precipitation.