基于信息熵的我国日降水量随机性和时空差异性

我国日降水过程呈现明显的随机性与时空差异性,如何准确认识其时空变化规律对洪涝灾害防治等实际工作的影响具有重要意义.本文基于1961—2013年全国520个气象站点的日降水数据,选用信息熵指标研究我国日降水量的随机性.结果表明:研究期间,我国东南地区日降水量的随机性大于西北地区,且不同等级日降水量随机性的空间分布存在差异,小雨(降雨量0.1~10 mm,P_0)等级日降水量随机性较大,差异不明显,中雨(10~25 mm,P₁₀)、大雨(25~50 mm,P₂₅)等级日降水量随机性最大,差异明显,暴雨及以上(≥50 mm,P₅₀)等级日降水量随机性最小,差异最明显.整体上,日降水的信息熵值呈上升趋势,表明全球气候变化下我国大部分地区日降水量的随机性增大,尤其表现为极端暴雨发生的频次明显增大.日降水信息熵的空间分布及其变化趋势可以很好地综合反映我国日降水量随机性的空间分布格局,可为洪涝灾害防治、农业规划布局、生态环境规划等提供科学依据.

Stochastic characteristics of daily precipitation and its spatiotemporal difference over China based on information entropy

Daily precipitation process in China showed obvious randomness and spatiotemporal variation. It is important to accurately understand the influence of precipitation changes on control of flood and waterlogging disaster. Using the daily precipitation data measured at 520 stations in China during 1961-2013, we quantified the stochastic characteristics of daily precipitation over China based on the index of information entropy. Results showed that the randomness of daily precipitation in the southeast region were larger than that in the northwest region. Moreover, the spatial distribution of stochastic characteristics of precipitation was different at various grades. Stochastic characteri-stics of P₀(precipitation at 0.1-10 mm) was large, but the spatial variation was not obvious. The stochastic characteristics of P₁₀(precipitation at 10-25 mm) and P₂₅(precipitation at 25-50 mm) were the largest and their spatial difference was obvious. P₅₀(precipitation ≥50 mm) had the smallest stochastic characteristics and the most obviously spatial difference. Generally, the entropy values of precipitation obviously increased over the last five decades, indicating more significantly stochastic characteristics of precipitation (especially the obvious increase of heavy precipitation events) in most region over China under the scenarios of global climate change. Given that the spatial distribution and long-term trend of entropy values of daily precipitation could reflect thespatial distribution of stochastic characteristics of precipitation, our results could provide scientific basis for the control of flood and waterlogging disaster, the layout of agricultural planning, and the planning of ecological environment.