Uncertainty,entropy, scaling and hydrological stochastics. 1. Marginal distributional properties of hydrological processes and state scaling / Incertitude,entropie, effet d'échelle et propriétés stochastiques hydrologiques. 1. Propriétés distributionnelles marginales des processus hydrologiques et échelle d'état     

《水文科学杂志》2013,58(3)

Abstract

The well-established physical and mathematical principle of maximum entropy (ME), is used to explain the distributional and autocorrelation properties of hydrological processes, including the scaling behaviour both in state and in time. In this context, maximum entropy is interpreted as maximum uncertainty. The conditions used for the maximization of entropy are as simple as possible, i.e. that hydrological processes are non-negative with specified coefficients of variation (CV) and lag one autocorrelation. In this first part of the study, the marginal distributional properties of hydrological variables and the state scaling behaviour are investigated. Application of the ME principle under these very simple conditions results in the truncated normal distribution for small values of CV and in a nonexponential type (Pareto) distribution for high values of CV. In addition, the normal and the exponential distributions appear as limiting cases of these two distributions. Testing of these theoretical results with numerous hydrological data sets on several scales validates the applicability of the ME principle, thus emphasizing the dominance of uncertainty in hydrological processes. Both theoretical and empirical results show that the state scaling is only an approximation for the high return periods, which is merely valid when processes have high variation on small time scales. In other cases the normal distributional behaviour, which does not have state scaling properties, is a more appropriate approximation. Interestingly however, as discussed in the second part of the study, the normal distribution combined with positive autocorrelation of a process, results in time scaling behaviour due to the ME principle.  相似文献   

IPCC AR6报告解读：极端天气气候事件变化     

周波涛  钱进 《气候变化研究进展》2021,17(6):713-718

与IPCC第五次评估报告（AR5）相比,在第六次评估报告（AR6）评估中,观测的极端天气气候事件变化证据,特别是归因于人为影响的证据加强。人类活动造成的气候变化已影响到全球每个区域的许多极端天气气候事件。随着未来全球变暖进一步加剧,预估极端热事件、强降水、农业生态干旱的强度和频次以及强台风（飓风）比例等将增加,越罕见的极端天气气候事件,其发生频率的增长百分比越大。这些结论再次凸显了应对气候变化和极端天气气候事件的必要性和紧迫性。  相似文献   

大连地区阵风系数特征分析     

李昱茜  杨景泰  隋玉秀  邬晓冬  张黎红  孙立娟  王蕾  肖剑 《气象与环境学报》2022,38(5):98-105

利用2015年5月至2020年4月辽宁省大连地区9个国家气象站、2017年165个区域气象站逐10 min测风资料, 从风向、风级、月际变化、日变化、空间分布和天气影响系统等对大连地区最大、平均、最小阵风系数进行统计分析。结果表明: 1—12月平均阵风系数的变化范围为1.66~1.77, 秋末冬初平均阵风系数偏大, 春夏季节偏小; 与冷空气相对应风向的平均阵风系数大于与暖空气相对应的风向; 随着风级的增大, 最大、最小阵风系数向平均阵风系数收敛; 不同风级下阵风系数的频率分布均呈单峰型分布, 风级越大, 分布范围越窄。除西南风外, 其他风向的阵风系数均表现出白天大、夜间小的特点。大连地区阵风系数具有明显的地域特点, 东南和西北部沿海区域的阵风系数比内陆和西南沿海偏小, 风向基本不影响阵风系数的空间分布。大连的大风过程多受海上气旋和高压前部双系统共同影响, 气旋、台风以及雷暴大风的平均阵风系数大于同风级的平均值。  相似文献   

用Gumbel极值分布推算气候极值的方法   总被引：1，自引：0，他引：1  

胡基福  姜宏川  周庆满  林滋新 《中国海洋大学学报(自然科学版)》1993,(1)

介绍了用Gumbel极值分布理论推算气候极值的矩法、Thomas曲线公式和最小二乘法。并计算多年一遇的年最高气温、年最大均风速、年最大日降雨量和年最大波高。指出,变率小的要素极值再现期短;变率大的要素极值再现期长;Thomas曲线公式的计算结果较其它两种方法接近历史实况,且计算简便。  相似文献   

Changes of temperature extremes for 1960–2004 in Far-West China     

Qiang Zhang  Chong-Yu Xu  Zengxin Zhang  Yongqin David Chen 《Stochastic Environmental Research and Risk Assessment (SERRA)》2009,23(6):721-735

The spatial and temporal patterns of the temperature extremes defined by 5th and 95th percentiles based on daily maximum/minimum temperature dataset were analyzed using Mann–Kendall test and linear regression method. The research results indicate that: (1) the seasonal minimum temperature is in stronger increasing trend than the seasonal maximum temperature; (2) in comparison with the changes of the maximum temperature, more stations display significantly increasing trends of minimum temperature in frequency and intensity; (3) comparatively, more stations have significantly decreasing trends in the intra-seasonal extreme temperature anomaly in summer and winter than in spring and autumn. The areal mean minimum temperature is in stronger increasing trend than areal mean maximum temperature; (4) the warming process in the Far-West (FW) China is characterized mainly by significantly increasing minimum temperature. The research will be helpful for local human mitigation to alterations in water resource and ecological environment in FW China due to changes of temperature extremes, as the ecologically fragile region of China.  相似文献