An evaluation of the consistency of extremes in gridded precipitation data sets
An evaluation of the consistency of extremes in gridded precipitation data sets
复制标题
DOI：
10.1007/s00382-018-4537-0
复制
发表时间：
2019-01
期刊：
影响因子：
4.6
通讯作者：
B. Timmermans;M. Wehner;D. Cooley;T. O’Brien;Harinarayan Krishnan
中科院分区：
文献类型：
--
作者：
B. Timmermans;M. Wehner;D. Cooley;T. O’Brien;Harinarayan Krishnan
注意到了解降水极值的强烈必要性，以及相当大的不确定性影响观测数据集，本文比较了一些广泛使用的每日网格产品中极值的表示，这些产品来自雨量计数据、卫星检索和对美国邻近地区的再分析。分析基于多元极值理论中出现的“尾依赖性”概念，推断产品两两比较降水概率分布联合尾的时间依赖性水平。通过这种方式，我们将产品范围视为一个整体，并检查成员之间的关系，而不是试图定义或比较产品与某些基本事实。还计算了产品之间的线性相关性。每年和季节产品组之间的巨大差异与源数据和复杂的地形有关。特别是，基于雨量计数据的产品显示出显著的相似性，但差异很大，与卫星产品相比，山区DJF期间几乎完全丧失了极值依赖性。此外，模拟的再预报结果显示与大规模极端天气在时间上有一定的一致性。在所有产品中发现的差异的多样性和程度提出了关于其使用的重要问题，我们敦促谨慎，特别是来自卫星数据的产品。
Noting a strong imperative to understand precipitation extremes, and that considerable uncertainty affects observational data sets, this paper compares the representation of extremes in a number of widely used daily gridded products, derived from rain gauge data, satellite retrieval and reanalysis for the conterminous United States. Analysis is based upon the concept of “tail dependence” arising in multivariate extreme value theory, and we infer the level of temporal dependence in the joint tail of the precipitation probability distribution for pairwise comparisons of products. In this way, we consider the range of products more like an ensemble and examine the relationships between members, and do not attempt to define, or compare products to, some ground truth. Linear correlation between products is also computed. Considerable discrepancy between groups of products, both annually and seasonally, is linked to source data and complex terrain. In particular, products based on rain gauge data showed remarkable similarity, but differed considerably, showing almost total loss of extremal dependence during DJF in mountainous regions, when compared with satellite products. Additionally, simulated re-forecasts revealed reasonable temporal agreement with large scale generated extremes. The diversity and extent of discrepancies identified across all products raises important questions about their use, and we urge caution, particularly for products derived from satellite data.