欧洲年最高气温分布的变化

Q1 Mathematics
G. Auld, G. Hegerl, I. Papastathopoulos
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引用次数: 0

摘要

摘要在这项研究中,我们检测并量化了1950-2018年欧洲日温度的大型观测网格数据集中年最高日最高温度(TXx)的分布变化。考虑了几种统计模型,每种模型都使用广义极值(GEV)分布分析TXx, GEV参数在空间上平滑变化。与之前的几项研究在网格盒级别拟合独立的GEV模型相比,我们的模型从相邻的网格盒中提取信息,以获得更有效的参数估计。使用大气CO2的对数作为协变量,允许GEV位置和尺度参数随时间变化。GEV位置参数的变化最为强烈,TXx分布通常向更热的温度方向移动。在我们的空间范围内,以2018年气候为基础的100年TXx的平均气温比以1950年气候为基础的100年气温高约2°C(95%可信区间为[2.03,2.12]°C)。此外,在整个空间域中平均,基于1950年气候的TXx的100年回归水平大致相当于2018年气候的6年回归水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Changes in the distribution of annual maximum temperatures in Europe
Abstract. In this study we detect and quantify changes in the distribution of the annual maximum daily maximum temperature (TXx) in a large observation-based gridded data set of European daily temperature during the years 1950–2018. Several statistical models are considered, each of which analyses TXx using a generalized extreme-value (GEV) distribution with the GEV parameters varying smoothly over space. In contrast to several previous studies which fit independent GEV models at the grid-box level, our models pull information from neighbouring grid boxes for more efficient parameter estimation. The GEV location and scale parameters are allowed to vary in time using the log of atmospheric CO2 as a covariate. Changes are detected most strongly in the GEV location parameter, with the TXx distributions generally shifting towards hotter temperatures. Averaged across our spatial domain, the 100-year return level of TXx based on the 2018 climate is approximately 2 ∘C (95 % confidence interval of [2.03,2.12] ∘C) hotter than that based on the 1950 climate. Moreover, averaged across our spatial domain, the 100-year return level of TXx based on the 1950 climate corresponds approximately to a 6-year return level in the 2018 climate.
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来源期刊
Advances in Statistical Climatology, Meteorology and Oceanography
Advances in Statistical Climatology, Meteorology and Oceanography Earth and Planetary Sciences-Atmospheric Science
CiteScore
4.80
自引率
0.00%
发文量
9
审稿时长
26 weeks
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