Changes in the distribution of annual maximum temperatures in Europe
Changes in the distribution of annual maximum temperatures in Europe
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DOI：
10.5194/ascmo-9-45-2023
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发表时间：
2023-05
影响因子：
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通讯作者：
G. Auld;G. Hegerl;I. Papastathopoulos
中科院分区：
文献类型：
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作者：
G. Auld;G. Hegerl;I. Papastathopoulos
抽象的。在这项研究中，我们检测并量化了 1950 年至 2018 年期间欧洲每日温度的基于观测的大型网格数据集中的年度最高每日最高温度 (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) 分布来分析 TXx，其中 GEV 参数在空间上平滑变化。与之前在网格盒级别拟合独立 GEV 模型的几项研究相比，我们的模型从相邻网格盒中提取信息以实现更有效的参数估计。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明显，TXx 分布通常向温度更高的方向移动。在我们的空间域内平均，基于 2018 年气候的 TXx 100 年回归水平比基于 1950 年气候的 TXx 100 年回归水平大约高 2 ∘C（95% 置信区间为 [2.03,2.12] ∘C）。此外，在我们的空间域内平均，基于 1950 年气候的 TXx 100 年回报水平大约相当于 2018 年气候的 6 年回报水平。
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.