A dataset of climate extreme indices at 0.1° resolution in China (1979–2018)

在全球气候变化的背景下，极端天气事件频发，对生态环境和人类社会产生了重大影响。特别是，复合极端事件的发生，如气温上升、局部干旱和高温威胁增加，同时变暖也导致春霜冻的风险增加，对农业生产产生各种复合和连锁效应。对极端天气事件的研究对于准确定量预测和预防灾难性天气事件，保护生态环境和人们的生命财产，减少损失至关重要。然而，现有的极端气候指数数据集由于时空分辨率低，限制了区域极端气候的影响和评估研究。本研究基于中国地表气象要素驱动数据集 （CMFD） 和中国近地表气温数据集 （CDAT） 使用 R 语言程序包 climdex.pcic 计算了 1979-2018 年中国 0.1° 极端气候指数数据集 CECID（中国极端气候指数数据集），该数据集涵盖了 27 个极端气候指数。与现有的极端气候指数数据集 HadEX3、CEI_0p25 和 CECID_0p25 相比，大部分指标（如霜冻日数 FD、热带夜晚 TR、中雨日数 R10mm、年降水量 PRCPTOT）的相关系数均在 0.7 以上，保证了数据集的较强可靠性。此外，其 0.1° 的空间分辨率超过了同类数据集，增强了其可用性。CECID 可用于研究中国极端气候事件的特点及其对生态系统的影响。它在灾害预防、气候变化评估和相关领域具有实用价值和意义。

Against the backdrop of global climate change, extreme weather events occur frequently, exerting significant impacts on ecological environments and human society. Particularly, the occurrence of compound extreme events—such as rising temperatures, increasing regional drought and heatwave threats, as well as elevated spring frost risk driven by warming—exerts various compound and cascading effects on agricultural production. Research on extreme weather events is critical for the accurate quantitative prediction and prevention of catastrophic weather events, the protection of ecological environments and human lives and property, and the reduction of disaster losses. However, existing extreme climate index datasets suffer from low spatiotemporal resolution, which constrains research on the impacts and assessment of regional extreme climate. This study calculated the 0.1° Chinese Extreme Climate Index Dataset (CECID, Chinese Extreme Climate Index Dataset) for the period 1979–2018 using the R package climdex.pcic, based on the China Meteorological Forcing Dataset (CMFD) and China Near-Surface Air Temperature Dataset (CDAT). This dataset covers 27 extreme climate indices. Compared with existing extreme climate index datasets including HadEX3, CEI_0p25 and CECID_0p25, the correlation coefficients of most indices (e.g., frost days FD, tropical nights TR, moderate rain days R10mm, annual total precipitation PRCPTOT) all exceed 0.7, which ensures the strong reliability of this dataset. In addition, its 0.1° spatial resolution outperforms that of similar datasets, enhancing its usability. CECID can be used to study the characteristics of extreme climate events in China and their impacts on ecosystems. It holds practical value and significance for disaster prevention, climate change assessment and related research fields.

搜集汇总

背景与挑战

背景概述

该数据集是一个高分辨率（0.1°）的中国极端气候指数数据集，覆盖1979-2018年，包含27个指数，基于CMFD和CDAT数据计算生成。其特点是空间分辨率超过同类数据集，且大部分指标具有高可靠性（相关系数在0.7以上），适用于研究极端气候事件及其对生态系统的影响、灾害预防和气候变化评估。