CHELSAcruts - High resolution temperature and precipitation timeseries for the 20th century and beyond

CHELSAcruts is a delta change monthly climate dataset for the years 1901-2016 for mean monthly maximum temperatures, mean monthly minimum temperatures, and monthly precipitation sum. Here we use the delta change method by B-spline interpolation of anomalies (deltas) of the CRU TS 4.01 dataset. Anomalies were interpolated between all CRU TS grid cells and are then added (for temperature variables) or multiplied (in case of precipitation) to high resolution climate data from CHELSA V1.2 (Karger et al. 2017, Scientific Data). This method has the assumption that climate only varies on the scale of the coarser (CRU TS) dataset, and the spatial pattern (from CHELSA) is consistent over time. This is certainly a rather crude assumption, and for time periods for which more accurate data is available CHELSAcruts should be avoided if possible (e.g. use CHELSA V1.2 for 1979-2015). Different to CHELSA V1.2, CHELSAcruts does not take changing wind patterns, or temperature lapse rates into account, but rather expects them to be constant over time, and similar to the long term averages.
CHELSAcruts is licensed under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.

CHELSAcruts是一套覆盖1901-2016年的逐月气候增量变化数据集，包含月均最高气温、月均最低气温与月降水量总和三类变量。本数据集采用基于CRU TS 4.01数据集距平（增量）的B样条插值（B-spline interpolation）增量变化方法：首先将距平在所有CRU TS网格单元间进行插值，随后针对气温变量将插值结果与CHELSA V1.2（Karger等，2017，《Scientific Data》）的高分辨率气候数据相加，针对降水变量则进行相乘操作。该方法假设气候仅在分辨率较粗的CRU TS数据集尺度上发生变化，且源自CHELSA的空间格局随时间保持一致。这显然是一个较为粗略的假设，若存在更精确的气候数据，则应尽量避免使用CHELSAcruts数据集（例如1979-2015年可使用CHELSA V1.2）。与CHELSA V1.2不同，CHELSAcruts未考虑风场模式或气温递减率的时空变化，而是假设它们随时间保持恒定，且与长期平均值一致。
CHELSAcruts采用知识共享署名2.0通用（Creative Commons Attribution 2.0 Generic，CC BY 2.0）许可协议进行授权。

搜集汇总

背景与挑战

背景概述

CHELSAcruts是一个高分辨率月度气候数据集，覆盖1901年至2016年，提供全球范围内的月平均最高温度、月平均最低温度和月降水总和数据。它采用delta change方法，通过B样条插值CRU TS 4.01的异常数据，并结合CHELSA V1.2的高分辨率空间模式生成，适用于长期气候分析，但假设气候仅在粗分辨率尺度上变化。