摘要
评估当前和未来多年冻土空间分布和动态变化对全球碳循环模拟、气候变化预测以及工程风险评估至关重要。本文使用经广泛验证和应用的半经验模型Kudryavtsev方法,综合考虑温度、积雪、植被、土壤等因素对冻土的影响,以国际耦合模式比较计划第六阶段(CMIP6)模式模拟结果和SoilGrids 2.0数据集等作为输入,计算了2015-2100年北半球冻土顶板温度与活动层厚度在SSP126、SSP245、SSP370和SSP585四种不同情景下的逐年时间序列数据,并根据顶板温度计算了北半球冻土面积。该数据集填补了未来不同情境下冻土分布预测数据的空缺,为冻土退化、气候变化、北极生态等相关研究提供了数据参考。数据集包括2015-2100年逐年以下实验数据:(1)冻土顶板温度数据;(2)活动层厚度数据;(3)冻土面积数据。数据集存储为.tif和.xls格式,空间分辨率为0.625°×0.4712°,由690个数据文件组成,数据量为35.6 MB。
Understanding the spatial distribution and dynamics of current and future permafrost is critical for global carbon flow simulation, climate change prediction, and engineering risk assessment. The 0.625°×0.4712° raster dataset of temperature at the top of permafrost and active layer thickness in the northern hemisphere(2015-2100) was developed using the widely validated and applied Kudryavtsev method, which integrates the effects of temperature, snow, vegetation, and soil on permafrost, based on the model outputs from the sixth phase of the International Coupled Model Intercomparison Project(CMIP6) and the Soil Grids 2.0 dataset. The data were calculated under four different scenarios, SSP126, SSP245, SSP370, and SSP585, from 2015 to 2100. The permafrost area was obtained based on the temperature at the top of the permafrost. This dataset fills the gap in permafrost distribution data for the future under different scenarios for CMIP6. It includes the data covering 2015-2100:(1) mean annual temperature at the top of the permafrost;(2) annual active layer thickness;and(3) annual permafrost area. The resolution of the spatial data is 0.625°×0.4712°. The dataset is archived in.tif and.xls data formats, and consists of 690 data files with data size of 35.6 MB(Compressed to one single file with 27.9 MB).
作者
吴潇然
赵娜
叶延磊
Wu,X.R.;Zhao,N.;Ye,Y.L.(State Key Laboratory of Resources and Environmental Information System,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China;College of Resources and Environment,University of Chinese Academy of Sciences,Beijing 100049,China;Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application,Nanjing 210023,China;Zhengyuan Geomatics Group Co.,Ltd.,Beijing 101300,China)
出处
《全球变化数据学报（中英文）》
CSCD
2022年第3期479-486,V0479-V0486,共16页
Journal of Global Change Data & Discovery
基金
中国科学院(XDA20030203)。
