%0 Dataset
%T Dataset of the Temperature Effect of Arctic Land Vegetation Greening
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/712afedd-b1f0-4e2c-98ae-f45fc0b04247
%W NCDC
%R 10.12072/ncdc.arctic-change.db7154.2026
%A Yu Linfei
%A Leng Guoyong
%K Multi source data;vegetation;land evapotranspiration;temperature effects
%X This dataset is dedicated to filling the research gap in the quantitative assessment of the temperature feedback effect of Arctic vegetation greening on regional warming. The data core is based on the comprehensive processing of remote sensing products and reanalysis data for land surface and atmospheric variables over the Arctic region spanning from 1982 to 2015. The main inputs include: the Normalized Difference Vegetation Index (NDVI) (utilizing multiple products such as GIMMS3g and PKU GIMMS to ensure robustness), near-surface Air Temperature (TEM) (using the multi-product average of CRU TS, UDEL, and CHGN to mitigate single-source uncertainty), surface albedo, evapotranspiration, and water vapor (primarily sourced from ERA5, MERRA-2, and other reanalysis products). All data were uniformly resampled to a 10 km EASE-Grid spatial resolution. The data accuracy assessment employed a comparative validation method against FLUXNET 2015 Arctic flux station observations, using the Correlation Coefficient (CC) and Relative Bias (RB) to ensure the reliability of the input data. Specifically, the multi-product average air temperature was confirmed to possess the highest accuracy, exhibiting the lowest relative bias of -10.36%.