TY  - Data
T1  - Dataset of the Temperature Effect of Arctic Land Evapotranspiration Variation
A1  - Yu Linfei
A1  - Leng Guoyong
DO  - 10.12072/ncdc.arctic-change.db7152.2026
PY  - 2026
DA  - 2026-05-13
PB  - National Cryosphere Desert Data Center
AB  - Under the context of global warming, vegetation greening in the Arctic is a well-recognized phenomenon, profoundly affecting regional water and energy cycles. Against this backdrop, the present dataset aims to quantify the cooling effect induced by changes in terrestrial evapotranspiration (ET) over significantly greening areas in the Arctic from 1982 to 2015. The results indicate that ET processes exerted an important cooling effect on Arctic climate during summer. Within the significantly greening regions, the long-term mean cooling in July was -0.27°C, in August -0.20°C, and the average for the two months was -0.24°C.This dataset is a derived product calculated based on physical empirical formulas, with core input data sourced from multiple authoritative databases. Specifically, the key ET data were obtained as the ensemble mean of three products—GLEAM (Global Land Evaporation Amsterdam Model), TerraClimate, and Synthesized-ET—to reduce uncertainties associated with any single dataset. Temperature data were obtained from the CRU (Climatic Research Unit) time series, used to calculate latent heat flux and air density. The study extent, i.e., the “significantly greening areas,” was defined using the Peking University GIMMS NDVI product. All input data were harmonized to a spatial resolution of 10 km and a monthly temporal resolution.To ensure data reliability, the ET data, as a key input, underwent a strict accuracy evaluation. A “point-to-pixel” validation strategy was applied, using in-situ measurements from 11 FLUXNET stations across the Arctic as ground truth. Multiple statistical metrics—including correlation coefficient (CC), mean bias (BIAS), and root mean square error (RMSE)—were used for assessment. The results showed that the ensemble mean of the three ET products performed best overall, exhibiting the highest correlation coefficient (0.69) and the lowest RMSE (14.70 mm), and was thus selected as the final basis for calculations. This rigorous validation 
DB  - NCDC
UR  - http://www.ncdc.ac.cn/portal/metadata/cc2f7254-6297-4557-b0a4-4e7b093824b9
ER  -