%0 Dataset
%T Daily 2-meter air temperature dataset for the Loess Plateau from WRF simulations (1999-2018)
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/6a529e85-f0ba-48fc-9fdd-51ef4434e314
%W NCDC
%R 10.12072/ncdc.loess.db7329.2026
%A ZHANG Baoqing 
%K WRF simulation;air temperature;long-term;high resolution
%X Accurately characterizing the spatiotemporal distribution of surface air temperature at 2 m height (T2) is a fundamental prerequisite for regional climate change analysis. However, observed T2 data inherently encompass the combined influences of natural climate variability and human activities on regional hydroclimatic conditions. This is particularly significant in regions undergoing large-scale vegetation restoration, such as the Loess Plateau, where the quantitative contribution of human interventions—primarily through ecological engineering projects—to regional climate change remains insufficiently quantified. To elucidate the hydroclimatic effects of vegetation restoration, this study employed the Weather Research and Forecasting (WRF) regional climate model. The model simulations were driven by ERA-Interim reanalysis data, with land surface conditions prescribed using two distinct datasets: one incorporating dynamically varying surface parameters and another maintaining static parameters. Long-term, high-resolution climate simulations were conducted over the Loess Plateau under two contrasting scenarios: vegetation restoration (DYN) and a control without restoration (CTL). This framework produced two corresponding datasets of daily mean T2 for the period 1999–2018 at a 10 km spatial resolution. Comparative validation with the China Meteorological Forcing Dataset (CMFD) indicated that the WRF simulations under both scenarios achieved a spatial correlation coefficient (PCC) greater than 0.94, a root mean square error (RMSE) below 1.17 °C, and biases predominantly within the range of −1 °C to 1 °C. These metrics confirm the good applicability of the simulated data over the Loess Plateau. Consequently, these datasets provide a reliable and robust foundation for the quantitative assessment of the hydroclimatic effects induced by vegetation restoration on the Loess Plateau.The dataset is stored in NetCDF format (*.nc) and comprises two data files. The naming convent