TY  - Data
T1  - Long-term daily temperature dataset for the Loess Plateau from 1982 to 2020
A1  - ZHANG Baoqing 
DO  - 10.12072/ncdc.loess.db7327.2026
PY  - 2026
DA  - 2026-05-21
PB  - National Cryosphere Desert Data Center
AB  - Temperature time series data serve as crucial fundamental data for global and regional climate research, hydrological modeling, and ecosystem assessments. However, despite the existence of various air temperature data products, the assessment of long-term temperature dynamics and trends at the regional scale remains subject to some uncertainty. This uncertainty arises primarily from the uneven distribution of observational networks over the Loess Plateau and the systematic biases between reanalysis data and measured values. To address this issue, this study utilizes version 1.7 of the China Meteorological Forcing Dataset (CMFD) to generate a historical air temperature data product for the Loess Plateau covering the period from 1982 to 2020. The spatial coverage of the dataset spans from 33.75°N to 41.25°N in latitude and 100.95°E to 114.55°E in longitude, featuring a high spatial resolution of 0.1° and a daily temporal resolution. Compared to other datasets, the core advantage of this product lies in its high-resolution temperature data, which enables a more detailed characterization of the spatio-temporal distribution of air temperature. This significantly enhances the capability to simulate localized extreme temperature events, such as heatwaves, thereby providing more reliable data support for regional climate modeling and research on extreme temperature events.This dataset is saved in NetCDF format (*.nc). The data file is named in the format of LoessPlateau_temp_1982_2020, where LoessPlateau stands for the study area and temp refers to the variable name.The air temperature variable is defined as yearly_day_temp, with daily temporal resolution and 10 km spatial resolution, spanning the period 1982–2020. Variables lat and lon represent the latitude and longitude of grid cells respectively.
DB  - NCDC
UR  - http://www.ncdc.ac.cn/portal/metadata/de737835-3206-4dac-825d-8cb76c813692
ER  -