HRLT: a high-resolution (1 d, 1 km) and long-term (1961–2019) gridded dataset for surface temperature and precipitation across China

作者：Rongzhu Qin, Zeyu Zhao, Jia Xu, Jian‐Sheng Ye, Feng‐Min Li, Feng Zhang · 发表于：Earth system science data · 年份：2022 · DOI：10.5194/essd-14-4793-2022 · 被引用次数：95 · 研究领域：Climate variability and models、Precipitation Measurement and Analysis、Hydrology and Watershed Management Studies

Accurate long-term temperature and precipitation estimates at high spatial and temporal resolutions are vital for a wide variety of climatological studies. We have produced a new, publicly available, daily, gridded maximum temperature, minimum temperature, and precipitation dataset for China with a high spatial resolution of 1 km that covers a long-term period (1961 to 2019). It has been named the HRLT, and the dataset is publicly available at https://doi.org/10.1594/PANGAEA.941329 (Qin and Zhang, 2022). In this study, the daily gridded data were interpolated using comprehensive statistical analyses, which included machine learning methods, the generalized additive model, and thin plate splines. It was based on the 0.5 ∘ × 0.5 ∘ gridded dataset from the China Meteorological Administration, together with covariates for elevation, aspect, slope, topographic wetness index, latitude, and longitude. The accuracy of the HRLT daily dataset was assessed using observation data from meteorological stations across China. The maximum and minimum temperature estimates were more accurate than the precipitation estimates. For maximum temperature, the mean absolute error (MAE), root mean square error (RMSE), Pearson's correlation coefficient (Cor), coefficient of determination after adjustment ( R 2 ), and Nash–Sutcliffe modeling efficiency (NSE) were 1.07 ∘ C, 1.62 ∘ C, 0.99, 0.98, and 0.98, respectively. For minimum temperature, the MAE, RMSE, Cor, R 2 , and NSE were 1.08 ∘ C, 1.53 ∘ C, 0....