1 km monthly temperature and precipitation dataset for China from 1901 to 2017
Chinese Academy of Sciences · Institute of Soil and Water Conservation · +3 more institutions
Abstract
Abstract. High-spatial-resolution and long-term climate data are highly desirable for understanding climate-related natural processes. China covers a large area with a low density of weather stations in some (e.g., mountainous) regions. This study describes a 0.5′ (∼ 1 km) dataset of monthly air temperatures at 2 m (minimum, maximum, and mean proxy monthly temperatures, TMPs) and precipitation (PRE) for China in the period of 1901–2017. The dataset was spatially downscaled from the 30′ Climatic Research Unit (CRU) time series dataset with the climatology dataset of WorldClim using delta spatial downscaling and evaluated using observations collected in 1951–2016 by 496 weather stations across China. Prior to…
Citation impact
- FWCI
- 33.39
- Percentile
- 100%
- References
- 31
Authors
4- SPShouzhang PengCorresponding
Chinese Academy of Sciences, Institute of Soil and Water Conservation, Ministry of Water Resources of the People's Republic of China, Northwest A&F University
- YDYongxia DingCorresponding
Shaanxi Normal University
- WLWenzhao LiuCorresponding
Chinese Academy of Sciences, Institute of Soil and Water Conservation, Ministry of Water Resources of the People's Republic of China, Northwest A&F University
- ZLZhi LiCorresponding
Northwest A&F University
Topics & keywords
- Cru
- Downscaling
- Climatology
- Bilinear interpolation
- Environmental science
- Precipitation
- Mean squared error
- Interpolation (computer graphics)
- Climate action