三江源国家公园星空地一体化生态监测数据平台
Ecological Data Center of Sanjiangyuan National Park

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Six Years of High-resolution Monthly Air Temperature and Precipitation Dataset for China Published

A high spatial resolution 0.025° (~2.5 km) gridded dataset of monthly air temperature and precipitation in China from 1951 to 2011, was recently published by a research team led by Prof. HUANG Wei at Lanzhou University. The dataset is developed based on data from 1153 temperature stations and 1202 precipitation stations in China and neighboring countries, using a partial thin plate smoothing method embedded in the ANUSPLIN software. The dataset was recently released at the National Tibetan Plateau Data Center and is available for free download.

Comparing the dataset with the reserved 265 stations, the results show that the monthly interpolation data of the dataset are close to the actual data with mean absolute difference of 0.59℃ and 70.5mm, standard deviation of 1.27℃ and 122.6mm, and the variation of standard deviation is consistent with the variation of GCV (Generalized Cross Validation); comparing the dataset with the 0.5° dataset published by the China Meteorological Administration (CMA), the results show that the correlation coefficient with the CMA is high, the standard deviation is close, and the root mean square error of normalization is small; comparing the dataset with the CAMP-Tibet data, the results show that only a few stations' precipitation data are not significantly related to the dataset, but most stations' temperature and precipitation data are significantly related to the dataset with correlation above 0.87.

The high-resolution nature of the dataset can characterize more climate types such as tundra and polar climates in the Himalayan region not identified by the coarse-resolution dataset, and can also serve as a basis for studying regional climate change and precision agro-climates under global climate change.

Data available at: https://data.tpdc.ac.cn/en/data/1121cc40-f1a6-405a-a34a-f27f2c8e63f3/

Full-text available at: https://link.springer.com/article/10.1007%2Fs00704-019-02830-y