CUG-CMA DATASET and its grid data product description

The daily meteorological observation data of the early period (pre-1950) were critically important for investigating the long-term trends and multi-decadal scale variability of extreme climate events. The high-resolution surface air temperature (SAT) data are lacking in China. We extended the SAT observations of China back to 1840 through developing a pre-1950 dataset. The early period daily SAT were manually corrected for the input and clerical errors, and then according to the length or coverage of time, the main series for each of the cities was determined. The observation time system of unknown sites is determined by the difference method. After these operations, the data of all sites are unified into the same format. By using the ridge regressions established by data from modern reference stations, the missing maximum temperature (Tmax) and minimum temperature (Tmin) are interpolated. the early period data are combined with modern data to form the long-term daily SAT dataset of 1840-2020 in China. RHtest software was used to adjust the inhomogeneities in the single-site data. Finally, the century-long homogenized daily SAT dataset including 45 key city stations in China was obtained. Among the stations, there are 20 stations with observation record more than one hundred years. The length of temperature observation series of 17 stations is between 80 and 100 years. The series length of the remaining 7 sites is between 68 and 80 years. The data integrity is good, with 18 stations having an integrity of 85–100%, and all of them having an integrity of more than 50%. Finally, the angular distance weighting (ADW) method is used to interpolate the data into grid products, and the grid size is 2.5 ° × 2.5 °. Climatic Research Unit dataset (CRU dataset) was used for comparing and verifying the new dataset. The high correlation coefficient between the two datasets indicates that the newly developed dataset in this paper is relatively reliable.