The CDAT dataset contains near surface temperature data of China from 1979 to 2018. This product integrates multiple data sources, such as reanalysis data (ERA5, CMFD), remote sensing data (MODIS), and in-situ data, and distinguishes between clear and non clear sky weather conditions by combining temperature strategies. For Tmax, validation using in-situ data shows that the root mean square error (RMSE) ranges from 0.86 ° C to 1.78 ° C, the mean absolute error (MAE) ranges from 0.63 ° C to 1.40 ° C, and the Pearson coefficient (R2) ranges from 0.96 to 0.99. The RMSE of Tmin is 0.78 ° C~2.09 ° C, MAE is 0.58 ° C~1.61 ° C, and R2 is 0.95~0.99. For Tavg, the RMSE range is 0.35 ° C~1.00 ° C, the MAE range is 0.27 ° C~0.68 ° C, and the R2 range is 0.99~1.00. In addition, using multiple evaluation indicators to analyze the spatiotemporal trend of Ta, the increase in Tavg is greater than 0.0 ° C/a, which is consistent with the overall trend of global warming. In summary, this dataset has high spatial resolution and reliable accuracy, which compensates for the missing temperature values (Tmax, Tmin, and Tavg) previously observed at high spatial resolution. This dataset also provides key parameters for studying climate change, especially high temperature drought and low temperature cold damage.
XXXXTYPE. zip: It contains data for CDAT. It contains 120 folders (each representing a temperature type for one year), including Tmax, T minutes, and Tavg. The time range is from January 1979 to December 2018.
XXXX is this year. TYPE is a temperature type, named as maximum, minimum avg。 Each stage consists of two files, including * TIF (CDAT image) and * TFW (TIFF Image Coordinate Information).
This product integrates multiple data sources, such as reanalysis data (ERA5, CMFD), remote sensing data (MODIS), and in-situ data, and is obtained by combining temperature strategies to distinguish between clear and non clear sky weather conditions.
Different Ta reconstruction models were established for different weather conditions, and data accuracy was further improved by establishing correction equations for different regions.
For Tmax, validation using in-situ data shows that the root mean square error (RMSE) ranges from 0.86 ° C to 1.78 ° C, the mean absolute error (MAE) ranges from 0.63 ° C to 1.40 ° C, and the Pearson coefficient (R2) ranges from 0.96 to 0.99. The RMSE of Tmin is 0.78 ° C~2.09 ° C, MAE is 0.58 ° C~1.61 ° C, and R2 is 0.95~0.99. For Tavg, the RMSE range is 0.35 ° C~1.00 ° C, the MAE range is 0.27 ° C~0.68 ° C, and the R2 range is 0.99~1.00. In addition, using multiple evaluation indicators to analyze the spatiotemporal trend of Ta, the increase in Tavg is greater than 0.0 ° C/a, which is consistent with the overall trend of global warming. Due to the lack of observation data from early meteorological stations in South China Sea Islands, the data quality cannot be guaranteed and cannot be given here.
This work is licensed under
CC BY 4.0 (Creative Commons Attribution 4.0 International License).
CSTR:11738.11.NCDC.ZENODO.DB6683.2024
10.5281/zenodo.5502275
