1. Dataset information Dataset name: CHM_Tmax Summary: CHM_Tmax, an innovative and comprehensive long-term daily Maximum temperature (Tmax) dataset with a spatial resolution of 0.1° and data collected from 1961 to 2024 in mainland China. Content of the data set: (1) Metadata for CHM_Tmax.docx: This document provides detailed information about the dataset. (2) CHM_Tmax_01_daily_1961_2024.zip: Compressed file containing gridded daily maximum temperature (Tmax) fields at 0.1° spatial resolution for the period 1961–2024 (NetCDF format; “01” = 0.1°, “daily” = interpolated daily data, “1961_2024” = years). To facilitate downloading, we have split the data into nc data every ten years. CHM_Tmax_1961_1969.nc CHM_Tmax_1970_1979.nc CHM_Tmax_1980_1989.nc CHM_Tmax_1990_1999.nc CHM_Tmax_2000_2009.nc CHM_Tmax_2010_2019.nc CHM_Tmax_2020_2024.nc 2. Brief calculation introduction: The dataset utilizes high-density meteorological station data and follows a structured framework based on the China Hydro-Meteorology dataset (CHM; https://zenodo.org/communities/chm/records?q=&l=list&p=1&s=10). To ensure data integrity, rigorous quality control was applied and missing values were removed to facilitate reliable interpolation. Key meteorological variables—Tmax, Tmin, Tmean—were interpolated to a 0.1° spatial resolution using angular distance weighting (ADW). This method incorporates both angular and distance weighting, improving robustness against outliers. We interpolated the basic meteorological variables (Tmax, Tmin, Tmean; see Fig. 1), and in the interpolation process adopted ADW interpolation, which considers angle weight in addition to the distance weight function, making it more robust to outliers. We interpolated meteorological elements to 0.1° spatial resolution, which is consistent with CHM_Drought (https://zenodo.org/records/14634774) and CHM_PRE (https://zenodo.org/records/15735374). The ADW approach employed a modified Shepard’s algorithm, which integrates the correlation decay distance (CDD). CDD defines the distance at which inter-station correlation falls below 1/e, roughly equivalent to a 0.05 significance level in large samples (Tmax≈272, Tmeans≈99, Tmins≈136). Using CDD to constrain the number of stations per grid cell enhances interpolation accuracy. 3. Data advantage characteristics: In addition, compared with other datasets, the three temperature data (Tmax, Tmin, Tmean) in this dataset all take into account the influence of altitude. For every 100 meters increase in altitude, the temperature drops by approximately 0.6 degrees Celsius. 4. Details of the variables in the file Each NetCDF file contains the following four variables: (1) lat: Latitude dimension, measured in degrees (°). (2) lon: Longitude dimension, measured in degrees (°). (3) time: Time dimension, measured in days since January 1, 1961. (4) Tmax: Daily Maximum temperature (time, lat, lon). 5. Authors and contacts Qi Zhang (qizhang@qhnu.edu.cn) Chiyuan Miao (miaocy@bnu.edu.cn) Jinlong Hu (Hujl98@mail.bnu.edu.cn)