To analyze the adaptability of the CLDAS soil relative humidity product in Northern Anhui, based on the data from 26 farmland moisture monitoring points and 28 automatic soil moisture monitoring stations from June 2023 to August 2024, mathematical statistics methods such as correlation analysis were employed, combined with software tools like SPSS and MATLAB, to conduct a comprehensive assessment of the CLDAS soil (0-20 cm layer) relative humidity product and application analysis. The results showed that: (1) Overall assessment indicated that the CLDAS soil relative humidity product had a relatively obvious correlation with the farmland moisture monitoring point data. The correlation coefficient (R) of the farmland moisture monitoring points ranged from 0.59 to 0.97, with 20 stations passing the significance test at P<0.01 and 2 stations passing at P<0.05. The R of the automatic soil moisture monitoring stations ranged from 0.50 to 0.92, with 23 stations passing the significance test at P<0.01 and 3 stations passing at P<0.05. The CLDAS soil relative humidity product had good applicability in study area. (2) Seasonal-scale analysis showed that the CLDAS soil relative humidity product and the farmland moisture monitoring point data had a positive correlation. The R of spring, summer, and winter passed the significance test at P<0.01, and that of autumn passes at P<0.05. The average deviation in spring, summer, and autumn remains negative, while in winter it remained positive. (3) In terms of terrain and soil type assessment, the CLDAS soil relative humidity product and the farmland moisture monitoring point data had a positive correlation for different terrains and soil types, with R>0.50, and all pass the significance test at P<0.01, indicating that the product performs relatively smoothly in terms of terrain and soil type. (4) Different soil moisture type assessment showed that the CLDAS soil relative humidity product exhibited distinct characteristics for suitable and slightly dry soil moisture monitoring, with an average deviation < 5% and a root mean square error > 10%. (5) Using the CLDAS soil relative humidity product for soil moisture monitoring, it was found that from June 2023 to April 2024, there was no significant change in soil moisture in northern Anhui. The monthly average value of soil relative humidity was between 65% and 85%, and the soil moisture was in a suitable type. However, from May to June 2024, the soil relative humidity decreased, and the soil moisture showed a shortage. In August, it tended to stabilize. (6) The CLDAS soil relative humidity value was positively correlated with cumulative precipitation and negatively correlated with average temperature, showing obvious feasibility in the application of fine-scale soil moisture monitoring in study area. In conclusion, the CLDAS soil relative humidity product has strong applicability and feasibility in Northern Anhui.