Soil moisture is one of the popular variables for various processes and models in hydrological research and the Earth sciences due to its high interaction among the land surface and atmosphere, land surface, and underground. Many satellite missions, such as SMAP, SMOS, or AMSR-E/2, have been launched to observe precise soil moisture in extensive or global spatial coverage, which is the limitation of in situ ones. In recent years, the satellite soil moisture products such as SMAP have also been reported to comprise errors caused by the so-called "temperature effects" found in the in situ soil moisture observed by dielectric sensors several decades ago. Though the temperature effect removal methods proposed for in situ data can apply to satellite soil moisture, there are limitations, such as global application. In this work, we also confirmed the existence of these errors in AMSR2 soil moisture products. We developed a new algorithm to remove them using satellite data at ascending and descending times. Three-centimeter depth soil water content (SWC) and soil temperature from 5^th September 2016 to 31^st October 2019 at the Mongolia site were used as the reference data. The correlation coefficient values between the corrected AMSR2 and corrected in situ SWC are between 0.1595 and 0.3542, while the values of the original ones range from 0.1846 to 0.3153. As well as, the values of MD, MAE, RMSE, and ubRMSE became lower in corrected data when compared to the original data. These indicate that the corrected AMSR2 products are better than the original AMSR2 products in the Mongolia network region. These results reveal that the correction method can successfully remove the temperature effects from AMSR2 soil moisture products.