Surface emissivity has a significant impact on atmospheric parameter retrievals from microwave sounding instruments. To reduce the dependence of retrievals on surface emissivity, a double channel differences equation is deduced, and a corresponding retrieval scheme is constructed. Retrieval experiments are performed using Advanced Microwave Sounding Unit-A (AMSU-A) and Microwave Humidity Sounder (MHS) simulations and global measurements. Simulation experiments show that the double channel differences scheme can reduce the root mean square errors (RMSE) of the temperature and humidity profiles in the middle and lower atmosphere. Retrieval experiments based on AMSU-A and MHS global measurements show that the proposed scheme can significantly reduce the RMSE of temperature profiles in the lower atmosphere and humidity profiles in the middle and lower atmosphere for cloudy and cloudless conditions, different surface types, and different scan angles, with maximum reduction values of 0.64 K and 9.03%, respectively. Regarding RMSE improvement, that of the cloudy condition is greater than that of the cloudless condition, that of the land is greater than that of the coast and the sea, and there is no significant dependence on the scan angles. The double channel differences scheme is very sensitive to initial near-surface temperatures. Reducing the initial near-surface temperature error can significantly improve the temperature retrieval accuracy below 900 hPa, with maximum reduction value of 3.25 K.Plain language summary Microwave sounding instruments such as AMSU-A/MHS provide an unique ability to acquire global atmospheric temperature and humidity profiles. However, at present, their ability to acquire temperature and humidity information in the lower atmosphere has not been fully exploited, mainly due to the impact of surface emissivity. Therefore, reducing the impact of surface emissivity is a key issue. In this paper, a temperature and humidity profiles retrieval scheme is constructed by using the relationship between the surface emissivity of adjacent channels. The research shows that the scheme can significantly improve temperature and humidity retrieval accuracy for cloudy and cloudless conditions, different surfaces types, different scan angles. Reducing initial values error in the scheme can further improve retrieval accuracy. Key Points:• We propose a microwave temperature and humidity retrieval scheme based on double channel differences • We show the accuracy performance of the double channel differences retrieval scheme for AMSU-A/MHS measurements • Results demonstrate a significant retrieval improvement over a traditional AMSU-A/MHS neural network retrieval scheme

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Due to surface emissivity, the retrieval accuracy of hyperspectral infrared temperature and humidity profiles is typically poor in the lower atmosphere. To solve this problem, we use the double channel differences method (DCDM) to retrieve the temperature and humidity profiles of the Infrared Atmospheric Sounding Interferometer (IASI) with different surfaces, zenith angles, and data sources. Results show that DCDM can effectively improve IASI retrieval performance. The root mean square error (RMSE) reductions are large and exhibit no marked change with the zenithal angle. Compared with prior profiles, prior near‐surface temperatures can markedly improve the retrieval performance of temperature profiles. Humidity profile retrieval using both humidity and temperature channels can reduce the RMSE and the dependence on the precision of the prior inputs. The DCDM can markedly reduce errors in temperature and relative humidity retrievals, and the retrievals agree with ERA‐Interim better than IASI L2. With the DCDM, the lower temperature and relative humidity RMSE can be ∼3.5 K/14% (land), ∼3 K/13% (coast), ∼1.4 K/7% (sea). Compared with radiosonde observations and ERA‐Interim, the DCDM can reduce errors in temperature and humidity retrievals, and the improvement in performance is equivalent.

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