Atmospheric boundary layer detection is in urgent demand in meteorological and climate research and is closely related to human life and agricultural production. Atmospheric microwave fine-spectral sounding is a cutting-edge means to break through the regional and even global all-weather atmospheric boundary layer temperature and humidity profiling observations. In this paper, we carry out field campaigns using a unmanned aerial vehicle-based (UAV-based) fine-spectral microwave radiometer to solve key technologies of boundary layer detection and inversion, and realize the sounding of atmospheric water condensate and the study of the evolution.

This paper conducts an in-depth analysis of spaceborne hyperspectral microwave radiometers for remotely sensing atmospheric boundary layers’ temperature and humidity profiles. Utilizing 137 vertical-level atmospheric profile data from the European Centre for Medium-Range Weather Forecasts (ECMWF), the study employs the Atmospheric Radiative Transfer Simulator (ARTS) to construct a forward model of an Earth-based spaceborne microwave radiometer, enabling the computation of the Jacobian matrix. This research thoroughly evaluates the posterior probability of retrieval errors and vertical resolution by analyzing both the background error covariance matrix and the measurement error covariance matrix alongside the Jacobian matrix. Findings reveal that a spectral resolution of 10 MHz significantly enhances the accuracy of posterior retrieval errors and improves vertical resolution, in contrast to the 1000 MHz resolution, which shows lesser efficacy. While hyperspectral microwave radiometers offer clear benefits for detailed atmospheric profiling, the increase in spectral resolution does not uniformly translate to performance enhancements due to the accompanying rise in system noise. These results underscore the importance of conducting meticulous assessments to determine the most effective spectral resolution for radiometers, considering the intricate balance between information gain and noise.

This article investigates the potential of microwave sounders for a future international Venusian lower atmosphere exploration mission. Venusian microwave atmospheric radiative transfer (RT) calculations from a spaceborne perspective are performed with appropriate settings of the specific observation geometry and input atmospheric scenarios. An atmospheric profile perturbation analysis was undertaken to determine the channel selection and corresponding retrieval accuracy. Meanwhile, a suitable configuration of microwave sounder is proposed based on the gas absorption characteristics, sensitivity, and retrieval error analysis. The channel frequency selected includes 21 (2) channels of SO2 (H2SO4) absorption lines and its sidebands, as well as 37 channels between 6 and 42 GHz. Due to the strong coupling between temperature, SO2, and H2SO4 in the lower atmosphere, a joint physical retrieval method [optimal estimation method (OEM)] is proposed. Under ideal model conditions, the RMSE of retrieved temperature profiles improves by 1.3 K to stay within 2 K for 0–65 km, while the maximum RMSEs for SO2 and H2SO4 volume mixing ratios (VMRs) show improvements of at least 15% and 10%, reaching 30% and 25%, respectively. These results validate the proposed microwave sounder’s effectiveness for temperature and SO2 (H2SO4) profiling up to 65 km (30–75 km for SO2 and 35–55 km for H2SO4). However, increasing model error reduces retrieval accuracy, emphasizing the importance of model development for accurate joint observations of these parameters.

In the calibration of Microwave Humidity and Temperature Sounder (MWHTS) onboard the Fengyun-3E (FY-3E) satellite, the ideal rectangular spectral response function is normally used. However, the measured spectral response function has in-band fluctuation, which will not only cause errors to the calibration, but also is essential to the subsequent data retrieval and assimilation applications. In this paper, the spectral response function (SRF) of five channels located near the frequency of 183.31-GHz is studied. The results demonstrate that different channels have different responses to the measured SRF and the ideal rectangular SRF. The closer the channel is the frequency 183.31-GHz, the maximum deviation is nearly 0.2 K. In addition, a constant noise, uniform noise, Gaussian noise and Chebyshev 1 ripple noise were added respectively. The greater the noise amplitude, the greater the brightness temperature deviation, and the results of four different noise was consistent. When the noise amplitude is set to 3 dB, the brightness temperature deviation reaches 0.1 K. The results can not only provide reference for the design of the sensor, but also provide a new idea for data calibration, so as to improve the accuracy of data calibration.

This paper demonstrated the advantages of spaceborne hyperspectral microwave radiometer in retrieving temperature and humidity profiles. Build a forward model using the Atmospheric Radiative Transfer Simulator (ARTS) and input profile datasets from the ECMWF 137 level short range forecasts to calculate simulated brightness temperature. A physical retrieval algorithm (Optimal Estimation Method, OEM) was used to retrieve temperature profiles ranging from 0-40 km and humidity profiles ranging from 0-10 km. The results showed that 10 MHz can more effectively retrieve temperature and humidity profiles. The mean values of root-mean-square error integrated over the height are 0.6096 K (0.6093 K) and 2.6373% (2.7210%) for land (ocean) temperature and relative humidity profiles, respectively. The information content (IC) of different spectral resolutions slightly differs from OEM retrieval results. 10 MHz and 100 MHz spectral resolutions have maximum channel IC for retrieving temperature and humidity profiles, respectively. In conclusion, spaceborne microwave hyperspectral sounder can improve the retrieval accuracy of temperature and humidity profiles by increasing spectral resolution.