Accurate sea level pressure (SLP) data are critical for the forecasting and monitoring of tropical cyclones (TCs). Previous studies have explored SLP retrieval for TCs using passive microwave observations in a single oxygen band (60 or 118 GHz). Leveraging the Fengyun-3 (FY-3) satellite’s capability to simultaneously observe radiation in both 60 and 118 GHz bands, this study proposes a neural network-based algorithm to retrieve TC SLP fields from combined observations of brightness temperature (TB) and warm TB anomalies in both frequency bands. Application studies were carried out using the joint observations from the Microwave Temperature Sounder-2 (MWTS-2) and Microwave Humidity Sounder-2 (MWHS-2) onboard the FY-3D satellite. Optimal frequency channels for the SLP retrieval were selected based on an information content analysis. SLP retrievals within the TC core regions (within a 2° radius from the centers) were compared with SLP data from the Global Data Assimilation System Final Analysis (GDAS/FNL). The results showed root mean square errors (RMSEs) of 2.78 hPa for tropical depressions and storms, 4.23 hPa for hurricanes or typhoons, and 6.15 hPa for major hurricanes or severe typhoons. Retrievals were also compared within situobservations, and the corresponding RMSEs were 3.82, 4.86, and 5.14 hPa, respectively. Furthermore, comparative experiments between the new algorithm and the previous algorithm that used only observations from a single oxygen band demonstrated that the new algorithm provides more comprehensive SLP information and achieves higher accuracy.

Ice sheet internal temperature profile plays a key role in the study of ice sheet thermodynamics and ice sheet mass balance. Wideband radiometric remote sensing measurement has been demonstrated to be an effective approach for estimating the ice sheet internal temperature profile. In this study, we make model analysis of the sensitivity of emission observation on different frequency channel to ice sheet internal temperature at different depth, aiming at assessing the value of each channel in deriving ice sheet internal temperature profile. As the emission contribution depth profile can give insight into the emission compositions and emission sensitivity to the ice sheet internal properties at different depth, this study analyses the impact on ice sheet emission contribution depth profile due to the uncertainties of ice sheet temperature profile based on Comprehensive Layer Emission Model (CLEM). The correlation of different frequency channel are further discussed. The analysis results give guidance to construct retrieval approach for better extraction and utilization of the information on ice sheet internal temperature profile providing by the wideband emission observation.

This article is the preliminary results of the in-cloud wind observation of an airborne Doppler scatterometer. This experiment took place on the Qinghai-Tibet Plateau in 2022 and it’s the first time to carry wind observation experiment in this place. During the process procedure, the dual-PRF process was used to extend the max unambiguous velocity, and the VVP method was used to invert the three-dimensional wind. The result provides a 40-second observation of the in-cloud wind, which indicates that the in-cloud wind in the plateau area can be detected through an airborne scatterometer.

The hostile environment and thick sulfuric acid clouds make it difficult to measure the Venusian lower and middle atmosphere. The Venus Volcano Imaging and Climate Explorer (VOICE), which is an orbiting mission, has planned to exploring the thermal structure and composition of the Venusian lower and middle atmosphere by the Microwave Radiometric Sounder (MWRS). This study presents a forward- and inversion- model for the Venusian lower and middle atmosphere at microwave and submillimeter wavelengths, which is developed to simulate the nadir and limb sounding from the MWRS. Important properties of the model with respect to the Venusian atmosphere are its inclusion of molecular thermal movement and collisions induced spectral lines broadening as well as the effects of refraction on the signal propagation in the atmosphere. The model also has potential applications for definition studies for future downward-looking and limb-looking sensors dedicated to Venus exploration.

The Doppler spectrum of a Doppler scatterometer signal is determined by the relative motion between the scatterometer and the ocean surface, including ocean surface motion and platform motion. It is also determined by the modulation from the backscattering coefficient. Estimating the Doppler centroid is an important issue for the application of a spaceborne Doppler scatterometer in ocean surface current retrieval. In this study, we use an echoed signal simulation model to analyze the Doppler spectrum with different incidence angle. Our results show that the satellite velocity and the backscattering coefficient modulation are the main influencing factors that affect the shape of the Doppler spectrum. With the increase of incidence angle, the radial platform velocity increases, and the modulation from the backscattering coefficient decreases. At 52° incidence angle, the Doppler spectrum is closest to the Gaussian distribution, which is suitable for Doppler scatterometer.

Reported radiometric measurements indicate that incoherent and coherent radiative transfer processes characterize the microwave emission features of layered irregular and inhomogeneous medium. In order to develop a forward emission model to be capable of considering the medium and boundary scattering and coherent boundary interaction that may exist in general layered medium, in this article, we present a comprehensive layer emission model (CLEM) based on the scattering operator formulation. We introduce wave-based coherent multiple reflection operators to account for coherent boundary interaction and first integrate them with the intensity-based multiple scattering processes, allowing the comprehensive description of rough boundary scattering, volume scattering, medium/boundary interaction, and coherent boundary interaction in the framework of CLEM. Simulations and analyses for ice- and snow-covered ground cases are conducted based on CLEM to evaluate the coherent boundary interaction and different impacting factors. Validation on CLEM is conducted with emission observations of snow-covered terrain in campaign Nordic Snow Radar Experiment (NoSREx) 2010–2013 during dry snow period and time-series emission observations of frozen soil during freezing and thawing processes. CLEM simulation results show a good agreement with measurements. For NoSREx, root-mean-square errors (RMSEs) at L- to Ka-band are below 5.5 K for both polarizations, which are of different levels of promotion compared with the incoherent model simulations, especially for horizontal polarization at L- and X-band. Application to frozen soil case illustrates the capability of CLEM to explain coherent oscillation feature with impact from incoherent scattering effect.

Ice cloud parameters have an important influence on global climate research and weather forecast. According to the atmospheric radiation theory, sub-millimeter wave is the best frequency band for ice cloud remote sensing. In this paper, the principle and research status of ice cloud remote sensing is analyzed. The detection capabilities of different ice cloud sounders are compared, and a sub-millimeter wave ice cloud sounder for the next generation meteorological satellite is designed. The ice cloud sounder covers five detection frequencies of 183GHz, 243GHz, 325GHz, 448GHz and 664GHz, and uses cone scanning mode, with the spatial resolution better than 10km, noise temperature better than 3000K.

Previous studies used 50-60 GHz or 118 GHz passive microwave measurements separately for surface pressure retrieval. To improve the retrieval accuracy, a joint retrieval method is proposed in this study to use the 50-60 GHz and 118 GHz passive microwave measurements simultaneously for surface pressure retrieval over oceans. Based on information content analysis and footprint matching, collocated passive observations of the two bands are obtained, and then are used to establish back-propagation neural network retrieval models. Using the 50-60 GHz passive observations of Microwave Temperature Sounder-II (MWTS-II) onboard the Fengyun-3D (FY-3D) satellite and the 118.75 GHz observations of the Microwave Humidity and Temperature Sounder (MWHTS) onboard the FY-3D satellite, joint retrieval experiments are completed. Experimental results show that when using the 50-60 GHz and 118.75 GHz oxygen absorption band together for surface pressure measurements, more surface pressure information and better retrieval accuracy can be obtained than using them separately.

This paper makes a comparison of the retrieval of sea level pressure using 50-60 GHz and 118.75 GHz passive microwave observations. The 50-60 GHz passive observations of the Microwave Temperature Sounder-II (MWTS-II) and 118.75 GHz observations of the Microwave Humidity and Temperature Sounder (MWHTS) onboard the Chinese Fengyun-3D (FY-3D) meteorological satellite were used to carry out the comparison. Based on neural network-based retrieval algorithm, sea surface atmospheric pressure retrieval models for MWTS-II and MWHTS were established, respectively. Passive microwave observations from January 2018 to October 2019 and the corresponding Global Data Assimilation System (GDAS) Final (FNL) analysis data were used to develop and test the retrieval models. Results show that the accuracy of sea surface atmospheric pressure from MWTS-II retrieval is similar to that of the MWHTS retrieval for both usual weather conditions and tropical cyclone (TC) conditions. This provides a reference for high spatial resolution surface pressure observations by passive microwave instruments from low orbit satellites and high temporal resolution observations from geostationary orbit in the future.

The paper investigates the retrieval of typhoon and hurricane surface barometric pressure by passive measurements. The SVR based retrieval algorithm is presented and the passive microwave measurements from the SNPP/ATMS are used for the algorithm training and verification. The assessment of the retrieval performance is done by comparing the case-by-case retrievals with dropsonde measurements and tropical cyclone best track data. The validation results show that the established retrieval algorithm can estimate typhoon and hurricane surface barometric pressure with the accuracy better than 8hpa. As a preliminary conclusion, this method can provide some important sea surface barometric pressure information for typhoon and hurricane structure and dynamic characteristics analysis and offers a new idea for the study of typhoon and hurricane from microwave radiometer data.

The paper investigates the retrieval of sea surface barometric pressure under clear sky by passive measurements. Several linear and nonlinear statistical algorithms are presented and the passive microwave measurements from the Advanced Technology Microwave Sounder (ATMS) on S-NPP satellite are used for the algorithm training and verification. The retrieval are assessed by evaluation of root mean square error (RMSE), with comparison with the reanalysis data of European Centre for Medium-Range Weather Forecasts (ECMWF). The validated results show that Support Vector Regression (SVR) has the best performance and the corresponding RMSE of sea surface pressure is 1.53mb. The accuracy is comparable with the other traditional in-situ methods, and satisfy the requirements for meteorological applications.