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Passive microwave remote sensing is a vital tool for acquiring valuable information regarding the Earth's surface, with significant applications in agriculture, water management, forestry, and various environmental disciplines. Precision agricultural (PA) practices necessitate the availability of field-scale, high-resolution remote sensing data products. This study focuses on the design and development of a cost-effective, portable L-band microwave radiometer capable of operating from an unmanned aircraft system platform to measure high-resolution surface brightness temperature ($T_{B}$). This radiometer consists of a dual-polarized (Horizontal polarized, H-pol and Vertical polarized, V-pol) antenna and a software-defined radio-based receiver system with a 30 MHz sampling rate. The post-processing methodology encompasses the conversion of raw in-phase and quadratic (I&Q) surface emissions to radiation $T_{B}$ through internal and external calibrations. Radiometric measurements were conducted over an experimental site covering both bare soil within an agricultural field and a large water body. The results yielded a high-resolution $T_{B}$ map that effectively delineated the boundaries between land and water, and identified land surface features. The radiometric temperature measurements of the sky and blackbody demonstrated a standard deviation of 0.95 K for H-pol and 0.57 K for V-pol in the case of the sky and 0.39 K for both H-pol and V-pol in the case of the blackbody observations. The utilization of I&Q samples acquired via the radiometer digital back-end facilitates the generation of different time–frequency (TF) analyses through short-time Fourier transform and power spectral density (PSD). The transformation of radiometer samples into TF representations aids in the identification and mitigation of radio frequency interference originating from the instrument itself and external sources.

The HY-2D satellite was successfully launched in 2022, which marks the first phase of the HY-2 satellite constellation. In order to reduce the deviation of wet path delay (WPD) between different satellites in the HY-2 satellite constellation and increase precision in the correction microwave radiometer (CMR) products, on-orbit calibration must be performed to the brightness temperature (BT) of the CMR in this constellation. This study describes the principle and process of on-orbit calibration for CMR in detail. For the three satellites of the HY-2 satellite constellation, after cross-matching with each other within a limited spatio-temporal range, the HY-2B satellite with sounding on the global ocean is selected to the calibration source, calibrating BT from the CMR of the HY-2C and HY-2D satellites to the BT dimension of the HY-2B satellite CMR. To check on-orbit calibration, a retrieval algorithm is built using atmospheric profile data from ECMWF and BT data, obtained from the CMR of the HY-2B satellite; this is used to calculate the atmospheric water vapor (AWV) and WPD from the HY-2 satellite constellation. After on-orbit calibration to the CMRs of the HY-2 satellite constellation, the deviation between the CMR products of different satellites is significantly reduced by over 20%, and the RMS of WPD for the same type of products from the Jason-3 satellite is less than 1 cm. It may be concluded that on-orbit calibration improves the accuracy of AWV and WPD by normalizing the BT dimension for CMRs of the HY-2 satellite constellation, so this calibration method is effective and credible for enhancing the quality of altimeter products in the HY-2 satellite constellation.

This paper presents a method for retrieving optical parameters from volcanic sulfate aerosols from the AHI radiometer on board the Himawari-8 satellite. The proposed method is based on optical models for various mixtures of aerosol components from volcanic clouds, including ash particles, ice crystals, water drops, and sulfate aerosol droplets. The application of multi-component optical models of various aerosol compositions allows for the optical thickness and mass loading of sulfate aerosol to be estimated in the sulfuric cloud formed after the Karymsky volcano eruption on 3 November 2021. A comprehensive analysis of the brightness temperatures of the sulfuric cloud in the infrared bands was performed, which revealed that the cloud was composed of a mixture of sulfate aerosol and water droplets. Using models of various aerosol compositions allows for the satellite-based estimation of optical parameters not only for sulfate aerosol but also for the whole aerosol mixture. [ABSTRACT FROM AUTHOR]

In this letter, we present a validation of the wind speed retrieval from data from the calibration microwave radiometer onboard the Haiyang-2B (HY-2B) satellite against the observations from the stepped-frequency microwave radiometer (SFMR) onboard hurricane aircraft of the National Oceanic and Atmospheric Administration (NOAA) during 50 tropical cyclones (TCs). These data were collected during the cyclone season for the period from 2019 to 2022. The validation yields a root mean square error (RMSE) of 2.99 m s−1, a correlation coefficient (r) of 0.69, and a scatter index (SI) of 0.21 for the wind speed at wind speeds of <25 m s−1, which are worse than those achieved through the comparison with the HY-2B scatterometer, i.e. an RMSE of 1.15 m s−1, an r value of 0.96, and an SI of 0.11. This is probably caused by the fact that the brightness temperature measurement from the calibration microwave radiometer is likely affected by whitecaps caused by wave breaking; however, whitecaps have less influence on the sea surface backscattering signal under a regular sea state. At wind speeds of >25 m s−1, the accuracy is reduced to an RMSE of 2.19 m s−1, an r value of 0.75, and an SI of 0.07. In the presence of rain, significant distortion was observed, i.e. a variation of 3 m s−1 for a rain rate of 15 mm hr−1. This behaviour was also observed in the analysis of the HY-2B scatterometer product at low-to-moderate wind speeds. In this sense, it is believed that correction associated with rain has to be conducted in wind retrieval from HY-2B data. [ABSTRACT FROM AUTHOR]

Surface melt on ice shelves has been linked to hydrofracture and subsequent ice shelf breakup. Since the 1990s, scientists have been using microwave radiometers to detect melt on ice shelves and ice sheets by applying various statistical thresholding techniques to identify significant increases in brightness temperature that are associated with melt. In this study, instead of using a fixed threshold, we force the Snow Microwave Radiative Transfer model (SMRT) with outputs from the Community Firn Model (CFM) to create a dynamic, physics-based threshold for melt. In the process, we also combine our method with statistical thresholding techniques and produce microwave grain-size information. We run this "hybrid method" across the Larsen C ice shelf as well as 13 sites on the Antarctic Ice Sheet. Melt and non-melt days from the hybrid method and three statistical thresholding techniques match with the surface energy balance within 94 ± 1 %; the effect of melt on the passive microwaves is mostly binary and thus largely detectable by statistical thresholding techniques as well as physics-based techniques. Rather than always replacing statistical thresholding techniques with the hybrid method, we recommend using the hybrid method in studies where the melt volume or grain size is of interest. In this study, we show that the hybrid method can be used to (a) model dry-snow brightness temperatures of Antarctic snow and (b) derive a measure of grain size; therefore, it is an important step forwards towards using firn and radiative-transfer modeling to quantify melt rather than to simply detect melt days. [ABSTRACT FROM AUTHOR]

Abstract This study evaluated feasibility statistically and analyzed, during the freezing period, the relationship between brightness temperature (Tb) data of the 37V polarisation and the GR3719 (Gradient Ratio 37V and 19V) obtained by Special Sensor Microwave/Imager from F11 and F13 satellites with sea ice thickness (SIT) data obtained in the Weddell Sea through Antarctic Sea Ice Processes and Climate program. The multiple linear regression (MLR) was applied at 1,520 points, with 70% of these points being randomly separated to generate the MLR and 30% to carry out the validation. To perform the temporal mapping, the MLR was applied only to pixels with sea ice concentration (SIC) ≥ 90%, obtained through the fraction image calculated from the spectral linear mixing model (SLMM) using the Tb in the channels and polarizations 19H, 19V and 37V. The results of the SLMM validation process for estimating the SIC were σ = 10.5%, RMSE = 11.0%, and bias = -2.8%, and the SIT based on the MLR, the results were R² = 0.57, RMSE = 0.268 m, and bias = 0.103 m. In the SIT mapping, we highlight the trend of thickness reduction on the east coast of the Antarctic Peninsula during the period 1992–2009.

Thin ice with a thickness of less than half a meter produces strong salt and heat fluxes which affect deep water circulation and weather in the polar oceans. The identification of thin ice areas is essential for ship navigation. We have developed thin ice detection algorithms for the AMSR2 and FY-3C MWRI radiometer data over the Arctic Ocean. Thin ice (<20 cm) is detected based on the classification of the H-polarization 89–36-GHz gradient ratio (GR8936H) and the 36-GHz polarization ratio (PR36) signatures with a linear discriminant analysis (LDA) and thick ice restoration with GR3610H. The brightness temperature ( T B ) data are corrected for the atmospheric effects following an EUMETSAT OSI SAF correction method in sea ice concentration retrieval algorithms. The thin ice detection algorithms were trained and validated using MODIS ice thickness charts covering the Barents and Kara Seas. Thin ice detection is applied to swath T B datasets and the swath charts are compiled into a daily thin ice chart using 10 km pixel size for AMSR2 and 20 km for MWRI. On average, the likelihood of misclassifying thick ice as thin in the ATIDA2 daily charts is 7.0% and 42% for reverse misclassification. For the MWRI chart, these accuracy figures are 4% and 53%. A comparison of the MWRI chart to the AMSR2 chart showed a very high match (98%) for the thick ice class with SIC > 90% but only a 53% match for the thin ice class. These accuracy disagreements are due to the much coarser resolution of MWRI, which gives larger spatial averaging of T B signatures, and thus, less detection of thin ice. The comparison of the AMSR2 and MWRI charts with the SMOS sea ice thickness chart showed a rough match in the thin ice versus thick ice classification. The AMSR2 and MWRI daily thin ice charts aim to complement SAR data for various sea ice classification tasks. [ABSTRACT FROM AUTHOR]

The HY-2D satellite was successfully launched in 2022, which marks the first phase of the HY-2 satellite constellation. In order to reduce the deviation of wet path delay (WPD) between different satellites in the HY-2 satellite constellation and increase precision in the correction microwave radiometer (CMR) products, on-orbit calibration must be performed to the brightness temperature (BT) of the CMR in this constellation. This study describes the principle and process of on-orbit calibration for CMR in detail. For the three satellites of the HY-2 satellite constellation, after cross-matching with each other within a limited spatio-temporal range, the HY-2B satellite with sounding on the global ocean is selected to the calibration source, calibrating BT from the CMR of the HY-2C and HY-2D satellites to the BT dimension of the HY-2B satellite CMR. To check on-orbit calibration, a retrieval algorithm is built using atmospheric profile data from ECMWF and BT data, obtained from the CMR of the HY-2B satellite; this is used to calculate the atmospheric water vapor (AWV) and WPD from the HY-2 satellite constellation. After on-orbit calibration to the CMRs of the HY-2 satellite constellation, the deviation between the CMR products of different satellites is significantly reduced by over 20%, and the RMS of WPD for the same type of products from the Jason-3 satellite is less than 1 cm. It may be concluded that on-orbit calibration improves the accuracy of AWV and WPD by normalizing the BT dimension for CMRs of the HY-2 satellite constellation, so this calibration method is effective and credible for enhancing the quality of altimeter products in the HY-2 satellite constellation. [ABSTRACT FROM AUTHOR]

The Electrically Scanning Microwave Radiometer (ESMR) instrument onboard the NIMBUS 5 satellite was a one-channel microwave radiometer that measured the 19.35 GHz horizontally polarized brightness temperature (TB) from 11 December 1972 to 16 May 1977. The original tape archive data in swath projection have recently been made available online by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Even though the ESMR was a predecessor of modern multi-frequency radiometers, there are still parts of modern processing methodologies which can be applied to the data to derive the sea ice extent globally. Here, we have reprocessed the entire dataset using a modern processing methodology that includes the implementation of pre-processing filtering, dynamical tie points, and a radiative transfer model (RTM) together with numerical weather prediction (NWP) for atmospheric correction. We present the one-channel sea ice concentration (SIC) algorithm and the model for computing temporally and spatially varying SIC uncertainty estimates. Post-processing steps include resampling to daily grids, land-spillover correction, the application of climatological masks, the setting of processing flags, and the estimation of sea ice extent, monthly means, and trends. This sea ice dataset derived from the NIMBUS 5 ESMR extends the sea ice record with an important reference from the mid-1970s. To make it easier to perform a consistent analysis of sea ice development over time, the same grid and land mask as used for EUMETSAT's OSI-SAF SMMR-based sea-ice climate data record (CDR) were used for our ESMR dataset. SIC uncertainties were included to further ease comparison to other datasets and time periods. We find that our sea ice extent in the Arctic and Antarctic in the 1970s is generally higher than those available from the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC), which were derived from the same ESMR dataset, with mean differences of 240 000 and 590 000 km 2 , respectively. When comparing monthly sea ice extents, the largest differences reach up to 2 million km 2. Such large differences cannot be explained by the different grids and land masks of the datasets alone and must therefore also result from the differences in data filtering and algorithms, such as the dynamical tie points and atmospheric correction. The new ESMR SIC dataset has been released as part of the ESA Climate Change Initiative (ESA CCI) program and is publicly available at 10.5285/34a15b96f1134d9e95b9e486d74e49cf. [ABSTRACT FROM AUTHOR]

For synthetic aperture microwave radiometers, the problem of Radio Frequency Interference (RFI) is becoming more and more serious, which affects both the scientific retrieval of remote sensing data and the imaging quality of brightness temperature (BT) images. In the visibility data domain, the array factor synthesis algorithm is commonly employed to mitigate RFI sources and their Gibbs trailing. In the BT image domain, the CLEAN algorithm is typical applied to mitigate RFI sources and their Gibbs trailing. However, the array factor synthesis algorithm can result in anomalous BT points near the "zero trap" region, and the CLEAN algorithm will miss some BT points below a certain threshold. In this paper, a Bi-domain combined mitigation algorithm is proposed to mitigate RFI sources and their Gibbs trailing. Following initial mitigation in the visibility data domain, dual thresholds are applied to normalize anomalous BT points near the "zero trap" region, thereby enhancing imaging quality. The effectiveness of the Bi-domain combined mitigation algorithm is verified by using both measured data from SMOS L1A and simulated data. The experimental results demonstrate that the Bi-domain combined mitigation algorithm is superior to the array factor synthesis algorithm and the CLEAN algorithm in mitigating RFI sources and their Gibbs trailing. [ABSTRACT FROM AUTHOR]

Subject and Purpose. One of the relevant areas of remote sensing of the environment is the development of microwave methods of passive sensing of the atmosphere. The biggest challenge occurring in radiometric measurements is measuring system calibration. The reason lies in the lack of external calibration elements whose brightness temperatures are known with a high accuracy. The paper deals with the method for determining the sky brightness temperature by relative measurements at different elevation angles. The brightness temperatures refined in the way fit for radiometric system calibration. Methods and Methodology. Basically, the approach is governed by the dependence of the atmospheric brightness temperature on the elevation angle in terms of the plane-layered isothermal atmospheric model. The measurements rely on a three-centimeter radiometric system having a horn-reflector antenna combined with the MPL-1 weather radar, the entire range of elevation angles being accessible. Besides, a combined setup of two, 10 GHz and 36 GHz, radiometers is involved for measurements from a building window. Results. The previously proposed methodology for radiometric system calibration against the sky temperature obtained by relative measurements at different elevation angles has been analyzed and tested. The calibration possibility has been examined in the case that zenith measurements are unavailable. Conclusion. The proposed method for getting sky temperatures upon relative measurements at different elevation angles significantly increases accuracy of radiometric system calibration and extends a range of weather conditions admitting calibration of the kind. It has been shown that the radiometric system calibration against the sky temperature is possible even with zenith measurements excluded.

For an aperture synthesis radiometer (ASR), the visibility and the modified brightness temperature (BT) are related to the Fourier transform when the distance between the system and the source is in the far-field region. BT reconstruction can be achieved using G-matrix imaging. However, for ASRs with large array sizes, the far-field condition is not satisfied when performing performance tests in an anechoic chamber due to size limitations. Using far-field imaging methods in near-field conditions can introduce errors in the images and fail to correctly reconstruct the BT. Most of the existing methods deal with visibilities, converting near-field visibilities to far-field visibilities, which are suitable for point sources but not good for extended source correction. In this paper, two near-field imaging methods are proposed based on the near-field distance. These methods enable BT reconstruction in near-field conditions by generating improved resolving matrices: the near-field G-matrix and the F-matrix. These methods do not change the visibility measurements and can effectively image both the point source and the extended source in the near field. Simulations of point sources and extended sources in near-field conditions demonstrate the effectiveness of both methods, with F-matrix imaging outperforming near-field G-matrix imaging. The feasibility of both near-field imaging methods is further validated by carrying out experiments on a 10-element Y-array system. [ABSTRACT FROM AUTHOR]

Lunar cryptomare records both early-stage mare volcanisms and large-scale impact cratering, which can provide important information about the thermal evolution of the Moon. We built a mixing dielectric constant model to represent the cryptomare deposits mixed by highland debris and mare deposits, and the proper radiative transfer simulation was constructed to evaluate the thermal emission features of surface deposits in the cryptomare region. The microwave radiometer (MRM) data in the Balmer-Kapteyn region were extracted, and the linear interpolation method was used to generate brightness temperature (TB) maps at noon and at night. To enhance the correlation between cryptomare deposits and TB performances, normalized TB (nTB) and TB difference (dTB) maps were also generated. Combined with the datasets, including Lunar Reconnaissance Orbiter Wide Angle Camera, Lunar Orbiter Laser Altimeter, and Diviner and Clementine UV–VIS, the main findings are as follows: (1) The mare-like cryptomare deposits were discovered and identified according to the nTB and dTB performances. Combined with the surface compositions, at least two kinds of buried mare deposits were identified in the B-K region, which erupted during different episodes. (2) A construct-like volcanic feature was suggested by the nTB and dTB performances. (3) The results of our analysis indicated the presence of materials with low dTB anomalies in the northern and southwestern parts of the cryptomare region and in the mare unit within the Vendelinus crater, which illustrates the heterogeneity of the lunar crust in the vertical direction.

Ground-based multi-channel microwave radiometers (MWRs) can continuously detect atmospheric profiles in the tropospheric atmosphere. This makes MWR an ideal tool to supplement radiosonde and satellite observations in monitoring the thermodynamic evolution of the atmosphere and improving numerical weather prediction (NWP) through data assimilation. The analysis of product characteristics of MWR is the basis for applying its data to real-time monitoring and assimilation. In this paper, observations from the latest generation of ground-based multi-channel MWR RPG-HATPRO-G5 installed in Shanghai, China, are compared with the radiosonde observations (RAOB) observed in the same location. The detection performance, characteristics of various channels, and the accuracy of the retrieval profile products of the MWR RPG are comprehensively evaluated during various weather conditions. The results show that the brightness temperatures (BTs) observed by the ground-based MWR RPG during precipitation conditions were high, which affected its detection performance. The bias and the standard deviation (SD) between the BT observed by MWR RPG and the simulated BT during clear and cloudy sky conditions were slight and large, respectively, and the coefficient of determination (R2) was high and low, respectively. However, when the cloud liquid water (CLW) information was added when simulating BT, the bias and the SD of the observed BT and the simulated BT during cloudy days were reduced and the R2 value improved, which indicated that CLW information should be taken into account when simulating BT during cloudy conditions. The temperature profiles of the MWR retrieval had the same accuracy of RMSEs (root-mean-square error) with heights during both clear-sky and cloudy sky conditions, where the RMSEs were below 2 K when the heights were below 4 km. In addition, the MWR RPG has the potential ability to retrieve the temperature inversion in the boundary layer, which has important application value for fog and air pollution monitoring.

Mare Frigoris is the fifth largest and almost northernmost mare located on the near side of the Moon. Mare Frigoris has an elongated shape, with a length of approximately 1500 km and a width of approximately 200 km, which makes it susceptible to becoming contaminated by the impact ejecta from the nearby highlands. Comparatively speaking, microwave radiometer (MRM) data have good penetration capabilities. Therefore, the MRM data from Chang’e-2 satellite were employed to study the volumetric thermal emission features of basaltic deposits in Mare Frigoris. Combining the MRM data with the basaltic units with FeO and TiO2 abundances identified using the small crater rim and ejecta probing (SCREP) methodology and with the gravity from Gravity Recovery and Interior Laboratory (GRAIL), the four potential conclusions that were obtained are as follows: (1) The MRM data are strongly related to the (FeO + TiO2) abundance of pristine basalts and are less influenced by ejecta contamination; (2) in every quadrant of Mare Frigoris, the (FeO + TiO2) abundance of the basalt decreases with an increase in age; (3) at least in Mare Frigoris, the main influencing factor regarding the brightness temperature remains the (FeO + TiO2) abundance of surface deposits; (4) a warm microwave anomaly was revealed in the western-central and eastern-central areas of Mare Frigoris which has a strong relationship with the positive Bouguer gravity anomaly derived from GRAIL data in terms of spatial distribution. The results are significant in the context of improving our understanding the basaltic igneous rock and thermal evolution of the Moon using MRM data.

In this study, a one-dimensional variational algorithm that combines brightness temperatures (BTs), measured by ocean-based microwave radiometers (MWR), with reanalysis data was developed to generate high accuracy temperature profiles. A forward radiative transfer model was used to simulate the BTs. For the V band (50–70 GHz), there is a good agreement between observations and simulations, but for K band (20–30 GHz), which is more affected by water vapor, large errors are observed. To reduce the errors, a combined temperature and water vapor background error covariance matrix is applied to the 1D-Var algorithm. In addition, a correction factor is added to the 1D-Var iterative equation to improve retrieval accuracy. The results of the improved 1D-Var method have been compared with the MWR built-in neural network (NN) method, original 1D-Var method, and radiosonde data, which shows that the retrievals of the combined 1D-Var method showed significant improvements between 0 to 10 km. The statistical results show that the maximum mean absolute error of the combined 1D-Var method is less than 2 K in clear sky and cloudy conditions. This paper demonstrates that the proposed combined 1D-Var method has better performance than many known retrieval methods.

Enhancing the spatial resolution of real-aperture microwave radiometers is an essential research topic. The accuracy of the numerical values of brightness temperatures (BTs) observed using microwave radiometers directly affects the precision of the retrieval of marine environmental parameters. Hence, ensuring the accuracy of the enhanced brightness temperature values is of paramount importance when striving to enhance spatial resolution. A spectrum extension (SE) method is proposed in this paper, which restores the suppressed high-frequency components in the scene BT spectrum through frequency domain transformation and calculations, specifically, dividing the observed BT spectrum by the conjugate of the antenna pattern spectrum and applying a Taylor approximation to suppress error amplification, thereby extending the observed BT spectrum. By using a convolutional neural network to correct errors in the calculated spectrum and then reconstructing the BT through inverse fast Fourier transform (IFFT), the enhanced BTs are obtained. Since the extended BT spectrum contains more high-frequency components, namely, the spectrum is closer to that of the original scene BT, the reconstructed BT not only achieves an enhancement in spatial resolution, but also an improvement in the accuracy of BT values. Both the results from simulated data and satellite-measured data processing illustrate that the SE method is able to enhance the spatial resolution of real-aperture microwave radiometers and concurrently improve the accuracy of BT values. [ABSTRACT FROM AUTHOR]

The Calibration Microwave Radiometer (CMR) is a three-band radiometer deployed on the HY-2C satellite in a near-Earth orbit, and since it launched, there are few studies presented on the performance of CMR to date. Therefore, this paper focuses on providing an assessment of HY-2C CMR brightness temperature and wet troposphere correction (WTC). CMR works at 18.7 GHz, 23.8 GHz and 37 GHz in a nadir-viewing direction, aligned with the HY-2C radar altimeter. The wet troposphere path delay of the radar altimeter signal caused by water vapour and cloud liquid water content can be monitored and corrected by CMR. In this paper, guided by the concept of antenna pattern correction algorithm and a purely statistical method, we directly establish the function between the CMR antenna temperature and the model-derived WTC calculated by the European Centre from Medium-Range Weather Forecasting (ECMWF) Reanalysis data, which can obtain the brightness temperature and the WTC of CMR simultaneously. Firstly, the algorithm principle of CMR to establish the function between the antenna temperature and the model-derived WTC is introduced, and then the brightness temperature of CMR is evaluated using reference brightness temperatures of the Advanced Microwave Radiometer 2 (AMR-2) on Jason-3 satellite at crossover points. Furthermore, the performance of the CMR WTC is validated in three ways: (1) directly comparing with the colocated WTC measured by Jason-3 AMR-2, (2) directly comparing with model-derived WTC from ECMWF, which allows a rapid check at a global scale, (3) comparing the standard deviation of the Sea Surface Height (SSH) difference at crossover points using different WTC retrieval methods. The linear fit with Jason-3 brightness temperature and WTC in all non-precipitation conditions demonstrated a good agreement with Jason-3. In addition, the WTC of CMR has an obvious decrease in the standard deviation of the SSH difference compared with model-derived WTC, indicating the CMR can significantly improve the accuracy of the HY-2C SSH measurements. All the assessments indicate that the CMR performances are satisfying the expectations and fulfilling the mission requirements. [ABSTRACT FROM AUTHOR]

In a joint effort, MeteoSwiss and Deutscher Wetterdienst (DWD) address the need for improving the initial state of the atmospheric boundary layer (ABL) by exploiting ground‐based profiling observations that aim to fill the existing observational gap in the ABL. We implemented brightness‐temperature observations from ground‐based microwave radiometers (MWRs) in our data assimilation systems using a local ensemble transform Kalman filter (LETKF) with Radiative Transfer for TIROS Operational Vertical Sounder, ground‐based (RTTOV‐gb) as a forward operator. We were able to obtain a positive impact on the brightness temperature first guess and analysis, as well as a slight impact on the ABL humidity, using two MWRs at MeteoSwiss. These results led to a subsequent operational implementation of the observing system at MeteoSwiss. Furthermore, we performed an extensive set of assimilation experiments at DWD to investigate further various aspects such as the vertical localisation of selected single channels. We obtained a positive impact on the 6‐hr forecast of ABL temperature and humidity by assimilating two channels employing a dynamical localisation based on the sensitivity functions of RTTOV‐gb but also with a static localisation in a single‐channel setup. Our experiments indicate the importance of vertical localisation when using more than one channel, although reliable improvements are challenging to obtain without a larger number of observations for both assimilation and verification. [ABSTRACT FROM AUTHOR]

The Electrically Scanning Microwave Radiometer (ESMR) instrument on board the NIMBUS 5 satellite was a one channel microwave radiometer measuring the 19.35 GHz horizontally polarised brightness temperature (TB) from Dec. 11, 1972 to May. 16. 1977. The original tape archive data in swath projection have recently been made available online by NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Even though ESMR was a predecessor of modern multi frequency radiometers, there are still parts of modern processing methodology which can be applied to the data to derive the sea ice extent globally. Here we have reprocessed the entire data set using a modern processing methodology, that includes implementation of preprocessing filtering, dynamical tie-points, and a radiative transfer model (RTM) together with numerical weather prediction (NWP) for atmospheric correction. We present the one channel sea ice concentration (SIC) algorithm and the model for computing temporally and spatially varying SIC uncertainty estimates. Post-processing steps include re-sampling to daily grids, land-spill-over correction, application of climatological masks, setting of processing flags and estimation of sea ice extent, monthly means and estimation of trends. This sea ice dataset derived from NIMBUS 5 ESMR extends the sea ice record with an important reference from the mid 1970s. To make a consistent analysis of the sea ice development through time easier, the same grid and landmask as for EUMETSAT's OSI-SAF SMMR based sea ice CDR have been used for our ESMR dataset. SIC uncertainties have been included for further ease of comparison to other datasets and time periods. We find that our sea ice extent in the Arctic and Antarctic in the 1970s is generally higher than those available from the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) derived from the same ESMR dataset, with mean differences of 240.000 and 590.000 km², respectively. The largest differences reach up to 2 million km², when comparing monthly sea ice extents. Such large differences cannot be explained by the different grids and landmasks of the datasets alone, and must therefore also result from the difference in data filtering and algorithms, such as the dynamical tiepoints and atmospheric correction. The new ESMR SIC data set has been released as part of the ESA Climate Change Initiative Programme (ESA CCI) and is publicly available at: http://dx.doi.org/10.5285/34a15b96f1134d9e95b9e486d74e49cf (Tonboe et al., 2023). [ABSTRACT FROM AUTHOR]

Mount Qomolangma, known as the "Roof of the World," holds significant importance in exploring the vertical characteristics of the atmosphere, providing insights into high-altitude atmospheric features, and improving numerical models for forecasting downstream regions. Ground-based microwave radiometers (GWR) enable continuous profiling of atmospheric conditions in the troposphere, complementing radiosonde and satellite observations. This study explores the performance of the MWP967KV GWR installed at Qomolangma Base Camp by comparison with concurrent radiosonde measurements. The assessment covers GWR's atmospheric radiative brightness temperatures (T b) detection capability, accuracy of atmospheric parameter retrievals, and uncertainties in atmospheric parameters under different weather conditions. Using MonoRTM to calculate simulated T b from radiosonde, the results indicate a high precision of GWR's T b observations, showing a strong correlation (R ≈ 0.99) and a deviation of merely 2.4 K compared to simulated T b. Moreover, GWR exhibits high reliability in temperature (R ≈ 0.98) and water vapor density (ρ v) (R ≈ 0.91) observations, while the accuracy of relative humidity (RH) measurements requires improvement (R ≈ 0.55). The GWR observations are affected by clouds, precipitation, and surrounding Qomolangma mountain ridges, leading to significant uncertainties in atmospheric parameter retrievals between 2000 m to 6000 m above ground level. Additionally, GWR's sensitivity to temperature variations is limited, resulting in missed detections of temperature inversion. Despite these limitations, this study offers crucial insights into meteorological observations at high altitudes using GWR. These findings hold substantial implications for meteorological research and mountaineering activities in high-altitude regions. • The world's highest observation experiment of microwave radiometer. • Microwave radiometer's brightness temperature yielded an R of 0.99 and a bias of 2.4 K. • Microwave radiometer retrieved temperature and vapor density exhibited reliability. • Uncertainties in microwave radiometer under rainy, clear and cloudy conditions. [ABSTRACT FROM AUTHOR]

Ground-based multichannel microwave radiometers (GMRs) can observe the atmospheric microwave radiation brightness temperature at K-bands and V-bands and provide atmospheric temperature and humidity profiles with a relatively high temporal resolution. Currently, microwave radiometers are operated in many countries to observe the atmospheric temperature and humidity profiles. However, a theoretical analysis showed that a radiometer can be used to observe solar radiation. In this work, we improved the control algorithm and software of the antenna servo control system of the GMR so that it could track and observe the sun and we use this upgraded GMR to observe solar microwave radiation. During the observation, the GMR accurately tracked the sun and responded to the variation in solar radiation. Furthermore, we studied the feasibility for application of the GMR to measure the absolute brightness temperature (TB) of the sun. The results from the solar observation data at 22.235, 26.235, and 30.000 GHz showed that the GMR could accurately measure the TB of the sun. The derived solar TB measurements were 9950 ± 334, 10,351 ± 370, and 9217 ± 375 K at three frequencies. In a comparison with previous studies, we obtained average percentage deviations of 9.1%, 5.3%, and 4.5% at 22.235, 26.235, and 30.0 GHz, respectively. The results demonstrated that the TB of the sun retrieved from the GMR agreed well with the previous results in the literature. In addition, we also found that the GMR responded to the variation in sunspots and a positive relationship existed between the solar TB and the sunspot number. According to these results, it was demonstrated that the solar observation technique can broaden the field usage of GMR.

A digital automatic gain compensation (AGC) drone-borne K-band microwave radiometer with continuous high-speed acquisition and fast storage functions is designed and applied to obtain high-resolution radiation brightness temperature (TB) images. In this paper, the composition of the drone-borne passive microwave observation system is introduced, a data processing method considering the topography and angle correction is proposed, the error analysis of the projection process is carried out, and finally, a high-resolution microwave radiation TB image is obtained by a demonstration area experiment. The characteristics of the radiometer are tested by experiments, and the standard deviation of the TB is 1K. The data processing method proposed is verified using a demonstration case. The corrected data have a good correlation with the theoretical values, of which the R2 is 0.87. A high-resolution radiation TB image is obtained, and the results show the TB characteristics of different objects well. The boundary of the ground object is closer to the real value after correction. [ABSTRACT FROM AUTHOR]

Methods for passive sensing the atmosphere in the microwave range are one of important directions of remote sensing of environmental protection. To develop simple and cost-effective technical solutions and radiometric measuring techniques is an important task. A simple mobile radiometric system of 3-cm wavelength range designed for meteorological research has been presented. The radiometer is made on the basis of modulation scheme with some features of construction elements and input calibration. A method for accurate determination of the sky brightness temperature used for calibrating radiometric system has been proposed. A variant of constructing a radiometer with the use of satellite converter gas been implemented.

The Chinese Ocean Salinity Satellite is designed to monitor global sea-surface salinity (SSS). One of the main payloads onboard the Chinese Ocean Salinity Satellite, named the Interferometric Microwave Radiometer (IMR), is a two-dimensional interferometric radiometer system with an L-band, Y-shaped antenna array. The comparison of two different array orientations is analyzed by an end-to-end simulation based on the configuration of the IMR. Simulation results of the different array orientations are presented and analyzed, including the brightness temperature (TB) images, the distribution of the incidence angles in the field of view, the TB radiometric resolutions, the spatial resolutions, the number of measurements in the Earth grid and the expected SSS accuracy. From the simulations we conclude that one of the array orientations has better performance for SSS inversion than the other one. The advantages mainly result in wider swath and better SSS accuracy at the edge of the swath, which then improve the accuracy of the monthly SSS after averaging. The differences of the Sun’s effects for two different array orientations are also presented. The analysis in this paper provides the guidance and reference for the in-orbit design of the array orientation for the IMR.

In this study, the enhancement of the spatial resolution of microwave radiometer measurements is addressed by contrasting the accuracy of a gradient-like antenna pattern deconvolution method with its accelerated versions. The latter are methods that allow reaching a given accuracy with a reduced number of iterations. The analysis points out that accelerated methods result in improved performance when dealing with spot-like discontinuities; while they perform in a similar way to the canonical gradient method in case of large discontinuities. A key application of such techniques is the research on global warming and climate change, which has recently gained critical importance in many scientific fields, mainly due to the huge societal and economic impact of such topics over the entire planet. In this context, the availability of reliable long time series of remotely sensed Earth data is of paramount importance to identify and study climate trends. Such data can be obtained by large-scale sensors, with the obvious drawback of a poor spatial resolution that strongly limits their applicability in regional studies. Iterative gradient techniques allow obtaining super-resolution gridded passive microwave products that can be used in long time series of consistently calibrated brightness temperature maps in support of climate studies. [ABSTRACT FROM AUTHOR]

Sea ice is an important marine phenomenon in the Arctic region, and it is of great importance to study the motion of Arctic sea ice in the present day when its melting is accelerated by global warming. This study proposes a method to retrieve the motion of sea ice based on the maximum cross-correlation (MCC) and the successive correction method (SCM). The proposed method can apply different scales of search ranges to template matching according to the location of sea ice in the Arctic area. In addition, the data assimilation method can assign different weights to different data. We used 36.5 GHz and 89 GHz brightness temperature (Tb) data from the microwave radiometer imager (MWRI) aboard the Fengyun-3D (FY-3D) satellite, for the first time in the literature, to retrieve the sea ice motion in the Beaufort Sea from January to April 2019. The retrieved sea ice motion results were in good agreement with those obtained from the motion of the buoys. Compared with the data from the buoys, the root mean-squared error (RMSE) of the sea ice motion retrieved from FY-3D/MWRI Tb data was 1.1418 cm/s in the zonal direction and 1.0481 cm/s in the meridional direction, and the mean absolute error (MAE) between them was 0.7166 cm/s in the zonal direction and 0.6777 cm/s in the meridional direction. The RMSE between the sea ice motion obtained from the National Snow and Ice Data Center (NSIDC) and the motion of the buoys was 0.9515 cm/s in the zonal direction and 0.67003 cm/s in the meridional direction, and the MAE between them was 0.6576 cm/s in the zonal direction and 0.4922 cm/s in the meridional direction. The RMSE of daily average velocity from the FY-3D/MWRI results and NSIDC data product was 2.2726 cm/s in zonal and 1.9270 cm/s in meridional, and the MAE was 1.5103 cm/s in zonal and 1.1071 cm/s in zonal. The density of the merged data was higher than that obtained from a single polarization or frequency in this paper. The results indicate that FY-3D/MWRI Tb data can retrieve the sea ice motion successfully.

From 2015 to 2020, using the spectral gradient radiometric method, the possibility of the frozen/thawed (FT) state identification of tundra soil was investigated based on Soil Moisture Active Passive (SMAP) and Global Change Observation Mission – Water Satellite 1 (GCOM-W1) satellite observations of 10 test sites located in the Arctic regions of Canada, Finland, Russia, and the USA. It is shown that the spectral gradients of brightness temperature and reflectivity (measured in the frequency range from 1.4 to 36.5 GHz with horizontal polarization, a determination coefficient from 0.775 to 0.834, a root-mean-square error from 6.6 to 10.7 d and a bias from - 3.4 to + 6.5 d) make it possible to identify the FT state of the tundra topsoil. The spectral gradient method has a higher accuracy with respect to the identification of the FT state of tundra soils than single-frequency methods based on the calculation of polarization index. [ABSTRACT FROM AUTHOR]

A ground-based multichannel microwave radiometer (GMR) is commonly used to observe the atmospheric radiation brightness temperature (TB) in order to retrieve atmospheric temperature and humidity profiles. At present, GMRs are used only in meteorology and climate monitoring. However, theoretical analysis showed that GMRs can be also used to observe the solar radiation. Therefore, we tried to improve the antenna servo control system of a GMR so that it could track and observe the sun, and the results showed that the GMR could respond to the variation of solar radiation. A further question was: can a GMR observe the variation of the sun during a solar eclipse? Fortunately, two solar eclipse events were captured by the GMR on 26 December 2019 and 21 June 2020 in Xi'an, China. We used the upgraded GMR to observe the variation of solar radiation during the two solar eclipses. The observation and analysis results showed that (1) the GMR could accurately track the sun and respond to the variation of solar radiation during the solar eclipse. We analyzed the variation features of the solar radiation by combining the solar phase during the two solar eclipses. (2) We found that the GMR could respond to the variation of the solar radiation arising from the Earth–Sun distance, and we further propose a novel method to measure the eccentricity of earth orbit with the GMR by using the passive solar observation. The results show that the eccentricity measured was 0.0169, which agreed quite well with the value of 0.0167 in the literature. (3) The average variation percentages of both the Earth–Sun distance and the intensity of the incident solar radiation throughout the year were estimated to be 3.44% and 6.6%, respectively. According to these results, the solar observation techniques can broaden the field usage of GMR. [ABSTRACT FROM AUTHOR]