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The advanced microwave radiometer-climate quality (AMR-C) is a part of the European Sentinel-6A/B series, a collaboration between ESA and NASA, of two Earth-observing satellites, which will be launched in 2020 and 2025. Compared to its predecessor, Jason-3, the two AMR-C radiometer instruments have an external calibration system which enables higher radiometric stability accomplished by moving the secondary mirror between well-defined targets. Sentinel-6 allows continuing the study of the ocean circulation, climate change, and sea-level rise for at least another decade. Besides the external calibration for the AMR heritage radiometer (18.7, 23.8, and 34 GHz channels), the AMR-C contains a high-resolution microwave radiometer (HRMR) with radiometer channels at 90, 130, and 168 GHz. This subsystem allows for a factor of 5× higher spatial resolution at coastal transitions. This article presents a brief description of the instrument and the measured performance of the completed AMR-C-A and AMR-C-B instruments.

Land surface temperature (LST) is a key parameter and plays an important role in hydrology, ecology, environment, and biogeochemistry. It is difficult for the existing satellites to acquire global LST with spatial and temporal consistency. The Moon-based Earth observation platform with a long life, large coverage can observe continuously the Earth, and obtain the global-scale LST. At present, various approaches for retrieving LST from passive microwave remote sensing data have been developed for the satellite remote sensing data with small and constant viewing zenith angle, however, the Moon-based Earth observation platform located outside the Earth's ionosphere has the viewing zenith angle of 0-90°. In this study, a modified physical-based method of LST retrieval from passive microwave data was developed for wide viewing zenith angles, and the LST and emissivity can be simultaneously estimated through the analysis of various atmospheric and ionosphere parameters. Three types of data, including the FengYun-3B satellite microwave radiation imager data, the multichannel Advanced Microwave Scanning Radiometer data, and Moon-based microwave radiation simulation data with the viewing zenith angles of 52-53°, 55°, and 0-90°, respectively, were used to retrieve LST. Results show that the estimation accuracy of LST decreases with the increase of viewing zenith angle. The 23.8 and 36.5 GHz brightness temperature is optimum for the LST estimation under a large-scale viewing zenith angle, and the root mean square errors of the LST are 5.18, 5.44, and 4.79 K, respectively.

This paper reports on development of a scattering model of a soybean canopies at L-band. The scattering model will be used for active and passive remote sensing of soybean plants with an emphasis on mature soybeans where the presence of pods is important to the observed microwave signal. The active problem is treated using the Distorted Born Approximation (DBA) and the passive problem is analyzed using Peake's method. These results are compared with field measurements made in 2012 by the truck-mounted ComRAD system, which is a combined radar and radiometer instrument operating at L-band. Investigation of backscatter from the soybean canopy shows good agreement between the radar measurement data and modeling results. The results also indicate that the L-band radar backscatter can be used to monitor both the soil moisture and the growth of the soybean pods. Past passive modeling efforts have not considered soybeans late in the growing season when pods are important. A new passive radiation model of soybean canopy will be developed based on the backscatter model.

Recent lunar observations have concluded that significant water ice deposits may exists in the regolith, especially in the permanently shadowed regions near the lunar poles. Detection and utilization of these reserves is very important to sustain the continuous human presence on the Moon. This paper, using analytical models and numerical simulations, demonstrates that wideband microwave radiometers are promising instruments for exploring underground water ice deposits on the Moon as their brightness temperature spectra are highly sensitive to water presence in the regolith.

Distributed from L to high frequency band, Radio frequency interferences (RFIs) are contaminating the geophysical parameters estimated from the measurements of microwave radiometers. Chinese researchers are developing series of Earth observation satellites focusing on the marine dynamic environment for numerical weather prediction and climate monitoring. The scanning microwave radiometer onboard HY-2B (Haiyang-2B) has been monitoring sea surface temperature observations since 2018. After more than 2 years in orbit, an overview of RFI scenario worldwide has been provided and lessons have been learnt from HY-2B RFI activities. The Interferometric Microwave Radiometer (IMR) will be a main payload onboard the Chinese Ocean Salinity Satellite. Preliminary studies have been carried out on RFI detection and localization to improve the performance of this mission.

The launch of L-band passive microwave radiometer satellites in the last decade (SMOS, Aquarius, and SMAP) started a new era in Earth Observation at low frequency. On the trails of these missions, recent studies showed that microwave radiometers operating at even lower frequencies (P-band) can provide new information for cryospheric and ocean science and improve the current understanding of Earth processes. In particular, experimental airborne campaigns were conducted in both Artic and Antarctica, within the NASA's UWBRAD project, by using a wide band radiometer operating in the range 0.5-2 GHz, aimed at investigating the temperature profiles of ice sheets and the sea ice thickness. By leveraging the results of UWBRAD system, a new mission concept was proposed to ESA Earth Explorer 10 and 11 (called CryoRad) and NASA EVI-6 (called PolarRad) featuring a spacebome 0.4-2 GHz nadir-looking microwave radiometer for the monitoring of polar regions. Even though the main goals of all these sensors are related to observables such as soil moisture, ocean salinity, and geophysical parameters of the cryosphere, all of them suffer from the emission due the atmosphere. In the spectral range comprised between 0.5 and 2 GHz the atmosphere is considered almost transparent, being the major contributions to the emission due to the water vapor (in both physical phases) and to the molecular oxygen, however a clear assessment is still lacking in literature. The aim of this paper is to provide an accurate estimate of the atmospheric effect on measured T B from space at low frequency for different climate scenario by using a combination of in-situ data (i.e. radio-sounding) and microwave emission model.

The NASA Soil Moisture Active Passive (SMAP) mission design includes two instruments that make coincident active and passive measurements in the low frequency microwave L-band range. In the design, the two instruments share the large (6 meter) light-weight mesh rotating reflector and some of the antenna subsystems. The passive radiometer measurements provide measurements that are highly sensitive to surface soil moisture but at coarse resolution. The active radar measurements provide high-resolution measurements but less sensitive to soil moisture variations because of two-way attenuation through the overlying vegetation canopy and more complex rough soil surface scattering. The synergy between the active and passive measurements allows retrieval of surface soil moisture at intermediate scales and with intermediate accuracy. The SMAP radar failed after three months, thus allowing only about three months of active-passive products. The SMAP project switched to using the Copernicus Sentinel 1-A and 1-B C-band SAR measurements for its active-passive product. The disadvantage of the switch-over is the greater vegetation attenuation and more complex rough-surface scattering of C-band when compared to L-band. The advantages are greater resolution of the C-band Synthetic Aperture Radar (SAR). The revisit times are also affected since data from two platforms with different swath widths have to be combined. In this presentation we explore the algorithm issues associated with the switch and compare the products during the period when both the SMAP radar and Sentinel-1 SARs were operating.

Low frequency microwave measurements have been used to gain insight into what happens deep inside ice sheets for some time now. In this paper, we used a deep neural network to classify each pixel within SMAP radiometer footprints over the Antarctica ice sheet as melt or no-melt. NASA's SMAP mission offers a valuable additional set of observations. The SMAP L-band (1.4 GHz) radiometer retrievals also cover virtually the entire Antarctica ice sheet twice a day. Consistent morning and evening sampling are provided by 6 AM/PM equator-crossings of the satellite ascending and descending polar orbits. The spatial resolution of the instrument is about 40 km. The cross-entropy loss function is used in our network. To make training and test sets, we used air temperature records from available weather stations to distinguish melt and no-melt ice sheet conditions. Our results show that the ice sheet experienced extensive surface melting during the 2015–2016 melt season, and also intensive melting in 2019–2020, particularity on the West Antarctic Ice Sheet.

The Special Sensor Microwave Imager/Sounder (SSMIS) provides vital long-term microwave radiometer observations as a member of the Global Precipitation Measurement (GPM) mission constellation. There are four SSMIS sensors that have been launched with three still in operation. In preparation for the GPM Version 7 (V07) data release, previous SSMIS calibration corrections are reexamined and updated using the latest data and recent knowledge gained from calibrating similar microwave radiometers. These calibration updates are presented here and include pointing parameters that affect geolocation, along-scan bias adjustments to correct for fall-off at the edge of the scan, and thermal heating issues caused by an emissive reflector and solar intrusions. The new updates greatly improve the accuracy of the SSMIS observations that will be released as part of the GPM V07 dataset.

Modern microwave radiometers have demonstrated the feasibility of monitoring surface salinity from space and also the need for better accuracy in cold water. Accuracy could be improved by adding measurements at lower frequencies (lower than the measurement at 1.4 GHz currently used) and closer to the peak in sensitivity of brightness temperature to changes in salinity. Proposals to accomplish this have focused on wide bandwidth receivers which include at the low end frequencies close to the peak in sensitivity. This strategy involves trade-offs, some obvious such as radio frequency interference (RFI) when operating outside the protected band at 1.4 GHz and the loss of spatial resolution at lower frequencies. Others stemming from the interdependence of the retrieval of salinity on water temperature and surface roughness are more subtle. The objective of this manuscript is to examine this interdependence and its implications to future wide bandwidth instruments for remote sensing of salinity from space.

An advanced method for sea ice concentration (SIC) retrieval, based on measurements of the Advanced Microwave Scanning Radiometer 2 (AMSR2), is validated. An advancement relates to tie point choice for the polarization difference in satellite measurements over open water. The approach is based on the results of physical modeling of the sea ice - ocean - atmosphere system and analysis of the AMSR2 measurements in the Arctic region. The validation is done for summer months using MODIS Sea Ice Extent data as a source of ground-truth information. Areas of 100% open water and 100% sea ice are compared for the MODIS Sea Ice Extent and the AMSR2 retrieved SIC. It is found that the AMSR2 algorithm systematically underestimates 100% SIC as compared with the MODIS 100% SIC in summer months.

The Chinese Ocean Salinity Satellite is part of the Chinese ocean dynamic satellite series, and is dedicated to global SSS observation with two payloads onboard. These two payloads, named the Interferometric Microwave Radiometer (IMR) and the Microwave Imager Combined Active and Passive (MICAP), both adopt interferometric aperture synthesis technology. IMR is a two-dimensional L-band interferometric radiometer system with a Y -shaped antenna array. MICAP is a one-dimensional passive/active combined system, where the L-, C-, and K-band interferometric radiometers' antenna arrays are arranged in a line, and the active device is an L-band scatterometer. Based on the payload configurations, an end-to-end simulation shows that, with the assistance of the C- and K-band radiometers and the L- band scatterometer, the combined retrieval accuracy improves compared with the SSS retrieved using only L-band TB and auxiliary parameters. The best accuracy of SSS is achieved when considering all the available measurements from two payloads together in a combined retrieval.

The Microwave Single Pixel Imager is a project to determine whether compressive sensing techniques can be leveraged to reduce the required aperture size for microwave radiometers. A novel antenna assembly, the Mechanically-Actuated Reconfigurable Reflectarray, is a key enabler, allowing the development of a number of known sampling patterns which can properly sample the scene according to the needs of the compressive sensing imaging algorithm. Further development and testing of this novel antenna assembly is discussed, including further design details, expected parameter values for the prototype version, and an updated schedule for the hardware development and laboratory measurements to verify the simulated and expected parameter values.

Passive microwave radiometers provide brightness temperature (TB) measurements in a large spectral range with relatively high temporal resolution. Because of their significant role in environmental studies, it is imperative to have a higher temporal resolution and more consistent datasets. This research aims to build a TB diurnal cycle at the Global scale. The shape (amplitude and phase) of the diurnal cycle for each month is obtained by merging several days of Global Precipitation Measurement (GPM) Microwave Imager (GMI) TB measurements because the acquisition times of GMI vary from day to day. This preliminary shape will later be improved by using the other sensors with daily fixed acquisition times such as three Special Sensor Microwave Imager/Sounder (SSMIS) and Advanced Microwave Scanning Radiometer 2 (AMSR2). The final product is a highly frequent diurnal cycle that can help prediction of the time of the freeze thaw transition states.

The Flexible Microwave Payload -2 is the microwave remote sensing payload of the FSSCat mission. The instrument is the outcome of years of work of the Universitat Politécnica de Catalunya Passive Remote Sensing Laboratory, and the NanoSat-Lab. The FSSCat mission was launched on board the Vega VV16, on September the 3 rd , 2020. The instrument was executed for the very first time on September the 16 th , 2020, and it was commissioned less than two weeks later. This extended abstract presents the geo-located FMPL-2 measurements, which consist of a Global Navigation Satellite System - Reflectometer and an L-band radiometer. The performance of the instrument and preliminary level 1C results are presented, showing that CubeSats can to perform passive microwave remote sensing scientific missions. This work was supported by 2017 ESA S3 challenge and Copernicus Masters overall winner award (“FSSCat” project). This work has been (partially) sponsored by project SPOT: Sensing with Pioneering Opportunistic Techniques grant RTI2018-099008-B-C21 / AEI / 10.13039/501100011033, and by the Unidad de Excelencia Maria de Maeztu MDM- 2016-0600.

Low frequency microwave measurements have been used to gain insight into what happens deep inside ice sheets for some time. In this paper, the response of SMAP (Soil Moisture Active Passive) L-band measurements to surface melting of the ice sheet from 2015 through 2019 is investigated. SMAP covers virtually the entire Antarctica ice sheet twice a day with its L-band (1.4 GHz) radiometer. The overpasses center on morning and evening hours as the satellite is on a 6 AM/6PM equator-crossing orbit. The spatial resolution of the instrument is about 40 km. We applied a newly developed geophysical model-based algorithm to detect snow wetness, which can be used as an indicator of melt extent and intensity. It is shown that the ice sheet experienced extensive surface melting during the 2015-2016 melt season (~10% melt extent), and also underwent intensive melting in the 2019-2020 season (median of 0.3% snow wetness), particularity on the West Antarctic Ice Sheet.

In this work, a comparative analysis of experimental measurements of the azimuthal anisotropy of microwave radiation from a rough water surface is carried out. A large set of experimental data was obtained during experiments aimed on study of the interaction between the water surface and the atmosphere using microwave radiometers. The experiments were carried out on the oceanographic platform of the Black Sea Hydrophysical Testing Ground of the Russian Academy of Science in the period from 2005 to 2019. Over the years, the set of radiometric instruments changed, but radiometers with a frequency of about 36 GHz were used in each experiment, so the results are presented specifically for this frequency. A qualitative comparison of the measurement results with model calculations and other experimental studies of anisotropy are carried out. It is shown that there is a strong sensitivity of changes in the radio emission of a rough water surface, both to the wind speed and to its direction at different incidence angles.

In the framework of a project funded by the Italian Space Agency (Algoritmi-METEMW), experimental activities based on airborne multi-frequency microwave radiometric measurements and simultaneous ground-truth data collection have been carried out in Central Italy, in an agricultural area close to Florence. The aim of the project was the development of innovative algorithms for the estimate of hydrological parameters integrating active and passive microwave data. The retrieval algorithms are based on Artificial Neural Networks (ANN). IFAC multi-frequency microwave radiometers (at L, C, and X bands) have been installed on ultralight helicopters, which overflew the area in concomitance with SMAP and Sentinel-1 (S-1) image acquisitions. Comparisons of new data with past results confirmed the already stated relationships between microwave indices and soil and vegetation parameters. Soil moisture content (SMC) values estimated from L-band radiometric data are very close to those retrieved using the ANN algorithm. This result confirms the possibility of validating satellite algorithms with airborne microwave radiometers.

Passive microwave brightness temperature (TB) radiometers are widely used to retrieve several atmospheric and surface parameters such as precipitation, soil moisture, freeze and thaw, water vapor, air temperature profile, and land surface emissivity. Since TBs are measured at different microwave frequencies with various instruments, incident angles, footprints, spatial resolutions, and radiometric characteristics, a combination of data from different microwave sensors could be inconsistent. For this reason, this study primarily uses the nonsynchronous Global Precipitation Measurement (GPM) Microwave Imager (GMI) measurements to construct the diurnal cycle of TBs for each month. This diurnal pattern could be used as a point of reference to validate and calibrate the diurnal cycle of TBs from fusing the measurements of other sensors with daily fixed acquisition times (SSM/I, SSMIS, AMSR2, and etc.). The data from these sensors should also be merged and harmonized in order to build a comprehensive global diurnal cycle of passive microwave TBs. This highly frequent diurnal cycle will eventually help predict the emissivity estimation and potentially further advance the accurate prediction of the estimated time of the freeze/thaw (FT) transition states. Global comparison of TBs obtained from different sensors shows a moderate variance with a significant dependence on land cover type. The results of this study can enhance the temporal detection of freeze and thaw which is more helpful during the transition times when multiple FT changes may occur within a day.

Probing of the typhoon Hagibis in stage of maximum intensification with satellite active and passive microwave sensors onboard GPM (Global Precipitation Measurements), GCOM-W1, Meteor-M No. 2–2 and Sentinel-1 satellites permitted retrieving the ocean surface and atmospheric parameters and investigate evolution of their spatial structure. Wind speed W, cloud liquid water content $Q$ and total atmospheric water vapor content $V$ were estimated from GMI and AMSR2 data with original algorithm based on total atmospheric absorption at frequency of 10.65 GHz τ(10). Mean square slope (mss) was retrieved from Ku-band channel of DPR radar. The location of typhoon center was traced due to the difference of retrieved parameters between the eye and surrounding area. Hagibis warm core was found by MTVZA-GY radiometer at several frequencies at oxygen absorption band. The position of the sharp gradient zones in V, Q and τ(10) fields served as an indicator of the change of typhoon area and structure. The calm cloudless region in the western Japan Sea was used as the reference area for matching to zero level of the retrieved wind speed and mss.

NEDT is a critical metric for assessing the noise level and instrument performance of microwave radiometers. In the study, we have reviewed different algorithms of calculating NEDT including those of EUMESAT, UK Met Office, and NOAA. We found that these algorithms suffer from a number of issues resulting in an overall underestimate of NEDT. We develop an algorithm with solid physical and mathematical substance and apply it to ATMS. The algorithm provides unbiased estimate of NEDT and is validated against ground thermal vacuum chamber measurement and simulation.

Microwave measurements have been previously used to detect melt events due to their sensitivity to the presence of liquid water in snow. Since NASA's SMAP mission offers a valuable set of low frequency radiometer measurements, SMAP measurements have been used as a tool to detect melt events. SMAP's L-band radiometer also covers virtually the entire Greenland ice sheet twice daily. The overpasses center on morning and evening hours as the satellite is on a 6AM/6PM equator-crossing orbit, and the spatial resolution of the instrument is about 40 km. In this paper, the response of L-band measurements to surface melting of the ice sheet from 2015 through 2019 melt seasons is investigated. It is shown that the Greenland ice sheet experienced an unusually strong melt event at the end of July 2019, which extended the melt area across much of dry snow zone of the ice sheet over a period of two days.

Chinese ocean salinity satellite is a mission designed for global ocean salinity monitoring. Two main payloads equipped onboard the satellite are the Interferometric Microwave Radiometer (IMR) and the Microwave Imager Combined Active and Passive (MICAP) which both have L-band radiometer and adopt aperture synthesis technology. A simulation is designed according to the payloads' configurations and consists of three parts: the brightness temperature generator, the radiometer system and the parameters retrieval. Preliminary results, which contain IMR and MICAP's brightness temperature resolution, spatial resolution, and parameter retrieval accuracy, are presented.

Passive microwave remote sensing data and measured soil moisture content in AMSR-E (Advanced Microwave scanning Radiometer - Earth Observing System) had been adopted for hilly region of Central Sichuan province from 2006 to 2010. Using Tbv6.9, Tbv10.7, Tbv18.7 and Tbh36.5 as input factors, A GRNN neural network was established to retrieve soil water content, and the correlation coefficient between the simulated value and the spatial and temporal sequence of measured soil water was calculated. The results showed that the GRNN neural network's correlation coefficient inversion of soil moisture and the measured soil moisture is relatively higher than the one of soil moisture retrieved by the equation inversion of standard atmospheric transmission and the measured soil moisture. Thus using AMSR-E data based on GRNN neural network model to simulate the soil moisture is feasible.

Distributed from low frequency to terahertz (THz) band, radio frequency interference (RFI) are contaminating the retrievals of geophysical parameters from the measurements of microwave radiometers. GeoSTAR-III, working at 180 GHz, may also face such problem. Accurate localization is very important for effectively switching off illegal RFI sources. In this work, a precise RFI localization approach is presented to reduce computation load. The proposed RFI localization method utilizes the minimum difference in the vicinity of the RFI source. This method can reduce computation complexity without reducing accuracy.

In this paper we present a room temperature radiometer that can eliminate the need of using cryostats in satellite payload reducing its weight and improving reliability. The proposed radiometer is based on an electro-optic upconverter that boosts up microwave photons energy by upconverting them into an optical domain what makes them immune to thermal noise even if operating at room temperature. The converter uses a high-quality factor whispering gallery mode (WGM) resonator providing naturally narrow bandwidth and therefore might be useful for applications like microwave hyperspectral sensing. The upconversion process is explained by providing essential information about photon conversion efficiency and sensitivity. To prove the concept, we describe an experiment which shows state-of-the-art photon conversion efficiency $\eta =10^{-5}$ per mW of pump power at the frequency of 80 GHz.

This paper analyzes the detection principle of microwave radiometers and the composition of base data, and introduces a new method to measure data reliability, i.e., to measure the stability of the voltage value based on the lv0 data shear. Through continuous analysis of stability of the Vbb_nd value as well as comparison and analysis of data obtained during the good and poor time periods, it was shown that there is a positive correlation between the stability of the voltage value based on the lv0 data shear and the accuracy of the product. Temperature products are more consistent with the sounding data than humidity products. Meanwhile, in this paper, the relative humidity and unstable stratification data inversed from the observation data obtained from microwave radiometers between July 2017 and August 2018 at the Huaian National Benchmark Meteorological Station are used to comparatively analyze the characteristics of the data observed by the microwave radiometer prior to the short-time rainstorm process. The relative humidity of the entire 0-6KM shear observed by the microwave radiometer was nearly saturated or saturated within 1 hour prior to rainfall. Before the occurrence of rainfall, the transition of relative humidity from unsaturated to saturated or nearly saturated state usually indicates the start of the rainfall process. Before the occurrence of short-term heavy precipitation, the atmospheric stratification is usually in an unstable state with the maximum K index exceeding 40 and the maximum TT index exceeding 50, which are closely related to the occurrence and development of rainfall.

L-band microwave radiometers (1.4 GHz) are relied in the field of remote sensing to retrieve and analyze land surface characteristics. However, the existing ground based L-band microwave radiometers are not portable and requires heavy maintenance. This paper focuses on introducing a new terrestrial hand held L-band microwave radiometer to measure the passive microwave data over bare ground surface. Soil temperature, brightness temperature (TB), emissivity and soil moisture of the bare ground is measured and the relationships between the measured values are evaluated for the present study.

Rutherford Appleton Laboratory Space Department (RAL Space) and Radiometer Physics GmbH are responsible for the provision of millimetre-wave front-end receivers operating from 165 GHz to 664 GHz for three instruments on board the MetOp Second Generation (MetOp-SG) satellites. Qualification of the Engineering Qualification Models (EQMs) is recently completed. This paper presents the results of the EQM qualification for receivers operating at 165 GHz, 183 GHz and 229 GHz for the MWS and MWI instruments.

In this work we report progress towards a single pixel microwave radiometric system implemented using a reconfigurable reflectarray of binary-state elements (BSEs). The BSEs are used to randomly modulate the incoming field prior to projecting towards a radiometer. Reconstruction of the scene is then achieved through first-order iterative convex programming algorithms. We describe the design of our modulation patterns and examine an appropriate sparsity-promoting basis using modeled brightness temperature data. Image reconstruction results of the proposed approach are then demonstrated using computational electromagnetic simulations of the reflectarray.

Cross-track microwave sounders make up a significant percentage of the radiometers included in the Global Precipitation Measurement (GPM) constellation. Therefore, it is important to properly assess the calibration of each sounder instrument and to understand the impact of the calibration on the derived precipitation rates. This ensures an accurate precipitation product is produced for the entire constellation. This paper will use data from past and current microwave sounders to show how offsets in the calibration can impact the precipitation using the GPM Level 2 GPROF algorithm. Potential improvements to the instrument calibration will be assessed by analyzing how they would positively impact the precipitation trends and agreement among the constellation sensors.

For many years Radio Frequency Interference (RFI) has been an increasing problem especially for spaceborne radiometers; as a result, there has been an increasing effort on developing algorithms and hardware for counteracting RFI. Due to the amount of time it takes to develop and build spaceborne systems, this development has had a limited effect on current spaceborne systems. In spaceborne radiometer systems currently being built the need for onboard detection and blanking of RFI has been acknowledged. This paper addresses the efforts to implement RFI detection and blanking techniques on European operational spaceborne systems, MetOp Second Generation (MetOp-SG) satellites and the Copernicus High Priority Mission Passive Imaging Microwave Radiometer (CIMR) satellites.

This paper describes the method tropospheric delay estimation using microwave radiometry for the radio navigation. Application of microwave radiometers for measuring the atmospheric water vapor, cloud liquid, profiles of temperature and tropospheric delay is discussed. Some results of experimental research of tropospheric wet delay in different regions are presented.

Taklamakan is the second largest shifting sand desert in the world and a major source of dust aerosols in East Asia. The time series of GCOM-W1 AMSR2 brightness temperatures T B s were constructed over the Tazhong weather station (39.00° N, 83.40° E, elevation H =1100 m) in Taklamakan desert for the period 1 January 2015 - 31 December, 2016. T B s were analyzed together with the time series of meteorological variables: air pressure, temperature and humidity, measured 8 times per a day. The AMSR2 sensing was performed on the ascending (A) and descending (D) orbits at approximately 1:30 PM and 1:30 AM (local time), which is close to the daily maximum and minimum air surface temperature T air , respectively. Land surface temperature was not measured. The T B s were averaged each day separately for ascending and descending orbits. The seasonal, synoptic, and diurnal T B variations differ significantly with frequency and polarization. The influence of the variations of atmosphere parameters and the surface emissivity on T B s was estimated by numerical integrating of the microwave radiation transfer equation in the atmosphere-underlying surface system The linear regression equations T air = F[T B (ν)] were derived and the T air retrieval errors were estimated. The proposed method of T air estimating can be applied in areas with different physical-geographic conditions, including Greenland and Antarctica, as well as for external calibration of satellite microwave radiometers.

The application of passive microwave soil moisture products is limited by the poor spatial resolution. In this study, a spatially-based regression method was tested using the PLMR(Polarimetric L-band Multibeam Radiometer) observation data acquired in the Heihe Watershed Allied Telemetry Experimental Research (HiWATER). The land surface temperature data were used as the auxiliary data to perform downscaling soil moisture and brightness temperature. The root-mean-square errors (RMSEs) of brightness temperature and soil moisture are 5.5 K and 0.021 cm3/cm3 between the calculated values and refenced values, respectively. This method provided a potential way for the downscaling of passive microwave brightness temperature and soil moisture.

The AMSR-E (Advanced Microwave Scanning Radiometer - EOS) sensor onboard NASA’s Aqua satellite is a passive microwave radiometer and is widely used in land surface Soil Moisture (SM) retrieval. The NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) archives and distributes a daily SM product (AMSR-E/NASA) from 2002 to 2011 at 25km resolution retrieved by a simplified soil moisture retrieval algorithm derived from a simplified radiative transfer model. However, the SM dynamic range of this product is very narrow, which basically cannot reflect intra- and inter-annual variations. This paper analyzed the AMSR-E/NASA SM product and compared it with the AMSR-E/JAXA SM. Furthermore, the reason of the narrow intra- and inter-annual variation of AMSR-E/NASA SM was analyzed in depth. Finally, the AMSR-E/NASA SM product was improved using in-situ data collected in the Tibetan Plateau. Results indicated that the improved monthly SM AMSR-E product was better than AMSR-E/NASA and AMSR-E/JAXA in Naqu study area from January to September of 2011, as documented by a lower RMSE (Root Mean Square Error) against in-situ SM data, i.e. 0.065 cm3 cm-3.

Neural networks were used to estimate the ability of different sets of predictors to capture the variability of above ground biomass (AGB). SMOS brightness temperatures (TBs) for only two incidence angles capture 85% of the AGB variance. Adding soil moisture or L-band vegetation optical depth (L-VOD) increase the ability to capture the AGB variance to 90 % and 92 %, respectively. With respect to using only TBs, L-VOD improves the AGB estimation in regions of low vegetation.

A new airborne synthetic aperture radar (SAR) system was recently developed for the estimation of snow water equivalent (SWE). The radar is part of the SWESARR (Snow Water Equivalent Synthetic Aperture Radar and Radiometer) instrument, an active passive microwave system specifically designed for the accurate estimation of SWE. The dual polarization (VV, VH) radar operates at three frequency bands (9.65 GHz, 13.6 GHz, and 17.25 GHz), with bandwidths of up to 200 MHz. The radar flew its first flight campaign in November 2019, along with SWESARR’s -already operational – radiometer. The radar collected comprehensive data sets over various terrains that show a successful system performance. The instrument is slated to participate in future SnowEx campaigns.

Radio Frequency Interference (RFI) at 18.7 GHz in and around the continental United States observed by passive microwave radiometers such as the Global Precipitation Measurement (GPM) Microwave Imager (GMI) has been noted in multiple publications. A large part of this RFI arises from reflected geosynchronous direct broadcast satellite transmissions. The interference yields surprisingly high artificial brightness temperature values, ranging from a few Kelvin up to over 1000 Kelvin. Some of the highest levels and most direct reflections occur over land from specular reflections from smooth surfaces such as lakes and rivers. Over the ocean surrounding the United States, the reflections are generally less directional, occurring at higher glint angles and often with lower peak levels than over land. The interference corrupts the GMI measurements about 13% of the time over the ocean around the US, and over 5% of the time over the affected land areas.

Multiband passive microwave imagery in X to W Bands has a nearly 40-year history of utilization for measurement of multiple geophysical parameters (e.g., precipitation rate, ocean surface wind speed, sea ice concentration, and land surface temperature). Spatial resolution is limited by aperture size, and although aperture sizes have grown to 1-2 meters, current capability will not meet future spatial resolution needs. As aperture size increases, new antenna feed techniques are needed to maintain contiguous coverage and obtain Nyquist sampling. Here we apply the correlator array-fed radiometer architecture adapted from radio astronomy and show how it can meet emerging needs. Simulation results of a 0.8-m, 36.5-GHz, array-fed reflector (equivalent to 20 meters at 1.41 GHz) show the feasibility of creating multiple over-lapping beams.

Global Satellite Mapping of Precipitation (GSMaP) is a system to produce global surface precipitation field with 0.1 degree and 1 hour resolution from geostationary infrared imager and microwave radiometer in low earth orbit (Ushio et al. 2019, Mega et al. 2018). On this system, the input data sets are precipitation rate retrieved from the microwave radiometers and infrared images to compute the moving vector fields. Based on the moving vector fields calculated from the successive IR images, precipitation fields are propagated and refined on the Kalman filter model which uses the relationship between the infrared brightness temperature and surface precipitation rate. Because of this methodology, basically the resolution of the GSMaP products is limited on the resolution of the geostationary infrared images.

The FSSCat mission is a two nano-satellite Earth Observation mission based on 6-unit CubeSats. This paper is focused on the description of one of the remote sensing payloads: the Flexible Microwave Payload 2 (FMPL-2), on board the 3 Cat-5/A. The payload design is based on a Software Defined Radio, aiming to demonstrate the capabilities of nano-satellites to provide valuable scientific data. Two different instruments are integrated into a single payload: a multi-constellation (GPS and Galileo) Global Navigation Satellite System Reflectometer (GNSS-R), and a Total Power Radiometer (TPR) with Radio Frequency Interference (RFI) detection and mitigation capabilities. This paper presents the payload design, and the tests conducted during the qualification campaign. This work was supported by the ESA S3 challenge award (FSSCat project) 2017 Copernicus Masters overall winner, by the Spanish Ministry of Economy and Competitiveness, by the Spanish Ministry of Science, Innovation and Universities, ”Sensing with Pioneering Opportunistic Techniques”, grant RTI2018-099008-B-C21, by the Unidad de Excelencia Maria de Maeztu MDM-2016-0600, and by the ICREA Academia award by the Generalitat de Catalunya.

Moderate to high spatial resolution (

The Global Change Observation Mission-Water (GCOM-W) satellite was launched by the Japan Aerospace Exploration Agency (JAXA) in May 2012. It carries the Advanced Microwave Scanning Radiometer 2 (AMSR2), which is a 6-band multi-frequency, dual-polarization microwave radiometer with a 2-m aperture antenna. The GCOM-W/AMSR2 completed its 5-year designed mission life in May 2017, and has transferred to extended-mission phase. Besides the 10-month gaps between AMSR-E and AMSR2, the AMSR series provide long-term global observation data for studies of the global water cycle, airsea interactions and polar environments. An overview of these studies is given in this paper.