Showing papers on "Radiometer published in 2020"

An overview of and issues with sky radiometer technology and SKYNET

Abstract: . This paper is an overview of the progress in sky radiometer technology and the development of the network called SKYNET. It is found that the technology has produced useful on-site calibration methods, retrieval algorithms, and data analyses from sky radiometer observations of aerosol, cloud, water vapor, and ozone. A formula was proposed for estimating the accuracy of the sky radiometer calibration constant F0 using the improved Langley (IL) method, which was found to be a good approximation to observed monthly mean uncertainty in F0 , around 0.5 % to 2.4 % at the Tokyo and Rome sites and smaller values of around 0.3 % to 0.5 % at the mountain sites at Mt. Saraswati and Davos. A new cross IL (XIL) method was also developed to correct an underestimation by the IL method in cases with large aerosol retrieval errors. The root-mean-square difference (RMSD) in aerosol optical thickness (AOT) comparisons with other networks took values of less than 0.02 for λ≥500 nm and a larger value of about 0.03 for shorter wavelengths in city areas and smaller values of less than 0.01 in mountain comparisons. Accuracies of single-scattering albedo (SSA) and size distribution retrievals are affected by the propagation of errors in measurement, calibrations for direct solar and diffuse sky radiation, ground albedo, cloud screening, and the version of the analysis software called the Skyrad pack. SSA values from SKYNET were up to 0.07 larger than those from AERONET, and the major error sources were identified as an underestimation of solid viewing angle (SVA) and cloud contamination. Correction of these known error factors reduced the SSA difference to less than 0.03. Retrievals of other atmospheric constituents by the sky radiometer were also reviewed. Retrieval accuracies were found to be about 0.2 cm for precipitable water vapor amount and 13 DU (Dobson Unit) for column ozone amount. Retrieved cloud optical properties still showed large deviations from validation data, suggesting a need to study the causes of the differences. It is important that these recent studies on improvements presented in the present paper are introduced into the existing operational systems and future systems of the International SKYNET Data Center.

Studying the Composition and Mineralogy of the Hermean Surface with the Mercury Radiometer and Thermal Infrared Spectrometer (MERTIS) for the BepiColombo Mission: An Update

Abstract: Launched onboard the BepiColombo Mercury Planetary Orbiter (MPO) in October 2018, the Mercury Radiometer and Thermal Infrared Spectrometer (MERTIS) is on its way to planet Mercury. MERTIS consists of a push-broom IR-spectrometer (TIS) and a radiometer (TIR), which operate in the wavelength regions of 7-14 μm and 7-40 μm, respectively. This wavelength region is characterized by several diagnostic spectral signatures: the Christiansen feature (CF), Reststrahlen bands (RB), and the Transparency feature (TF), which will allow us to identify and map rock-forming silicates, sulfides as well as other minerals. Thus, the instrument is particularly well-suited to study the mineralogy and composition of the hermean surface at a spatial resolution of about 500 m globally and better than 500 m for approximately 5-10% of the surface. The instrument is fully functional onboard the BepiColombo spacecraft and exceeds all requirements (e.g., mass, power, performance). To prepare for the science phase at Mercury, the team developed an innovative operations plan to maximize the scientific output while at the same time saving spacecraft resources (e.g., data downlink). The upcoming fly-bys will be excellent opportunities to further test and adapt our software and operational procedures. In summary, the team is undertaking action at multiple levels, including performing a comprehensive suite of spectroscopic measurements in our laboratories on relevant analog materials, performing extensive spectral modeling, examining space weathering effects, and modeling the thermal behavior of the hermean surface.

Combined land surface emissivity and temperature estimation from Landsat 8 OLI and TIRS

Abstract: Remote sensing of Land Surface Temperature (LST) generally requires atmospheric parameters and the emissivity ( ∊ ) of the target to be estimated. The atmospheric up- and downwelling radiances and transmittance can be accurately modelled using radiative transfer models and profiles of relative humidity and temperature, either measured by radiosonde probes or retrieved from assimilating weather models. The estimation of ∊ is a large source of uncertainty in the resulting LST product, and there are various approaches using multi-angle observations, multispectral optical or multispectral thermal infrared imagery. In this paper, the estimation of LST from the Thermal InfraRed Sensor (TIRS) on board Landsat 8 is evaluated using more than 6 years of in situ temperature measurements from a network of 14 Autonomous Weather Stations (AWS) in Belgium. ∊ is estimated from concomitant atmospherically corrected imagery from the Operational Land Imager (OLI) using two new neural network approaches trained on ECOSTRESS spectra, and an established NDVI based method. Results are compared to using ∊ = 1 and the ASTER Global Emissivity Dataset. LST retrievals from L8/TIRS perform well for all emissivity data sources for >500 matchups with AWS subsoil temperature measurements: Mean Differences 0.8–3.7 K and unbiased Root Mean Squared Differences of 2.9–3.5 K for both B10 and B11. The use of unity emissivity gives the best results in terms of MD (0.8 K) and unb-RMSD (3 K). Similar ranges of unb-RMSD are found for >500 matchups with broadband radiometer temperatures (2.6–3.1 K), that have lower absolute MD values (−2.2–0.6 K). For the radiometer temperatures, both the neural net approaches gave lowest MD, in the best case ± 0.1 K. The present investigation can hence recommend the neural nets to derive ∊ for the retrieval of LST over the AWS in Belgium. Using published matchup results from other authors however, no single source of ∊ data performed better than ∊ = 1 , but this could be due to their low number of matchups. Further efforts for estimating representative pixel average emissivities are needed, and establishing a denser in situ measurement network over varied land use, with rather homogeneous land cover within a TIRS pixel, may aid further validation of a per pixel and per scene ∊ estimates from multispectral imagery. AWS data seems valuable for evaluation of satellite LST, with the advantage of a much lower cost and higher potential matchup density compared to conventional radiometers.

Sensitivity analysis of the dark spectrum fitting atmospheric correction for metre- and decametre-scale satellite imagery using autonomous hyperspectral radiometry

Abstract: The performance of the dark spectrum fitting (DSF) atmospheric correction algorithm is evaluated using matchups between metre- and decametre-scale satellite imagery as processed with ACOLITE and measurements from autonomous PANTHYR hyperspectral radiometer systems deployed in the Adriatic and North Sea. Imagery from the operational land imager (OLI) on Landsat 8, the multispectral instrument (MSI) on Sentinel-2 A and B, and the PlanetScope CubeSat constellation was processed for both sites using a fixed atmospheric path reflectance in a small region of interest around the system’s deployment location, using a number of processing settings, including a new sky reflectance correction. The mean absolute relative differences (MARD) between in situ and satellite measured reflectances reach 600 nm). The results presented in this article should serve as guidelines for general use of ACOLITE and the DSF.

First Comparisons of Surface Temperature Estimations between ECOSTRESS, ASTER and Landsat 8 over Italian Volcanic and Geothermal Areas

Abstract: The ECO System Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) is a new space mission developed by NASA-JPL which launched on July 2018. It includes a multispectral thermal infrared radiometer that measures the radiances in five spectral channels between 8 and 12 μm. The primary goal of the mission is to study how plants use water by measuring their temperature from the vantage point of the International Space Station. However, as ECOSTRESS retrieves the surface temperature, the data can be used to measure other heat-related phenomena, such as heat waves, volcanic eruptions, and fires. We have cross-compared the temperatures obtained by ECOSTRESS, the Advanced Spaceborne Thermal Emission and Reflectance radiometer (ASTER) and the Landsat 8 Thermal InfraRed Sensor (TIRS) in areas where thermal anomalies are present. The use of ECOSTRESS for temperature analysis as well as ASTER and Landsat 8 offers the possibility of expanding the availability of satellite thermal data with very high spatial and temporal resolutions. The Temperature and Emissivity Separation (TES) algorithm was used to retrieve surface temperatures from the ECOSTRESS and ASTER data, while the single-channel algorithm was used to retrieve surface temperatures from the Landsat 8 data. Atmospheric effects in the data were removed using the moderate resolution atmospheric transmission (MODTRAN) radiative transfer model driven with vertical atmospheric profiles collected by the University of Wyoming. The test sites used in this study are the active Italian volcanoes and the Parco delle Biancane geothermal area (Italy). In order to test and quantify the difference between the temperatures retrieved by the three spaceborne sensors, a set of coincident imagery was acquired and used for cross comparison. Preliminary statistical analyses show a very good agreement in terms of correlation and mean values among sensors over the test areas.

The Flexible Microwave Payload-2: A SDR-Based GNSS-Reflectometer and L -Band Radiometer for CubeSats

Abstract: This article presents the FMPL-2 on board the FSSCat mission, the 2017 ESA Small Sentinel Satellite Challenge and overall Copernicus Masters Competition winner. FMPL-2 is a passive microwave instrument based on a software-defined radio that implements a conventional global navigation satellite system—Reflectometer and an L -band radiometer, occupying 1 U of a 6 U CubeSat. The article describes the FSSC at mission context, the payload design and implementation phases, the tests results in a controlled environment, and finally the calibration algorithms applied to the downloaded data in order to extract the appropriate geophysical parameters: sea-ice coverage, sea-ice thickness (SIT), and low-resolution soil moisture. This article covers the overall payload design, from a high-level block diagram down to single-component specifications from both hardware and software points of view. The main block of the instrument is based on the combination of an FPGA, which virtualizes a dual-core ARM processor, where most of the calculus are performed, and a software-defined radio module, in charge of I/Q data demodulation. The article also explains the design and implementation of a signal conditioning board required for the correct operation and calibration of both instruments.

PAMTRA 1.0: the Passive and Active Microwave radiative TRAnsfer tool for simulating radiometer and radar measurements of the cloudy atmosphere

Abstract: . Forward models are a key tool to generate synthetic observations given the knowledge of the atmospheric state. In this way they are an integral part of inversion algorithms that aim to retrieve geophysical variables from observations or in data assimilation. Their application for the exploitation of the full information content of remote sensing observations becomes increasingly important when these are used to evaluate the performance of cloud resolving models (CRMs). Herein, CRMs profiles or fields provide the input to the forward model whose simulation results are subsequently compared to the observations. This paper introduces the freely available comprehensive microwave forward model PAMTRA (Passive and Active Microwave TRAnsfer), demonstrates its capabilities to simulate passive and active measurements across the microwave spectral region for up- and downward looking geometries, and illustrates how the forward simulations can be used to evaluate CRMs and to interpret measurements to improve our understanding of cloud processes. PAMTRA is unique as it treats passive and active radiative transfer (RT) in a consistent way with the passive forward model providing up- and down-welling polarized brightness temperatures and radiances for arbitrary observation angles. The active part is capable of simulating the full radar Doppler spectrum and its moments. PAMTRA is designed to be flexible with respect to instrument specifications, interfaces to many different formats of in- and output type, especially CRMs, spanning the range from bin-resolved microphysical output to one- and two-moment schemes, and to in situ measured hydrometeor properties. A specific highlight is the incorporation of the self-similar Rayleigh--Gans Approximation (SSRGA) both for active and passive applications which becomes especially important for the investigation of frozen hydrometeors.

SI-traceable Spectral Irradiance Radiometric Characterization and Absolute Calibration of the TSIS-1 Spectral Irradiance Monitor (SIM)

Abstract: The current implementation for continuous, long-term solar spectral irradiance (SSI) monitoring is the Total and Spectral Solar Irradiance Sensor (TSIS-1) Spectral Irradiance Monitor (SIM) that began operations from the International Space Station (ISS) in March 2018 and nominally provides an SSI spectrum every 12 h. Advances in both instrument design and spectral irradiance calibration techniques have resulted in the TSIS-1 SIM achieving higher absolute accuracy than its predecessor instrument in the wavelength range (200–2400 nm). A comprehensive detector-based Spectral Radiometer Facility (SRF) was developed in collaboration with the US National Institute for Standards and Technology (NIST) to ensure the ties to spectral SI standards in power and irradiance. Traceability is achieved via direct laser calibration of a focal plane electrical substitution radiometer (ESR) against a cryogenic radiometer in power and also irradiance responsivity via calibrated apertures. The SIM accuracy definition followed an absolute sensor approach based on a full radiometric measurement equation where component-level performance characterizations and calibrations were quantified with an associated uncertainty error budget and verified by independent measurements for each parameter. Unit-level characterizations were completed over the full operational envelope of external driving factors (e.g., pointing and temperature ranges) and were allowed for the independent parameterization of sub-assembly performance for expected operating conditions. Validation and final instrument end-to-end absolute calibration in the Laboratory for Atmospheric and Space Physics (LASP)-SRF achieved low combined standard uncertainty (uc < 0.25%, k = 1) in spectral irradiance.

The Roles of the S3MPC: Monitoring, Validation and Evolution of Sentinel-3 Altimetry Observations

Abstract: The Sentinel-3 Mission Performance Centre (S3MPC) is tasked by the European Space Agency (ESA) to monitor the health of the Copernicus Sentinel-3 satellites and ensure a high data quality to the users. This paper deals exclusively with the effort devoted to the altimeter and microwave radiometer, both components of the Surface Topography Mission (STM). The altimeters on Sentinel-3A and -3B are the first to operate in delay-Doppler or SAR mode over all Earth surfaces, which enables better spatial resolution of the signal in the along-track direction and improved noise reduction through multi-looking, whilst the radiometer is a two-channel nadir-viewing system. There are regular routine assessments of the instruments through investigation of telemetered housekeeping data, calibrations over selected sites and comparisons of geophysical retrievals with models, in situ data and other satellite systems. These are performed both to monitor the daily production, assessing the uncertainties and errors on the estimates, and also to characterize the long-term performance for climate science applications. This is critical because an undetected drift in performance could be misconstrued as a climate variation. As the data are used by the Copernicus Services (e.g., CMEMS, Global Land Monitoring Services) and by the research community over open ocean, coastal waters, sea ice, land ice, rivers and lakes, the validation activities encompass all these domains, with regular reports openly available. The S3MPC is also in charge of preparing improvements to the processing, and of the development and tuning of algorithms to improve their accuracy. This paper is thus the first refereed publication to bring together the analysis of SAR altimetry across all these different domains to highlight the benefits and existing challenges.

A Fundamental Climate Data Record of SMMR, SSM/I, and SSMIS brightness temperatures

Abstract: . The Fundamental Climate Data Record (FCDR) of Microwave Imager Radiances from the Satellite Application Facility on Climate Monitoring (CM SAF) comprises inter-calibrated and homogenized brightness temperatures from the Scanning Multichannel Microwave Radiometer (SMMR), the Special Sensor Microwave/Imager (SSM/I), and the Special Sensor Microwave Imager/Sounder SSMIS radiometers. It covers the time period from October 1978 to December 2015 including all available data from the SMMR radiometer aboard Nimbus-7 and all SSM/I and SSMIS radiometers aboard the Defense Meteorological Satellite Program (DMSP) platforms. SMMR, SSM/I, and SSMIS data are used for a variety of applications, such as analyses of the hydrological cycle, remote sensing of sea ice, or as input into reanalysis projects. The improved homogenization and inter-calibration procedure ensures the long-term stability of the FCDR for climate-related applications. All available raw data records from different sources have been reprocessed to a common standard, starting with the calibration of the raw Earth counts, to ensure a completely homogenized data record. The data processing accounts for several known issues with the instruments and corrects calibration anomalies due to along-scan inhomogeneity, moonlight intrusions, sunlight intrusions, and emissive reflector. Corrections for SMMR are limited because the SMMR raw data records were not available. Furthermore, the inter-calibration model incorporates a scene dependent inter-satellite bias correction and a non-linearity correction in the instrument calibration. The data files contain all available original sensor data (SMMR: Pathfinder level 1b) and metadata to provide a completely traceable climate data record. Inter-calibration and Earth incidence angle normalization offsets are available as additional layers within the data files in order to keep this information transparent to the users. The data record is complemented with noise-equivalent temperatures (Ne Δ T), quality flags, surface types, and Earth incidence angles. The FCDR together with its full documentation, including evaluation results, is freely available at: https://doi.org/10.5676/EUM_SAF_CM/FCDR_MWI/V003 ( Fennig et al. , 2017 ) .

Real-Time Passive Brain Monitoring System Using Near-Field Microwave Radiometry

Abstract: Objective : Near-field microwave radiometry has emerged as a tool for real-time passive monitoring of local brain activation, possibly attributed to local changes in blood flow that correspond to temperature and/or conductivity changes. The aim of this study is to design and evaluate a prototype system based on microwave radiometry intended to detect local changes of temperature and conductivity in depth in brain tissues. A novel radiometric system that comprises a four port total power Dicke-switch sensitive receiver that operates at 1.5 GHz has been developed. Methods and Results : The efficacy of the system was assessed through simulation and experiment on brain tissue mimicking phantoms under different setup conditions, where temperature and conductivity changes were accurately detected. In order to validate the radiometer's capability to sense low power signals occurring spontaneously from regions in the human brain, the somatosensory cortices of one volunteer were measured under pain-inducing psychophysiological conditions. The promising results from the initial in vivo measurements prove the system's potential for more extensive investigative trials. Conclusion and Significance : The significance of this study lies on the development of a compact and sensitive radiometer for totally passive monitoring of local brain activation as a potential complementary tool for contributing to the research effort for investigating brain functionality.

In-orbit validation of the fmpl-2 instrument—the gnss-r and l-band microwave radiometer payload of the fsscat mission

Abstract: The Flexible Microwave Payload-2 is the GNSS-R and L-band Microwave Radiometer Payload on board 3Cat-5/A, one of the two 6-unit CubeSats of the FSSCat mission, which were successfully launched on 3 September 2020 on Vega flight VV16. The instrument occupies nearly a single unit of the CubeSat, and its goal is to provide sea-ice extension and thickness over the poles, and soil moisture maps at low-moderate resolution over land, which will be downscaled using data from Cosine Hyperscout-2 on board 3Cat-5/B. The spacecrafts are in a 97.5° inclination Sun-synchronous orbit, and both the reflectometer and the radiometer have been successfully executed and validated over both the North and the South poles. This manuscript presents the results and validation of the first data sets collected by the instrument during the first two months of the mission. The results of the validation are showing a radiometric accuracy better than 2 K, and a sensitivity lower than the Kelvin. For the reflectometer, the results are showing that the sea-ice transition can be estimated even at short integration times (40 ms). The presented results shows the potential for Earth Observation missions based on CubeSats, which temporal and spatial resolution can be further increased by means of CubeSat constellations.

Calibration of the HP 3 Radiometer on InSight

Abstract: The Heatflow and Physical Properties Package (HP3) radiometer is currently operating on Mars, observing two spots approximately 1 and 3 m north-north-west of the InSight lander. The instrument has primary sensors that are sensitive in the range of 8 to 14 μm and two more sensors with more narrow spectral ranges per field of view. The radiometer underwent radiometric and geometric calibration at DLR—Berlin; and on Mars radiometric self-calibration is performed regularly. The self-calibration confirms that one of the two primary sensors has been stable since the ground calibration, but environmental parameters that are likely associated with the thermal contact of sensor and instrument main body may have slightly changed. The other primary sensor has increased in sensitivity for an unknown reason but is still within expectation from the sensor design. The uncertainty of the two primary sensors is approximately 3 K at night, with somewhat larger errors in the late afternoon. This estimate includes the effect of sensitivity changes that would be too small to be reliably detected by the self-calibration.

Land Surface Emissivity Product for NOAA JPSS and GOES-R Missions: Methodology and Evaluation

Abstract: Land surface emissivity (LSE) is a key parameter for the determination of land surface temperature (LST) from thermal remotely sensed data. A new LSE product has been developed at the National Oceanic and Atmospheric Administration (NOAA), College Park, MD, USA, to enhance the LST product for the Joint Polar Satellite System (JPSS) and the Geostationary Operational Environmental Satellite R-Series (GOES-R) missions as well as to support the forecasting models. A 1-km resolution bare ground emissivity was derived from the historical Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Emissivity Dataset (ASTER-GED) and Moderate Resolution Imaging Spectroradiometer (MODIS) LSE product. It is then spectrally adjusted to the split window (SW) channels of Visible/Infrared Imager Radiometer Suite (VIIRS) onboard JPSS and Advanced Baseline Imager (ABI) from GOES-R. VIIRS daily green vegetation fraction and snow fraction products are subsequently used to account for the dynamic variations. Validation results indicate that the product has a good agreement with in situ observations, with an emissivity difference less than 0.006 at the bare surface sites and a difference less than 0.007 at one cropland site with three growth stages. The intercomparison with NASA VIIRS daily LSE product proves a good agreement with a standard deviation of less than 0.012. To evaluate the LSE performance in LST retrieval, a whole year VIIRS LST is produced and validated over the SURFace RADiation budget observing network (SURFRAD) sites. The results indicate that the LSE works well with LST RMSE of 1.78 (daytime) and 1.58 K (nighttime). The new LSE algorithm has been integrated to NOAA-20 LST with the status of provisional maturity and will be applied on GOES-16/17 LST product in the near future.

Nighttime Cool Skin Effect Observed from Infrared SST Autonomous Radiometer (ISAR) and Depth Temperatures

Abstract: The nighttime ocean cool skin signal ΔT [defined as skin sea surface temperature (SSTskin) minus depth SST (SSTdepth)] is investigated using 103 days of matchups between shipborne Infrared ...

Determining the daytime Earth radiative flux from National Institute of Standards and Technology Advanced Radiometer (NISTAR) measurements

Abstract: . The National Institute of Standards and Technology Advanced Radiometer (NISTAR) onboard the Deep Space Climate Observatory (DSCOVR) provides continuous full-disk global broadband irradiance measurements over most of the sunlit side of the Earth. The three active cavity radiometers measure the total radiant energy from the sunlit side of the Earth in shortwave (SW; 0.2–4 µ m), total (0.4–100 µ m), and near-infrared (NIR; 0.7–4 µ m) channels. The Level 1 NISTAR dataset provides the filtered radiances (the ratio between irradiance and solid angle). To determine the daytime top-of-atmosphere (TOA) shortwave and longwave radiative fluxes, the NISTAR-measured shortwave radiances must be unfiltered first. An unfiltering algorithm was developed for the NISTAR SW and NIR channels using a spectral radiance database calculated for typical Earth scenes. The resulting unfiltered NISTAR radiances are then converted to full-disk daytime SW and LW flux by accounting for the anisotropic characteristics of the Earth-reflected and emitted radiances. The anisotropy factors are determined using scene identifications determined from multiple low-Earth orbit and geostationary satellites as well as the angular distribution models (ADMs) developed using data collected by the Clouds and the Earth's Radiant Energy System (CERES). Global annual daytime mean SW fluxes from NISTAR are about 6 % greater than those from CERES, and both show strong diurnal variations with daily maximum–minimum differences as great as 20 Wm −2 depending on the conditions of the sunlit portion of the Earth. They are also highly correlated, having correlation coefficients of 0.89, indicating that they both capture the diurnal variation. Global annual daytime mean LW fluxes from NISTAR are 3 % greater than those from CERES, but the correlation between them is only about 0.38.

Comparisons of snowmelt detected by microwave sensors on the Shackleton Ice Shelf, East Antarctica

Abstract: Surface snowmelt is of great importance to the ice sheet’s mass and energy balance. Microwave sensors, including radiometer and scatterometer can be used to map snowmelt. Two new microwave ...

Precision heterodyne oxygen-corrected spectrometry: vertical profiling of water and carbon dioxide in the troposphere and lower stratosphere

Abstract: We describe the development of a near-infrared laser heterodyne radiometer: the precision heterodyne oxygen-corrected spectrometer (PHOCS). The prototype instrument is equipped with two heterodyne receivers for oxygen and water (measured near 1278 nanometers) and carbon dioxide (near 1572 nanometers) concentration profiles, respectively. The latter may be substituted by a heterodyne receiver module equipped with a laser to monitor atmospheric methane near 1651 nanometers. Oxygen measurements are intended to provide dry gas corrections and—more importantly—determine accurate temperature and pressure profiles that, in turn, improve the precision of the CO2 and H2O column retrievals. Vertical profiling is made feasible by interrogating the very low-noise absorption lines shapes collected at ≈0.0067cm−1 resolution. PHOCS complements the results from the Orbiting Carbon Observatory (OCO-2), Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS), and ground-based Fourier transform spectrometers. In this paper, we describe the development of the instrument by Mesa Photonics and present the results of initial tests in the vicinity of Washington, DC.

Real-Time Detection and Filtering of Radio Frequency Interference Onboard a Spaceborne Microwave Radiometer: The CubeRRT Mission

Abstract: The Cubesat radiometer radio frequency interference technology validation mission (CubeRRT) was developed to demonstrate real-time onboard detection and filtering of radio frequency interference (RFI) for wide bandwidth microwave radiometers. CubeRRT's key technology is its radiometer digital backend (RDB) that is capable of measuring an instantaneous bandwidth of 1 GHz and of filtering the input signal into an estimated total power with and without RFI contributions. CubeRRT's onboard RFI processing capability dramatically reduces the volume of data that must be downlinked to the ground and eliminates the need for ground-based RFI processing. RFI detection is performed by resolving the input bandwidth into 128 frequency subchannels, with the kurtosis of each subchannel and the variations in power across frequency used to detect nonthermal contributions. RFI filtering is performed by removing corrupted frequency subchannels prior to the computation of the total channel power. The 1 GHz bandwidth input signals processed by the RDB are obtained from the payload's antenna (ANT) and radiometer front end (RFE) subsystems that are capable of tuning across RF center frequencies from 6 to 40 GHz. The CubeRRT payload was installed into a 6U spacecraft bus provided by Blue Canyon Technologies that provides spacecraft power, communications, data management, and navigation functions. The design, development, integration and test, and on-orbit operations of CubeRRT are described in this article. The spacecraft was delivered on March 22nd, 2018 for launch to the International Space Station (ISS) on May 21st, 2018. Since its deployment from the ISS on July 13th, 2018, the CubeRRT RDB has completed more than 5000 h of operation successfully, validating its robustness as an RFI processor. Although CubeRRT's RFE subsystem ceased operating on September 8th, 2018, causing the RDB input thereafter to consist only of internally generated noise, CubeRRT's key RDB technology continues to operate without issue and has demonstrated its capabilities as a valuable subsystem for future radiometry missions.

Gas flaring activity and black carbon emissions in 2017 derived from the Sentinel-3A Sea and Land Surface Temperature Radiometer

Abstract: . Gas flares are a regionally and globally significant source of atmospheric pollutants. They can be detected by satellite remote sensing. We calculate the global flared gas volume and black carbon emissions in 2017 by applying (1) a previously developed hot spot detection and characterisation algorithm to all observations of the Sea and Land Surface Temperature Radiometer (SLSTR) instrument on board the Copernicus satellite Sentinel-3A and (2) newly developed filters for identifying gas flares and corrections for calculating both flared gas volumes (billion cubic metres, BCM) and black carbon (BC) emissions (g). The filter to discriminate gas flares from other hot spots uses the observed hot spot characteristics in terms of temperature and persistence. A regression function is used to correct for the variability of detection opportunities. A total of 6232 flaring sites are identified worldwide. The best estimates of the annual flared gas volume and the BC emissions are 129 BCM with a confidence interval of [35, 419 BCM] and 73 Gg with a confidence interval of [20, 239 Gg], respectively. Comparison of our activity (i.e. BCM) results with those of the Visible Infrared Imaging Radiometer Suite (VIIRS) Nightfire data set and SWIR-based calculations show general agreement but distinct differences in several details. The calculation of black carbon emissions using our gas flaring data set with a newly developed dynamic assignment of emission factors lie in the range of recently published black carbon inventories, albeit towards the lower end. The data presented here can therefore be used e.g. in atmospheric dispersion simulations. The advantage of using our algorithm with Sentinel-3 data lies in the previously demonstrated ability to detect and quantify small flares, the long-term data availability from the Copernicus programme, and the increased detection opportunity of global gas flare monitoring when used in conjunction with the VIIRS instruments. The flaring activity and related black carbon emissions are available as “GFlaringS3” on the Emissions of atmospheric Compounds and Compilation of Ancillary Data (ECCAD) website ( https://doi.org/10.25326/19 , Caseiro and Kaiser , 2019 ).

GeoColor: A Blending Technique for Satellite Imagery

Abstract: Value-added imagery is a useful means of communicating multispectral environmental satellite radiometer data to the human analyst. The most effective techniques strike a balance between sci...

Additional Microwave Radiation From Experimentally Loaded Granite Covered With Sand Layers: Features and Mechanisms

Abstract: The additional microwave radiation from underground rock mass (lithosphere) that is caused by tectonic activity and alternating crustal stress has been shown to be a detectable electromagnetic signal via satellite remote sensing. However, the emission of microwave radiation produced inside the lithosphere will be affected by its overburden matter, such as sand, soil, water, and vegetation, and this effect is unknown. In this article, we use a C-band microwave radiometer to detect the variations in the microwave brightness temperature ( $T_{B}$ ) of rock samples in the process of axial loading. For the rock samples, the surface was bare and covered with dry sand or humid sand. The experimental detection illustrates that the dry sand unexpectedly allows more stress-associated additional radiation ( $\Delta T_{B}$ ) to be received by the radiometer, while humid sand shows significant extinction of $\Delta T_{B}$ . Both the radiative transfer theory and the stress-activated positive hole hypothesis are applied to interpret the mechanisms of the effect of dry and humid sand layers on $\Delta T_{B}$ . The outflow of stress-activated positive holes is from inside the loaded rock, and hence their accumulation beneath the surface of the sand layer is expected to reduce the local dielectric permittivity of sand, thereby making the detected $\Delta T_{B}$ by the microwave radiometer to be larger than that extrapolated theoretically in accordance with radiative transfer theory. This article is valuable for understanding the diverse $T_{B}$ anomalies that have been observed prior to tectonic earthquakes, and it facilitates the evaluation of the potential application of $\Delta T_{B}$ to seismic monitoring and earthquake prediction.