Surface Brightness Temperature Research Articles

Quantifying the influence of snow over sea ice morphology on L-band passive microwave satellite observations in the Southern Ocean

Abstract. Antarctic snow on sea ice can contain slush, snow ice, and stratified layers, complicating satellite retrieval processes for snow depth, ice thickness, and sea ice concentration. The presence of moist and brine-wetted snow alters microwave snow emissions and modifies the energy and mass balance of sea ice. This study assesses the impact of brine-wetted snow and slush layers on L-band surface brightness temperatures (TBs) by synergizing a snow stratigraphy model (SNOWPACK) driven by atmospheric reanalysis data and the RAdiative transfer model Developed for Ice and Snow in the L-band (RADIS-L) v1.0 The updated RADIS-L v1.1 further introduces parameterizations for brine-wetted snow and slush layers over Antarctic sea ice. Our findings highlight the importance of including both brine-wetted snow and slush layers in order to accurately simulate L-band brightness temperatures, laying the groundwork for improved satellite retrievals of snow depth and ice thickness using satellite sensors such as Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP). However, biases in modelled and observed L-band brightness temperatures persist, which we attribute to small-scale sea ice heterogeneity and snow stratigraphy. Given the scarcity of comprehensive in situ snow and ice data in the Southern Ocean, ramping up observational initiatives is imperative to not only provide satellite validation datasets but also improve process-level understanding that can scale up to improving the precision of satellite snow and ice thickness retrievals.

A physics-guided automated machine learning approach for obtaining surface radiometric temperatures on sunny days based on UAV-derived images

Urban surface radiometric temperatures, approximate to the surface kinetic temperatures, are predominantly retrieved using satellites or unmanned aerial vehicles (UAVs) and exhibit pronounced spatiotemporal variations. Despite numerous methods ranging from empirical to physical models for obtaining urban microscale surface radiometric temperatures via UAVs, challenges remain given the limited physical significance and substantial professional barriers to method application. Against this background, this study introduces a novel and straightforward approach for acquiring spatially distributed radiometric temperatures on sunny days without understanding the complex radiative transfer process as well as acquiring low-altitude atmospheric parameters. An automated machine learning was employed to train a model capable of efficiently estimating radiometric temperatures. Training and testing datasets were created based on the urban radiative transfer equation, incorporating three independent variables: UAV-measured surface brightness temperature, broadband emissivity, and sky view factor, which collectively represent the diverse thermal environments across different surface characteristics and urban layouts during sunny transitional and summer seasons. The model's accuracy was subsequently confirmed through direct comparisons with radiometric temperatures retrieved from UAV-collected multimodal images and kinetic temperatures synchronously collected on the ground across four periods. The results indicate that AutoGluon achieved high accuracy (MAE: 0.04 K; RMSE: 0.06 K; R2: 0.99). Additional ground measurement validations further demonstrated the model's reliability, with absolute biases on sunlit surfaces maintained within 1.25 K. Given its capability for real-time, high-spatial-resolution mapping of radiometric temperatures (April test: 8.70 cm, July test: 6.89 cm) in urban microscales with considerable heterogeneity, such a method is envisioned to be an effective tool for the dynamic monitoring and management of thermal environments at the microscale level in urban settings.

Recovering the gas properties of protoplanetary disks through parametric visibility modeling: MHO 6

The composition and distribution of the gas in a protoplanetary disk plays a key role in shaping the outcome of the planet formation process. Observationally, the recovery of information such as the emission height and brightness temperature from interferometric data is often limited by the imaging processes. To overcome the limitations of image-reconstruction when analyzing gas emission from interferometric observations, we have introduced a parametric model to fit the main observable properties of the gaseous disk component in the visibility plane. This approach is also known as parametric visibility modeling. We applied our parametric visibility modeling to the gas brightness distribution of the molecular line emission from 12CO J=3-2 and 13CO J=3-2 in the disk around MHO\,6, a very-low-mass star in the Taurus star-forming Region. To improve the flux fidelity of our parametric models, we combined models with different pixel resolution before the computation of their visibilities, referred to as ``nesting images.'' When we apply our parametric visibility modeling to MHO\,6, with independent fits to the emission from its CO isopotologues, the models return the same consistent results for the stellar mass, disk geometry, and central velocity. The surface height and brightness temperature distribution are also recovered. When compared to other disks, MHO\,6 surface height is among the most elevated surfaces, consistent with the predictions for disks around very-low-mass stars. This work demonstrates the feasibility of running rapidly iterable parametric visibility models in moderate resolution and sensitivity interferometric observations. More importantly, this methodology opens the analysis of disk's gas morphology to observations where image-based techniques are unable to robustly operate, as in the case of the compact disk around MHO\,6.

Study on potential application of brightness temperature models in passive remote sensing

In the modern science and practice of remote sensing of any surface, including various types of land cover, radio systems are widely used. Due to low energy consumption and high stealth, the most promising direction of technical tools for remote sensing is the development of passive remote sensing systems. To estimate the specific parameters of the surface, information on the relation between the signals of the thermal radiation and these parameters is needed. Therefore, it is relevant to study and analyze the existing types of such relations that connect the brightness temperature and the parameters of the Earth’s surfaces; this is the subject matter of the study in this paper. The goal of this study is to analyze existing relation models and study the conditions of their application in terms of operating frequencies, geometric characteristics, type of surface coverage (with vegetation, without vegetation, etc.), as well as the method of obtaining mathematical relations (electrodynamic models or empirical models). Due to the large number of different types of earth surface coverings and different types of surface models, in order to simplify remote sensing tasks for passive systems, as well as to improve the results of modeling or experiments, the following tasks are formulated: to study and classify existing models of the relation between surface parameters and brightness temperature, and to calculate and analyze the potential accuracy of estimating surface parameters by passive remote sensing systems. The following results were obtained: the impact of the atmosphere on the surface’s brightness temperature, described by the electrodynamic flat model, for the operating frequencies 75–110 GHz of the radiometer was analyzed. The impact of the atmosphere on the brightness temperature appears at sighting angles greater than 50° at horizontal polarization and greater than 80° at vertical polarization. According to the results, it can be said that the estimation accuracy of the imaginary part of the complex permittivity decreases with an operating wavelength decrease, and the estimation accuracy of the real part is the opposite. Conclusions. The results of simulation modeling show that for radiometers with the above-mentioned operating frequencies, it is possible to estimate the real permittivity or only the real component separately in the case of describing the surface with a complex permittivity parameter. It is recommended that the study be conducted at vertical and horizontal polarizations, without and with the impact of the atmosphere. To estimate the surface conductivity (the imaginary part of the complex permittivity of a surface), systems with lower operating frequencies are required. Thus, this study presents an analysis of existing models, calculates the potential accuracy of parameters estimation when using these models, and provides recommendations for practical experiments or modeling.

Far infrared radiative properties of Mars atmospheric aerosols and their application to Mars Climate Sounder retrievals of aerosol profiles, aerosol columns and surface temperatures

Limb sounding of thermal emission in the infrared wavelength range is a powerful technique for measuring temperature and aerosols in the martian atmosphere. However, the long optical path may provide challenges to limb retrievals in high aerosol conditions. These can be mitigated by considering limb measurements in the far infrared, where opacities of most aerosols are lower than in the mid-infrared. We present analyses of radiative properties of Mars dust and water ice aerosols at far infrared wavelengths based on measurements by the Mars Climate Sounder (MCS) in limb geometry at mid- and far infrared wavelengths. For dust aerosols, derived far infrared radiative properties show a homogeneous behavior that is consistent with particle sizes in the order of 1 μm effective radius. Far infrared radiative properties for water ice aerosols exhibit a larger variability in local time and region, leading to significant differences between the aphelion cloud belt and the north polar hood, with the resulting parameters suggesting particle sizes around 3 μm or larger. Using the derived parameters, we develop a method for retrieving aerosol profiles from MCS limb measurements that combines information from mid- and far infrared spectroscopic channels. The use of far infrared channels enables aerosol profile retrievals from limb measurements that typically reach about a scale height deeper into the atmosphere than would be possible using mid-infrared channels only. The extended vertical range of the aerosol profiles allows the derivation of aerosol column optical depths through vertical integration, with dust column derivations in global or large-scale regional dust storms also being available by extrapolating dust profiles below the lowest retrievable altitude of a limb measurement. The quantification of aerosol columns allows us to retrieve surface brightness temperatures from MCS on-planet viewing measurements that are corrected for atmospheric contributions. We show that differences between surface brightness and top-of-the-atmosphere temperatures are typically within 20 K, with surface brightness temperatures generally being warmer (colder) than top-of-the-atmosphere temperatures at daytime (nighttime), except at high latitudes.

Correction of the SMAP Sea Surface Brightness Temperature and Retrieval of Sea Surface Salinity Incorporating CYGNSS Observables

Correction of the SMAP Sea Surface Brightness Temperature and Retrieval of Sea Surface Salinity Incorporating CYGNSS Observables

Effects of variable ice–ocean surface properties and air mass transformation on the Arctic radiative energy budget

Abstract. Low-level airborne observations of the Arctic surface radiative energy budget are discussed. We focus on the terrestrial part of the budget, quantified by the thermal-infrared net irradiance (TNI). The data were collected in cloudy and cloud-free conditions over and in the vicinity of the marginal sea ice zone (MIZ) close to Svalbard during two aircraft campaigns conducted in the spring of 2019 and in the early summer of 2017. The measurements, complemented by ground-based observations available from the literature and radiative transfer simulations, are used to evaluate the influence of surface type (sea ice, open ocean, MIZ), seasonal characteristics, and synoptically driven meridional air mass transports into and out of the Arctic on the near-surface TNI. The analysis reveals a typical four-mode structure of the frequency distribution of the TNI as a function of surface albedo, the sea ice fraction, and surface brightness temperature. Two modes prevail over sea ice and another two over open ocean, each representing cloud-free and cloudy radiative states. Characteristic shifts and modifications of the TNI modes during the transition from winter to spring and early summer conditions are discussed. Furthermore, the influence of warm air intrusions (WAIs) and marine cold-air outbreaks (MCAOs) on the near-surface downward thermal-infrared irradiances and the TNI is highlighted for several case studies. It is concluded that during WAIs the surface warming depends on cloud properties and evolution. Lifted clouds embedded in warmer air masses over a colder sea ice surface, decoupled from the ground by a surface-based temperature inversion, have the potential to warm the surface more strongly than near-surface fog or thin low-level boundary layer clouds because of a higher cloud base temperature. For MCAOs it is found that the thermodynamic profile of the southward-moving air mass adapts only slowly to the warmer ocean surface.

The SSR Brightness Temperature Increment Model Based on a Deep Neural Network

The SSS (sea surface salinity) is an important factor affecting global climate changes, sea dynamic environments, global water cycles, marine ecological environments, and ocean carbon cycles. Satellite remote sensing is a practical way to observe SSS from space, and the key to retrieving SSS satellite products is to establish an accurate sea surface brightness temperature forward model. However, the calculation results of different forward models, which are composed of different relative permittivity models and SSR (sea surface roughness) brightness temperature increment models, are different, and the impact of this calculation difference has exceeded the accuracy requirement of the SSS inversion, and the existing SSR brightness temperature increment models, which primarily include empirical models and theoretical models, cannot match all the relative permittivity models. In order to address this problem, this paper proposes a universal DNN (deep neural network) model architecture and corresponding training scheme, and provides different SSR brightness temperature increment models for different relative permittivity models utilizing DNN based on offshore experiment data, and compares them with the existing models. The results show that the DNN models perform significantly better than the existing models, and that their calculation accuracy is close to the detection accuracy of a radiometer. Therefore, this study effectively solves the problem of SSR brightness temperature correction under different relative permittivity models, and provides a theoretical support for high-precision SSS inversion research.

A thermal infrared channel field radiometer. Part I: Characterization and laboratory test

To meet the needs of the on-orbit radiometric calibration of remote sensors, the development of independent intellectual property rights of infrared radiometer, a thermal infrared channel field radiometer (TICFR) for measurements of radiance or brightness temperature are presented for in situ measurements. The design philosophy of the optical system and structure is described, and the thermal shock resistance and working environment performance were performed using a prototype in the laboratory. The results show that the TICFR has a high resistance to thermal shock and can be used in working environments ranging from − 20–50 ℃. Then, the performances of TICFR in our laboratory are deemed to be satisfactory, based on initial requirements, The electrical autonomy, the automated operation, the portability, were experimented in situ and proved to be satisfactory. To verify the accuracy of the TICFR measurements and to check the reliability of the instrument, a laboratory experiment was carried out to compare the TICFR and the CE312. The results show that TICFR is in very good agreement with the surface brightness temperatures derived by CE312. The average deviation of the surface brightness temperatures measured by the corresponding channels of the two instruments is less than 0.1 ℃, and the standard deviation is less than 0.05 ℃. These results confirm that the measurement accuracy and stability of the TICFR are similar to those of the CE312. The TICFR has important applications in the site calibration of remote sensing in the thermal infrared band.

Science objectives of the MMX rover

The Martian Moons eXploration (MMX) mission by the Japan Aerospace Exploration Agency, JAXA, will explore the Martian moons Phobos and Deimos. In addition to investigating the moons remotely and returning samples from Phobos, MMX will also deliver a small (about 25 kg) Rover to the surface of Phobos. The payload of the Rover consists of four scientific instruments: RAX, a Raman spectrometer to measure signatures of the mineralogical composition of the surface material, NavCam, a stereo pair of cameras to investigate the terrain and allow for navigation, miniRAD a radiometer to measure the surface brightness temperature of both, regolith and rocks, and two WheelCams which will observe the wheel-surface interface, and thus investigate the properties and dynamics of the regolith. The cameras, will serve both, technological and scientific needs.The rover will be deployed during the rehearsal phase of the landing operations for the main spacecraft and will thus land in proximity to the first sampling area. During its operational lifetime on Phobos (about 100 days), the in-situ measurements performed with the rover payload will provide scientific context for the returned samples, provide ground truth, study the surface heterogeneity and obtain information on the physical properties of undisturbed surface material. The MMX launch is planned for September 2024 and the Rover delivery is scheduled for 2027.The Rover is a contribution by the Centre National d’Etudes Spatiales (CNES) and the German erospace Center (DLR) with additional contributions from INTA (Spain) and JAXA.

Land Surface Temperature Retrieval From Sentinel-3A SLSTR Data: Comparison Among Split-Window, Dual-Window, Three-Channel, and Dual-Angle Algorithms

Land surface temperature (LST) is a vital parameter for studying global ecological, climatic, and environmental changes. Although various LST retrieval algorithms have been proposed, including split-window (SW), dual-window (DW), three-channel (TC), and dual-angle (DA) algorithms, few studies have compared these algorithms using the same satellite observations. The Sea and Land Surface Temperature Radiometer (SLSTR) onboard Sentinel-3A provides a unique opportunity to conduct this comparison owing to its dual-angle viewing capability and multiple thermal infrared (TIR) and mid-infrared (MIR) channels. Here, we implemented two SW algorithms, one DW algorithm, two TC algorithms and one DA algorithm for the SLSTR data. The LST retrievals from these six algorithms were validated, along with the SLSTR operational LST product based on an emissivity-implicit SW algorithm. Temperature-based and radiance-based validation methods were used to evaluate different LST retrievals across different land cover types. The results indicated that the proposed SW algorithm had the highest accuracy, followed by the Pérez-Planells SW and the official algorithms. The overall root-mean-square errors (RMSEs) of these three SW algorithms were 1.42 K, 1.79 K and 2.05 K, respectively. The three algorithms involving the MIR channel (one DW and two TC algorithms) were more suitable for nighttime LST retrieval and had similar performances to the three SW algorithms, with a nighttime RMSE of approximately 1.36 K. The LST retrieval accuracy of the DA algorithm had the highest uncertainty and was closely related to the angular variation in surface emissivity and brightness temperature. The findings of this study contribute to a better understanding of the different LST retrieval algorithms and facilitate potential improvements in the official LST retrieval algorithm for SLSTR.

Classical novae in the ASKAP pilot surveys

Abstract We present a systematic search for radio counterparts of novae using the Australian Square Kilometer Array Pathfinder (ASKAP). Our search used the Rapid ASKAP Continuum Survey, which covered the entire sky south of declination $+41^{\circ}$ ( $\sim$ $34000$ square degrees) at a central frequency of 887.5 MHz, the Variables and Slow Transients Pilot Survey, which covered $\sim$ $5000$ square degrees per epoch (887.5 MHz), and other ASKAP pilot surveys, which covered $\sim$ 200–2000 square degrees with 2–12 h integration times. We crossmatched radio sources found in these surveys over a two–year period, from 2019 April to 2021 August, with 440 previously identified optical novae, and found radio counterparts for four novae: V5668 Sgr, V1369 Cen, YZ Ret, and RR Tel. Follow-up observations with the Australian Telescope Compact Array confirm the ejecta thinning across all observed bands with spectral analysis indicative of synchrotron emission in V1369 Cen and YZ Ret. Our light-curve fit with the Hubble Flow model yields a value of $1.65\pm 0.17 \times 10^{-4} \rm \:M_\odot$ for the mass ejected in V1369 Cen. We also derive a peak surface brightness temperature of $250\pm80$ K for YZ Ret. Using Hubble Flow model simulated radio lightcurves for novae, we demonstrate that with a 5 $\sigma$ sensitivity limit of 1.5 mJy in 15-min survey observations, we can detect radio emission up to a distance of 4 kpc if ejecta mass is in the range $10^{-3}\rm \:M_\odot$ , and upto 1 kpc if ejecta mass is in the range $10^{-5}$ – $10^{-3}\rm \:M_\odot$ . Our study highlights ASKAP’s ability to contribute to future radio observations for novae within a distance of 1 kpc hosted on white dwarfs with masses $0.4$ – $1.25\:\rm M_\odot$ , and within a distance of 4 kpc hosted on white dwarfs with masses $0.4$ – $1.0\:\rm M_\odot$ .

Reconstruct SMAP brightness temperature scanning gaps over Qinghai-Tibet Plateau

• SMAP brightness temperature ( TB ) scanning gaps were compensated. • Daily variation of TB was analyzed in function of influencing factors. • Seamless TB benefits the refinements of SMAP soil moisture products. Soil Moisture Active Passive (SMAP) satellite was used to monitor global soil moisture and freeze–thaw state using surface brightness temperature (TB). However, due to the limitation of scanning width and shifting track, the daily TB observation had stripe gaps in varying degrees, which imped scientific applications of SMAP official product. To solve this issue, we proposed a temporal fitting algorithm to produce daily seamless TB data over Qinghai-Tibet Plateau (QTP) from 2015 to 2021. This method was composed of two steps: (1) overall time trend fitting which used a spline function to fit the overall mean time trend for each pixel from 2015 to 2021; (2) daily variation correction which accounted for several influential factors including surface temperature, precipitation, and vegetation to establish an Ordinary Least Squares (OLS) model for predicting daily variation of TB in numerous time slices. Consequently, the missing TB observation was reconstructed by combining the overall temporal trend and daily variation. A 10-fold cross-validation and product comparison were carried out to validate the robustness of the proposed method. For cross-validation, we randomly removed available SMAP observations in certain periods as unavailable, and then compared the reconstructed values with the removed practical ones. The cross-validation results indicated the reconstructed TB agreed well with actual SMAP TB, with a high overall coefficient of determination (R 2 = 0.94) and low RMSE (RMSE = 3.7 K), implying the desirable performance of our proposed method. By comparison with Soil Moisture and Ocean Salinity (SMOS) TB, the reconstructed data had an approximate performance with actual SMAP TB. Furthermore, the effects of surface temperature and precipitation on TB in different periods (frozen and unfrozen) over QTP were also analyzed. Our method has the potential to generate seamless SMAP products.

Adaptive thermal image velocimetry of spatial wind movement on landscapes using near-target infrared cameras

Abstract. Thermal image velocimetry (TIV) is a near-target remote sensing technique for estimating two-dimensional (2D) near-surface wind velocity based on spatio-temporal displacement of fluctuations in surface brightness temperature captured by an infrared camera. The addition of an automated parameterization and the combination of ensemble TIV results into one output made the method more suitable to changing meteorological conditions and less sensitive to noise stemming from the airborne sensor platform. Three field campaigns were carried out to evaluate the algorithm over turf, dry grass, and wheat stubble. The derived velocities were validated with independently acquired observations from fine-wire thermocouples and sonic anemometers. It was found that the TIV technique correctly derives atmospheric flow patterns close to the ground. Moreover, the modified method resolves wind speed statistics close to the surface at a higher resolution than the traditional measurement methods. Adaptive thermal image velocimetry (A-TIV) is capable of providing contactless spatial information about near-surface atmospheric motion and can help to be a useful tool in researching turbulent transport processes close to the ground.

Evaluating GOES-16 ABI surface brightness temperature observation biases over the central Sierra Nevada of California

Thermal infrared imagery from NOAA's Geostationary Operational Environmental Satellites (GOES) R-series presents an opportunity to observe mountain surface temperatures at high temporal resolution. These observations are needed to better understand the transient surface energy balance, influenced by near-surface air temperatures and water fluxes ranging from evapotranspiration to snowmelt. From geostationary orbit, the GOES Advanced Baseline Imager (ABI) instrument views the Earth from a fixed longitude above the equator. ABI images therefore have increasingly off-nadir view angles and increasingly larger pixel dimensions the further a point on the Earth's surface is from the sub-satellite point. In thermal infrared imagery from ABI, these 2+ km pixels blur together the different surface temperatures of heterogeneous mountain landscapes. We compared GOES-16 ABI band 14 (11.2 μm) brightness temperatures to 90 m spatial resolution ASTER band 14 (11.3 μm) and 1 km spatial resolution MODIS band 31 (11.03 μm) brightness temperatures and investigated how differences change over space and time for a study region in the central Sierra Nevada of California for the 2017–2020 snow seasons. We demonstrated the necessity of orthorectifying ABI imagery of mountain terrain to correct for the parallax effect in off-nadir imagery. This reduced the mean difference between ABI and ASTER ~11 μm brightness temperatures from 1.6 °C to 1.0 °C and increased the r-squared value between ABI and ASTER thermal infrared brightness temperatures from 0.43 to 0.93. The ABI brightness temperatures were found to more closely match those of forest canopy temperatures than snow surface (with RMS differences of 1.2 °C and 3.0 °C respectively), and those of sunlit slopes as opposed to slopes facing away from the sun (with RMS differences of 1.6 °C and 3.4 °C respectively), in coincident ASTER imagery. This work demonstrates the use of GOES ABI, and associated challenges, for observing surface temperatures of forested mountain environments with seasonal snow.

A New Statistical Distance Scale for Planetary Nebulae, Based on Gaia EDR3

The present work aims to build a new statistical distance scale for planetary nebulae (PNe) based on a rigorous calibration sample. The distances of the calibration sample are derived from the trigonometric parallax method using the recent measurements of Gaia Early Data Release 3 (Gaia EDR3). The new distance scale is created by applying the well-known linear relationship between the radio surface brightness temperature and the nebular radius. The calibration sample is made up of 96 PNe of accurately computed distances with uncertainties less than 20%. Earlier ground- and space-based trigonometric parallaxes of PNe display inconsistency with those of Gaia, particularly the Hipparcos results. In addition, these measurements have appreciably lower precision than those of Gaia. When compared to the trigonometric technique, the expansion and kinematic methods exhibited more consistency than the spectroscopic, extinction, gravity, and photoionization methods. Furthermore, contrary to earlier results in the literature, the extinction and gravity methods, on average, underestimate and slightly overestimate the PN distances respectively. As a byproduct of extracting the Gaia parallaxes, we detect the radial velocity and variability for 14 and 3 PN central stars (CSs), respectively. To our knowledge, the variability of Hen 2-447 CS has been determined for the first time.

Comparison between Physical and Empirical Methods for Simulating Surface Brightness Temperature Time Series

Land surface temperature (LST) is a vital parameter in the surface energy budget and water cycle. One of the most important foundations for LST studies is a theory to understand how to model LST with various influencing factors, such as canopy structure, solar radiation, and atmospheric conditions. Both physical-based and empirical methods have been widely applied. However, few studies have compared these two categories of methods. In this paper, a physical-based method, soil canopy observation of photochemistry and energy fluxes (SCOPE), and two empirical methods, random forest (RF) and long short-term memory (LSTM), were selected as representatives for comparison. Based on a series of measurements from meteorological stations in the Heihe River Basin, these methods were evaluated in different dimensions, i.e., the difference within the same surface type, between different years, and between different climate types. The comparison results indicate a relatively stable performance of SCOPE with a root mean square error (RMSE) of approximately 2.0 K regardless of surface types and years but requires many inputs and a high computational cost. The empirical methods performed relatively well in dealing with cases either within the same surface type or changes in temporal scales individually, with an RMSE of approximately 1.50 K, yet became less compatible in regard to different climate types. Although the overall accuracy is not as stable as that of the physical method, it has the advantages of fast calculation speed and little consideration of the internal structure of the model.

On the origin of diffuse radio emission in Abell 85 – insights from new GMRT observations

ABSTRACT Extended, steep, and ultra-steep spectrum radio emission in a galaxy cluster is usually associated with recent mergers. Simulations show that radio phoenixes are aged radio galaxy lobes whose emission reactivates when a low Mach shock compresses it. A85 hosts a textbook example of a radio phoenix at about 320 kpc southwest of the cluster centre. We present a new high-resolution 325 MHz GMRT radio map illustrating this radio phoenix’s complex and filamentary structure. The full extent of the radio structure is revealed for the first time from these radio images of A85. Using archival Chandra X-ray observations, we applied an automated 2D shock finder to the X-ray surface brightness and Adaptive Circular Binning temperature maps that confirmed a bow shock at the location of the radio phoenix. We also compared the Mach number from the X-ray data with the radio-derived Mach number in the same region using multifrequency radio observations and find that they are consistent within the 1σ error level.

Millimetre Wave Emission by Discrete Method in Sea-foam Layer at WindSat Frequencies

Computation of millimetre wave scattering by sea foam is a significant query which contributes immensely to measurement of sea surface emissivity and brightness temperature by passive microwave radiometers.

An Airborne C-Band One-Dimensional Microwave Interferometric Radiometer With Ocean Aviation Experimental Results

The medium- and large- scale global sea surface temperature (SSTs), which is an important ocean parameter, are mainly measured by the space-borne microwave radiometry. However, the resolution and sensitivity are greatly limited by antenna size, orbit altitude, and flight speed. In this paper, an airborne C-band one-dimensional (1-D) microwave interferometric radiometer (ACMIR) is developed to obtain the SSTs with a high resolution and sensitivity. The spatial resolution of the ACMIR ranges from 40.7m to 612m, corresponding to the flight height of 500m to 8000m, while the sensitivity varies from 0.25K to 0.36K, associating with the boresight to the edge of the field of view. In order to evaluate the performance of the ACMIR, an ocean aviation experiment was conducted in the coastal area of the Yellow Sea in September 2020. The land observation results indicate that typical ground objects can be clearly distinguished. Furthermore, thesea surface brightness temperatures acquired by the ACMIR are compared with the estimates based on the radiative transfer model, with SST retrieval error of 0.77°C. The ACMIR can offer a high-resolution and accuracy of SST especially in coastal areas, and can meet several application requirements related to SSTs.