Brightness Temperature Measurements Research Articles

Evaluation of Soil Moisture Retrievals from a Portable L-Band Microwave Radiometer

A novel Portable L-band radiometer (PoLRa), compatible with tower-, vehicle- and drone-based platforms, can provide gridded soil moisture estimations from a few meters to several hundred meters yet its retrieval accuracy has rarely been examined. This study aims to provide an initial assessment of the performance of PoLRa-derived soil moisture at a spatial resolution of approximately 0.7 m × 0.7 m at a set of sampling pixels in central Illinois, USA. This preliminary evaluation focuses on (1) the consistency of PoLRa-measured brightness temperatures from different viewing directions over the same area and (2) whether PoLRa-derived soil moisture retrievals are within an acceptable accuracy range. As PoLRa shares many aspects of the L-band radiometer onboard NASA’s Soil Moisture Active Passive (SMAP) mission, two SMAP operational algorithms and the conventional dual-channel algorithm (DCA) were applied to calculate volumetric soil moisture from the measured brightness temperatures. The vertically polarized brightness temperatures from the PoLRa are typically more stable than their horizontally polarized counterparts across all four directions. In each test period, the standard deviations of observed dual-polarization brightness temperatures are generally less than 5 K. By comparing PoLRa-based soil moisture retrievals against the simultaneous moisture values obtained by a handheld capacitance probe, the unbiased root mean square error (ubRMSE) and the Pearson correlation coefficient (R) are mostly below 0.05 m3/m3 and above 0.7 for various algorithms adopted here. While SMAP models and the DCA algorithm can derive soil moisture from PoLRa observations, no single algorithm consistently outperforms the others. These findings highlight the significant potential of ground- or drone-based PoLRa measurements as a standalone reference for the calibration and validation of spaceborne L-band synthetic aperture radars and radiometers. The accuracy of PoLRa-yielded high-resolution soil moisture can be further improved via standardized operational procedures and appropriate tau-omega parameters.

Research on Multispectral Brightness Temperature Measurement Method Based on Computational Spectral Splitting

Research on Multispectral Brightness Temperature Measurement Method Based on Computational Spectral Splitting

A hidden active galactic nucleus population: the first radio luminosity functions constructed by physical process

ABSTRACT Both star formation (SF) and active galactic nuclei (AGNs) play an important role in galaxy evolution. Statistically quantifying their relative importance can be done using radio luminosity functions (RLFs). Until now these relied on galaxy classifications, where sources with a mixture of radio emission from SF and AGN are labelled as either a star-forming galaxy or an AGN. This can cause the misestimation of the relevance of AGN. Brightness temperature measurements at 144 MHz with the International LOw Frequency ARray telescope can separate radio emission from AGN and SF. We use the combination of sub-arcsec and arcsec resolution imaging of 7497 sources in the Lockman Hole and ELAIS-N1 fields to identify AGN components in the sub-arcsec resolution images and subtract them from the total flux density, leaving flux density from SF only. We construct, for the first time, RLFs by physical process, either SF or AGN activity, revealing a hidden AGN population at $L_{\textrm {144 MHz}}$$\lt 10^{24}$ W Hz$^{-1}$. This population is 1.56 $\pm$ 0.06 more than expected for $0.5\lt z\lt 2.0$ when comparing to RLFs by galaxy classification. The star-forming population has only 0.90 $\pm$ 0.02 of the expected SF. These ‘hidden’ AGNs can have significant implications for the cosmic SF rate and kinetic luminosity densities.

New Rankine Vortex Models Developed Based on SMAP Measurements

Abstract The L-band passive microwave radiometer on board the NASA Soil Moisture Active Passive (SMAP) satellite can measure brightness temperature to retrieve sea surface wind speed under tropical cyclone (TC) conditions without being affected by rainfall or signal saturation caused by high wind speeds. Based on this advantage, this paper used the SMAP wind products for parameterizing the key decay exponent α of the Rankine vortex model (a traditional parametric model of the TC wind field) and finally developed new Rankine models. The SMAP dataset included 67 TC cases. Through data statistics, we examined the relationship between α and the maximum wind speed Um, the relationship between α and the radius of maximum wind speed (Rm), and the relationship between Rm and the averaged radius of 17 m s−1 (R17). Results showed that the three relationships were both positive correlations, indicating that α can be parameterized in three empirical ways. The first way is to calculate solely with Um. The second way is to calculate solely with Rm. The third way is to calculate Um and Rm together. The three ways correspond to three new models: the SMAP Rankine Model-1 (SRM-1), the SMAP Rankine Model-2 (SRM-2), and the SMAP Rankine Model-3 (SRM-3). Finally, comparisons were made between the new models and three existing Rankine models, according to the model simulations and the Advanced Microwave Scanning Radiometer 2 measurements of 49 TC cases. Results showed that the SRM-3 performed best overall. Significance Statement Ocean surface wind fields are important driving factors for numerical models to guide evolution forecasting and risk assessment of tropical cyclones. The purpose of this study is to utilize the SMAP products to modify the traditional Rankine vortex model for tropical cyclone surface wind field estimation. Rankine decay exponent was found between 0.3 and 0.9 and positively dependent upon maximum wind speed and its radius. Based on these characteristics, the proposed new Rankine models could calculate the decay exponent and further the TC surface wind field symmetrically with high accuracy, simply using maximum wind and its radius. This paper shows a practical use of SMAP measurements on TC wind field monitoring, analyzing, and modeling.

On sea ice emission modeling for MOSAiC's L-band radiometric measurements

Abstract The retrieval of sea ice thickness using L-band passive remote sensing requires robust models for emission from sea ice. In this work, measurements obtained from surface-based radiometers during the MOSAiC expedition are assessed with the Burke, Wilheit and SMRT radiative transfer models. These models encompass distinct methodologies: radiative transfer with/without wave coherence effects, and with/without scattering. Before running these emission models, the sea ice growth is simulated using the Cumulative Freezing Degree Days (CFDD) model to further compute the evolution of the ice structure during each period. Ice coring profiles done near the instruments are used to obtain the initial state of the computation, along with Digital Thermistor Chain (DTC) data to derive the sea ice temperature during the analyzed periods. The results suggest that the coherent approach used in the Wilheit model results in a better agreement with the horizontal polarization of the in situ measured brightness temperature. The Burke and SMRT incoherent models offer a more robust fit for the vertical component. These models are almost equivalent since the scattering considered in SMRT can be safely neglected at this low frequency, but the Burke model misses an important contribution from the snow layer above sea ice. The results also suggest that a more realistic permittivity falls between the spheres and random needles formulations, with potential for refinement, particularly for L-band applications, through future field measurements.

JWST reveals the rapid and strong day-side variability of 55 Cancri e

Context. The nature of the close-in rocky planet 55 Cnce is puzzling, despite it having been observed extensively. Its optical and infrared occultation depths show temporal variability, in addition to a phase curve variability observed in the optical. Aims. We wish to explore the possibility that the variability originates from the planet being in a 3:2 spin–orbit resonance, and thus showing different sides during occultations. We proposed and were awarded Cycle 1 time at the James Webb Space Telescope (JWST) to test this hypothesis. Methods. JWST/NIRCam (Near Infrared Camera) observed five occultations (secondary eclipses) of the planet – of which four were observed within a week – simultaneously at 2.1 and 4.5 µm. While the former gives band-integrated photometry, the latter provides a spectrum between 3.9–5.0 µm. Results. We find that the occultation depths in both bandpasses are highly variable and change between a non-detection (−5 ± 6 ppm and 7 ± 9 ppm) to 96 ± 8 ppm and 119−19+34 ppm at 2.1 µm and 4.5 µm, respectively. Interestingly, the variations in both bandpasses are not correlated and do not support the 3:2 spin-orbit resonance explanation. The measured brightness temperature at 4.5 µm varies between 873–2256 K and is lower than the expected day-side temperature of bare rock with no heat redistribution (2500 K), which is indicative of an atmosphere. Our atmospheric retrieval analysis of occultation depth spectra at 4.5 µm finds that different visits statistically favour various atmospheric scenarios including a thin outgassed CO/CO2 atmosphere and a silicate rock vapour atmosphere. Some visits even support a flat line model. Conclusions. The observed variability could be explained by stochastic outgassing of CO/CO2, which is also hinted at by retrievals. Alternatively, the variability observed at both 2.1 and 4.5 µm could be the result of a circumstellar patchy dust torus generated by volcanism on the planet.

Machine learning-based retrieval of total column water vapor over land using GMI-sensed passive microwave measurements

ABSTRACT The Global Precipitation Measurement (GPM) Microwave Imager (GMI) is a microwave (MW) radiometer that has near-global coverage and frequent revisit time. To date, operational total column water vapor (TCWV) data records from the GPM GMI sensor have been exclusively offered over oceanic regions. It is challenging to retrieve TCWV over land from satellite MW measurements because of varying land surface characteristics. In this paper, a novel Light Gradient Boosting Machine-based retrieval algorithm is proposed to derive TCWV over land from GMI-sensed MW brightness temperature (BT) observations. The GMI-observed MW BT at 18.7 GHz and 23.8 GHz, differential BT between 18.7 GHz and 23.8 GHz, latitude, longitude, and month are selected and utilized as the input variables of the retrieval approach, because of their strong correlation with satellite-sensed MW TCWV retrievals. Instead of surface emissivity data or radiative transfer model, we take into account the spatial and temporal elements, namely latitude, longitude, and month. The training of the retrieval method is performed based on ground-based TCWV estimates from worldwide 4,471 Global Navigation Satellite System (GNSS) stations in 2017. The performance of the newly proposed retrieval algorithm is independently validated in a worldwide coverage using reference TCWV from additional 4,341 GNSS stations in 2018–2020 and 605 radiosonde stations in 2017–2020. The newly retrieved TCWV estimates over land have a correlation coefficient of 0.76 and 0.83, a root-mean-square error (RMSE) of 5.82 mm and 6.02 mm, a relative RMSE of 34.91% and 34.36%, and a mean bias of 0.02 mm and −0.42 mm compared to reference TCWV from GNSS and radiosonde, respectively. The performance of the retrieval algorithm is satisfactory when compared to that of land-purpose TCWV of other satellite missions, though we have not used either surface emissivity data or radiative transfer model. This result increases confidence in retrieving TCWV over land from satellite-sensed MW BT measurements based on machine learning using ground-based TCWV observations. The newly developed retrieval algorithm has the potential for integration into operational satellite missions or meteorological services, thereby enhancing weather forecasting, climate modeling, and other relevant applications.

Measuring Clear‐Air Vertical Motions From Space

AbstractMeasuring vertical velocity in the atmosphere has long been a challenge due to its small magnitude. Taking advantage of the modulation of free tropospheric relative humidity by vertical motions, we derive analytical relationships that allow us to retrieve vertical motions in clear air from geostationary measurements of brightness temperature in the infrared absorption band of water vapor. The new observations have a resolution of 1 hr and 2 km in time and space, respectively. They capture the variability of mesoscale and large‐scale vertical velocity measured during field campaigns. In the mid‐troposphere, clear‐sky vertical motions are mostly subsiding but highly heterogeneous in space and time. Around organized deep convective systems, strong subsidence (>500 hPa·day−1) is observed within a distance of a few hundred kilometers. In contrast, transient upward motions of up to 100 hPa·day−1 can occur at the mesoscale. Vertical motions in the clear‐sky atmosphere appear to be primarily associated with buoyancy and gravity waves at the mesoscale, and with radiative cooling and equatorial waves at larger spatial scales. This new retrieval reveals a rich range of dynamical features that were previously invisible, thus shedding new light on tropical meteorology.

Assessment of long-term multisource surface and subsurface soil moisture products and estimate methods on the Tibetan Plateau

This research is the first attempt to extensively assess the accuracy of commonly used surface and subsurface soil moisture (SM) datasets in reproducing temporal dynamics and trend changes SM observations for a long period on the Tibetan Plateau (TP). To this end, 12 satellite-based and 10 model-based SM products are evaluated using a 10-year upscaled SM dataset obtained from two in situ monitoring networks situated respectively in humid and arid climate zones over the TP. Moreover, the ability of using the outperforming satellite-based surface SM data in combination with cumulative distribution function (CDF) matching and exponential filter (ExpF) methods to improve model-based SM profile estimations is investigated for the first time. Among the 12 satellite-based products, SMAP_L3 provides the best surface SM retrievals, with the DCA and SCA-V products showing superior performance in the humid and arid areas, respectively. Consequently, the harmonized products produced based on the SMAP data (i.e., SMOSMAP and NNsm) also give relatively higher accuracy. It is surprised to find that the latest version of both CCI passive and active products presents degraded performance compared to its predecessor (i.e. v5.3). Among the 10 model-based products, SMAP_L4 with assimilation of L-band brightness temperature (TB) measurements provides relatively better estimations of surface and subsurface SM on the TP. Above findings highlight the superiority of utilizing the L-band TB measurements especially from the SMAP satellite to generate surface SM and improve the model-based SM estimations via data assimilation. Alternatively, it is further demonstrated that incorporating surface SM data from SMAP_L3, in conjunction with both CDF matching and ExpF methods, significantly enhances the precision of model-based SM estimations. This may open up a new possibility for improving the model-based SM profile data across the TP.

First very long baseline interferometry detection of Fornax A

Radio galaxies harbouring jetted active galactic nuclei are a frequent target of very long baseline interferometry (VLBI) because they play an essential role in our exploration of how jets form and propagate. Hence, only a few have not yet been detected with VLBI; Fornax A was one of the most famous examples. Here we present the first detection of the compact core region of Fornax A with VLBI. At 8.4 GHz the faint core is consistent with an unresolved point source. We constrained its flux density to be S0 = 47.5 − 62.3 mJy and its diameter to be D0min ≤ 70 μas. The high values of the measured brightness temperature (TB ≳ 1011 K) imply that the observed radiation is of non-thermal origin, likely associated with the synchrotron emission from the active galactic nucleus. We also investigated the possibility of a second radio source being present within the field of view. Adding a second Gaussian component to the geometrical model fit does not significantly improve the quality of the fit, and we therefore, conclude that our detection corresponds to the compact core of Fornax A. Analysis of the non-trivial closure phases provides evidence for the detection of a more extended flux density, on the angular scale of ∼4000 μas. Finally, the fractional circular polarisation of the core is consistent with zero, with a conservative upper limit being mcirc ≤ 4%.

Validation of wind speed retrieval from HY-2B calibration microwave radiometer data during tropical cyclones

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

Frequency Channel Selection and Performance Simulation of a Microwave Radiometer for Temperature and Sulfuric Compound Profiling of the Venusian Lower Atmosphere

AbstractExploring the Venusian lower atmosphere is crucial for studying the atmospheric circulation, surface‐atmosphere interactions, and origin and evolution of the Venusian atmosphere and climate. In this study, we investigate the theoretical capabilities of a downward‐looking passive microwave sounder placed in low Venus orbit to measure the temperature, sulfur dioxide (SO2) and gaseous sulfuric acid (H2SO4(g)) profiles. A nonlinear iterative retrieval algorithm combining a radiative transfer (RT) model and an optimal‐estimation‐based inversion algorithm is established. With the RT model adapted to the Venusian atmosphere, simulations under different atmospheric conditions are performed to optimize the selection of frequency channels. The achievable altitude coverage, vertical resolution and corresponding expected precision of the temperature, SO2 and H2SO4(g) retrievals from the multi‐channel brightness temperature measurements are quantified via retrieval simulations. The temperature can be retrieved from the surface of Venus to an altitude of ∼61 km with a precision of 1–3.5 K and a vertical resolution of 6–15 km. A precision of 10%–35% is expected for SO2 in the ∼12–64 km altitude range and with a vertical resolution of 8–19 km. H2SO4(g) can be retrieved in the ∼36–54 km altitude range with a precision of 10%–30% and a vertical resolution of 6–13 km.

Multifrequency Very Long Baseline Interferometry Imaging of the Subparsec-scale Jet in the Sombrero Galaxy (M104)

We report multifrequency and multiepoch very long baseline interferometry studies of the subparsec jet in the Sombrero galaxy (M104, NGC 4594). Using Very Long Baseline Array data at 12, 22, 44, and 88 GHz, we study the kinematics of the jet and the properties of the compact core. The subparsec jet is clearly detected at 12 and 22 GHz, and the inner jet base is resolved down to ∼70 Schwarzschild radii (R s) at 44 GHz. The proper motions of the jet are measured with apparent subrelativistic speeds of 0.20 ± 0.08c and 0.05 ± 0.02c for the approaching and the receding jet, respectively. Based on the apparent speed and jet-to-counterjet brightness ratio, we estimate the jet viewing angle to be larger than ∼37°, and the intrinsic speed to be between ∼0.10c and 0.40c. Their joint probability distribution suggests the most probable values of the viewing angle and intrinsic speed to be 66°−6°+4° and 0.19 ± 0.04c, respectively. We also find that the measured brightness temperatures of the core at 12, 22, and 44 GHz are close to the equipartition brightness temperature, indicating that the energy density of the radiating particles is comparable to the energy density of the magnetic field in the subparsec jet region. Interestingly, the measured core size at 88 GHz (∼25 ± 5 R s) deviates from the expected frequency dependence seen at lower frequencies. This may indicate a different origin for the millimeter emission, which can be explained by an advection-dominated accretion flow (ADAF) model. This model further predicts that at 230 and 340 GHz, the ADAF may dominate the radio emission over the jet.

An Effective Onboard Cold-Sky Calibration Strategy for Spaceborne L-Band Synthetic Aperture Radiometers

The L band frequency shows high sensitivity to sea surface salinity. More stable brightness temperature (TB) measurements are required for L-band radiometers to reduce salinity retrieval errors than for high-frequency radiometers. Due to the complexity of L-band synthetic aperture radiometers, a carefully selected cold-sky target should be viewed using an L-band synthetic aperture radiometer for the purpose of absolute TB calibration since the celestial sky is relatively well characterized and stable in the L band. A novel, effective cold-sky calibration strategy is presented in this paper. The strategy of cold-sky calibration of the synthetic aperture radiometer is applied when and where the antenna main lobe points to the ‘flat’ celestial sky, and the impact of each type of foreign source, such as the sun or moon, on visibility values should be minimized in the meantime. Additionally, antenna thermal stability is also considered, which can cause antenna deformation, and the antenna patterns are affected. A high-precision and high-fidelity simulator is built for the cold-sky calibration optimized strategy. The orbital beta angle is introduced to characterize the variation in space environment temperatures. A planet that is considered spherical in shape requires significantly less computation than an ellipsoid one in the simulator. The trade-off study results for the planet shape assumption in the cold-sky calibration simulator are presented. Finally, the calibration uncertainty and performance are assessed.

Calculated brightness temperatures of solar structures compared with ALMA and Metsähovi measurements

AbstractThe Atacama Large Millimeter/submillimeter Array (ALMA) allows for solar observations in the wavelength range of 0.3–10 mm, giving us a new view of the chromosphere. The measured brightness temperature at various frequencies can be fitted with theoretical models of density and temperature versus height. We use the available ALMA and Metsähovi measurements of selected solar structures (quiet sun (QS), active regions (AR) devoid of sunspots, and coronal holes (CH)). The measured QS brightness temperature in the ALMA wavelength range agrees well with the predictions of the semiempirical Avrett–Tian–Landi–Curdt–Wülser (ATLCW) model, better than previous models such as the Avrett–Loeser (AL) or Fontenla–Avrett–Loeser model (FAL). We scaled the ATLCW model in density and temperature to fit the observations of the other structures. For ARs, the fitted models require 9%–13% higher electron densities and 9%–10% higher electron temperatures, consistent with expectations. The CH fitted models require electron densities 2%–40% lower than the QS level, while the predicted electron temperatures, although somewhat lower, do not deviate significantly from the QS model. Despite the limitations of the one‐dimensional ATLCW model, we confirm that this model and its appropriate adaptations are sufficient for describing the basic physical properties of the solar structures.

Machine Learning Model-Based Retrieval of Temperature and Relative Humidity Profiles Measured by Microwave Radiometer

The accuracy of temperature and relative humidity (RH) profiles retrieved by the ground-based microwave radiometer (MWR) is crucial for meteorological research. In this study, the four-year measurements of brightness temperature measured by the microwave radiometer from Huangpu meteorological station in Guangzhou, China, and the radiosonde data from the Qingyuan meteorological station (70 km northwest of Huangpu station) during the years from 2018 to 2021 are compared with the sonde data. To make a detailed comparison on the performance of machine learning models in retrieving the temperature and RH profiles, four machine learning algorithms, namely Deep Learning (DL), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGBoost) and Random Forest (RF), are employed and verified. The results show that the DL model performs the best in temperature retrieval (with the root-mean-square error and the correlation coefficient of 2.36 and 0.98, respectively), while the RH of the four machine learning methods shows different excellence at different altitude levels. The integrated machine learning (ML) RH method is proposed here, in which a certain method with the minimum RMSE is selected from the four methods of DL, GBM, XGBoost and RF for a certain altitude level. Two cases on 29 January 2021 and on 10 February 2021 are used for illustration. The case on 29 January 2021 illustrates that the DL model is suitable for temperature retrieval and the ML model is suitable for RH retrieval in Guangzhou. The case on 10 February 2021 shows that the ML RH method reaches over 85% before precipitation, implying the application of the ML RH method in pre-precipitation warnings.

Microwave Observations of Venus with CLASS

We report on the disk-averaged absolute brightness temperatures of Venus measured at four microwave frequency bands with the Cosmology Large Angular Scale Surveyor. We measure temperatures of 432.3 ± 2.8, 355.6 ± 1.3, 317.9 ± 1.7, and 294.7 ± 1.9 K for frequency bands centered at 38.8, 93.7, 147.9, and 217.5 GHz, respectively. We do not observe any dependence of the measured brightness temperatures on solar illumination for all four frequency bands. A joint analysis of our measurements with lower-frequency Very Large Array observations suggests relatively warmer (∼7 K higher) mean atmospheric temperatures and lower abundances of microwave continuum absorbers than those inferred from prior radio occultation measurements.

Polar firn properties in Greenland and Antarctica and related effects on microwave brightness temperatures

Abstract. In studying the mass balance of polar ice sheets, fluctuations in firn density near the surface is a major uncertainty. In this paper, we explore these variations at locations on the Greenland Ice Sheet and at the Dome C location in Antarctica. Borehole in situ measurements, snow radar echoes, microwave brightness temperatures, and modeling results from the Community Firn Model (CFM) are used. It is shown that firn density profiles can be represented using three processes: “long-scale” and “short-scale” density variations and “refrozen layers”. Consistency with this description is observed in the dynamic range of airborne 0.5–2 GHz brightness temperatures and snow radar echo peaks in measurements performed in Greenland in 2017. Based on these insights, a new analytical partially coherent model is implemented to explain the microwave brightness temperatures using the three-scale description of the firn. Short- and long-scale firn processes are modeled as a 3D continuous random medium with finite vertical and horizontal correlation lengths as opposed to past 1D randomly layered medium descriptions. Refrozen layers are described as deterministic sheets with planar interfaces, with the number of refrozen-layer interfaces determined by radar observations. Firn density and correlation length parameters used in forward modeling to match measured 0.5–2 GHz brightness temperatures in Greenland show consistency with similar parameters in CFM predictions. Model predictions also are in good agreement with multi-angle 1.4 GHz vertically and horizontally polarized brightness temperature measured by the Soil Moisture and Ocean Salinity (SMOS) satellite at Dome C, Antarctica. This work shows that co-located active and passive microwave measurements can be used to infer polar firn properties that can be compared with predictions of the CFM. In particular, 0.5–2 GHz brightness temperature measurements are shown to be sensitive to long-scale firn density fluctuations with density standard deviations in the range of 0.01–0.06 g cm−3 and vertical correlation lengths of 6–20 cm.

Spatial and temporal differences in surface and subsurface meltwater distribution over Greenland ice sheet using multi-frequency passive microwave observations

Increasingly larger portions of the Greenland ice sheet are undergoing seasonal melting-refreeze cycles due to global climate warming. The cycle begins with the arrival of high temperatures and increased solar radiation in the spring and summer seasons generating meltwater on the ice sheet's surface. Meltwater percolates to deeper ice layers, either refreezing within the firn, creating longer-term meltwater pockets (firn aquifers), or generating peripheral runoff. Depending on the location and climate, the refreeze duration, the depth of infiltration, and meltwater persistence are temporally and spatially complex. Our recent study showed that multi-frequency passive microwave measurements in the 1.4 GHz to 36.5 GHz range effectively distinguished seasonal meltwater between the immediate surface and deeper firn layers at an experiment site in the accumulation zone of the southwestern Greenland ice sheet. Here, we further explored the vertically and horizontally polarized multi-frequency melt response at the pan-Greenland scale. We employed 1.4 GHz brightness temperature (TB) measurements from the NASA Soil Moisture Active Passive (SMAP) satellite and 6.9, 10.7, 18.9, and 36.5 GHz TB measurements from the JAXA Global Change Observation Mission-Water Shizuku (GCOM-W) satellite. The results show that the frequency-dependent response was consistent across the ice sheet. The multi-frequency melt indications match with lasting seasonal subsurface meltwater with delayed refreezing compared to the surface. These results suggest persistent seasonal subsurface meltwater occurrences that are spatially and temporally significant but concealed from the high-frequency observations. Retrieving the meltwater evolution in snow and firn presents a complex problem; this work represents an initial step toward developing an ice-sheet-wide algorithm for more comprehensive retrieval of the meltwater profile.

Quiet solar corona: daily images at 8.8–10.7 cm wavelengths

We discuss results of test observations of the 3–6 GHz range array of the Siberian Radio Heliograph (SRH). A method for calibrating brightness temperatures of images was verified using measurements of the brightness temperature of the quiet Sun at a minimum between solar activity cycles 20 and 21 known in the literature. The obtained time dependences of the integral solar flux at 2.8 GHz are similar to those measured at the Dominion Radio Astrophysical Observatory (DRAO), but the absolute values of SRH fluxes are lower relative to the DRAO fluxes by 10–15 %.&#x0D; The spectral density of the solar microwave flux at a frequency of 2.8 GHz, the so-called F10.7 index, is one of the main solar activity indices used as input parameters in models of Earth’s ionosphere. The paper considers the relationship between total radio fluxes and changes in the structure of sources on the solar disk during an interval of 50 days. During the period of daily observations from September 1 to October 20, 2021, the number of active regions on the disk changed several times, and the integral flux density at 2.8 GHz changed up to 1.5 times. We determine the relative contributions to the integral flux of bremsstrahlung of near-limb brightenings and plage regions, as well as bremsstrahlung in magnetic fields of active regions. The measured brightness temperatures of SRH radio maps are compared to the model temperatures calculated from observations of extreme ultraviolet emission (EUV) with the AIA/SDO telescope. The results of the analysis can be used to organize regular measurements of the corrected solar activity proxy index F10.7 at SRH, in which the contribution of gyroresonance emission is excluded.