Search

Two-plasmon decay instabilities (TPDIs) are a class of parametric instabilities where a gyrotron beam, polarized in X-mode, decays nonlinearly into two upper hybrid waves at approximately half frequency. Here, we present the design of a simple radiometer that was installed at Tokamak á configuration variable to diagnose TPDIs as well as a novel technique that was used to calibrate the radiometer using thermal electron cyclotron emissions. We show examples of measured radiation from TPDIs that occur when the gyrotron beam intersects blob filaments in the scrape-off layer and demonstrate that the frequency separation of the TPDI daughter waves can be used to assess the densities of the blob filaments. This technique could be utilized to diagnose density fluctuations due to both blobs, ELMs, and rotating magnetic islands. [ABSTRACT FROM AUTHOR]

AbstractThis paper examines the spatiotemporal inequality in electricity consumption at the subnational level of Bangladesh using nighttime light (NTL) data. The NTL data, sourced from the Visible Infrared Imaging Radiometer Suite (VIIRS) day/night band (DNB) for the period from 2013 to 2020, reveals persistent variability in electricity consumption among the districts. Notably, the gap between urban and non-urban areas has widened. While within district inequality (measured by NTL Gini) has declined over time, it remains high in several districts. Convergence analysis confirms that while lagging districts are showing a catching up effect, the sub-districts are diverging among themselves (in terms of mean NTL per capita). Interestingly, the rural sub-districts are converging among themselves despite urban sub-district divergence. The study also identifies regions with significant imbalance between NTL, population, and built-up area density values. These findings have implications for policymakers aiming to ensure electricity for all and reduce inequality. [ABSTRACT FROM AUTHOR]

Cloud base height (CBH) is a crucial parameter for cloud radiative effect estimates, climate change simulations, and aviation guidance. However, due to the limited information on cloud vertical structures included in passive satellite radiometer observations, few operational satellite CBH products are currently available. This study presents a new method for retrieving CBH from satellite radiometers. The method first uses the combined measurements of satellite radiometers and ground-based cloud radars to develop a lookup table (LUT) of effective cloud water content (ECWC), representing the vertically varying cloud water content. This LUT allows for the conversion of cloud water path to cloud geometric thickness (CGT), enabling the estimation of CBH as the difference between cloud top height and CGT. Detailed comparative analysis of CBH estimates from the state-of-the-art ECWC LUT are conducted against four ground-based millimeter-wave cloud radar (MMCR) measurements, and results show that the mean bias (correlation coefficient) is 0.18±1.79 km (0.73), which is lower (higher) than 0.23±2.11 km (0.67) as derived from the combined measurements of satellite radiometers and satellite radar-lidar (i.e., CloudSat and CALIPSO). Furthermore, the percentages of the CBH biases within 250 m increase by 5% to 10%, which varies by location. This indicates that the CBH estimates from our algorithm are more consistent with ground-based MMCR measurements. Therefore, this algorithm shows great potential for further improvement of the CBH retrievals as ground-based MMCR are being increasingly included in global surface meteorological observing networks, and the improved CBH retrievals will contribute to better cloud radiative effect estimates. [ABSTRACT FROM AUTHOR]

In this study, we assess the homogeneity of aerosol optical depth (AOD) between two sun photometer networks, the Global Atmosphere Watch-Precision Filter Radiometer (GAW-PFR) and the European SKYNET radiometers network (ESR), at the common wavelengths of their main instruments (500 and 870 nm). The main focus of this work is to evaluate the effect of the improved Langley plot calibration method (ILP) used by SKYNET and to investigate the factors affecting its performance. We used data from three intercomparison campaigns that took place during 2017–2021. Each campaign was organized at two locations (mountainous rural – Davos, Switzerland; urban – Rome, Italy). Our analysis shows that differences in AOD due to post-processing and instrument differences are minor. The main factor leading to AOD differences is the calibration method. We found a systematic underestimation of AOD in ESR compared to in GAW-PFR due to underestimation of the calibration constant calculated with the ILP method compared to the calibration transfers using the PFR as a reference. The calibration and AOD differences are smaller in Davos, where the traceability criteria are satisfied at 870 nm and where the median differences are below 0.01 at 500 nm. In Rome, the AOD median differences at 500 nm were in the 0.015–0.034 range. We conducted a sensitivity study, which shows that part of the difference can potentially be explained by errors in the assumed surface albedo and instrument solid-view angle provided as inputs to the ILP code (based on Skyrad pack 4.2). Our findings suggest that the ILP method is mainly sensitive to the measured sky radiance. The underestimation in calibration is probably caused by an error in the retrieved scattering AOD (sc-AOD) through the sky radiance inversion. Using an alternative retrieval method (Skyrad MRI pack version 2) to derive sc-AOD and to recalibrate the instruments with the ILP method, we found no significant differences between the retrieved sc-AOD and no systematic increase in the ILP-derived calibration constant when using the MRI pack for sc-AOD inversion instead of the Skyrad 4.2. The potential error may be a result of the model assumptions used for the sky radiance simulations. In conclusion, the on-site calibration of sun photometers has several advantages, including the fact that instrument shipments and data gaps can be avoided. However, it has also the disadvantages of a larger uncertainty and significant systematic differences compared to the traditional Langley calibration performed under low- and constant-AOD conditions at high-altitude sites. The larger uncertainty of the ILP method can be attributed to the required modelling and input parameters. [ABSTRACT FROM AUTHOR]

(1) Background: To compare the degree of conversion of resin cores in various types of cavities and determine an effective irradiation method for achieving a higher degree of conversion. (2) Methods: Four different-sized cavities (narrow–shallow, narrow–deep, wide–shallow, and wide–deep) were simulated using a Teflon mold. The light irradiance reaching the bottom of each mold was measured by positioning a radiometer. The degree of conversion of the dual-cure resin core after irradiation (400 mW/cm2 for 20 s, 400 mW/cm2 for 40 s, and 800 mW/cm2 for 20 s) was measured using Fourier-transform near-infrared spectroscopy. (3) Results: The highest light irradiance was found at the bottom of wide–shallow cavities, followed by wide–deep, narrow–shallow, and narrow–deep ones (p < 0.001). In narrow cavities, irradiation at 800 mW/cm2 for 20 s led to a significantly higher degree of conversion (p < 0.001). In wide cavities, irradiation at 400 mW/cm2 for 40 s and 800 mW/cm2 for 20 s both led to a significantly higher degree of conversion (p < 0.001). (4) Conclusions: Less curing light reaches the bottom of cavities with a smaller diameter and greater depth. Providing a higher irradiance of light can induce a higher degree of conversion of resin composites in narrower cavities. [ABSTRACT FROM AUTHOR]

The NOAA-AVHRR (National Oceanographic and Atmospheric Administration–Advanced Very High-Resolution Radiometer) archive includes data from 1981 onwards, which allow for estimating land surface temperature (LST), a key parameter for the study of global warming as well as surface characterization. However, algorithms for LST retrieval were developed before the latest sensors and were based on more reduced atmospheric datasets. Here, we present 50 novel sets of coefficients for an LST retrieval algorithm from NOAA-AVHRR sensors, to which we added one historical methodology, which we validate against historical in situ as well as independent satellite data. This validation shows that the historical algorithm performs surprisingly well, with an in situ RMSE below 1.5 K and a quasi-null bias when compared with independent satellite data. A couple of the novel algorithms also perform within expectations (errors below 1.5 K), so any of these could be used for the complete processing of the AVHRR dataset. In our case, considering consistency with previous works, we opt for the use of the historical algorithm, now also tested for more recent periods. [ABSTRACT FROM AUTHOR]

Polar lows are small, high-latitude, intense maritime cyclones and frequently have severe impacts on the ocean such as strong winds, high waves and heavy rainfall. They are difficult to observe and forecast due to their short lifetime (<48 hours), small horizontal scales (200 ~ 1000 km), and the sparse synoptic observing network that exists in the subarctic and Arctic oceans. Previous studies have identified and monitored polar lows by visual analysis of visible and thermal infrared imagery from satellites. However, this manual inspection method is subjective, time-consuming and inevitably involves errors in polar low detections. In this study, we present an automatic objective procedure which we demonstrate by detecting polar lows using spaceborne active synthetic aperture radar (SAR) and passive microwave radiometer observations. Based on the marker-controlled watershed segmentation method and the morphological image thinning algorithm, the centre locations of polar lows are determined using RADARSAT-2 and Sentinel-1A high-resolution SAR images and total atmospheric water vapour content fields from radiometers (AMSR2, SSM/I, GMI, and WindSat). Furthermore, the trajectories of polar lows are constructed, using detected centres from multi-temporal SAR and radiometer observations. Polar low detections are confirmed by high surface wind speeds from SAR, scatterometer, and radiometer data, the presence of cloud vortex signatures visible in MODIS, AVHRR, and VIIRS thermal infrared imagery, as well as the difference between the sea surface temperature and the air temperature at 500 hPa. These results show that the proposed methods have potential to automatically detect and track polar lows from multisensor data. We also estimate the characteristic parameters of detected polar lows. The diameters, translation speeds, and distances travelled are 189 km and 225 km, 8 m/s and 4.9 m/s, and 318 km and 263 km, respectively. [ABSTRACT FROM AUTHOR]

In this study, a series of hypervelocity impact tests were carried out based on a two-stage light gas gun, and the sequence spectrum and radiation evolution data of the impact products under different impact conditions were obtained. The diameter of the projectile is 3e5 mm, the impact velocity is 3.13e6.58 km/s, and the chamber pressure is 0.56e990 Pa. The spectrum of ejected debris cloud in the 250e310 nm band were obtained using a transient spectral measurement system and a multi-channel radiometer measurement system. The test results reveal that the flash radiation intensity increases as a power function with the kinetic energy of the impact. Furthermore, the peak value of the line spectrum decreases as the chamber vacuum degree increases, while the radiation width gradually expands. The line spectrum in the spectral characterization curve corresponds to the ejected debris clouds splitting phase, which does not produce significant line spectrum during material fragmentation and is dominated by the continuum spectrum produced by blackbody radiation. There will appear one or three characteristic peaks in the flash radiation time curve, the first and second peaks correspond to the penetration phase and the third peak corresponds to the expansion phase of the ejected debris clouds on the time scale, the first and second peaks are more sensitive to the chamber vacuum degree, and when the pressure is higher than 99 Pa, the first and second characteristic peaks will disappear. The radiant heat attenuation of the flash under different impact conditions is significantly different, the attenuation exponent has a power function relationship with the impact velocity and the chamber vacuum degree, while the attenuation exponent has a linear relationship with the diameter of the projectile, the specific expression of the attenuation exponent is obtained by fitting. The findings from this research can serve as a valuable reference for remote diagnostic technologies based on flash radiation characteristics. [ABSTRACT FROM AUTHOR]

Wheat (Triticum aestivum) yield predictions can be improved by using multispectral remote sensing to identify different genotypes and crop growth stages. We propose an innovative machine learning technique aimed at classifying diverse wheat crop genotypes and providing accurate estimations of plant age. Multispectral reflectance data was obtained from different sites where various wheat genotypes were cultivated. This approach involved analyzing incoming radiation and canopy light reflectance across five distinct spectral bands using a multispectral radiometer. The newly collected remote sensing data was utilized as input for the machine learning algorithm. Impressively, the random forest model achieved an accuracy rate of 98.77% in wheat crop genotype classification. Furthermore, the proposed approach's effectiveness was confirmed through a 10‐fold cross‐validation mechanism. Moreover, a multiple linear regression model for predicting the age of wheat genotypes explained 91% of the observed variation. These findings signify significant progress in wheat crop genotype and age prediction, ultimately leading to enhanced wheat yield. Core Ideas: This research addresses a significant challenge in wheat crop genotype and age prediction.We propose an innovative machine learning methodology to classify different wheat crop genotypes.We collected different wheat seed genotype samples using the multispectral radiometer. [ABSTRACT FROM AUTHOR]

The soil moisture at the medium spatial scale is strongly desired in the context of satellite remote sensing data validation. The use of a ground-installed passive L-band radiometer ELBARA at the Bubnów-Sęków test site in the east of Poland gave a possibility to provide reference soil moisture data from the area with a radius of 100 m. In addition, the test site comprised three different land cover types that could be investigated continuously with one day resolution. The studies were focused on the evaluation of the ω-τ model coefficients for three types of land cover, including meadow, wetland, and cropland, to allow for the assessment of the soil moisture retrievals at a medium scale. Consequently, a set of reference time-dependent coefficients of effective scattering albedo, optical depth, and constant-in-time roughness parameters were estimated. The mean annual values of the effective scattering albedo including two polarisations were 0.45, 0.26, 0.14, and 0.54 for the meadow with lower organic matter, the meadow with higher organic matter, the wetland, and the cropland, respectively. The values of optical depth were in the range from 0.30 to 0.80 for the cropland, from 0.40 to 0.52 for the meadows (including the two investigated meadows), and from 0.60 to 0.70 for the wetland. Time-constant values of roughness parameters at the level of 0.45 were obtained. [ABSTRACT FROM AUTHOR]

The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, deployed on multiple satellites including the Suomi National Polar-orbiting Partnership (S-NPP), National Oceanic and Atmospheric Administration 20 (NOAA-20), NOAA-21, Joint Polar Satellite System (JPSS-3), and JPSS-4 spacecraft, with launches in 2011, 2017, 2022, 2032, and 2027, respectively, has polarization sensitivity that affects the at-aperture radiometric Sensor Data Record (SDR) calibration in the Visible Near InfraRed (VNIR) spectral region. These SDRs are key inputs into the VIIRS atmospheric, land, and water Environmental Data Records (EDRs) that are integral to weather and climate applications. If the polarization sensitivity of the VIIRS instrument is left uncorrected, EDR quality will degrade, causing diminished quality of weather and climate data. Pre-launch characterization of the instrument's polarization sensitivity was performed to mitigate this on-orbit calibration effect and improve the quality of the EDRs. Specialized ground test equipment, built specifically for the VIIRS instrument, enabled high-fidelity characterization of the instrument's polarization performance. This paper will discuss the polarization sensitivity characterization test approach, methodology, and results for the JPSS-3 and -4 builds. This includes a description of the ground test equipment, instrument requirements, and how the testing was executed and analyzed. A comparison of the polarization sensitivity results of the on-orbit S-NPP, NOAA-20, and -21 instruments with the JPSS-3 and -4 VIIRS instruments will be discussed as well. [ABSTRACT FROM AUTHOR]

The Peak Design Ltd hyperspectral radiometer (HSR1) was tested at the Atmospheric Radiation Measurement (ARM) user facility Southern Great Plains (SGP) site in Lamont, Oklahoma, for 2 months from May to July 2022. The HSR1 is a prototype instrument that measures total (Ftotal) and diffuse (Fdiffuse) spectral irradiance from 360 to 1100 nm with a spectral resolution of 3 nm. The HSR1 spectral irradiance measurements are compared to nearby collocated spectral radiometers, including two multifilter rotating shadowband radiometers (MFRSRs) and the Shortwave Array Spectroradiometer–Hemispheric (SASHe) radiometer. The Ftotal at 500 nm for the HSR1 compared to the MFRSRs has a mean (relative) difference of 0.01 W m -2 nm -1 (1 %–2 %). The HSR1 mean Fdiffuse at 500 nm is smaller than the MFRSRs' by 0.03–0.04 (10 %) W m -2 nm -1. The HSR1 clear-sky aerosol optical depth (AOD) is also retrieved by considering Langley regressions and compared to collocated instruments such as the Cimel sunphotometer (CSPHOT), MFRSRs, and SASHe. The mean HSR1 AOD at 500 nm is larger than the CSPHOT's by 0.010 (8 %) and larger than the MFRSRs' by 0.007–0.017 (6 %–18 %). In general, good agreement between the HSR1 and other instruments is found in terms of the Ftotal , Fdiffuse , and AODs at 500 nm. The HSR1 quantities are also compared at other wavelengths to the collocated instruments. The comparisons are within ∼ 10 % for the Ftotal and Fdiffuse , except for 940 nm, where there is relatively larger disagreement. The AOD comparisons are within ∼ 10 % at 415 and 440 nm; however, a relatively larger disagreement in the AOD comparison is found for higher wavelengths. [ABSTRACT FROM AUTHOR]

A new cost-effective radiometer has been designed, built, and tested to measure direct normal solar irradiance (DNI). The proposed instrument for solar irradiance measurement is based on an optical fiber as the light beam collector, a semiconductor photodiode to measure the optical power, and a calibration algorithm to convert the optical power into solar irradiance. The proposed radiometer offers the advantage of separating the measurement point, where the optical fiber collects the solar irradiation, from the place where the optical power is measured. A calibration factor is mandatory because the semiconductor photodiode is only spectrally responsive to a limited part of the spectral irradiance. Experimental tests have been conducted under different conditions to evaluate the performance of the proposed device. The measurements confirm that the proposed instrument performs similarly to the expensive high-accuracy pyrheliometer used as a reference. [ABSTRACT FROM AUTHOR]

The non-scanning radiometer with short-wavelength (SW: 0.2–5.0 μm) and total-wavelength (TW: 0.2–50.0 μm) channels is the primary payload of the Integrated Earth–Moon Radiation Observation System (IEMROS), which is designed to provide comprehensive Earth radiation measurements and lunar calibrations at the L1 Lagrange point of the Earth–Moon system from a global perspective. This manuscript introduces a radiometer preflight calibration methodology, which involves background removal and is validated using accurate and traceable reference sources. Simulated Earth view tests are performed to evaluate repeatability, linearity, and gain coefficients over the operating range. Both channels demonstrate repeatability uncertainties better than 0.34%, indicating consistent and reliable measuring performance. Comparative polynomial regression analysis confirms significant linear response characteristics with two-channel nonlinearity less than 0.20%. Gain coefficients are efficiently determined using a two-point calibration approach. Uncertainty analysis reveals an absolute radiometric calibration accuracy of 0.97% for the SW channel and 0.92% for the TW channel, underscoring the non-scanning radiometer's capability to provide dependable global Earth radiation budget data crucial to environmental and climate studies. [ABSTRACT FROM AUTHOR]

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

The observation of the global 21 cm signal produced by neutral hydrogen gas in the intergalactic medium (IGM) during the Dark Ages, Cosmic Dawn, and Epoch of Reionization requires measurements with extremely well-calibrated wideband radiometers. We describe the design and characterization of the Mapper of the IGM Spin Temperature (MIST), which is a new ground-based, single-antenna, global 21 cm experiment. The design of MIST was guided by the objectives of avoiding systematics from an antenna ground plane and cables around the antenna, as well as maximizing the instrument's on-sky efficiency and portability for operations at remote sites. We have built two MIST instruments, which observe in the range 25–105 MHz. For the 21 cm signal, this frequency range approximately corresponds to redshifts 55.5 > z > 12.5, encompassing the Dark Ages and Cosmic Dawn. The MIST antenna is a horizontal blade dipole of 2.42 m in length, 60 cm in width, and 52 cm in height above the ground. This antenna operates without a metal ground plane. The instruments run on 12 V batteries and have a maximum power consumption of 17 W. The batteries and electronics are contained in a single receiver box located under the antenna. We present the characterization of the instruments using electromagnetic simulations and lab measurements. We also show sample sky measurements from recent observations at remote sites in California, Nevada, and the Canadian High Arctic. These measurements indicate that the instruments perform as expected. Detailed analyses of the sky measurements are left for future work. [ABSTRACT FROM AUTHOR]

This study focuses on the characterization of aerosol hygroscopicity using remote sensing techniques. We employ a Mie–Raman–fluorescence lidar (Lille Lidar for Atmospheric Study, LILAS), developed at the ATOLL platform, Laboratoire d'Optique Atmosphérique, Lille, France, in combination with the RPG-HATPRO-G5 microwave radiometer to enable continuous aerosol and water vapor monitoring. We identify hygroscopic growth cases when an aerosol layer exhibits an increase in both aerosol backscattering coefficient and relative humidity. By examining the fluorescence backscattering coefficient, which remains unaffected by the presence of water vapor, the potential temperature, and the absolute humidity, we verify the homogeneity of the aerosol layer. Consequently, the change in the backscattering coefficient is solely attributed to water uptake. The Hänel theory is employed to describe the evolution of the backscattering coefficient with relative humidity and introduces a hygroscopic coefficient, γ , which depends on the aerosol type. The particularity of this method revolves around the use of the fluorescence which is employed to take into account and correct the aerosol concentration variations in the layer. Case studies conducted on 29 July and 9 March 2021 examine, respectively, an urban and a smoke aerosol layer. For the urban case, γ is estimated as 0.47 ± 0.03 at 532 nm; as for the smoke case, the estimation of γ is 0.5 ± 0.3. These values align with those reported in the literature for urban and smoke particles. Our findings highlight the efficiency of the Mie–Raman–fluorescence lidar and microwave radiometer synergy in characterizing aerosol hygroscopicity. The results contribute to advance our understanding of atmospheric processes, aerosol–cloud interactions, and climate modeling. [ABSTRACT FROM AUTHOR]

As populations and temperatures of urban areas swell, more people face extreme heat and are at increasing risk of adverse health outcomes. Radiation accounts for much of human heat exposure but is rarely used as heat metric due to a lack of cost-effective and accurate sensors. To this end, we fuse the concepts of a three-globe radiometer-anemometer with a cylindrical human body shape representation, which is more realistic than a spherical representation. Using cost-effective and readily available materials, we fabricated two combinations of three cylinders with varying surface properties. These simple devices measure the convection coefficient and the shortwave and longwave radiative fluxes. We tested the devices in a wind tunnel and at fourteen outdoor sites during July 2023's record-setting heat wave in Tempe, Arizona. The average difference between pedestrian-level mean radiant temperature (MRT) measured using research-grade 3-way net radiometers and the three-cylinder setup was 0.4 ± 3.0 °C (± 1 SD). At most, we observed a 10 °C MRT difference on a white roof site with extreme MRT values (70 °C to 80 °C), which will be addressed through discussed design changes to the system. The measured heat transfer coefficient can be used to calculate wind speed below 2 m·s−1; thus, the three cylinders combined also serve as a low-speed anemometer. The novel setup could be used in affordable biometeorological stations and deployed across urban landscapes to build human-relevant heat sensing networks. [ABSTRACT FROM AUTHOR]

Surface radiometer data from Ross Island, Antarctica, collected during the austral summer 2015–2016 by the US Department of Energy Atmospheric Radiation Measurement (ARM) program West Antarctic Radiation Experiment (AWARE), are used to evaluate how shortwave and longwave irradiance respond to changing cloud properties as governed by contrasting meteorological regimes. Shortwave atmospheric transmittance is derived from pyranometer measurements, and cloud conservative-scattering optical depth is derived from filter radiometer measurements at 870 nm. With onshore flow associated with marine air masses, clouds contain mostly liquid water. With southerly flow over the Transantarctic Mountains, orographic forcing induces substantial cloud ice water content. These ice and mixed-phase clouds attenuate more surface shortwave irradiance than the maritime-influenced clouds and also emit less longwave irradiance due to colder cloud base temperature. These detected irradiance changes are in a range that can mean onset or inhibition of surface melt over ice shelves. This study demonstrates how basic and relatively low-cost broadband and filter radiometers can be used to detect subtle climatological influences of contrasting cloud microphysical properties at very remote locations. [ABSTRACT FROM AUTHOR]

In this study, we assess the homogeneity of aerosol optical depth (AOD) between the sun photometer networks Global Atmospheric Watch-Precision Filter Radiometer (GAW-PFR) and European Skynet Radiometers network (ESR) at the 2 common wavelengths of their main instruments 500 nm and 870 nm. The main focus of the work is on evaluating the effect of the Improved Langley calibration method, (ILP) used by SKYNET and investigating the factors affecting its performance. We used data from three intercomparison campaigns that took place in the period 2017–2021. Each campaign has two phases in two locations. One is mountainous rural (Davos, Switzerland) and the other urban (Rome, Italy). Our analysis shows that the AOD differences due to post processing and instrument differences are minor. The major factor leading to AOD differences is the calibration method where we found a systematic underestimation of AOD compared to GAW-PFR due to an underestimation in the ILP calibration. The calibration and AOD differences are smaller in Davos where at 870 nm the traceability criteria are satisfied and at 500 nm the median differences are below 0.01. In Rome at 500 nm the AOD median differences per campaign are between 0.015–0.035. Attempting to explain the differences we found no association between the calibration performance and the level or the variability of the aerosol properties. We also conducted a sensitivity study, which shows that part of the difference can be potentially explained by errors in the assumed surface albedo and instrument solid view angle provided as inputs to the ILP code (based on Skyrad pack 4.2). Our findings suggest that the ILP method is mainly sensitive to the measured sky radiance. The calibration underestimation is probably caused by an error on the retrieved scattering aerosol optical depth (sc-AOD) through the sky radiance inversion. Using an alternative retrieval method (Skyrad MRI pack version 2) to derive sc-AOD and repeat ILP calibration, we found no significant differences between the retrieved sc-AOD nor systematic increase of the calibrations. The potential error may be a result of the forward model assumptions, To conclude, calibration of sun photometers on site offers the advantage of avoiding instrument shipments and data gaps. However, ILP shows larger uncertainty and significant systematic difference compared to the traditional Langley calibration performed under low and constant AOD conditions at high altitude sites, due to the uncertainties of the calibration method and the input parameters needed for it. In the following sections we report on results on the AOD retrievals of several instruments in different environments using different principles in their calibration methods. We also perform an investigation to explain the causes of differences. [ABSTRACT FROM AUTHOR]

The sea ice albedo can amplify global climate change and affect the surface energy in the Arctic. In this paper, the data from Visible and Infra-Red Radiometer (VIRR) onboard Fengyun-3C satellite are applied to derive the Arctic sea ice albedo. Two radiative transfer models, namely, 6S and FluxNet, are used to simulate the reflectance and albedo in the shortwave band. Clear sky sea ice albedo in the Arctic region (60°~90°N) from 2016 to 2019 is derived through the physical process, including data preprocessing, narrowband to broadband conversion, anisotropy correction, and atmospheric correction. The results are compared with aircraft measurements and AVHRR Polar Pathfinder-Extended (APP-x) albedo product and OLCI MPF product. The bias and standard deviation of the difference between VIRR albedo and aircraft measurements are −0.040 and 0.071, respectively. Compared with APP-x product and OLCI MPF product, a good consistency of albedo is shown. And analyzed together with melt pond fraction, an obvious negative relationship can be seen. After processing the 4-year data, an obvious annual trend can be observed. Due to the influence of snow on the ice surface, the average surface albedo of the Arctic in March and April can reach more than 0.8. Starting in May, with the ice and snow melting and melt ponds forming, the albedo drops rapidly to 0.5–0.6. Into August, the melt ponds begin to freeze and the surface albedo increases. [ABSTRACT FROM AUTHOR]

The 2012 satellite ASTER geoscience maps of Australia were designed to provide public, web-accessible, and spatially comprehensive surface mineralogy for improved mapping and solutions to geoscience challenges. However, a number of the 2012 products were clearly compromised by variable green and/or dry vegetation cover. Here, we show a strategy to first estimate and then unmix the contributions of both these vegetation components to leave, as residual, the target surface mineralogy. The success of this unmixing process is validated by (i) visual suppression/removal of the regional climate and/or local fire-scar vegetation patterns; and (ii) pixel values more closely matching field sample data. In this process, we also found that the 2012 spectral indices used to gauge the AlOH content, AlOH composition, and water content can be improved. The updated (new indices and vegetation unmixed) maps reveal new geoscience information, including: (i) regional "wet" and "dry" zones that appear to express "deep" geological characters often expressed through thick regolith cover, with one zone over the Yilgarn Craton spatially anti-correlated with Archaean gold deposits; (ii) a ~1000 km wide circular feature over the Lake Eyre region defined by a rim of abundant "muscovite" that appears to coincide with opal deposits; (iii) a N–S zonation across the western half of the continent defined by abundant muscovite in the south and kaolinite in the north, which appears to reflect opposing E ↔ W aeolian sediment transport directions across the high-pressure belt; (iv) various paleo-drainage networks, including those over aeolian sand covered the "lowlands" of the Canning Basin, which are characterized by low AlOH content, as well as those over eroding "uplands", such as the Yilgarn Craton, which have complicated compositional patterns; and (v) a chronological history of Miocene barrier shorelines, back-beach lagoons, and alluvial fans across the Eucla Basin, which, to date, had proved elusive to map using other techniques, with potential implications for heavy mineral sand exploration. Here, we explore the latter three issues. [ABSTRACT FROM AUTHOR]

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

The satellite-based aerosol optical depth (AOD), which can provide continuous spatial observations of aerosol loadings, is widely adopted to estimate atmospheric environmental quality and evaluate its risk for human health. However, current satellite-retrieved AOD products characterized by a comparatively coarse spatial resolution (≥1 km) can hardly analyze the structure of atmospheric pollution or its correlation with urban landscapes over populated urban areas. Existed studies have tried to address this deficiency by retrieving high-resolution AOD using Landsat images, whose long revisit period (16 days nominally), however, largely limits its applications related to urban air pollution research. To achieve both high spatial resolution and expected revisit period from satellite observation, in this study, a comprehensive AOD retrieval framework is developed for Wide-Field-of-View (WFV) satellite sensors to yield a daily AOD dataset over urban areas with 160 m spatial resolution, based on the Gaofen-1 and Gaofen-6 synergistic observations. To address the crucial challenge that the high spatial resolution and complex urban landscape both contribute a dramatic variation of land surface bidirectional reflectance, a Simulated-Annealing-coupled Semiempirical Modified Rahman-Pinty-Verstraete (SAS-MRPV) scheme is proposed to model and estimate the land surface reflectance (LSR) in the AOD retrieval framework, where the SAS-MRPV scheme is implemented using simulated annealing iteration initialized by the bidirectional reflectance distribution function (BRDF) products from the Moderate Resolution Imaging Spectrometer (MODIS) as a priori knowledge. The validation results demonstrate that the Gaofen WFV AOD retrievals exhibit good agreement with the ground-based AErosol RObotic NETwork (AERONET) and SONET (Sun-sky radiometer Observation NETwork) AOD, demonstrating the correlation coefficient and the expected error (EE)±(0.05 + 0.15AOD AERONET/SONET) ratio respectively reaching up to 0.97 and over 80 %, and only slight bias fluctuations are found under different land cover types, aerosol loading, and seasonal conditions. Moreover, the validation results of Gaofen WFV AOD retrievals, with LSR estimated based on the SAS-MRPV scheme, the MODIS BRDF Products, and the Minimum Reflectance Technique (MRT) method, demonstrate better accuracy and completeness of AOD retrievals using the SAS-MPRV scheme over both natural and impervious land surfaces, indicating the stability and reliability of proposed SAS-MRPV LSR determination scheme in WFV AOD retrieval. In addition to that, the error analyses and quality control results demonstrate that the SAS-MRPV scheme is effective and necessary to guarantee the reliability and accuracy of land surface bidirectional reflectance estimation by identifying and excluding the land surface pixels unsuitable for LSR modeling, which mitigates the uncertainty and yield better accuracy in the final WFV AOD products. Furthermore, the inter-comparison between WFV-derived AOD against the operational MODIS Deep Blue (10 km), Dark Target (3 km), and Multi-Angle Implementation of Atmospheric Correction (MAIAC, 1 km) AOD products demonstrates that the 160 m WFV AOD retrievals, on the basis of obtaining similar aerosol overall descriptions as MODIS AOD retrievals, possess the capability to characterize the spatial distribution of atmospheric pollution at a finer scale with smoother variation under both clean and polluted conditions. With outstanding accuracy and reliable performance, the developed comprehensive high-resolution AOD retrieval framework exhibits substantial potential for operational AOD retrieval of Gaofen WFV satellite observations, which could be directly applied to other urban areas supporting further studies related to air pollution emission management and health risk assessment at extra-fine spatial scale. [ABSTRACT FROM AUTHOR]

Verifying and validating waterleaving radiance measurements from space for an accurate derivation of Ocean/Water Colour biogeophysical products is based on concurrent high-quality fiducial reference measurements (FRM) carried out on the ground or water body. The FRM principles established by the Committee on Earth Observation Satellites (CEOS) recommend that in situ Ocean Colour radiometers (OCR) have a documented history of SI traceable calibrations including uncertainty budgets. Furthermore, there can be significant differences between calibration and use of the instruments in the field due to differences in operating temperature, angular variation of the light field (especially for irradiance sensors), the intensity of the measured radiation, and spectral variation of the target, among others. Each of these factors may interact with individual properties of the instrument when deployed in the field, and estimation of such uncertainties requires instrument characterization in addition to the absolute radiometric calibration if expanded uncertainties within ±10% (k = 2) are the aim. The FRM4SOC Phase 2 project - funded by the European Commission in the frame of the Copernicus Programme and implemented by EUMETSAT - contributes to these efforts, aiming at developing an operational and sustained network of radiometric measurements of FRM quality. Within FRM4SOC-2, scientists from the Tartu Observatory (TO) of the University of Tartu performed an unprecedented batch of calibrations and characterizations on a set of 37 hyperspectral field radiometers representative of the most used OCR classes within the OC community. The calibrations and characterizations performed include the determination of radiometric responsivity, long-term stability, the accuracy of the spectral scale, non-linearity and accuracy of integration times, spectral stray light, angular response of irradiance sensors in air, dark signal, thermal sensitivity, polarization sensitivity, and signal-to-noise ratio of individual OCRs. Consistent correction of biases and extended uncertainty analysis procedures of in situ data obtained from different instruments and measurement models need to be clearly defined, which is the objective of this paper. [ABSTRACT FROM AUTHOR]

Satellites are now routinely used for measuring water and land surface reflectance and hence environmentally relevant parameters such as aquatic chlorophyll a concentration and terrestrial vegetation indices. For each satellite mission, radiometric validation is needed at bottom of atmosphere for all spectral bands and covering all typical conditions where the satellite data will be used. Existing networks such as AERONET-OC for water and RadCalNet for land provide vital information for validation, but (AERONET-OC) do not cover all spectral bands or (RadCalNet) do not cover all surface types and viewing angles. In this Perspective Article we discuss recent advances in instrumentation, measurement methods and uncertainty estimation in the field of optical radiometry and put forward the viewpoint that a new network of automated hyperspectral radiometers is needed for multi-mission radiometric validation of water and land surface reflectance. The HYPERNETS federated network concept is described, providing a context for research papers on specific aspects of the network. This network is unique in its common approach to both land and water surfaces. The common aspects and the differences between land and water measurements are explained. Based on early enthusiasm for HYPERNETS data from validation-oriented workshops, it is our viewpoint that this new network of automated hyperspectral radiometers will be useful for multi-mission radiometric validation of water and multi-angle land surface reflectance. The HYPERNETS network has strong synergy with other measurement networks (AERONET, AERONET-OC, RadCalNet, FLUXNET, ICOS, skycam, etc.) and with optional supplementary measurements, e.g., water turbidity and fluorescence, land surface temperature and soil moisture, etc. [ABSTRACT FROM AUTHOR]

The satellite Earth observation (EO) sector is burgeoning with hundreds of commercial satellites being launched each year, delivering a rich source of data that could be exploited for societal benefit. Data streams from the growing number of commercial satellites are of variable quality, limiting the potential for their combined use in science applications that need long time-series data from multiple sources. The quality of calibration performed on optical sensors onboard many satellite systems is highly variable due to calibration methods, sensor design, mission objective, budget, or other operational constraints. A small number of currently operating well-characterised satellite systems with onboard calibration, such as Landsat-8/9 and Sentinel-2, and planned future missions, like the NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder, the European Space Agency (ESA)'s Traceable Radiometry Underpinning Terrestrial and Helio Studies (TRUTHS), and LIBRA from China, are considered benchmarks for optical data quality due to their traceability to international measurement standards. This paper describes the concept of a space-based transfer calibration radiometer called the Satellite Cross-Calibration Radiometer (SCR) that would enable the calibration parameters from satellites such as Landsat-8/9, Sentinel-2, or other benchmark systems to be transferred to a range of commercial optical EO satellite systems while in orbit. A description of the key characteristics of the SCR to successfully operate in orbit and transfer calibration from reference systems to client systems is presented. A system like the SCR in orbit could complement SI-Traceable satellites (SITSats) to improve data quality and consistency and facilitate the interoperable use of data from multiple optical sensor systems for delivering higher returns on the global investment in EO. [ABSTRACT FROM AUTHOR]

Underwater spectral detection plays an important role in the study of the underwater environment, ecology, oceanography, and environmental monitoring. A kind of underwater spectral radiometer that can observe the distribution of underwater spectral radiation bidirectionally has been developed. The flat-field concave holographic grating is used as the only optical component, the optical design parameters are optimized, and the system is miniaturized. The mechanism of stray light generation in the spectrometer is studied, and a method of suppressing stray light is proposed and simulated. The level of stray light in the system is suppressed to the order of 10−4, the signal-to-noise ratio of the system is improved, and the ability to detect weak light is enhanced. The wavelength calibration experiment was completed, and the experimental results show that the wavelength resolution of the underwater spectral radiometer is better than 3 nm. Finally, the quantitative relationship between spectral irradiance and digital output is obtained through radiation in the calibration of the system. [ABSTRACT FROM AUTHOR]

The paper presents the research work aimed at improving the quality characteristics of information products based on the MSU-GS/VE radiometer aboard the Arktika-M No. 1 satellite, as well as at obtaining data preprocessing products. All described methods are based on using machine learning algorithms, namely, neural networks of various architectures. The results of developing a technology for minimizing the interference that occurs in the channels of the satellite device are provided. The work on detecting cloud formations based on processing the channel data in the visible and infrared ranges is presented. It is shown that the use of neural networks makes it possible to implement automatic algorithms for obtaining thematic products that take into account various factors and have an accuracy that is commensurate with statistical and physical approaches and reduces the time of satellite data processing. [ABSTRACT FROM AUTHOR]

NASA's Soil Moisture Active Passive (SMAP) was originally designed to combine high-resolution active (radar) and coarse-resolution but highly sensitive passive (radiometer) L-band observations to achieve unprecedented spatial resolution and accuracy for soil moisture retrievals. However, shortly after SMAP was put into orbit, the radar component failed, and the high-resolution capability was lost. In this paper, the integration of an alternative radar sensor with the SMAP radiometer is proposed to enhance soil moisture retrieval capabilities over vegetated areas in the absence of the original high-resolution radar in the SMAP mission. ESA's Sentinel-1A C-band radar was used in this study to enhance the spatial resolution of the SMAP L-band radiometer and to improve soil moisture retrieval accuracy. To achieve this purpose, we downscaled the 9 km radiometer data of the SMAP to 1 km utilizing the Smoothing Filter-based Intensity Modulation (SFIM) method. An Artificial Neural Network (ANN) was then trained to exploit the synergy between the Sentinel-1A radar, SMAP radiometer, and the in situ-measured soil moisture. An analysis of the data obtained for a plant growing season over the Mississippi Delta showed that the VH-polarized Sentinel-1A radar data can yield a coefficient of correlation of 0.81 and serve as a complimentary source to the SMAP radiometer for more accurate and enhanced soil moisture prediction over agricultural fields. [ABSTRACT FROM AUTHOR]

Objectives. Quality control of instruments for measuring bactericidal irradiance of ultraviolet (UV) radiation is based on studying the main metrological characteristics. These characteristics include: angular and spectral sensitivity; linearity range; and absolute calibration in irradiance units. Deviations of the angular sensitivity of measuring instruments from the ideal cosine characteristic can significantly impact error estimation. They can also lead to the distortion of measurement results and a significant difference in instrument readings. The aim of this work is to enhance accuracy in resolving metrological problems of determining irradiance of bactericidal radiation.Methods. An effective method of resolving this problem is to introduce correction coefficients for the angular sensitivity of radiometers, spectroradiometers and dosimeters. The values are calculated based on the results of measurements on the goniometer when testing measuring instruments. An important role is played by computer models and digital twins of measuring instruments based on the results of studies of the metrological characteristics of radiometers by means of software. This includes modeling the measuring task.Results. The study of angular dependence of bactericidal UV radiometer sensitivity complemented by an analysis of measurement results obtained by other authors allows determining the value of the angular sensitivity correction coefficients by the deviation of the angular sensitivity of the irradiance measuring instruments of bactericidal radiation from the standard cosine dependence.Conclusions. Deviations of the angular dependence of bactericidal radiation UV radiometer sensitivity from the cosine characteristic lead to a significant underestimation of the irradiance measurements results from extended emitters. An effective solution is the use of digital angular sensitivity correction coefficients to measure the irradiance of bactericidal radiation determined during tests. When assessing the quality of radiometers, spectroradiometers and dosimeters for bactericidal radiation, incomplete control of the main metrological characteristics of the measuring instruments creates risks of serious errors in the measurement results of bactericidal irradiance.

High-wind structures were identified in the Cross-Calibrated Multi-Platform (CCMP) ocean wind vector reanalysis for comparison with winds measured by satellite radiometers, scatterometers, and synthetic aperture radar (SAR) instruments from February to October 2023. The comparison aims to evaluate bias, uncertainty, and spatial correlations with the goal of enhancing the accuracy of ocean wind datasets during tropical cyclones (TCs). In 10° longitude × 10° latitude blocks, each containing a TC, Soil Moisture Active Passive (SMAP) and Advanced Microwave Scanning Radiometer 2 (AMSR2) winds are 6.5 and 4.8% higher than CCMP, while Advanced Scatterometer (ASCATB) is 0.8% lower. For extratropical cyclones, AMSR2 and SMAP also show stronger winds with a 5% difference, and ASCATB is about 0.3% weaker compared to CCMP. The comparison between SAR and CCMP for TC winds, sampled at the locations and time frames of SAR tiles, indicates that SAR winds around TCs are about 9% higher than CCMP winds. Using empirically defined TC structural indices, we find that the TCs observed by CCMP are shifted in locations and lack a compact core region. A Random Forest (RF) regressor was applied to TCs in CCMP with corresponding SAR observations, nearly correcting the full magnitude of low bias in CCMP statistically, with a 15 m/s correction in the core region. The hierarchy of importance among the predictors is as follows: CCMP wind speed (62%), distance of SAR pixels to the eye region (21%) and eye center (7%), and distance of CCMP pixels to the eye region (5%) and eye center (5%).

This work aims at investigating the effect of NO2 absorption on aerosol optical depth (AOD) and Ångström exponent (AE) retrievals of sun photometers by synergistic use of the accurate NO2 characterization for optical depth estimation from co-located ground-based measurements. The analysis was performed for ~7 years (2017–2023) at a global scale for the AOD and AE retrievals by Aerosol Robotic Network (AERONET) sun photometers which uses OMI (Ozone Monitoring Instrument) climatology for NO2 representation. The deviations in AOD and AE retrievals by NO2 absorption is accounted for using high-frequency columnar NO2 measurements by co-located Pandora spectroradiometer belonging to Pandonia Global Network (PGN). The AERONET retrieved AOD was found to be overestimated in half of the cases while also underestimated in other cases as an impact of the NO2 deviation from "real" (PGN NO2) values. Over or underestimations are relatively low. About one-third of these stations showed a mean deviation in NO2 and AOD (at 380 nm and 440 nm) above 0.5x10-4 mol-m-2 and 0.002, respectively, which can be considered as a systematic contribution to the uncertainties of AOD retrievals that are reported to be in the order of 0.01. However, under extreme NO2 loading scenarios (i.e., 10 % highest deviations), even higher AOD deviations were observed that were at the limit or higher than the reported 0.01 uncertainty of the AOD retrieval. The PGN NO2 based sensitivity analysis of AOD deviation suggested that for PGN NO2 varying between 2x10-4 and 8x10-4 mol-m-2, the median AOD differences were found to rise above 0.01 (even above 0.02) with the increase in NO2 threshold (i.e., the lower limit from 2 x10-4 mol-m-2 to 8 x10-4 mol-m-2). The AOD-derivative product, AE, was also affected by the NO2 correction (discrepancies between the AERONET OMI climatological representation of NO2 values and the real PGN NO2 measurements) on the spectral AOD. The normalized frequency distribution of AE (at 440–870 nm and 380–675 nm wavelength pair) was found to be narrower for broader AOD distribution for some stations and vice versa for other stations and a higher relative error at the shorter wavelength (among the wavelength pairs used for AE estimation) lead to a shift in the peak of the AE distribution towards a higher value. Finally, the AOD and AE trends were calculated based on the original AERONET AOD (based on AERONET OMI climatological NO2) according to the data availability and it was further signified the importance of having a correct (real) NO2 representation in AOD retrievals as it would possibly impact the respective trends. [ABSTRACT FROM AUTHOR]

This work introduces CAECENET, a new system capable of automatically retrieving columnar and vertically-resolved aerosol properties running the GRASP (Generalized Retrieval of Atmosphere and Surface Properties) algorithm using sun-sky photometer (aerosol optical depth, AOD; and sky radiance measurements) and ceilometer (range corrected signal; RCS) data as input. This method, so called GRASPpac, is implemented in CAECENET, which assimilates sun-sky photometers data from CÆLIS database and ceilometer data from ICENET database (Iberian Ceilometer Network). CAECENET allows for continuous and near-real-time monitoring of both vertical and columnar aerosol properties. The main characteristics and workflow of CAECENET are explained in detail. This work also explores the potential of CAECENET to monitor and analyze the evolution of transported aerosol events on a regional scale by means of the distribution of CAECENET stations across the Iberian Peninsula. As an example, this paper analyzes, using the CAECENET products, the case of a Saharan dust outbreak that occurred between the 3rd and 5th of October 2022. This was an intense event, with AOD at 440 nm values around 0.5 in Madrid and Valladolid, and reaching 1.55 in Granada. Transport from the Canadian wildfires at the end of June 2023 is also studied. Despite the long-range transport of the smoke particles in this event, measured volume concentrations reached and surpassed 80 μ m3/ μ m2 in some stations. The results obtained point to the utility of this CAECENET tool for analyzing changes in the height and speed of the event propagation, in the aerosol concentration, and how this affects the optical properties. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Vegetation health (VH) is a powerful characteristic for forecasting malaria incidence in regions where the disease is prevalent. This study aims to determine how vegetation health affects the prevalence of malaria and create seasonal weather forecasts using NOAA/AVHRR environmental satellite data that can be substituted for malaria epidemic forecasts. Methods: Weekly advanced very high-resolution radiometer (AVHRR) data were retrieved from the NOAA satellite website from 2009 to 2021. The monthly number of malaria cases was collected from the Ministry of Health of Benin from 2009 to 2021 and matched with AVHRR data. Pearson correlation was calculated to investigate the impact of vegetation health on malaria transmission. Ordinary least squares (OLS), support vector machine (SVM) and principal component regression (PCR) were applied to forecast the monthly number of cases of malaria in Northern Benin. A random sample of proposed models was used to assess accuracy and bias. Results: Estimates place the annual percentage rise in malaria cases at 9.07% over 2009–2021 period. Moisture (VCI) for weeks 19–21 predicts 75% of the number of malaria cases in the month of the start of high mosquito activities. Soil temperature (TCI) and vegetation health index (VHI) predicted one month earlier than the start of mosquito activities through transmission, 78% of monthly malaria incidence. Conclusions: SVM model D is more effective than OLS model A in the prediction of malaria incidence in Northern Benin. These models are a very useful tool for stakeholders looking to lessen the impact of malaria in Benin. [ABSTRACT FROM AUTHOR]

Absolute calibration of Earth observation (EO) sensors is key to ensuring long-term stability and interoperability, and it is essential for long-term global climate records and forecasts. The Moon provides a photometrically stable calibration source within the range of the Earth's radiometric levels and is free from atmospheric interference. However, to use this ideal calibration source, one must model the variation in its disc-integrated irradiance resulting from changes in Sun–Earth–Moon geometries. The Lunar Irradiance Model of the European Space Agency (LIME) is a new lunar irradiance model developed from ground-based observations acquired using a lunar radiometer operating from the Izaña Atmospheric Observatory near Mount Teide, located in Tenerife, Spain. Nightly top-of-atmosphere (TOA) irradiance is determined using the Langley plot method, and each observation is traceable to the international system of units (SI) through the radiometer calibration performed at the National Physical Laboratory (NPL). Approximately 590 lunar observations acquired between March 2018 and December 2022 currently contribute to the model parameter derivation, which builds on the widely used ROLO (Robotic Lunar Observatory) model analytical formulation. This paper presents the strategy used to derive LIME parameters: the characterisation of the lunar radiometer, the derivation of nightly top-of-atmosphere lunar irradiance and a description of the model parameter derivation, along with the associated metrologically rigorous uncertainty. The model output has been compared to PROBA-V, Pléiades and Sentinel-3B, as well as to the VITO implementation of the ROLO model. Initial results indicate that LIME predicts 3 %–5 % higher lunar-disc-integrated irradiance than the ROLO model for the visible and near-infrared channels. The model output has an expanded (k=2) radiometric uncertainty of ∼ 2 % at the lunar radiometer wavelengths, and it is expected that planned observations until at least 2024 further constrain the model parameters in subsequent updates. [ABSTRACT FROM AUTHOR]

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

A method for radiometer-noise generation and its software implementation in the form of a Python library module is proposed. The method can be used to simulate radiometer noise with variable component properties: Gaussian white noise and flicker noise (random drift) with a power spectrum linearly increasing with decreasing frequency. The method is based on the transformation of spectral properties of Gaussian noise via sequential filtering by a differentiator, nonlinear threshold switch, and subsequent integration. By changing the integrator accumulation time constant and the threshold level relative to noise intensity one can change the resulting form of the spectrum and the corresponding statistical parameters of the output noise over a wide range: from stationary white noise to noise dominated by a -type spectrum component. Empirical polynomial approximation formulas for the dependence of the spectral index of the resulting noise records on the nonlinear threshold switch level in the 0.0– interval are derived based on numerical simulations using a software implementation of the model. Examples of noise-record implementations, their spectra, and autocorrelation functions are demonstrated. The generated noise is shown to be similar to the noise observed on radio telescopes of the Institute of Applied Astronomy of the Russian Academy of Sciences. [ABSTRACT FROM AUTHOR]

The stratospheric airship is a type of aerostat that uses solar energy as its power source and can fly continuously for months or even years in near space. The rapid and accurate prediction of the output power of its solar array is the key to maintaining energy balance and extending flight time. This paper establishes an online learning model for predicting the output power of the solar array of stratospheric airships. The readings of radiometers arranged on the surface of the airship are used as features for training the model. The parameters of the model can be updated in real-time during the flight process without retraining the entire model. The effect of radiometer placement on the model accuracy was also analyzed. The results show that for the continuous flight of 40 days, the online learning model can achieve an accuracy of 88% after training with 10 days of flight data and the accuracy basically reaches its highest level after 20 days. In addition, placing the radiometers at the four corners of the array can achieve a higher prediction accuracy of 95%. The online model can also accurately identify and reflect the effect of module efficiency attenuation or damage and maintain high accuracy. [ABSTRACT FROM AUTHOR]

Ocean salinity is a pivotal aspect of the ocean dynamic environment. Spaceborne L-band radiometers, like SMOS, Aquarius, and SMAP, offer a comprehensive approach to mapping out large-scale ocean salinity patterns. As China prepares for the launch of the Chinese Ocean Salinity and Soil Moisture Mission (COSM), it is essential to delve into the intricacies of radio frequency interference (RFI) detection, localization, and mitigation. The L-band, in particular, is highly susceptible to RFI. COSM will carry not one but two advanced instruments: a 2-D L-band aperture synthesis microwave radiometer (LASMR) and a 1-D L-C-K band microwave imager combined active and passive (MICAP). This article delves into the current state of RFI research, particularly in recent years, and introduces a fusion method that integrates MICAP and LASMR for more accurate RFI detection, localization, and mitigation. This fusion method relies on an algorithm that constructs localization and intensity objective functions based on the principle of least squares. By optimizing these functions, we can pinpoint the precise location and intensity of RFI. The resulting minimum mitigation residual offers a blueprint for achieving optimal RFI detection, localization, and mitigation. The experimental results, achieved in a controlled anechoic chamber, confirm that this fusion method—when weighted by variance—boosts detection accuracy, refines localization precision, and minimizes residual mitigation errors compared with standalone MICAP or LASMR techniques. [ABSTRACT FROM AUTHOR]

Visible spectral radiometry of seawater, often referred to as ocean colour, from space, provides a synoptic view of surface phytoplankton, and other opticallyactive constituents, at high temporal resolution, that is unsurpassed by any other technology. Yet, in-situ observations of ocean colour are critical to the success of the satellite, tracking the calibration of the radiometers and validating atmospheric correction algorithms. Owing to the high cost of commercial field radiometers, as well as the high costs associated with ocean-based field work, ocean colour scientists are plagued by a sparsity of high quality in-situ radiometric observations, particularly in remote regions. In this perspective article, we highlight potential to increase the number of in-situ observations of ocean colour by harnessing superyachts. Using openly-available data processing software, we show that automated ocean colour data collected using a superyacht can be used for the validation of an ocean colour satellite, with comparable results to traditional validation studies. Reaching out to wealthy citizen scientists may help fill gaps in our ability to monitor the colour of the ocean. [ABSTRACT FROM AUTHOR]

The Tibet Plateau is known as the "third pole" of the world, and its environmental change profoundly impacts East Asia and even the global climate. HDO is the stable isotope of water vapor, which acts as an ideal tracer for studying the water cycle, and which is commonly used for atmospheric circulation and climatic studies. To monitor the water vapor isotopic abundance in the Tibetan Plateau, a portable laser heterodyne radiometer was operated in Golmud in August 2019. The radiometer utilizes a narrow-linewidth 3.66 μm distributed feedback interband cascade laser as the local oscillator, the heterodyne module is been optimized and the radiometer performs with high resolution and stability in obtaining spectral data. Furthermore, the absorption spectra of atmospheric HDO and H2O are obtained, and the retrieval method for water vapor isotopic abundance is discussed. The optimal estimation method is adopted to retrieve the density of HDO and H2O. The average column density of H2O was 1.22 g/cm2, and the HDO/H2O ratio in Golmud was 178 ± 15 × 10−6 during the observation. For a better understanding of the retrieval, the retrieval errors are analyzed and compared. The results indicate that the smoothing error is significantly higher than the measurement error in this work. The backward trajectory analysis of atmospheric transport is used to investigate the relationship between water vapor density and atmospheric motion. The results indicate that the variation of H2O column density and HDO/H2O ratio have a relationship with atmospheric movements. [ABSTRACT FROM AUTHOR]