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The international GEOTRACES program was developed to enhance knowledge about the distribution of trace elements and their isotopes (TEIs) in the ocean and to reduce the uncertainty about their sources, sinks, and internal cycling. Recognizing the importance of intercalibration from the outset, GEOTRACES implemented intercalibration efforts early in the program, and consensus materials were generated that included the full range of TEIs dissolved in seawater, in suspended particles, and from aerosols. The GEOTRACES section cruises include "crossover station(s)" that are occupied by two or more sections and whereby all aspects of sample collection, preservation, and processing can be compared and intercalibrated. Once data-sets are generated, an international intercalibration committee reviews intercalibration reports and works with the community to address issues and provide intercalibrated data for intermediate data products. This process has resulted in a highly cooperative community that shares advances in protocols to strengthen capacity building and GEOTRACES outcomes, including an unprecedented oceanic atlas of TEIs, with data quality that is state-of-the-art. This article outlines the development and implementation of the successful GEOTRACES intercalibration process. [ABSTRACT FROM AUTHOR]

The regional coverage satellite constellations are in demand for fulfilling earth observation needs of specific user regions of interest as opposed to global coverage thus enhancing the revisit period for the area. In this paper, we present a few key mission aspects of the regional coverage constellation designed and operated by the Indian Space Research Organization (ISRO) in low earth orbit. ISRO developed three X-Band Synthetic Aperture Radar (SAR) Earth Observation satellites and placed them in three inclined orbit planes to enhance the Indian region's coverage. This is India's first inclined orbit constellation designed for remote sensing applications in low earth orbit. The satellites were built around a standard bus carrying a Synthetic Aperture Radar payload with a deployable Radial Rib Antenna (RRA). They were designed to achieve a high agility capability. As SAR sensors are capable of all-weather, day, and night imaging; thus, most suitable in inclined orbits where the illumination conditions vary continuously for imaging. Though the inclined orbits provide more revisit opportunities to the region of interest, their characteristics pose challenges in mission design and operations. Though the mission design and planning involved a host of elements, this paper brings out the details of a few key mission analysis elements, planning aspects and operations that were critical in the course of various mission phases. The mission analysis included mission-specific requirements like launch windows selection for the constellation and reference attitude generation specific to inclined orbit geometry. Mission planning had to take care of Radial Rib Antenna (RRA) deployment requirements which were very critical for the mission, apart from taking care of individual subsystem requirements. The SAR payload data product quality and targeting accuracy are very sensitive to the satellite image point range (vis-a-vis SAR operation data window). Extensive post-launch calibration activity was carried out to meet all these mission requirements and data product specifications. The challenge was in fixing the payload beam alignment and fixing the uncertainties in onboard and ground computations. The paper also describes the methods of fixing all possible error sources affecting the high-resolution SAR payload performance. • The regional coverage satellite constellations are in demand for area targets coverage. • Inclined orbit constellations are more suitable for regional coverage using SAR sensors. • Mission operations plans need to consider all the specific requirements of spacecraft systems. • Pre-launch and post -launch calibrations of sensors is mandatory for achieving system performance. [ABSTRACT FROM AUTHOR]

Most anthropogenic carbon dioxide (CO2) emissions originate from urban areas. To improve understandings of urban and regional emissions, we design and construct a low-cost UAV coordinated carbon observation network (LUCCN) which uses mid-accuracy (±1 ppm) CO2 sensors. In this paper, we introduce our multi-variable non-linear regression method for calibrating the non-dispersive infrared (NDIR) CO2 sensors for LUCCN's ground stations. We tested our calibration method with concentration data collected at the Xinglong Atmospheric Background Observatory. With comparison against data simultaneously collected by a high-accuracy cavity ring-down spectrometer, we found the maximum standard deviation of LUCCN's sensors to be 0.782 ppm in a controlled laboratory environment with a 1-second window size and 0.53 ppm in an outdoor environment with a 1-hour running average window size. As validation of LUCCN's ground measurements, we identify and present consistent trends between local CO2 concentration variations and aerosol pollution events captured by the space-based moderate resolution imaging spectrometer (MODIS). [ABSTRACT FROM AUTHOR]

The powertrain efficiency of most small unmanned air vehicles (SUAVs) depend on the aerodynamic performance of multiple propellers, which must be modelled before its optimisation. To predict propeller performance while capturing interaction effects not accountable for by momentum theories, the Virtual Blade Model (VBM) can be used at much lower costs than conventional Computational Fluid Dynamics (CFD). However, the accuracy of VBM depends on aerofoil polar data that often misrepresent rotational and three-dimensional effects that influence small propellers. In an attempt to expand the capabilities of VBM, it is a common practice to introduce correction models for aerofoil coefficients in its formulation, but the actual effectiveness of such approach for small propeller analysis remains unassessed. In this paper, VBM in OpenFOAM was extended with stall delay and tip loss models, while aerodynamic databases at low Reynolds numbers were built with XFOIL and extrapolated to the full angle of attack range. The accuracy of three VBM versions was validated against wind tunnel measurements of two off-the-shelf small propellers. For the lower-pitch propeller, thrust and power at low advance ratios and efficiency at high advance ratios were significantly improved by the stall delay model. But for the higher-pitch propeller, thrust and power were overpredicted with extended versions of VBM under most operating conditions, which is attributable to an excessive shift of effective angles of attack to the post-stall region by the stall delay model and to uncertainties in extrapolated polar data. The results suggest that without reliable procedures for obtaining polar data, correction models should be implemented in VBM only for the simulation of low-pitch propellers operating at low advance ratios, given their avoidance of the effective angle of attack range where XFOIL and extrapolation methods are mainly expected to fail in predicting lift behaviour. • Stall delay and tip loss models are implemented into VBM, a coupled BET-CFD model. • Small propeller performance is more sensitive to stall delay than it is to tip losses. • At lower advance ratios, thrust and power results are improved by the enhanced VBM. • Unreliable post-stall data inputs into the enhanced VBM cause power overprediction. [ABSTRACT FROM AUTHOR]

Annona squamosa (AS) and Cinnamomum tamala (CT) leaves have been used traditionally and have well reported various pharmacological activities which justify their topical use. But the majority of compounds present are phenolic compounds which due to their polar nature are unable to permeate through the skin. Therefore, polyherbal phytosomes of ethanolic extracts of AS and CT were combined in a ratio of 1:1 to get polyherbal Ethanolic extract (PHEE) and polyherbal phytosomes (PHP) were prepared and optimized using Response Surface methodology by applying Central Composite design (CCD) for studying the effect of drug soya lecithin ratio and speed of rotation on responses like vesicle size and entrapment efficiency. Followed by numerical optimization, PHP with vesicle size of 215.5 ± 0.45 nm and Entrapment efficiency of 85.24 ± 0.05% were obtained. These PHP were characterized with FTIR, DSC, SEM and XRD. The PHP showed % cumulative drug release of 84.22 ± 5.62%. For easy application on the skin these phytosomes were incorporated in Carbopol 934 gel matrix and evaluated for physical appearance, pH, viscosity and drug content. The ex vivo permeation of the phytosomal gel (PG) was compared with a conventional gel containing PHEE. A significant improvement in permeation was observed in case of PG with 36.62 ± 3.33 µg/cm2 of drug permeated in 24 hours whereas 17.06 ± 1.54 µg/cm2 through the conventional gel. The PHP and PG were found stable during stability studies for six months. Polyherbal phytosomal gel can be a good carrier for herbal extracts for topical delivery. [ABSTRACT FROM AUTHOR]

The Ozone Monitoring Suite-Nadir (OMS-N) instrument is the first hyperspectral remote sensor in the ultraviolet band of China's Fengyun series satellites. It can be used to detect several kinds of atmospheric constituents. This paper describes the prelaunch spectral calibration of the OMS-N onboard FengYun 3F. Several critical spectral parameters including the spectral resolution, spectral dispersion, and the instrument spectral response function were determined through laser-based measurements. A secondary peak of the instrument spectral response function from the short wavelength side of the ultraviolet band was found, and the possible influence on data applications was analyzed using a reference solar model and radiative transfer model. The results indicate that the spectral resolution and spectral accuracy of OMS-N meet the mission requirements. However, the asymmetries in the instrument spectral response function in the ultraviolet band were found near nadir rows, which are expressed as the "asymmetric central peak" and "secondary peak". The analysis results show that if the influences of the instrument spectral response function "asymmetric central peak" and "secondary peak" in the ultraviolet band are ignored, they will bring an error as large as 5% at the center of the absorption line. [ABSTRACT FROM AUTHOR]

We study some properties of the nonembeddable polar spaces related to octonion division rings (and related to the index E 7 , 3 28). More exactly, we classify its subspaces and show that its generating rank is equal to 5, whereas it was always believed to be at least 6. We also study self-projectivities of length 3 in the maximal singular subspaces, and these turn out to be polarities of octonion projective planes. We establish a connection between the conjugacy classes of such polarities and the orbits of the collineation group of the polar space on triples of opposite singular planes. Along the way, we classify all polar spaces for which each self-projectivity of length 3 in a maximal singular subspace is a polarity. [ABSTRACT FROM AUTHOR]

The efficiency of high-power operation of multiple quantum well (QW) light emitting diodes (LEDs) to a large degree depends on the realization of uniform hole distribution between the QWs. In long wavelength InGaN/GaN QW LEDs, the thermionic interwell hole transport is hindered by high GaN barriers. However, in polar LED structures, these barriers may be circumvented by the lateral hole injection via semipolar 10 1 ¯ 1 QWs that form on the facets of V-defects. The efficiency of such carrier transfer depends on the transport time since transport in the semipolar QWs is competed by recombination. In this work, we study the carrier transfer from the semipolar to polar QWs by time-resolved photoluminescence in long wavelength (green to red) LEDs. We find that the carrier transfer through the semipolar QWs is fast, a few tens of picoseconds with the estimated room temperature ambipolar diffusion coefficient of ∼5.5 cm2/s. With diffusion much faster than recombination, the hole transport from the p-side of the structure to the polar QWs should proceed without a substantial loss, contributing to the high efficiency of long wavelength GaN LEDs. [ABSTRACT FROM AUTHOR]

Two‐dimensional (2D) material photodetectors have gained great attention as potential elements for optoelectronic applications. However, the linearity of the photoresponse is often compromised by the carrier interaction, even in 2D photodiodes. In this study, a new device concept of dual‐floating van der Waals heterostructures (vdWHs) photodiode is presented by employing ambipolar MoTe2 and n‐type MoS2 2D semiconductors. The presence of type II heterojunctions on both sides of channel layers effectively depletes carriers and restricts the photocarrier trapping within the channel layers. As a result, the device exhibits robust linear photoresponse under photovoltaic mode from the visible (405 nm) to near‐infrared (1600 nm) band. With the built‐in electric field of the vdWHs, a linear dynamic range of ≈100 dB, responsivity of ≈1.57 A W−1, detectivity of ≈4.28 × 1011 Jones, and response speed of ≈30 µs are achieved. The results showcase a promising device concept with excellent linearity toward fast and low‐loss detection, high‐resolution imaging, and logic optoelectronics. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) models were developed to determine the center of tropical cyclones (TCs) in the western North Pacific. These models integrated information from six channels of geostationary satellite imagery: the brightness temperature of four infrared (IR) and one shortwave IR channels, as well as the reflectivity of one visible channel. The first model is a convolutional neural network designed for spatial data processing, and the second is a convolutional long short-term memory model that effectively captures spatiotemporal information. For training, verification, and testing purposes, spatial images from six channels were obtained from the Japanese Himawari-8 satellite from 2016 to 2021. The position of the European Centre for Medium-Range Weather Forecasts 6- or 12-h prediction was assigned as an initial value to the AI models. Errors in the initial value were 20–50 km compared to the Joint Typhoon Warning Center best track, depending on TC intensity. Weak (strong) TCs exhibited large (small) errors. This error dependency was found in Automated Rotational Center Hurricane Eye Retrieval (ARCHER) product, which is currently used by several operational organizations. ARCHER errors were typically small when observations from both geostationary and polar-orbiting satellites were included. Significant errors remained in the absence of microwave channel information from polar-orbiting satellites. This study successfully developed two AI models that consistently determined the location of the TC center using only six-channel images from geostationary satellites. These models exhibited comparable or better performance than the ARCHER products. The newly developed AI models can potentially be implemented for operational use. SIGNICANCE STATEMENT: This study has developed AI models that can determine the center of TCs in the western North Pacific, which can be applied to meteorological organizations that have limited access to real-time polar-orbiting satellite data. The newly developed AI models derived positions comparable to or better than ARCHER, which is currently one of the most precise systems for determining the position of the TC center. The successful development of these AI models is very opportune as it was only possible thanks to the recent availability of high-frequency data observed from geostationary satellite, coupled with the rapid technological advances in AI algorithms. [ABSTRACT FROM AUTHOR]

Inland and coastal environments are complex ecosystems composed of suspended and dissolved materials, affecting light propagation within the water column. Satellite-based water quality research relies on water optical properties provided by optical sensors on board of polar orbit satellites since the 1980's. Specifically, Geostationary (GEO) ocean colour satellites offer high temporal resolution (e.g. every 15-minute observations), moderate spatial resolution (0.5–1 km) at regional scale, making them a promising alternative to polar orbiting satellites for near-continuous monitoring of highly dynamic aquatic ecosystems. This literature review examines the evolution of geostationary satellite technology and its applications in monitoring inland and coastal waters. A summary of the most relevant studies using geostationary sensors is provided for key water quality indicators such as chlorophyll-a and algal organisms, total suspended solids, and turbidity. Also, geostationary missions were well-detailed, with their available sensors and characteristics. Although this research topic is still incipient, recent studies have demonstrated the potential of GEO multi-spectral observations in understanding sub-daily water quality patterns. Notably, most research studies have focused on Asia, suggesting unexplored opportunities globally. Advanced Himawari Imager (AHI) and Geostationary Ocean Colour Imager (GOCI) have been used to improve water quality estimates, and inherent challenges were documented, such as algorithm validation, limited spatial resolution, and high volume of images and auxiliary files to be managed. The opportunities for new studies range from algorithm development for atmospheric correction, cloud masking, and bidirectional reflectance corrections to inter-comparison with existing sun-synchronous satellites. Geostationary satellites are promising avenues for future research on near-continuous monitoring of inland and coastal water resources. [ABSTRACT FROM AUTHOR]

Coastal levees play a role in protecting coastal areas from storm surges and high waves, and they provide important input information for inundation damage simulations. However, coastal levee data with uniformity and sufficient accuracy for inundation simulations are not always well developed. Against this background, this study proposed a method to extract coastal levees by inputting high spatial resolution optical satellite image products (RGB images, digital surface models (DSMs), and slope images that can be generated from DSM images), which have high data availability at the locations and times required for simulation, into a deep learning model. The model is based on U-Net, and post-processing for noise removal was introduced to further improve its accuracy. We also proposed a method to calculate levee height using a local maximum filter by giving DSM values to the extracted levee pixels. The validation was conducted in the coastal area of Ibaraki Prefecture in Japan as a test area. The levee mask images for training were manually created by combining these data with satellite images and Google Street View, because the levee GIS data created by the Ibaraki Prefectural Government were incomplete in some parts. First, the deep learning models were compared and evaluated, and it was shown that U-Net was more accurate than Pix2Pix and BBS-Net in identifying levees. Next, three cases of input images were evaluated: (Case 1) RGB image only, (Case 2) RGB and DSM images, and (Case 3) RGB, DSM, and slope images. Case 3 was found to be the most accurate, with an average Matthews correlation coefficient of 0.674. The effectiveness of noise removal post-processing was also demonstrated. In addition, an example of the calculation of levee heights was presented and evaluated for validity. In conclusion, this method was shown to be effective in extracting coastal levees. The evaluation of generalizability and use in actual inundation simulations are future tasks. [ABSTRACT FROM AUTHOR]

This work presents the development of the MethaneAIR Level0–Level1B processor, which converts raw L0 data to calibrated and georeferenced L1B data. MethaneAIR is the airborne simulator for MethaneSAT, a new satellite under development by MethaneSAT LLC, a subsidiary of the Environmental Defense Fund (EDF). MethaneSAT's goals are to precisely map over 80 % of the production sources of methane from oil and gas fields across the globe to an accuracy of 2–4 ppb on a 2 km 2 scale. Efficient algorithms have been developed to perform dark corrections, estimate the noise, radiometrically calibrate data, and correct stray light. A forward model integrated into the L0–L1B processor is demonstrated to retrieve wavelength shifts during flight accurately. It is also shown to characterize the instrument spectral response function (ISRF) changes occurring at each sampled spatial footprint. We demonstrate fast and accurate orthorectification of MethaneAIR data in a three-step process: (i) initial orthorectification of all observations using aircraft avionics, a simple camera model, and a medium-resolution digital elevation map; (ii) registration of oxygen (O 2) channel grayscale images to reference Multispectral Instrument (MSI) band 11 imagery via Accelerated-KAZE (A-KAZE) feature extraction and linear transformation, with similar co-registration of methane (CH 4) channel grayscale images to the registered O 2 channel images; and finally (iii) optimization of the aircraft position and attitude to the registered imagery and calculation of viewing geometry. This co-registration technique accurately orthorectifies each channel to the referenced MSI imagery. However, in the pixel domain, radiance data for each channel are offset by almost 150–200 across-track pixels (rows) and need to be aligned for the full-physics or proxy retrievals where both channels are simultaneously used. We leveraged our orthorectification tool to identify tie points with similar geographic locations in both CH 4 and O 2 images in order to produce shift parameters in the across-track and along-track dimensions. These algorithms described in this article will be implemented into the MethaneSAT L0–L1B processor. [ABSTRACT FROM AUTHOR]

The Temporal Experiment for Storms and Tropical Systems Demonstration (TEMPEST-D) demonstrated the capability of CubeSat satellites to provide high-quality, stable microwave signals for estimating water vapor, clouds, and precipitation from space. Unlike the operational NOAA and MetOp series satellites, which combine microwave and hyperspectral infrared sensors on the same platforms to optimize retrievals, CubeSat radiometers such as TEMPEST do not carry additional sensors. In such cases, the high temporal and spatial resolution and multi-channel measurements from the Advanced Baseline Imager (ABI) on the next-generation series of Geostationary Operational Environmental Satellites (GOES-R) are ideal for assisting these smaller, stand-alone radiometers. Based on sensitivity tests, the water vapor retrievals from TEMPEST are improved by adding water-vapor-sounding channels at 6.2, 6.9, and 7.3 mm from ABI, which help to increase the vertical resolution of soundings and reduce retrieval errors. Under clear sky conditions, retrieval biases and root-mean-square errors improve by approximately 10 %, while under cloudy skies, biases remain unchanged but root-mean-square errors still decrease by 5 %. Humidity soundings are also validated using coastal radiosonde data from the Integrated Global Radiosonde Archive (IGRA) from 2019 to 2020. When ABI indicates clear skies, water vapor retrievals improve somewhat by decreasing the overall bias in the microwave only estimate by roughly 10 %, although layer root-mean-square errors remain roughly unchanged at 1 g/kg when three ABI channels are added. When ABI indicates cloudy conditions, there is little change in the results. The small number of matched radiosondes may limit the observed improvement. [ABSTRACT FROM AUTHOR]

Intelligent vehicles are constrained by road, resulting in a disparity between the assumed six degrees of freedom (DoF) motion within the Visual Simultaneous Localization and Mapping (SLAM) system and the approximate planar motion of vehicles in local areas, inevitably causing additional pose estimation errors. To address this problem, a stereo Visual SLAM system with road constraints based on graph optimization is proposed, called RC-SLAM. Addressing the challenge of representing roads parametrically, a novel method is proposed to approximate local roads as discrete planes and extract parameters of local road planes (LRPs) using homography. Unlike conventional methods, constraints between the vehicle and LRPs are established, effectively mitigating errors arising from assumed six DoF motion in the system. Furthermore, to avoid the impact of depth uncertainty in road features, epipolar constraints are employed to estimate rotation by minimizing the distance between road feature points and epipolar lines, robust rotation estimation is achieved despite depth uncertainties. Notably, a distinctive nonlinear optimization model based on graph optimization is presented, jointly optimizing the poses of vehicle trajectories, LPRs, and map points. The experiments on two datasets demonstrate that the proposed system achieved more accurate estimations of vehicle trajectories by introducing constraints between the vehicle and LRPs. The experiments on a real-world dataset further validate the effectiveness of the proposed system. [ABSTRACT FROM AUTHOR]

Recent polar motion data do not show a 6-year beat and indicate the absence of the Chandler wobble (CW), whereas we could observe the 6-year beat even in the 1920-40 s when the CW amplitude was known to be smallest. As a free mode, the CW needs excitation one or more sources that were debated decades ago but are now attributed to the atmosphere, ocean, and possibly land water. Here, we show that the anomaly started in 2015, after which two independent estimates of the atmospheric CW excitation became persistently smaller than before. However, the estimates of the oceanic and land–water contributions are too large, suggesting improved estimates are needed. Taking advantage of the recent CW anomaly, we show that the quality factor of CW is not as high as 100 as previously preferred. Although the CW excitation processes have been assumed random, a termination of near-resonant processes would rather be consistent with the present findings. [ABSTRACT FROM AUTHOR]

Surface net radiation (SNR) is a vital input for many land surface and hydrological models. However, most of the current remote sensing datasets of SNR come mostly at coarse resolutions or have large gaps due to cloud cover that hinder their use as input in models. Here, we present a downscaled and continuous daily SNR product across Europe for 2018–2019. Long-wave outgoing radiation is computed from a merged land surface temperature (LST) product in combination with Meteosat Second Generation emissivity data. The merged LST product is based on all-sky LST retrievals from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard the geostationary Meteosat Second Generation (MSG) satellite and clear-sky LST retrievals from the Sea and Land Surface Temperature Radiometer (SLSTR) onboard the polar-orbiting Sentinel-3A satellite. This approach makes use of the medium spatial (approx. 5–7 km) but high temporal (30 min) resolution, gap-free data from MSG along with the low temporal (2–3 d) but high spatial (1 km) resolution of the Sentinel-3 LST retrievals. The resulting 1 km and daily LST dataset is based on an hourly merging of both datasets through bias correction and Kalman filter assimilation. Short-wave outgoing radiation is computed from the incoming short-wave radiation from MSG and the downscaled albedo using 1 km PROBA-V data. MSG incoming short-wave and long-wave radiation and the outgoing radiation components at 1 km spatial resolution are used together to compute the final daily SNR dataset in a consistent manner. Validation results indicate an improvement of the mean squared error by ca. 7 % with an increase in spatial detail compared to the original MSG product. The resulting pan-European SNR dataset, as well as the merged LST product, can be used for hydrological modelling and as input to models dedicated to estimating evaporation and surface turbulent heat fluxes and will be regularly updated in the future. The datasets can be downloaded from 10.5281/zenodo.8332222 and 10.5281/zenodo.8332128. [ABSTRACT FROM AUTHOR]

The human body must stay within a certain temperature range for comfort and safety. However, challenges for thermoregulatory clothing exist for harsh application scenarios, such as full day/night cycles, frigid polar regions, and space travel. We developed a flexible and sustainable personal thermoregulatory clothing system by integrating a flexible organic photovoltaic (OPV) module to directly acquire energy from sunlight and bidirectional electrocaloric (EC) devices. The flexible OPV-EC thermoregulatory clothing (OETC) can extend the human thermal comfort zone from 22°–28°C to 12.5°–37.6°C with a fast thermoregulation rate. The low energy consumption and high efficiency of the EC device allows for 24 hours of controllable and dual-mode thermoregulation with 12 hours of sunlight energy input. This self-powered wearable thermoregulatory platform has a simple structure, compact design, high efficiency, and strong self-adaptability with sunlight as the sole energy source. [ABSTRACT FROM AUTHOR]

The results of observations of low-altitude spacecraft crossing the daytime sector of the auroral zone and of high-apogee spacecraft in the equatorial plane of the magnetosphere were analyzed in order to identify the main processes leading to the formation of dayside polar cusps. Observations from the DMSP F7 spacecraft were used to analyze the latitudinal characteristics of ion precipitation in the cusp region and to study the latitudinal profile of ion pressure in the cusp depending on the IMF parameters. A significant difference was found in identifying the cusp boundaries using an automated data processing system and direct analysis of spacecraft observations. It is shown that for small negative values of the Bz-component of the IMF (〈Bz〉 = –3.0 nT), an ordinary feature of the cusp is the latitudinal profile of the ion pressure (Pi) with a width of ~1° of latitude with two maxima, one of which is located in the equatorward and the other in the poleward of the cusp. For large negative Bz values (–6, –8 nT), the polar maximum in the latitudinal profile Pi disappears; only the equatorial maximum remains, the Pi level at the maximum increases, and the width of the cusp decreases to ~0.7°. For Bz IMF > 0, the most characteristic is the Pi profile with a maximum ion pressure in the polar part of the cusp. The cusp for Bz > 0 is located at higher latitudes than for Bz < 0, and its average latitudinal width increase to ~1.4° of latitude. In the prenoon sector MLT, the most typical for periods with a large negative By-component of the IMF (〈By〉 = –6.3 nT, 〈Bz〉 = –1.7 nT) is a cusp with a width of ~1.4° of latitude with a flat top in the latitudinal Pi profile. Comparison of the pressure distributions observed at low heights with data from high-apogee satellites confirmed the possibility of describing the formation of the cusp as a diamagnetic cavity and using observations in the cusp to determine the ion pressure in the magnetosheath. [ABSTRACT FROM AUTHOR]

With the increased availability of multi-view satellite images, the number of investigations on 3D urban scene reconstruction from multiple satellite images is also increasing. Conventional Multi-View Stereo (MVS) pipelines require the calibrated pose information of the satellite cameras to determine the epipolar geometry and the 3D structure of the stereo correspondences. In this study, we propose a novel Monocular Height estimation and Fusion (MHF) method for 3D reconstruction from uncalibrated multi-view satellite images. By employing a learned monocular depth network, the proposed method first obtains the height map of each satellite image. Second, all height maps obtained from the multi-view images are fused to a refined height map in each image plane. To fuse the height maps, all maps are affine transformed to a virtual reference coordinate system and the transformed maps are then projected to the image plane of each camera coordinate system. The monocular depth network was trained and evaluated on the Data Fusion Contest 2019 (DFC19) dataset including Jacksonville, FL, and Omaha, NE. We also evaluate the ATL-SN4 dataset covering Atlanta, GA to test on untrained new urban scenes. [ABSTRACT FROM AUTHOR]

The polar field reversal is a crucial process in the cyclic evolution of the large-scale magnetic field of the Sun. Various important characteristics of a solar cycle, such as its duration and strength, and also the cycle predictability, are determined by the polar field reversal time. While the regular measurements of solar magnetic field have been accumulated for more than half a century, there is no consensus in the heliophysics community concerning the interpretation of the Sun's polar field measurements and especially the determination of polar field reversal time. There exists a severe problem of non-reproducibility in the reported results even from studies of the same observational data set, and this causes an obstacle to make more accurate forecasts of solar cycle. Here, we analyze the solar magnetograms from four instruments for the last four cycles, to provide a more correct interpretation of the polar field observations and to find more accurate time of the reversals. We show the absence of triple (multiple) reversals in Cycles 21–24, significant variations in the time interval between reversals in the hemispheres and in the time interval between a reversal and a cycle beginning. In order to understand the origin of the reversal time variation, we perform Surface Flux Transport (SFT) simulations and find out that the presence of the 'anomalous' bipolar magnetic regions (BMRs) in different phases of a cycle can cause cycle-to-cycle variations of the reversal time within the similar range found in observations. [ABSTRACT FROM AUTHOR]

The atmospheric environment monitoring satellite DQ-1 was launched in April 2022, which consists of a spaceborne High Spectral Resolution Lidar (HSRL) system. This new system enables the accurate measurements of global aerosol optical properties, which can be used in Geo-scientific community after the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) retirement. Developing a suitable retrieval algorithm and validating retrieved results are prominently needed. This research demonstrates a retrieval algorithm for aerosol optical properties using the DQ-1 HSRL system. This method has retrieved the aerosol depolarization ratio, backscatter coefficient, extinction coefficient, and optical depth. For validation purposes, we compared retrieved results with those obtained through CALIPSO. The results have shown a continuous profile alignment between the two datasets, with DQ-1 describing an improved signal-to-noise ratio of approximately 10 dB. Optical property profiles from NASA Micro Pulse Lidar NETwork (MPLNET) stations were selected for validation with the DQ-1 measurements, resulting in a relative error of 25%. Between June 2022 and December 2022, aerosol optical depth measurements using the DQ-1 satellite and the AErosol RObotic NETwork (AERONET) were correlated and yielded a value of R2 0.803. We use the DQ-1 dataset to initially investigate the transport processes of the Saharan dust and the South Atlantic volcanic ash. These validations and applications show that the DQ-1 HSRL system can accurately measure global aerosols and holds significant prospects for earth science applications. [ABSTRACT FROM AUTHOR]

Rapid provision of Earth orientation parameters (EOPs, here polar motion and dUT1) is indispensable in many geodetic applications and also for spacecraft navigation. There are, however, discrepancies between the rapid EOPs and the final EOPs that have a higher latency but the highest accuracy. To reduce these discrepancies, we focus on a data‐driven approach, present a novel method named ResLearner, and use it in the context of deep ensemble learning. Furthermore, we introduce a geophysically constrained approach for ResLearner. We show that the most important geophysical information to improve the rapid EOPs is the effective angular momentum functions of atmosphere, ocean, land hydrology, and sea level. In addition, semidiurnal, diurnal, and long‐period tides coupled with prograde and retrograde tidal excitations are important features. The influence of some climatic indices on the prediction accuracy of dUT1 is discussed, and El Niño Southern Oscillation is found to be influential. We developed an operational framework, providing the improved EOPs on a daily basis with a prediction window of 63 days to fully cover the latency of final EOPs. We show that under the operational conditions and using the rapid EOPs of the International Earth Rotation and Reference Systems Service (IERS), we achieve improvements as high as 60%, thus significantly reducing the differences between rapid and final EOPs. Furthermore, we discuss how the new final series IERS 20 C04 is preferred over 14 C04. Finally, we compare against EOP hindcast experiments of the European Space Agency, on which ResLearner presents comparable improvements. Plain Language Summary: The International Earth Rotation and Reference Systems Service (IERS) provides rapid Earth orientation parameters (EOPs) using different space‐geodetic techniques to bridge the latency of the final, most accurate EOPs solution. However, these rapid EOPs are not in full agreement with the final EOPs. In order to reduce the differences between the rapid and final EOPs, we focus on the application of machine learning and present a novel method named ResLearner, which is based on geodetic data and geophysical constraints. We present the method in the context of deep ensemble learning, focusing on a prediction window of 63 days. We also attempt to link informative geophysical effects to these discrepancies. We show that they are linked to a mixture of atmospheric, oceanic, hydrological, and sea level effective angular momentum functions, dominance of the Global Navigation Satellite Systems‐derived polar motion, and various short‐ and long‐term tidal excitations. El Niño Southern Oscillation is also relevant for dUT1 prediction. The methodology can provide significant improvements of up to 60% in operational settings with respect to rapid EOPs provided by IERS. Additional validation is done by using the data of Jet Propulsion Laboratory final EOP series and also EOP series provided by the European Space Agency. Key Points: We introduce a novel machine learning algorithm named ResLearner to improve the accuracy of rapid and predicted Earth orientation parameters (EOPs)We also present geophysically constrained ResLearner, using Earth's effective angular momentum functions, tides, and climatic indicesBesides prediction, ResLearner is also able to effectively correct deficits in rapidly processed EOPs with respect to final EOPs [ABSTRACT FROM AUTHOR]

Over the past 20 years, the Gravity Recovery and Climate Experiment (GRACE), and its successor mission, GRACE‐Follow On (GRACE‐FO) have made significant contributions to time‐variable gravity field modeling. A Chinese low‐low satellite‐to‐satellite tracking gravimetry mission (i.e., Chinese future gravimetry mission) has been confirmed to be selected as the polar‐orbiting satellite gravimetry mission for China, because of the capability to collect gravity data globally. However, the analysis of potential contributions to geosciences from GRACE‐FO coupling with the Chinese future gravimetry mission is still limited. This study combines GRACE‐FO and Chinese future gravimetry missions as the Dual GRACE‐like Polar satellite Constellation (DGPC). By carefully choosing the initial orbit parameters of the Chinese future gravimetry mission with the differential evolution algorithm, the DGPC is expected to mitigate the temporal aliasing effects by improving the temporal resolution of time‐variable gravity solutions (i.e., 1‐day and 3‐day solutions). Regarding the spectral‐domain evaluation, zonal, tesseral, and sectorial coefficients estimated by the DGPC show approximately 6.01%–13.42% noise reductions compared with GRACE‐FO. Regarding the spatial‐domain evaluation, the DGPC can suppress noises of about 39.44% and 31.12% in annual amplitude and long‐term trend, respectively. On this basis, this paper analyzes the effectiveness of the DGPC in potential contributions to geosciences (e.g., hydrology, glaciology, and seismology). Specifically, the DGPC can improve accuracy by about 36.96%, 25.85%, and 33.16% with respect to GRACE‐FO for signals in the subhumid basin, signals of ice‐sheet mass balance over Greenland, and coseismic displacement of the fault zone, respectively. In general, the potential capability for high‐frequency signals recovery of the DGPC would facilitate contributions of satellite gravimetry to geosciences. Plain Language Summary: The Gravity Recovery And Climate Experiment (GRACE) mission and its successor GRACE Follow On (GRACE‐FO) have made significant contributions to time‐variable gravity field modeling. A polar gravity satellite mission (i.e., Chinese future gravimetry mission) has been confirmed to be selected as the polar‐orbiting satellite gravimetry mission for China because of its capability to collect gravity data globally. Including the GRACE‐FO mission, it is expected that there will be two polar pairs of gravity satellites (i.e., dual GRACE‐like polar satellite constellation) simultaneously within the next few years. What can we expect from the dual GRACE‐like polar satellite constellation? In this study, we introduce an optimization algorithm (i.e., differential evolution algorithm) to carefully choose the initial orbit parameters of the Chinese future gravimetry mission. The dual GRACE‐like polar satellite constellation has been demonstrated to have the potential to mitigate the temporal aliasing effects of time‐variable gravity solutions. It is found that the dual GRACE‐like polar satellite constellation can improve accuracy by about 36.96%, 25.85%, and 33.16% with respect to GRACE‐FO for signals in the subhumid basin, signals of ice‐sheet mass balance over Greenland, and coseismic displacement of the fault zone, respectively. The temporal improvement of Earth's mass transport estimated by coupling GRACE‐FO with a Chinese polar gravity satellite mission would facilitate contributions of satellite gravimetry to geosciences. Key Points: This paper introduces the differential evolution algorithm into the design of the dual Gravity Recovery And Climate Experiment (GRACE)‐like polar satellite constellationImproving the temporal resolution of time‐variable gravity solutions can potentially contribute to mitigating the temporal aliasing effectsThe dual GRACE‐like polar satellite constellation has high‐frequency signal recovery capabilities and stimulates potential contributions to geosciences [ABSTRACT FROM AUTHOR]

It remains challenging to accurately classify complicated clouds owing to the various types of clouds and their distribution on multiple layers. In this paper, multi-band radiation information from the geostationary satellite Himawari-8 and the cloud classification product of the polar orbit satellite CloudSat from June to September 2018 are investigated. Based on sample sets matched by two types of satellite data, a random forest (RF) algorithm was applied to train a model, and a retrieval method was developed for cloud classification. With the use of this method, the sample sets were inverted and classified as clear sky, low clouds, middle clouds, thin cirrus, thick cirrus, multi-layer clouds and deep convection (cumulonimbus) clouds. The results indicate that the average accuracy for all cloud types during the day is 88.4%, and misclassifications mainly occur between low and middle clouds, thick cirrus clouds and cumulonimbus clouds. The average accuracy is 79.1% at night, with more misclassifications occurring between middle clouds, multi-layer clouds and cumulonimbus clouds. Moreover, Typhoon Muifa from 2022 was selected as a sample case, and the cloud type (CLT) product of an FY-4A satellite was used to examine the classification method. In the cloud system of Typhoon Muifa, a cumulonimbus area classified using the method corresponded well with a mesoscale convective system (MCS). Compared to the FY-4A CLT product, the classifications of ice-type (thick cirrus) and multi-layer clouds are effective, and the location, shape and size of these two varieties of cloud are similar. [ABSTRACT FROM AUTHOR]

The Gaofen-1 satellite is equipped with four wide-field-of-view (WFV) instruments, enabling an impressive spatial resolution of 16 m and a combined swath exceeding 800 km. These WFV images have shown their valuable applications across diverse fields. However, achieving accurate radiometric calibration is an essential prerequisite for establishing reliable connections between satellite signals and biophysical, as well as biochemical, parameters. However, observations with large viewing angles (>20°) pose new challenges due to the bidirectional reflectance distribution function (BRDF) effect having a pronounced impact on the accuracy of cross-radiation calibrations, especially for the off-nadir WFV1 and WFV4 cameras. To overcome this challenge, a novel approach was introduced utilizing the combined observations from the Gaofen-1 and Gaofen-6 satellites, with Landsat-8 OLI serving as a reference sensor. The key advantage of this synergistic observation strategy is the ability to obtain a greater number of image pairs that closely resemble Landsat-8 OLI reference images in terms of geometry and observation dates. This increased availability of matching images ensures a more representative dataset of the observation geometry, enabling the derived calibration coefficients to be applicable across various sun–target–sensor geometries. Then, the geometry angles and bidirectional reflectance information were put into a Particle Swarm Optimization (PSO) algorithm incorporating radiative transfer modeling. This PSO-based approach formulates cross-calibration as an optimization problem, eliminating the reliance on complex BRDF models and satellite-based BRDF products that can be affected by cloud contamination. Extensive validation experiments involving satellite data and in situ measurements demonstrated an average uncertainty of less than eight percent for the proposed cross-radiation calibration scheme. Comparisons of top-of-atmosphere (TOA) results calibrated using our proposed scheme, the previous traditional radiative transfer modeling using MODIS BRDF products for BRDF correction (RTM-BRDF) method, and official coefficients reveal the superior accuracy of our method. The proposed scheme achieves a 36.99% decrease in root mean square error (RMSE) and a 38.13% increase in mean absolute error (MAE) compared to official coefficients. Moreover, it achieves comparable accuracy to the RTM-BRDF method while eliminating the need for MODIS BRDF products, with a decrease in RMSE exceeding 14% for the off-nadir WFV1 and WFV4 cameras. The results substantiate the efficacy of the proposed scheme in enhancing cross-calibration accuracy by improving image match-up selection, efficiently removing BRDF effects, and expanding applicability to diverse observation geometries. [ABSTRACT FROM AUTHOR]

The on-orbit radiometric calibration is a fundamental task in quantitative remote sensing applications. A widely used calibration method is the cross-calibration based on Simultaneous Nadir Observation (SNO), which involves using high-precision reference instruments to calibrate lower-precision onboard instruments. However, despite efforts to match the observation time, spatial location, field geometry, and instrument spectra, errors can still be introduced during the matching processes and linear regression analysis. This paper focuses on the error generated by sample matching and the error fitting method generated by the sample fitting method. An error propagation analysis is performed to develop a generic model for assessing the uncertainty of the SNO cross-calibration method itself in meteorological satellite infrared channels. The model is validated using the payload parameters of the Hyperspectral Infrared Atmospheric Sounder (HIRAS) and the Medium Resolution Spectral Imager (MERSI) instruments aboard the FengYun-3D (FY-3D). Simulation experiments are performed considering typical bright temperatures, different background fields, and varying matching threshold conditions. The results demonstrate the effectiveness of the proposed model in capturing the error propagation chain in the SNO cross-calibration process. The model provides valuable insight into error analysis in the SNO cross-calibration method and can assist in determining the optimal sample matching threshold for achieving radiometric calibration accuracy. [ABSTRACT FROM AUTHOR]

This paper describes an adaptation of a polar code decoding technique in favor of the extended Golay code. Based on the bridge provided by a permutation matrix between the code words of these two classes of codes, the Golay code can be decoded by any polar code technique. Contrary to the successive-cancellation list technique which is characterized by a serial estimation of the bits, we propose in this work an adaptation of the simplified successive-cancellation list technique to polar codes equivalent to the Golay code. The simulations have achieved the performance of a maximum likelihood decoding, with the low decoding complexity of polar codes, compared to one of the universal decoders of linear codes most known in the literature. [ABSTRACT FROM AUTHOR]

The measurement of sea surface temperature (SST) is of utmost importance in the realm of oceanography. The increasing utilization of satellite data in SST research has highlighted the crucial need to compare and evaluate various satellite data sources. Using iQuam2 in situ SST data, this study aims to assess the accuracy of SST datasets obtained from three polar-orbiting satellites (AVHRR, Modis-Aqua, and Modis-Terra) and one geostationary satellite (Himawari-8) in the Bohai-Yellow-East China Sea (BYECS) throughout 2019. The results showed a strong correlation between satellite and in situ data, with R correlation coefficients exceeding 0.99. However, the accuracy of the satellite datasets exhibited some variability, with Himawari-8 showing the highest deviation error and MODIS-Aqua showing the least. Subsequently, the Modis-Aqua data were used as a benchmark to evaluate the SST data of the other three satellites over the previous six years (July 2015–June 2021). The results indicate that, in addition to intricate temporal variations, the deviations of the three satellites from Modis-Aqua also show significant spatial disparities due to the effect of seawater temperature. Compared to Modis-Aqua, the deviation of Himawari-8 generally displayed a negative trend in BYECS and showed pronounced seasonal variation. The deviation of AVHRR showed a negative trend across all regions except for a substantial positive value in the coastal region, with the time variation exhibiting intricate features. The SST values obtained from MODIS-Terra exhibited only marginal disparities from MODIS-Aqua, with positive values during the day and negative values at night. All three satellites showed significantly abnormal bias values after December 2020, indicating that the MODIS-Aqua-derived SST reference dataset may contain outliers beyond this period. In conclusion, the accuracy of the four satellite datasets varies across different regions and time periods. However, they could be effectively utilized and integrated with relevant fusion algorithms to synthesize high-precision datasets in the future. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Radar (SAR) plays an important role in marine ship management due to its all-weather, multi-band, and multi-polar characteristics, but the complex environment on the ground and the limitation of the imaging principle lead to the existence of large noise interference in SAR imaging, which poses a greater challenge to the existing ship detection algorithm. To address the problem of low detection rate and high false alarm rate of ship detection in noise-laden SAR images, we propose a detection algorithm based on convolutional neural network and transformer. First, we design the processing structure of multi-scale feature maps based on the advantages of transformer global processing capability, then we use weighted fusion of different scale feature maps after global processing to enhance the detection capability of the model for noise-containing targets, and finally, the model is evaluated using the high noise SAR datasets (HNSAR) we constructed. The experimental results show that our model has better detection of noise-containing SAR images compared with other deep learning models. [ABSTRACT FROM AUTHOR]

The existence of significant cross-polar antenna patterns, as well as the scan-dependent measurement biases, inherent to the polarimetric phased array radar (PPAR), are among the most important risk factors for using this technology in weather observations. The cross-polar patterns on receive induce cross coupling between returns from the two orthogonal fields causing biases in polarimetric variable estimates. Furthermore, the electromagnetic coupling in hardware may exacerbate the cross-coupling effects. To address this problem, a pulse-to-pulse phase coding in either the horizontal or vertical ports of the transmission elements has been proposed. However, it does not affect the scan-dependent system biases in PPAR estimates, which require corrections via calibration mechanisms. Further, the cross-coupling signals are proportional to the cross-polar pattern power levels, rendering mitigation effective only at steering angles where these levels are sufficiently low (e.g., approximately less than −25 dB). In that regard, any approach that augments the number of such steering angles benefits the cross-coupling mitigation effectiveness. Herein, a simple approach that has a potential to achieve this via antenna tilt is presented. Significance Statement: The issue of biases caused by cross coupling (due to significant cross-polar patterns in PPARs) is one of the biggest challenges for their weather observation applications. Numerous approaches have been proposed to address this issue, but none has been comprehensive. This suggests that the solution to the cross-coupling issue should be a combination of various mitigation approaches. In that regard, it is suggested in this work that a small antenna tilt can aid in the mitigation of the cross-coupling issue. [ABSTRACT FROM AUTHOR]

The digital preservation of heritage resources has emerged as an essential method for communicating the significance of artifacts, buildings, and landscapes to descendant communities and the wider public. While virtual representations are becoming more commonplace, physical representations (physicalization) of heritage sites via 3D printing are used to a lesser degree. Physicalization provides new perspectives through the interplay between touch and vision and can facilitate a deeper understanding of the history being conveyed. This paper discusses how the physical models of heritage buildings and landscape features on Qikiqtaruk/Herschel Island Territorial Park were created from terrestrial laser scanning and UAV photogrammetry data. We demonstrate how to use this physicalization of polar heritage to communicate the significance of the buildings and landscape of the island to the local Indigenous communities and global audiences, as well as how they are being threatened by climate change. We also explore the transformation of a cove on the island into puzzles and data sculptures. In addition to the Cove, the fabricating of important buildings on larger scales has been a requirement. This multi-scale printing raises the issue of connecting the large-scale buildings with their small instances/copies on the Island (similar to focus + context visualization in the digital form). Due to the limitation of physicalization compared with digital representations, new methods, metaphors and designs are needed for supporting focus + context visualization. We have designed and implemented several such methods in our specific physicalization of heritage buildings and landscape on Qikiqtaruk/Herschel Island. We presented our physicalizations to the members of the Inuvialuit community of Aklavik NWT and received a positive response. [ABSTRACT FROM AUTHOR]

From December 2020 to February 2022, 66 lava fountains (LF) occurred at Etna volcano (Italy). Despite their short duration (an average of about two hours), they produced a strong impact on human life, environment, and air traffic. In this work, the measurements collected from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instrument, on board Meteosat Second Generation (MSG) geostationary satellite, are processed every 15 min to characterize the volcanic clouds produced during the activities. In particular, a quantitative estimation of volcanic cloud top height (VCTH) and ash/ice/SO2 masses' time series are obtained. VCTHs are computed by integrating three different retrieval approaches based on coldest pixel detection, plume tracking, and HYSPLIT models, while particles and gas retrievals are realized simultaneously by exploiting the Volcanic Plume Retrieval (VPR) real-time procedure. The discrimination between ashy and icy pixels is carried out by applying the Brightness Temperature Difference (BTD) method with thresholds obtained by making specific Radiative Transfer Model simulations. Results indicate a VCTH variation during the entire period between 4 and 13 km, while the SO2, ash, and ice total masses reach maximum values of about 50, 100, and 300 Gg, respectively. The cumulative ash, ice, and SO2 emitted from all the 2020–2022 LFs in the atmosphere are about 750, 2300, and 670 Gg, respectively. All the retrievals indicate that the overall activity can be grouped into 3 main periods in which it passes from high (December 2020 to March 2021), low (March to June 2021), and medium/high (June 2021 to February 2022). The different products have been validated by using TROPOspheric Monitoring Instrument (TROPOMI) polar satellite sensor, Volcano Observatory Notices for Aviation (VONA) bulletins, and by processing the SEVIRI data considering a different and more accurate retrieval approach. The products' cross-comparison shows a generally good agreement, except for the SO2 total mass in case of high ash/ice content in the volcanic cloud. [ABSTRACT FROM AUTHOR]

The cloud thermodynamic phase is a crucial parameter to understand the Earth's radiation budget, the hydrological cycle, and atmospheric thermodynamic processes. Spaceborne active remote sensing such as the synergistic radar-lidar DARDAR product is considered the most reliable method to determine cloud phase; however, it lacks large-scale observations and high repetition rates. These can be provided by passive instruments such as SEVIRI aboard the geostationary Meteosat Second Generation (MSG) satellite, but passive remote sensing of the thermodynamic phase is challenging and confined to cloud top. Thus, it is necessary to understand to what extent passive sensors with the characteristics of SEVIRI are expected to provide a relevant contribution to cloud phase investigation. To reach this goal, we collect five years of DARDAR data to model the cloud top phase (CTP) for MSG/SEVIRI and create a SEVIRI-like CTP through an elaborate aggregation procedure. Thereby, we distinguish between ice (IC), mixed-phase (MP), supercooled (SC), and warm liquid (LQ). Overall, 65% of the resulting SEVIRI pixels are cloudy, consisting of 49% IC, 14% MP, 13% SC, and 24% LQ cloud tops. The spatial resolution has a significant effect on the occurrence of CTP, especially for MP cloud tops, which occur significantly more often at the lower SEVIRI resolution than at the higher DARDAR resolution (9%). We find that SC occurs most frequently at high southern latitudes, while MP is found mainly in both high southern and high northern latitudes. LQ dominates in the subsidence zones over the ocean, while IC occurrence dominates everywhere else. MP and SC show little seasonal variability apart from high latitudes, especially in the south. IC and LQ are affected by the shift of the Intertropical Convergence Zone. The peak of occurrence of SC is at −3 ∘ C, followed by that for MP at −13 ∘ C. Between 0 and −27 ∘ C, the occurrence of SC and MP dominates IC, while below −27 ∘ C, IC is the most frequent CTP. Finally, the occurrence of cloud top height (CTH) peaks lower over the ocean than over land, with MP, SC, and IC being undistinguishable in the tropics but with separated CTH peaks in the rest of the MSG disk. Finally, we test the ability of a state-of-the-art AI-based ice cloud detection algorithm for SEVIRI named CiPS (Cirrus Properties for SEVIRI) to detect cloud ice. We confirm previous evaluations with an ice detection probability of 77.1% and find a false alarm rate of 11.6%, of which 68% are due to misclassified cloud phases. CiPS is not sensitive to ice crystals in MP clouds and therefore not suitable for the detection of MP clouds but only for fully glaciated (i.e., IC) clouds. Our study demonstrates the need for the development of dedicated cloud phase distinction algorithms for all cloud phases (IC, LQ, MP, SC) from geostationary satellites. [ABSTRACT FROM AUTHOR]

Rendezvous is one of the fundamental phases of on-orbit servicing (OOS) missions. Since it requires high accuracy and safety, modeling is an indispensable part. Therefore, this article puts forward an approach for boosting the exactitude of the final proximity phase of a servicer spacecraft using precise modeling. Unlike other similar works that solely use linear models to design controllers, this paper employs a fully nonlinear model and considers most possible uncertainties and disturbances. In this regard, first a complete nonlinear relative pose (i.e., concurrent position attitude) motion dynamic is developed, which includes (1) the role of the reaction wheels and (2) the major environmental force and torque model. Second, taking the thruster's adverse torque into account, two sliding mode-based control techniques with different nonlinear sliding surfaces are designed. Moreover, the Lyapunov stability criterion is used to handle high nonlinearity effects, control input saturation, actuator misalignment, external disturbance torque/force, measurement error, uncertainties of both inertia parameters, and control inputs. Even the PWPF modulator of the thrusters has been considered to make the outcomes more realistic. Finally, three different scenarios are comprehensively simulated to illustrate the feasibility and efficiency of the designed scheme. The results prove that the proposed closed-form controller is more executable to implement than other existing approaches. [ABSTRACT FROM AUTHOR]

The decades-long Clouds and Earth's Radiant Energy System (CERES) Project includes both cloud and radiation measurements from instruments on the Aqua, Terra, and Suomi National Polar-orbiting Partnership (SNPP) satellites. To build a reliable long-term climate data record, it is important to determine the accuracies of the parameters retrieved from the sensors on each satellite. Cloud amount, phase, and top height derived from radiances taken by the Visible Infrared Imaging Radiometer Suite (VIIRS) on the SNPP are evaluated relative to the same quantities determined from measurements by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) spacecraft. The accuracies of the VIIRS cloud fractions are found to be as good as or better than those for the CERES amounts determined from Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) data and for cloud fractions estimated by two other operational algorithms. Sensitivities of cloud fraction bias to CALIOP resolution, matching time window, and viewing zenith angle are examined. VIIRS cloud phase biases are slightly greater than their CERES MODIS counterparts. A majority of cloud phase errors are due to multilayer clouds during the daytime and supercooled liquid water clouds at night. CERES VIIRS cloud-top height biases are similar to those from CERES MODIS, except for ice clouds, which are smaller than those from CERES MODIS. CERES VIIRS cloud phase and top height uncertainties overall are very similar to or better than several operational algorithms, but fail to match the accuracies of experimental machine learning techniques. The greatest errors occur for multilayered clouds and clouds with phase misclassification. Cloud top heights can be improved by relaxing tropopause constraints, improving lapse-rate to model temperature profiles, and accounting for multilayer clouds. Other suggestions for improving the retrievals are also discussed. [ABSTRACT FROM AUTHOR]

The motion planning module is the core module of the automated vehicle software system, which plays a key role in connecting its preceding element, i.e., the sensing module, and its following element, i.e., the control module. The design of an adaptive polar lattice-based local obstacle avoidance (APOLLO) algorithm proposed in this paper takes full account of the characteristics of the vehicle's sensing and control systems. The core of our approach mainly consists of three phases, i.e., the adaptive polar lattice-based local search space design, the collision-free path generation and the path smoothing. By adjusting a few parameters, the algorithm can be adapted to different driving environments and different kinds of vehicle chassis. Simulations show that the proposed method owns strong environmental adaptability and low computation complexity. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) plays a dominant role in the surface energy budget (SEB) and hydrological cycling. Thermal infrared (TIR) remote sensing is the primary method of estimating LST globally. However, cloud cover leaves numerous data gaps in satellite LST products, which seriously restricts their applications. Efforts have been made to produce gap-free LST products from polar-orbiting satellites (e.g., Terra and Aqua); however, satellite data from limited overpasses are not suitable for characterizing the diurnal temperature cycle (DTC), which is directly related to heat waves, plant water stress, and soil moisture. Considering the high temporal variability in LST and the importance of the DTC, we refined the SEB-based cloudy-sky LST recovery method by improving its feasibility and efficiency and produced a global hourly, 5 km, all-sky land surface temperature (GHA-LST) dataset from 2011 to 2021. The GHA-LST product was generated using TIR LST products from geostationary and polar-orbiting satellite data from the Copernicus Global Land Service (CGLS) and the Moderate Resolution Imaging Spectroradiometer (MODIS). Based on ground measurements at the 201 global sites from the Surface Radiation Budget (SURFRAD), Baseline Surface Radiation Network (BSRN), Fluxnet, AmeriFlux, Heihe River basin (HRB), and Tibetan Plateau (TP) networks, the overall root-mean-square error (RMSE) of the hourly GHA-LST product was 3.31 K, with a bias of -0.57 K and R2 of 0.95. Thus, this product was more accurate than the clear-sky CGLS and MODIS MYD21C1 LST samples. The RMSE value of the daily mean LST was 1.76 K. Validation results at individual sites indicate that the GHA-LST dataset has relatively larger RMSEs for high-elevation regions, which can be attributed to high surface heterogeneity and input data uncertainty. Temporal and spatial analyses suggested that GHA-LST has satisfactory spatiotemporal continuity and reasonable variation and matches the reference data well at hourly and daily scales. Furthermore, the regional comparison of GHA-LST with other gap-free hourly datasets (ERA5 and Global Land Data Assimilation System, GLDAS) demonstrated that GHA-LST can provide more spatial texture information. The monthly anomaly analysis suggests that GHA-LST couples well with global surface air temperature datasets and other LST datasets at daily mean and minimum temperature scales, whereas the maximum temperature and diurnal temperature range of LST and air temperature (AT) have different anomalous magnitudes. The GHA-LST dataset is the first global gap-free LST dataset at an hourly, 5 km scale with high accuracy, and it can be used to estimate global evapotranspiration, monitor extreme weather, and advance meteorological forecasting models. GHA-LST is freely available at 10.5281/zenodo.7487284 (Jia et al., 2022b) and http://glass.umd.edu/allsky%5fLST/GHA-LST (last access: 10 February 2023; Jia et al., 2022c). [ABSTRACT FROM AUTHOR]

Using a conjunction of Cluster in the mid‐altitude dayside magnetosphere and Swarm in the low‐altitude ionosphere, we show, by employing multi‐spacecraft analysis, that matched, strong magnetic perturbations and the corresponding mesoscale field‐aligned current (FAC) structures are measured in the high latitude polar cusp region during the 7 October 2015 storm. Two pairs of opposite (positive/negative) FACs are observed by both Cluster and Swarm, which may relate to pulsed magnetic reconnection at the dayside magnetopause. Furthermore, the current intensity of these matched FACs decreases from high to low latitude, consistent with the time elapsed since reconnection. Corresponding geomagnetic disturbances are also observed by ground stations. Our observations provide direct evidence for the coupling of mesoscale FACs between the magnetosphere, ionosphere and ground in the polar cusp region, where the signatures are driven in this case by conditions suitable for inducing reconnection. Plain Language Summary: Field‐aligned currents (FACs) are the key medium for the interaction between the distant space magnetosphere (a region filled with Earth's magnetic field) and the near‐Earth space ionosphere. Magnetic reconnection is the most important process to transfer solar wind energy from dayside magnetosphere to nightside, which is accompanied by the generation of FACs extending from the high latitude region of the ionosphere to the magnetosphere. For such structures, extending across different space regions, joint observations by multiple spacecraft are necessary. Using simultaneous measurements of Cluster in the magnetosphere, Swarm in the ionosphere and geomagnetic stations on the ground, coordinated mesoscale FAC structures could show matched signatures in the magnetosphere and the ionosphere and the corresponding geomagnetic disturbances on the ground. Our observations provide direct evidence for the magnetosphere‐ionosphere‐ground coupling during the pulsed magnetic reconnection process. Key Points: Multi‐spacecraft Cluster and Swarm reveal matched magnetic perturbation and corresponding mesoscale field‐aligned currents (FACs) at different altitudes in the cusp regionMultiple pairs of opposite FACs associated with pulsed magnetic reconnection are dominant currents system at the dayside during storm timeDirect evidence for detailed dayside mesoscale FACs coupling between magnetosphere, ionosphere and ground is provided [ABSTRACT FROM AUTHOR]

In this work, we present the most updated catalog of Io hot spots based on Juno/JIRAM data. We find 242 hot spots, including 23 previously undetected. Over the half of the new hot spots identified, are located at high northern and southern latitudes (>70°). We observe a latitudinal variability and a larger concentration of hot spots in the polar regions, in particular in the North. The comparison between JIRAM and the most recent Io hot spot catalogs listing power output (Veeder et al., 2015, https://doi.org/10.1016/j.icarus.2014.07.028; de Kleer, de Pater, et al., 2019, https://doi.org/10.3847/1538-3881/ab2380), shows JIRAM detected 63% and 88% of the total number of hot spots, respectively. Furthermore, JIRAM observed 16 of the 34 faint hot spots previously identified. JIRAM data revealed thermal emission from 5 dark pateræ inferred to be active from color ratio images, thus confirming that these are hot spots. Plain Language Summary: We mapped the hot spot distribution on Io's surface by analyzing the images acquired by the JIRAM instrument onboard the Juno spacecraft. We identified 242 hot spots, including 23 not present in other catalogs. A large number of the new hot spots identified are in the polar regions, specifically in the northern hemisphere. The comparison between our work and the most recent and updated catalog reveals that JIRAM detected 82% of the most powerful hot spots previously identified and half of the intermediate‐power hot spots, thus showing that these are still active. JIRAM detected 16 out of the 34 faint hot spots previously reported. The resolution of JIRAM may not have been sufficient to detect these faint hot spots, or activity might have faded or stopped. Key Points: We produced a new Io hot spot map based on Juno/JIRAM dataWe identified 242 hot spots, including 23 previously undetectedThe latitudinal hot spot distribution is uneven with a larger concentration at the poles [ABSTRACT FROM AUTHOR]

In this paper, an irradiance-based absolute radiometric calibration campaign at Baotou calibration site during June and July 2018 was described. This radiometric calibration campaign made use of six radiometric calibration tarps. The synchronous measurements of parameters such as surface reflectance, atmospheric parameters, and diffuse-to-global irradiance ratio were collected at the satellite overpass. The top-of-atmospheric radiance was predicted by radiative transfer model with these synchronous measurements. The linear relationship between DNs of satellite sensor and band-specific top-of-atmospheric spectral radiance was established, and a stable and reliable absolute calibration coefficient of ZY3-02 MUX was determined in this campaign. We compared the calibration results of the irradiance-based method with those of the reflectance-based method. The results suggested that the irradiance-based method is better than reflectance-based method. [ABSTRACT FROM AUTHOR]

This paper develops a framework for geolocating ground-based moving targets with images taken from dual unmanned aerial vehicles (UAVs). Unlike the usual moving-target geolocation methods that rely heavily on accurate navigation state sensors or assumptions of the known target's altitude, the proposed framework does not have the same limitations and performs geolocation of moving targets utilizing dual UAVs equipped with the low-quality navigation state sensors. Considering the Gaussian measurement errors and yaw-angle measurement bias provided by low-quality sensors, we first propose an epipolar constraint-based corresponding-point-matching method, which enables the historical measurement data to be used to estimate the current position of the moving target; after that, we propose a target altitude estimation method based on multiview geometry, which utilizes multiple images, including historical images, to estimate the altitude of the moving target; finally, considering the negative influence of yaw-angle measurement bias on the processes of target altitude estimation and parameter regression, we take advantage of multiple iterations among the two processes to accurately estimate the moving target's two-dimensional position and the yaw-angle measurement biases of two UAVs. The effectiveness and practicability of the framework proposed in this paper are proved by simulation experiments and actual flight experiments. [ABSTRACT FROM AUTHOR]

Students from the University of Alabama in Huntsville successfully deployed three micro superpressure balloon satellites in winter 2021. Students planned and implemented all phases of the project: obtaining funding, determining project timelines, preparing equipment, launching balloons, designing and implementing a website, writing daily blogs on the balloon progress, and analyzing the data. The objective of the flights was to use the balloons as a meteorological tool to study conditions in the lower stratosphere (12–14 km), as a tracer for evaluating modeled air parcel trajectories, and as an outreach and educational tool. The three balloons successfully traveled hundreds of thousands of kilometers, making an accumulated total of 16 global circumnavigations. Throughout the project, students made connections with hundreds of researchers, ham radio operators, STEM groups, and other students around the globe. The balloons provided velocity telemetry within many different weather regimes, including vigorous jets over the Himalayas, slow-moving equatorial air masses over the middle of the Pacific Ocean, and dense polar air masses over the Arctic Circle. This study has found that the accuracy of HYSPLIT-calculated trajectories using numerical weather predication (NWP) meteorological data can be quantified using parcel velocity, duration of trajectory forecast, and spatial resolution of the NWP model. [ABSTRACT FROM AUTHOR]

Channel capacity refers to the maximum bit rate at which a channel can be transmitted. Polar codes were the first error correcting codes to achieve infinite block length channel capacity for symmetric binary input, memoryless channels. This achievement of polar codes has been decided to be used in the 5th Generation New Radio Communication standard. In this study, the implementation of the successive-cancellation decoder algorithm of polar codes at different block lengths and different code rates with field programmable gate arrays (FPGA) is explained. [ABSTRACT FROM AUTHOR]

Quantum random number generators find applications in both quantum and classical communications schemes, particularly in security protocols where they can be used as a source of random seed or key material. In this work, we describe the implementation of a quantum random number generator on-board a nanosatellite deployed in low Earth orbit. Our generator samples shot noise from an entangled photon-pair source based on spontaneous parametric down-conversion, linking the entropy of the output to the quantization of the down-converted beam. We present analyzed data from the orbiting instrument alongside data taken from a ground-based engineering model where the statistical test suites indicate a good match to the output from a uniform distribution. Finally, we use the source to implement a prototype for an off-grid randomness beacon. This work paves the way to future low Earth orbit based public quantum randomness beacons. Quantum Random Number Generators (QRNG) are important components of cryptographic protocols including prepare-and-measure based quantum key distribution protocols. The authors demonstrate laboratory, as well as in-orbit operation of their QRNG, showing its use to implement a public randomness beacon. [ABSTRACT FROM AUTHOR]

In response to ESA's "Voyage 2050" announcement of opportunity, we propose an ambitious L-class mission to explore one of the most exciting bodies in the Solar System, Saturn's largest moon Titan. Titan, a "world with two oceans", is an organic-rich body with interior-surface-atmosphere interactions that are comparable in complexity to the Earth. Titan is also one of the few places in the Solar System with habitability potential. Titan's remarkable nature was only partly revealed by the Cassini-Huygens mission and still holds mysteries requiring a complete exploration using a variety of vehicles and instruments. The proposed mission concept POSEIDON (Titan POlar Scout/orbitEr and In situ lake lander DrONe explorer) would perform joint orbital and in situ investigations of Titan. It is designed to build on and exceed the scope and scientific/technological accomplishments of Cassini-Huygens, exploring Titan in ways that were not previously possible, in particular through full close-up and in situ coverage over long periods of time. In the proposed mission architecture, POSEIDON consists of two major elements: a spacecraft with a large set of instruments that would orbit Titan, preferably in a low-eccentricity polar orbit, and a suite of in situ investigation components, i.e. a lake lander, a "heavy" drone (possibly amphibious) and/or a fleet of mini-drones, dedicated to the exploration of the polar regions. The ideal arrival time at Titan would be slightly before the next northern Spring equinox (2039), as equinoxes are the most active periods to monitor still largely unknown atmospheric and surface seasonal changes. The exploration of Titan's northern latitudes with an orbiter and in situ element(s) would be highly complementary in terms of timing (with possible mission timing overlap), locations, and science goals with the upcoming NASA New Frontiers Dragonfly mission that will provide in situ exploration of Titan's equatorial regions, in the mid-2030s. [ABSTRACT FROM AUTHOR]

We prove that the polar degree of an arbitrarily singular projective hypersurface can be decomposed as a sum of non-negative numbers which quantify local vanishing cycles of two different types. This yields lower bounds for the polar degree of any singular projective hypersurface. [ABSTRACT FROM AUTHOR]

Recent studies have shown that auroral kilometric radiation (AKR) can propagate from the polar source cavity into the equatorial radiation belt but there is no direct evidence yet. By examining 19‐month data from Arase satellite and Van Allen Probes, we report a unique event that distinct AKR emissions are observed simultaneously at high and low latitudes, with the peak wave spectra in the frequency 300–400 kHz. Using the three‐dimensional ray tracing method, we simulate the AKR ray paths at three typical frequencies (220, 350, and 550 kHz), and show that more ray paths for 350 kHz can propagate downward through the locations of Arase satellite and Van Allen Probe B than those for other two frequencies. This result can successfully explain the observation and provides a direct evidence that AKR can propagate to low latitude radiation belt under suitable conditions. Plain Language Summary: Auroral kilometric radiation (AKR) is a widely existing electromagnetic wave in the magnetosphere and has potential for acceleration or precipitation loss of energetic electrons, yielding serious damage to orbiting space systems or ozone destruction in the atmosphere. Previous observation and numerical simulation have shown that AKR originated from the polar cavity region can be presented in the low latitude even in the equator. However, there is no direct observational evidence yet due to lack of the correlated data at higher and lower latitudes. Here, we examine observations of Arase satellite and Van Allen Probes from 25 March 2017 to 30 October 2018, and find a unique AKR event detected simultaneously by the Arase satellite (at high latitude) and Probe B (at low latitude). Using 3‐D ray tracing method, we simulate AKR paths for different frequencies (220, 350, and 550 kHz) with suitable wave normal angles and azimuthal angles. We show that more ray paths for 350 kHz can pass through the locations of Arase satellite and Probe B than those for other two frequencies, consistent with the observations. The current result provides a direct evidence that AKR can propagate to low latitude radiation belt under suitable conditions. Key Points: A unique auroral kilometric radiation (AKR) event is reported simultaneously by Arase satellite and Van Allen Probes during 19‐month observationsSimulations show that more AKR for 350 kHz pass the locations of two satellites, consistent with observationsAKR raypaths are highly dependent on wave frequency, initial wave normal angles and azimuthal angles [ABSTRACT FROM AUTHOR]

Multi-epoch double-differenced pseudorange observation (MDPO) is a dual-satellite lunar navigation algorithm specially designed for a precursor mission, using a minimum number of lunar orbiting small satellites to realize a GNSS-like radio navigation system for the Moon. In this study, we evaluated the performance of the MDPO algorithm by using real pseudorange measurements obtained from a pair of GNSS ground stations, one of which represented a lander, and the other a rover on the Moon. It was natural that the resulting positioning accuracy varied largely by satellite geometry, but the estimated error distributions of the double-differenced pseudorange observations were consistent and agreed with the predicted value. The results showed that the MDPO algorithm worked properly with the real GNSS observables and was capable of providing the expected navigation performance for future lunar exploration missions. [ABSTRACT FROM AUTHOR]

We present a generalisation of the Maier-Saupe (MS) theory that incorporates the description of the ferroelectric nematic phase (NF) within its scope of application. The extension of the theory is carried out in a natural way, by adding to the nematic potential of MS a term proportional to cosθ and to the polar order parameter , where θ is the angle between the long molecular axis and the spontaneous polarisation. The NF phase can be reached by cooling from the isotropic phase with or without the formation of an intermediate normal nematic phase, depending on the relative intensity of the polar and non-polar terms of the nematic potential. For both phase sequences all the transitions are first order. The temperature dependence of the polar and non-polar order parameters is calculated, and some results derived from the theory are compared with the experimental observations. It is argued that the theory is a valuable first approximation to describe some of the properties of ferroelectric nematics. [ABSTRACT FROM AUTHOR]