Observation Satellite Research Articles

Mapping high spatial resolution ionospheric total electron content by integrating Time Series InSAR with International Reference Ionosphere model

Total electron content (TEC) is a key parameter for characterizing the ionosphere. Conventional TEC measurement methods have low spatial resolution, hindering accurate representation of ionospheric spatial characteristics. Synthetic Aperture Radar (SAR) and Interferometric SAR (InSAR) have shown their potential for high-spatial-resolution TEC estimation. However, SAR-based absolute TEC estimation typically relies on full-polarimetric SAR images, while the InSAR-based method can only extract differential TEC. This study proposes a novel TEC mapping method integrating Time Series InSAR (TS-InSAR) with the International Reference Ionospheric (IRI) model and does not leverage full-polarimetric SAR data. The Advanced Land Observing Satellite-1 (ALOS-1) SAR images covering the Chile and Greenland regions were collected to test the proposed method. The TECs derived from the IRI model and International GNSS Service (IGS) and the electron density observed by the Incoherent Scattering Radar (ISR) site of SONDRESTROM were acquired to evaluate the performance and validate the accuracy of the proposed method, respectively. The results show that the proposed method can achieve TEC mapping with resolutions of tens of meters, much higher than the tens or hundreds of kilometers of the IRI and IGS TECs. The spatial features of our method-derived TECs show overall good consistency with those of the IRI and IGS TECs, but the described spatial information is more detailed. Also, compared to the original IRI model, the improvement rates of root-mean-square errors (RMSEs) between the estimated electron density and ISR observations exceeded 21.67% after the update using the TEC obtained from the proposed method. These experiments demonstrate the proposed method’s feasibility and reliability for ionospheric TEC mapping.

An Optical Daytime Astronomy Pathfinder for the Huntsman Telescope

Abstract Observing stars and satellites in optical wavelengths during the day (optical daytime astronomy) has begun a resurgence of interest. The recent dramatic dimming event of Betelgeuse has spurred interest in continuous monitoring of the brightest variable stars, even when an object is only visible during the day due to their proximity to the Sun. In addition, an exponential increase in the number of satellites being launched into low Earth orbit in recent years has driven an interest in optical daytime astronomy for the detection and monitoring of satellites in space situational awareness (SSA) networks. In this paper we explore the use of the Huntsman Telescope as an optical daytime astronomy facility, by conducting an exploratory survey using a pathfinder instrument. We find that an absolute photometric accuracy between 1 - 10% can be achieved during the day, with a detection limit of V band 4.6 mag at midday in sloan g‚ and r‚ wavelengths. In addition we characterise the daytime sky brightness, colour and observing conditions in order to achieve the most reliable and highest signal-to-noise observations within the limitations of the bright sky background. We undertake a 7 month survey of the brightness of Betelgeuse during the day and demonstrate that our results are in agreement with measurements from other observatories. Finally we present our preliminary results that demonstrate obtaining absolute photometric measurements of the International Space Station during the day.

Probing Electromagnetic Gravitational-wave Emission Coincidence in a Type I Binary-driven Hypernova Family of Long Gamma-Ray Bursts at Very High Redshift

The repointing time of the X-Ray Telescope (XRT) instrument on the Neil Gehrels Swift Observatory satellite has posed challenges in observing and studying the early X-ray emissions within ≈40 s after a gamma-ray burst (GRB) trigger. To address this issue, we adopt a novel approach that capitalizes on the cosmological time dilation in GRBs with redshifts ranging from 3 to 9. Applying this strategy to Swift/XRT data, we investigate the earliest X-ray emissions of 368 GRBs from the Swift catalog, including short and long GRBs. We compare the observed time delay between the GRB trigger and the initial Swift/XRT observation, measured in the GRB observer frame, and the corresponding cosmological rest-frame time delay (RTD). This technique is here used in the analysis of GRB 090423 at z = 8.233 (RTD ∼8.2 s), GRB 090429B at z ≈ 9.4 (RTD ∼10.1 s), and GRB 220101A at z = 4.61 (RTD ∼14.4 s). The cosmological time dilation enables us to observe the very early X-ray afterglow emission in these three GRBs. We thus validate the observation of the collapse of the carbon–oxygen core and the coeval newborn neutron star (νNS) formation triggering the GRB event in the binary-driven hypernova (BdHN) scenario. We also evidence the νNS spin-up due to supernova ejecta fallback and its subsequent slowing down due to the X-ray/optical/radio synchrotron afterglow emission. A brief gravitational-wave signal may separate the two stages owing to a fast-spinning νNS triaxial-to-axisymmetric transition. We also analyze the long GRB redshift distribution for the different BdHN types and infer that BdHNe II and III may originate the NS binary progenitors of short GRBs.

Merged and Gridded GPM and Atmospheric River Data Product

AbstractThe Global Precipitation Measurement (GPM) Mission Core Observatory satellite launched in 2014 as a joint mission between National Aeronautics and Space Administration (NASA) and JAXA. Global Precipitation Measurement (GPM) has, since that time, provided continuous, valuable dual‐frequency radar and passive microwave radiometer observations. Here, we introduce a gridded data set of collocated GPM Core Observatory observational products merged with a reanalysis‐derived Atmospheric river (AR) data set in the North Atlantic and North Pacific sectors. The three data sets that are merged and gridded are: (a) the NASA Goddard Profiling (GPROF) precipitation product, which uses GPM passive microwave radiometer observations to derive surface precipitation rates, (b) a water vapor data product derived from the GPM Core Observatory radiometer, provided by Remote Sensing Systems (RSS), and (c) the Mattingly et al. (2018, https://doi.org/10.1029/2018jd028714) AR data set that is specifically tuned to the high‐latitude regions. This novel merged data set spans from May 2014 to December 2022 with plans to update annually through 2026 at minimum. This gridded product combines RSS passive water vapor and precipitation estimates with coincident AR detection. This data product benefits the scientific community by providing (a) user‐friendly gridded satellite data compared to standard satellite data sets, while maintaining high temporal resolution, and (b) coincident satellite observations to assess the link between ARs and precipitation.

Life Cycle of Precipitating Cloud Systems from Synergistic Satellite Observations: Evolution of Macrophysical Properties and Precipitation Statistics from Geostationary Cloud Tracking and GPM Active and Passive Microwave Measurements

Abstract Observations of clouds and precipitation in the microwave domain from the active dual-frequency precipitation radar (DPR) and the passive Global Precipitation Measurement (GPM) Microwave Imager (GMI) onboard the GPM Core Observatory satellite are used in synergy with cloud tracking information derived from infrared imagery from the GOES-13 and Meteosat-7 geostationary satellites for analysis of the life cycle of precipitating cloud systems, in terms of temporal evolution of their macrophysical characteristics, in several oceanic and continental regions of the tropics. The life cycle of each one of the several hundred thousand cloud systems tracked during the 2-yr (2015–16) analysis period is divided into five equal-duration stages between initiation and dissipation. The average cloud size, precipitation intensity, precipitation top height, and convective and stratiform precipitating fractions are documented at each stage of the life cycle for different cloud categories (based upon lifetime duration). The average life cycle dynamics is found remarkably homogeneous across the different regions and is consistent with previous studies: systems peak in size around midlife; precipitation intensity and convective fraction tend to decrease continuously from the initiation stage to the dissipation. Over the three continental regions, Amazonia (AMZ), central Africa (CAF), and Sahel (SAH), at the early stages of clouds’ life cycle, precipitation estimates from the passive GMI instrument are systematically found to be 15%–40% lower than active radar estimates. By highlighting stage-dependent biases in state-of-the-art passive microwave precipitation estimates over land, we demonstrate the potential usefulness of cloud tracking information for improving retrievals and suggest new directions for the synergistic use of geostationary and low-Earth-orbiting satellite observations.

Space Activities and the Simultaneous Development of the Economy in Türkiye

As space technologies have become an integral part of our daily lives, they have profoundly influenced the course of human civilization since 1957. These technologies have provided humanity with many remarkable insights. Therefore, they have an important role in modern society. Satellite technology is not only vital for military and defence but also for civil applications such as transportation, communication, disaster management, agriculture planning, land, and urban planning. These applications make the space sector an engine of economic growth having advanced and the state-of-the art technology. Technological advances in space continuously benefit the citizens of developed countries. The space economy is defined as all the actions and resources that produce value and benefit to people through exploration, research, knowledge, management, and utility of space. Through satellite communications, navigation systems, earth observation missions, space science and technology research, employment is created, economic growth is achieved, and many industries become more competitive in worldwide economic market. Spinoff companies are born from space activities. In 1994, the Türkiye had its first communication satellite TURKSAT 1B built by Aerospatiale; thus, Türkiye entered the space field being an operator in its region. After millennium, the Turkish space industry has ramped-up by developing its dedicated communication and observation satellites, and their subsystems and creating a launcher system for microsatellites. Türkiye is now developing space technology more comprehensively. This article describes recent developments of space activities and future work in Türkiye. In the article, the strategies in other countries in space technologies are also discussed and suggestions are made for space technology education, development of space economy and regulation of space activities for Türkiye.

The diversity of spectral shapes of hydrogen Lyman lines and Mg II lines in a quiescent prominence

Context. Broad sets of spectroscopic observations comprising multiple lines represent an excellent opportunity for diagnostics of the properties of the prominence plasma and the dynamics of their fine structures. However, they also bring significant challenges when they are compared with synthetic spectra provided by radiative transfer modeling. Aims. In this work, we provide a statistical spectroscopic analysis of a unique dataset of coordinated prominence observations in the Lyman lines (Lyα to Lyδ) and the Mg II k and h lines. The observed data were obtained by the Solar Ultraviolet Measurements of Emitted Radiation (SUMER) spectrograph on board of the Solar and Heliospheric Observatory (SoHO) satellite and the Interface Region Imaging Spectrograph (IRIS) on 22 October 2013. Only a few similar coordinated datasets of Lyman and Mg II k and h observations have ever been obtained in prominences and we present here the first analysis using these two sets of spectral lines. Moreover, for the first time, we assess the influence of noise on the statistical properties of the studied profile characteristics. Methods. We focus on the following profile characteristics: the shape of the observed line profiles based on the number of distinct peaks, the integrated line intensity, the center-to-peak ratio describing the depth of the reversal of two-peaked profiles, and the asymmetry of these peaks. Results. We show that the presence of noise has a negligible effect on the integrated intensity of all observed lines, but it significantly affects the classification of spectral profiles using the number of distinct peaks, the reversal depth, and also the peak asymmetry. We also demonstrate that by taking the influence of noise into account, we can assess which profile characteristics in which spectral lines are suitable for diagnostics of different properties of the observed prominence. For example, we show that the subordinate peaks (peaks below error bars) in the Lyman line profiles are mostly caused by noise, which means that only the dominant peaks should be used for statistical analyses or comparisons with synthetic spectra. On the other hand, in the Mg II k and h profiles, the key role in the distinction between the multi-peaked profiles with low peaks and the profiles with deep reversals is played by the dynamics of multiple fine structures located along a line of sight. The complex, multi-peaked profiles are observed in places where multiple fine structures with different line-of-sight velocities are crossing the line of sight, while the profiles with deep reversals likely correspond to instances when we observe single fine structures or more fine structures but with similar line-of-sight velocities. Conclusions. This study allows us to conclude that if we are interested in the diagnostics of the dynamics of prominence fine structures, the best approach is to use a combination of profile asymmetry in the Lyman lines together with the complex profiles of Mg II k and h lines. On the other hand, if we want to diagnose the temperature and pressure properties of individual prominence fine structures, we need to focus on the deeply reversed Mg II k and h lines in combination with the Lyman lines and to analyze the depth of the central reversal and the integrated intensities.

Onboard autonomous mission generation method based on user preference

This paper presents a method for autonomous onboard mission generation of Earth observation imaging satellites based on user preferences. The paper develops a planning database to store the previous user mission requirements, and proposes a database updating algorithm to track the changes in user preferences. The paper also proposes a mission generation method based on the planning database, which predicts target priorities and imaging methods. Finally, a mission allocation strategy is used to assign newly generated missions to the appropriate satellites. Simulations results show that the proposed method can effectively improve the utilization of satellite resources and thereby obtain higher mission return.

Evaluation of the performance of a CdZnTe-based soft γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\gamma $$\\end{document}-ray detector for CubeSat payloads

The low-energy γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\varvec{\\gamma }$$\\end{document}-ray (0.1-30 MeV) sky has been relatively unexplored since the decommissioning of the COMPTEL instrument on the Compton Gamma-Ray Observatory (CGRO) satellite in 2000. However, the study of this part of the energy spectrum (the “MeV gap”) is crucial for addressing numerous unresolved questions in high-energy and multi-messenger astrophysics. Although several large MeV γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\varvec{\\gamma }$$\\end{document}-ray missions like AMEGO and e-ASTROGAM are being proposed, they are predominantly in the developmental phase, with launches not anticipated until the next decade at the earliest. In recent times, there has been a surge in proposed CubeSat missions as cost-effective and rapidly implementable “pathfinder” alternatives. A MeV CubeSat dedicated to γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\varvec{\\gamma }$$\\end{document}-ray astronomy has the potential to serve as a demonstrator for future, larger-scale MeV payloads. This paper presents a γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\varvec{\\gamma }$$\\end{document}-ray payload design featuring a CdZnTe crystal calorimeter module developed by IDEAS. We report the detailed results of simulations to assess the performance of this proposed payload and compare it with those of previous γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\varvec{\\gamma }$$\\end{document}-ray instruments.

Reconstruction of 3D DPR Observations Using GMI Radiances

AbstractThree‐dimensional global precipitation observation is crucial for understanding climate and weather dynamics. While spaceborne precipitation radars provide precise but limited observations, passive microwave imagers are available much more frequently. In this study, we propose a deep learning approach to reconstruct active radar observations using passive microwave radiances. We introduce the Hybrid Deep Neural Network (HDNN) model, which utilizes reflectivity profiles from the Dual‐frequency Precipitation Radar (DPR) onboard the Global Precipitation Measurement (GPM) Core Observatory Satellite as the “target” and combines radiances from the GPM Microwave Imager (GMI) with supplementary reanalysis data to serve as the “features.” Results underscore the HDNN's exemplary performance, with a root mean square error below 4 dBZ across all altitude levels, and a consistent accuracy across different precipitation types. Its efficacy is further illustrated when applied to typhoon cases of Haishen and Khanun, emerging as a superior tool for capturing 3D structures of expansive precipitation systems.

Estimating the Hotspot Area Observed by Earth Imaging Satellite via ISAR Image Sequence

Estimating the Hotspot Area Observed by Earth Imaging Satellite via ISAR Image Sequence

Tropical Cyclone Precipitation, Infrared, Microwave, and Environmental Dataset (TC PRIMED)

Abstract To study tropical cyclones and generate forecast applications using satellite observations, researchers often consolidate disparate sources of raw and ancillary data. Data consolidation involves obtaining, collocating, and intercalibrating data from different sensors and derived products; calculating environmental diagnostics from a homogeneous source; and standardizing these various products for a straightforward analysis. To alleviate preprocessing issues and provide a long-term, global digital dataset of tropical cyclone satellite observations, we construct the Tropical Cyclone Precipitation, Infrared, Microwave, and Environmental Dataset (TC PRIMED). TC PRIMED contains tropical cyclone–centric 1) intercalibrated, multichannel, multisensor microwave brightness temperatures, 2) retrieved rainfall from NASA’s Goddard Profiling Algorithm (GPROF), 3) nearly coincident geostationary satellite infrared brightness temperatures and derived metrics, 4) tropical cyclone position and intensity information, 5) ECMWF fifth-generation reanalysis fields and derived environmental diagnostics, and 6) precipitation radar observations from the TRMM and GPM Core Observatory satellites. TC PRIMED consists of over 176,000 overpasses of 2,101 storms from 1998 to 2019, providing researchers with an analysis-ready dataset to promote and support research into improving our understanding of the relationship between tropical cyclone convective and precipitation structure, intensity, and environment. Here, we briefly describe data sources and processing steps to create TC PRIMED. To demonstrate TC PRIMED’s potential utility for studying important tropical cyclone processes and for application development, we present a shear-relative composite analysis of several multisensor satellite variables relative to the tropical cyclone lifetime maximum intensity. The composite analysis provides a simple example of how TC PRIMED can benefit future studies to advance our understanding of tropical cyclones and improve forecasts.

Anomaly Detection for Agile Satellite Attitude Control System Using Hybrid Deep-Learning Technique

Agile low-Earth-orbit (LEO) observation satellites need a robust attitude control and determination system. It is a critical satellite subsystem, which stabilizes the satellite to different desired orientations during its mission using different actuators. The detection of satellite misorientation is a highly challenging problem because it requires continuous monitoring of data from hundreds of satellite sensors to guarantee healthy operability. In this paper, the authors propose a data-driven deep-learning framework for detecting satellite misorientation by analyzing attitude control subsystem telemetry data. The proposed approach combines a hybrid predictive deep-learning model that consists of long short-term memory and convolutional neural networks in two parallel paths to predict telemetry data and a robust isolation forest classifier for anomaly detection purposes that can classify output residuals as normal or anomalous. The hybrid model was optimized by the particle swarm optimization algorithm to ensure faster fitness function convergence with optimal model hyperparameters. The suggested data-driven model was validated using real telemetry datasets, including real anomalous case studies. The experimental results proved the suggested approach’s superiority for identifying satellite misorientation as well as helping satellite operators monitor the system’s health and deduce the causes of anomalies to aid in decision-making.

Evaluation of EPIC oxygen bands stability with radiative transfer simulations over the South Pole

The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) satellite orbiting the Sun at the Lagrange-1 point was launched without onboard calibration systems. Vicarious calibration is conducted for 8 of the 10 UV/VIS/NIR channels using other low earth orbiting satellite instruments, while its two O2 bands (688 nm and 764 nm) rely on indirect moon-view calibrations because the same narrow-band O2 bands are not readily available from other in-flight instruments. This study compares EPIC measurements from the four O2 bands aiming at examining sensor stability over a uniquely suited location, i.e., the permanently snow-covered South Pole. The study utilizes radiative transfer model simulations with in-situ atmospheric soundings taken at South Pole during months of December and January from 2015 to 2022. The absolute discrepancy between the model simulations and observations is less than 1.0% for the two reference bands, but 5.75% and 15.63% for the 688 nm, and 764 nm absorption bands, respectively. The simulated A-band and B-band ratios are 16.09% and 4.74% higher than that from the observations. Various sensitivities are conducted to estimate possible contributions to the discrepancies from input atmospheric profiles, spectral surface albedos and surface BRDF. While none of the input uncertainties is likely to account for the large discrepancies in the oxygen absorption bands, a small shift in the instrument response function could be the main reason for these biases. On the other hand, the model simulations are able to capture systematic variations with observed angular measurements and explain the multi-year trends found in observed O2 band ratios due to satellite orbit shifting. When model simulated contributions from the angle variations are deducted from the observed O2 band ratios, the residual O2 band ratios are found to be stable since 2015.

Efficient Uncertainty Analysis of External Heat Flux of Solar Radiation with External Heat Flux Expansion for Spacecraft Thermal Design

Designing spacecraft involves a careful equilibrium to avoid overengineering or underdesigning, which underscores the importance of employing thermal uncertainty analysis. A key part of this analysis is modeling thermal conditions, but this is often a computationally heavy process. This is largely because ray-tracing calculations require determining the external heat flux of solar radiation across different operating conditions. Ray emission varies across conditions, which can lead to inefficient resource use in uncertainty calculations. Our study aims to address this by introducing a new approach to calculating the external heat flux of solar radiation that is better suited for uncertainty analysis than previous approaches. Our formula only requires ray tracing to be performed for one condition rather than for every condition. The other conditions are handled by simple matrix budgeting, negating the need for complicated ray tracing. In the aforementioned analytical procedure, certain matrices demonstrate sparsity properties. By exploiting this characteristic, optimization computations can be executed by utilizing sparse matrix algorithms. We tested this new formula, which we call the external heat flux expansion (EHFE) formula, on a specific spacecraft and compared the results with those obtained using the traditional method. Our findings suggest that the EHFE formula is ideal for calculating uncertainty. It significantly improves computational efficiency while maintaining accuracy. The formula is also user-adjustable, allowing the accuracy of uncertainty calculation results of the external heat flux of solar radiation to be fine-tuned by changing the value of the cutoff factor. This work establishes an essential theoretical framework pivotal to addressing inherent uncertainties in the thermal design of upcoming deep-space exploration spacecraft, solar observatory satellites, and space solar power stations.

A Preliminary Analysis of Typical Structures and Microphysical Characteristics of Precipitation in Northeastern China Cold Vortexes

The northeastern China cold vortex (NCCV) is the main weather system affecting Northeast China. Based on the precipitation products from the dual-frequency precipitation radar (DPR) onboard the Global Precipitation Measurement core observatory (GPM) satellite, the precipitation structures and microphysical properties for different rain types in 6432 NCCVs from 2014 to 2019 were studied using dynamic composite analysis. Our results show that the precipitation in NCCVs is dominated by stratiform precipitation. Regions with high stratiform and convective precipitation frequency have a comma shape. The growth mechanism of precipitation particles changes at ~4 km in altitude, the lower particles grow through collision (more pronounced in convective precipitation), and the upper hydrometeors grow through the Bergeron process. Additionally, the precipitation structures and microphysical properties exhibit great regional variations in NCCVs. The rainfall for all rain types is the strongest in the southeast region within an NCCV, mainly characterized by higher near-surface droplet concentration, while precipitation events occur more frequently in the southeast region for all rain types. There are active rimming growth processes above the melting layer for convective precipitation in the western region of an NCCV. In the southeast region of an NCCV, the collision growth of droplets in both types of precipitation is the most obvious.

Self-consistent propagation of flux ropes in realistic coronal simulations

Context.The text has been edited to adhere to American English based on the spelling style used in the text. In order to anticipate the geoeffectiveness of coronal mass ejections (CMEs), heliospheric simulations are used to propagate transient structures injected at 0.1 AU. Without direct measurements near the Sun, the properties of these injected CMEs must be derived from models coming from observations or numerical simulations, and thus they contain a lot of uncertainty.Aims.The aim of this paper is to demonstrate the possible use of the new coronal model COCONUT to compute a detailed representation of a numerical CME at 0.1 AU after its injection at the solar surface and propagation in a realistic solar wind, as derived from observed magnetograms.Methods.We present the implementation and propagation of modified Titov-Démoulin flux ropes in the COCONUT 3D magnetohydrodynamics coronal model. Background solar wind was reconstructed in order to model two opposite configurations representing a solar activity maximum and minimum, respectively. Both configurations were derived from magnetograms that were obtained by the Helioseismic and Magnetic Imager on board the Solar Dynamic Observatory satellite. We tracked the propagation of 24 flux ropes that differ only by their initial magnetic flux. In particular, we investigated the geometry of the flux ropes during the early stages of their propagation as well as the influence of their initial parameters and solar wind configuration on 1D profiles derived at 0.1 AU.Results.At the beginning of the propagation, the shape of the flux ropes varied between simulations during low and high solar activity. We found dynamics that are consistent with the standard CME model, such as pinching of the CME legs and the appearance of post-flare loops. Despite the differences in geometry, the synthetic density and magnetic field time profiles at 0.1 AU are very similar in both solar wind configurations. These profiles are also similar to those observed further in the heliosphere and suggest the presence of a magnetic ejecta composed of the initially implemented flux rope and a sheath ahead of it. Finally, we uncovered relationships between the properties of the magnetic ejecta, such as relationships between density or speed and the initial magnetic flux of our flux ropes.Conclusions.The implementation of the modified Titov-Démoulin flux rope in COCONUT enables us to retrieve the major properties of CMEs at 0.1 AU for any phase of the solar cycle. When combined with heliospheric simulations, COCONUT could lead to more realistic and self-consistent CME evolution models and thus more reliable predictions.

A new sequential homogeneous pixel selection algorithm for distributed scatterer InSAR

ABSTRACT Distributed scatterer interferometric synthetic aperture radar (DS InSAR) technology has been widely used in various fields. Homogeneous pixel selection is a crucial step in the use of DS InSAR, directly affecting the estimation precision and reliability of subsequent parameter calculations. The existing algorithms for selecting homogeneous pixels have inherent limitations, such as requiring many heterogeneous samples and strict requirements surrounding the required number of synthetic aperture radar (SAR) images. To address these problems, a new sequential selection algorithm for homogeneous pixels is proposed, based on the Baumgartner – Weiss–Schindler (BWS) test algorithm and dynamic interval estimation (DIE) theory. According to Monte Carlo simulation experiments, the average standard deviation (STD) of the mean of the rejection of the BWS-DIE algorithm under six sample conditions is 0.014. Compared with three existing algorithms, including the Kolmogorov‒Smirnov (KS), BWS and fast statistically homogeneous pixel selection (FaSHPS) algorithms, the BWS-DIE algorithm improves homogeneous pixel selection precision by 64.3%, 69.4% and 25.3%, respectively. In the real data experiment, 12 scenes of Advanced Land Observing Satellite-1 Phased Array type L-band Synthetic Aperture Radar (ALOS-1 PALSAR) data from February 2007 to March 2011 were used and the BWS-DIE multitemporal InSAR (MT InSAR) method based on the BWS-DIE algorithm was applied to surface subsidence monitoring in the western mining area of Xuzhou, Jiangsu Province, China. The experimental results show that, compared with the Stanford Method for Persistent Scatterers (StaMPS), the BWS-DIE MT InSAR method improves the ability to monitor the maximum subsidence by 12.3%, increases the point density by 5.7 times and decreases the root mean square error (RMSE) by 50%. In addition, new surface deformation patterns are found in the spatial-temporal evolution. The above experimental results show that the proposed BWS-DIE algorithm exhibits remarkable advantages in selection power and selection precision and is not limited by the number of SAR images. The proposed algorithm can further broaden the application scenarios for DS InSAR and provide high-quality and reliable monitoring data for subsequent scientific research.

Solar active region magnetic parameters and their relationship with the properties of halo coronal mass ejections

The coronal mass ejections (CMEs) from the sun consist of the plasma and strong magnetic fields (∼4–5 G at 1.3 R⊙) and generally, the fast CMEs are often associated with energetic particles of energy few hundreds of MeV. When the fast CMEs are ejected towards the Earth, they can disrupt the flow of solar wind in the heliosphere and impact the Earth's magnetosphere causing known space weather phenomena such as, geomagnetic storms, auroras, communication blackouts, satellite drag and failures. In this work, we have investigated a set of 60 halo coronal mass ejections (CMEs) associated with X-ray flares (≥C1.0) observed in 49 active regions during the period 2010–2016 in solar cycle 24. The X-ray flares and white light CMEs were observed by Geostationary Operational Environmental Satellite (GOES) and the Large Angle Spectrometric Coronagraph (LASCO) coronagraph on the Solar and Heliospheric Observatory (SOHO) satellite, respectively. The active region magnetic properties are obtained from Space - weather HMI Active Region Patch (SHARP) parameters for this set of events. For each active region (AR), the mean value is calculated from a 1-day time series for each of the 16 photospheric magnetic parameters extracted from the vector magnetogram products at a 12-min cadence. The dependency of flare flux and CME kinematics properties on the active region magnetic properties is further confirmed through correlation studies. As a result, we found a moderate to strong correlation value for flare flux and halo CME kinematic properties (like linear speed, space speed and kinetic energy) among the seven (USFLUX, TOTUSJZ, TOTUSJH, ABSNJZH, SAVNCPP, TOTPOT and MEANJZH) SHARP parameters. Most of the events (≥73%) were produced by βγδ, βγ and βδ Hale - type sunspot groups and Ekc/Dkc/Fkc McIntosh sunspot classes. It reveals that the most complex active regions are feasible sources of strong flare-associated halo CME productivity. The front side halo CME kinematic properties depend more on the vertical current helicity and polarity magnetic parameters than the other magnetic parameters. In addition, the flare intensity and speed of CME, calculated using an empirical model with the active region magnetic parameters, are found nearly equal to the observed values. This result will be useful to identify the important magnetic parameters for modelling the occurrence of flare-associated halo CMEs and to understand the physical relationship between them.

Ionosonde and GPS total electron content observations during the 26 December 2019 annular solar eclipse over Indonesia

Abstract. We report the investigation of the ionospheric response to the passage of an annular solar eclipse over Southeast Asia on 26 December 2019 using multiple sets of observations. Two ionosondes (one at Kototabang and another at Pontianak) were used to measure dynamical changes in the ionospheric layer during the event. A network of ground-based GPS receiver stations in Indonesia was used to derive the distribution of total electron content (TEC) over the region. In addition, extreme ultraviolet (EUV) images of the Sun from the Atmospheric Imaging Assembly (AIA) instrument on board the Solar Dynamics Observatory (SDO) satellite were also analyzed to determine possible impacts of solar-active regions on the changes that occurred in the ionosphere during the eclipse. We found −1.62 and −1.90 MHz reductions (24.0 % and 27.5 % relative reduction) in foF2 during the solar eclipse over Kototabang and Pontianak, respectively. The respective TEC reductions over Kototabang and Pontianak during the eclipse were −4.34 and −5.45 TECU (24.9 % and 27.9 % relative reduction). Data from both ionosondes indicate a consistent 34–36 min delay between maximum eclipse and minimum foF2. The corresponding time delays for eclipse-related TEC reduction at these two locations were 40 and 16 min, respectively. The ionospheric F layer was found to descend with a speed of 9–19 m s−1 during the first half of the eclipse period. We also found an apparent rise in the ionospheric F-layer height near the end of the solar eclipse period, equivalent to a vertical drift velocity of 44–47 m s−1. The GPS TEC data mapping along a set of cross-sectional cuts indicates that the greatest TEC reduction actually occurred to the north of the solar-eclipse path, opposite of the direction from which the lunar shadow fell. As the central path of the solar eclipse was located just to the north of the southern equatorial ionization anomaly (EIA) crest, it is suspected that such a peculiar TEC reduction pattern was caused by plasma flow associated with the equatorial fountain effect. Net perturbations of TEC were also computed and analyzed, which revealed the presence of some wavelike fluctuations associated with the solar-eclipse event. Some of the observed TEC perturbation patterns that propagated with a velocity matching the lunar shadow may be explained in terms of nonuniform EUV illumination that arose as various active regions on the Sun went obstructed and unobstructed during the eclipse. The remaining wavelike features are likely to be traveling ionospheric disturbances (TIDs) generated by the passage of the solar eclipse on top of other diurnal factors.