Low-latitude Regions Research Articles

Exploring the intermittency of magnetohydrodynamic turbulence by synchrotron polarization radiation

Context. Magnetohydrodynamic (MHD) turbulence plays a critical role in many key astrophysical processes, such as star formation, acceleration of cosmic rays, and heat conduction. However, its properties are still poorly understood. Aims. In this work, we explore how to extract the intermittency of compressible MHD turbulence from synthetic and real observations. Methods. We used three statistical methods, namely the probability distribution function, kurtosis, and scaling exponent of the multi-order structure function, to reveal the intermittency of MHD turbulence. Results. Our numerical results demonstrate that: (1) the synchrotron polarization intensity statistics can be used to probe the intermittency of magnetic turbulence, by which we can distinguish different turbulence regimes; (2) the intermittency of MHD turbulence is dominated by the slow mode in the sub-Alfvénic turbulence regime; and (3) the Galactic interstellar medium (ISM) in the low latitude region corresponds to the sub-Alfvénic and supersonic turbulence regime. Conclusions.We have successfully measured the intermittency of the Galactic ISM from synthetic and realistic observations.

Organic carbon decomposition temperature sensitivity positively correlates with the relative abundance of copiotrophic microbial taxa in cropland soils

Revealing the relationships between the temperature sensitivity of soil organic matter decomposition (Q10) and microbial communities is critical to predict ecosystem feedbacks to global warming. However, the relationships are still far from well understood, especially within the low latitude regions. To address this knowledge gap, soil samples were collected from >100 cropland sites in Southwest China, a region with highly diverse climatic and environmental conditions. The results showed that Q10 values substantially varied across the region, ranging from 1.85 to 6.81, with an average value of 3.27. They were significantly positively correlated with the contents of soil organic carbon, while negatively correlated with the ratios of soil dissolved organic carbon to total organic carbon content. This indicates that soils with high organic carbon contents are more vulnerable to global warming. Further analysis suggested that Q10 values were positively correlated with soil microbial respiration rates, fungal abundance, prokaryotic diversity, and the relative abundance of copiotrophic microbial lineages, but negatively correlated with the proportions of oligotrophic microbes and microbial co-occurrence network degree. The structural equation modeling analysis suggested that soil organic carbon and its quality, as well as microbial attributes were the main factors explaining the variation in Q10 values. The findings in this study highlight the crucial and complex roles of soil microbiome in determining ecosystem feedbacks to global warming.

A Regional Paleoclimate Record of the Tropical Aeolian Sands during the Last Deglaciation in Hainan, China

The KLD segment of the Kenweiyuan section in Wenchang, Hainan, China is a set of aeolian sand deposits of the Last Deglaciation. The chemical element and heavy mineral analysis performed in this study reveals the chemical index of alteration (CIA) in the segment to be as high as 93–95, with all the heavy minerals identified as stable and extremely stable making up 38–45% of the total. Furthermore, the zircon, tourmaline, and rutile content (ZTR index) of the segment is determined to range between 48–71. The (Al2O3 + TOFE)/SiO2 ratios display obvious fluctuations from old to new strata in the segment, with the low values corresponding to Heinrich event (H1), Dansgaard-Oeschager (D-O), and Younger Dryas (YD) and the high values corresponding to Bølling and Allerød. Our study suggests that these fluctuations are attributed to the alternation of the East Asian winter and summer monsoons. Hainan Island is also impacted by the surface ocean climate of the South China Sea, and characteristics of the KLD segment may be connected to the climate changes in the North Atlantic related to the winter monsoon season or westerlies. Furthermore, the segment presents a clear response to millennium-scale climate changes during the Last Deglaciation on Hainan Island. Based on the high CIA values in the KLD segment, and particularly due to the observed stable detrital minerals, the ratios can be linked to the overall tropical climate, indicating a relatively warm tropical climate environment in the Last Deglaciation in Hainan. The high CIA values also reveal the cause of aeolian sand formation under the tropical environmental conditions in the low latitude region of China in the Late Quaternary.

Mitigating ionospheric scintillation effects on RTK-based long-span bridge deformation monitoring

Ionospheric scintillation presents significant challenges to the application of Global Navigation Satellite System (GNSS) for positioning and bridge deformation monitoring in low-latitude region. This study aims to develop a GNSS positioning model to improve long-span bridge deformation monitoring performance under ionospheric scintillation. We propose a new Rate of Total Electron Content (ROT) calculation method using undifferenced estimated ionosphere delays for identifying ionospheric scintillation. Then, we construct an undifferenced and uncombined (UDUC) ionosphere-refined Real-time Kinematic (RTK) model by replacing ionospheric spatial constraints with temporal constraints to mitigate the impact of ionospheric scintillation. RTK experiments are conducted on the South China Sea Bridge (SCSB), spanning 55 km. The results indicate that the new ROT calculation method can effectively identify observations affected by ionospheric scintillation, and the ionosphere-refined RTK model shows superior performance compared to ionosphere-float and ionosphere-weighted RTK model in terms of convergence time, Time to First Fix (TTFF), and positioning accuracy.

Improved phenology-based rice mapping algorithm by integrating optical and radar data

Information on rice planting areas is critically important for food and water security, as well as for adapting to climate change. Mapping rice globally remains challenging due to the diverse climatic conditions and various rice cropping systems worldwide. Synthetic Aperture Radar (SAR) data, which is immune to climatic conditions, plays a vital role in rice mapping in cloudy, rainy, low-latitude regions but it suffers from commission errors in high-latitude regions. Conversely, optical data performs well in high-latitude regions due to its high observation frequency and less cloud contamination but faces significant omission errors in low-latitude regions. An effective integrated method that combines both data types is key to global rice mapping. Here, we propose a novel adaptive rice mapping framework named Rice-Sentinel that combines Sentinel-1 and Sentinel-2 data. First, we extracted key phenological phases of rice (e.g., the flooding and transplanting phase and the rapid growth phase), by analyzing the characteristic V-shaped changes in the Sentinel-1 VH curve. Second, we identified potential flooding signals in rice pixels by integrating the VH time series from Sentinel-1 with the Land Surface Water Index (LSWI) and Enhanced Vegetation Index (EVI) from Sentinel-2, utilizing the generated phenology phases. Third, the rapid growth signals of rice following its flooding phase were identified using Sentinel-2 data. Finally, rice fields were identified by integrating flooding and rapid growth signals. The resultant rice maps in six different case regions of the world (Northeast and South China, California, USA, Mekong Delta of Vietnam, Sakata City in Japan, and Mali in Africa) showed overall accuracies over 90 % and F1 scores over 0.91, outperforming the existing methods and products. This algorithm combines the strengths of both optical and SAR time series data and leverages biophysical principles to generate robust rice maps without relying on any prior ground truth samples. It is well-positioned for global applications and is expected to contribute to global rice monitoring efforts.

Comparative Study of Potential Habitats for Two Endemic Grassland Caterpillars on the Qinghai-Tibet Plateau Based on BIOMOD2 and Land Use Data.

This study has systematically investigated and compared the geographical distribution patterns and population density of G. menyuanensis (Gm) and G. qinghaiensis (Gq), which are endemic to the QTP region and inflict severe damage. Using a method combining the BIOMOD2 integration model (incorporating nine ecological niche models) and current species distribution data, this study has compared changes in potential habitats and distribution centers of these two species during ancient, present, and future climate periods and conducted a correlation test on the prediction results with land use types. The study results indicate that there are differences in geographical distribution patterns, distribution elevations, and population density of these two species. Compared with single models, the integration model exhibits prominent accuracy and stability with higher KAPPA, TSS, and AUC values. The distribution of suitable habitats for these two species is significantly affected by climatic temperature and precipitation. There is a significant difference between the potential habitats of these two species. Gm and Gq are distributed in the northeastern boundary area and the central and eastern areas of the QTP, respectively. The areas of their suitable habitats are significantly and positively correlated with the area of grassland among all land use types of QTP, with no correlations with the areas of other land use types of QTP. The potential habitats of both species during the paleoclimate period were located in the eastern and southeastern boundary areas of the QTP. During the paleoclimate period, their potential habitats expanded towards the Hengduan Mountains (low-latitude regions) in the south compared with their current suitable habitats. With the subsequent temperature rising, their distribution centers shifted towards the northeast (high-latitude) regions, which could validate the hypothesis that the Hengduan Mountains were refuges for these species during the glacial period. In the future, there will be more potential suitable habitats for these two species in the QTP. This study elucidates the ecological factors affecting the current distribution of these grass caterpillars, provides an important reference for designating the prevention and control areas for Gm and Gq, and helps protect the alpine meadow ecosystem in the region.

Ionospheric Total Electron Content Response to the Intense Geomagnetic Storm of 10th -11th May 2024 over Low, Mid and High Latitude Regions

In this paper, we investigated the response of ionospheric Total electron content (TEC) to the intense geomagnetic storm of 10th - 11th May 2024 using 6 Global Navigation Satellite System (GNSS) stations: BAKE (Geog. Lat.64.33o N; Geog. Lon. 96.02o W), BELE (Geog. Lat. 1.41o S; Geog. Lon. 48.46o W), MBAR (Geog. Lat. 0.60o S; Geog. Lon. 30.74o E), SUTH (Geog. Lat. 32.38o S; Geog. Lon. 20.81o E), BJFS (Geog. Lat. 39.61o N; Geo. Lon. 115.89o E) and DUND (Geog. Lat. 45.88o S; Geog. Lon.170.60o E) situated over low, mid and high latitude regions. The GPS-TEC data was extracted, processed and used to plot vertical total electron content (VTEC) verses universal time (UT) from 8th to 13th May 2024 for each GNSS receiver station. A contour plot of TEC variation was also plotted for each station from 8th to 13th May 2024. The results showed TEC enhancing significantly at the beginning of the storm, during daytime at the geomagnetic equator, with the exception of MBAR, where TEC increased at night. This was attributed to the effect of prompt penetration of electric field (PPEF). A reduction in TEC was also noted on 11th May 2024, during the recovery phase over all the GNSS receiver stations. This was attributed to the effect of the disturbance dynamo electric field (DDEF) and composition change. The contour plots showed diurnal variation in TEC concentration over each GNSS receiver station. The TEC concentration however reduced during the storm period.

On the low-latitude ionospheric irregularities under geomagnetically active and quiet conditions using NavIC observables: A spectral analysis approach

Ionospheric irregularities and associated scintillations under geomagnetically active/quiet conditions have detrimental effects on the reliability and performance of space- and ground-based navigation satellite systems, especially over the low-latitude region. The current work investigates the low-latitude ionospheric irregularities using the phase screen theory and the corresponding temporal Power Spectral Density (PSD) analysis to present an estimate of the outer irregularity scale sizes over these locations. The study uses simultaneous L5 signal C/No observations of NavIC (a set of GEO and GSO navigation satellite systems) near the northern crest of EIA (Indore: 22.52∘N, 75.92∘E, dip: 32.23∘N) and in between the crest and the dip equator (Hyderabad: 17.42∘N, 78.55∘E, dip: 21.69∘N). The study period (2017–2018) covers disturbed and quiet-time conditions in the declining phase of the solar cycle 24. The PSD analysis brings forward the presence of irregularities, of the order of a few hundred meters during weak-to-moderate and quiet-time conditions and up to a few km during the strong event, over both locations. The ROTI values validate the presence of such structures in the Indian region. Furthermore, only for the strong event, a time delay of scintillation occurrence over Indore, with values of 36 min and 50 min for NavIC satellites (PRNs) 5 and 6, respectively, from scintillation occurrence at Hyderabad is observed, suggesting a poleward evolution of irregularity structures. Further observations show a westward propagation of these structures on this day. This study brings forward the advantage of utilizing continuous data from the GEO and GSO satellite systems in understanding the evolution and propagation of the ionospheric irregularities over the low-latitude region.

Mg Exosphere of Mercury Observed by PHEBUS Onboard BepiColombo During Its Second and Third Swing‐Bys

AbstractMercury's exosphere is an important target for understanding the dynamics of coupled systems in space environments, tenuous planetary atmospheres, and planetary surfaces. Magnesium (Mg) is especially crucial for establishing methods for estimating the surface chemical composition distribution through observations of the exosphere because its distribution in the exosphere and on the surface is strongly correlated. However, owing to its low radiance, the Hermean Mg exosphere has only been detected by the Mercury Atmospheric and Surface Composition Spectrometer (MASCS) onboard the Mercury Surface, Space Environment, Geochemistry, and Ranging (MESSENGER) spacecraft. Thus, we have few observation data for areas other than low latitude regions in addition to few detection cases of short‐term or sporadic fluctuations, resulting in a poor understanding of ejection and transportation mechanisms of the Mg exosphere. In this study, we analyzed the distribution of the Hermean Mg exosphere by the Probing of Hermean Exosphere by Ultraviolet Spectroscopy (PHEBUS) onboard the Mercury Planetary Orbiter of the BepiColombo mission during its second and third Mercury swing‐bys (MSBs). First, we constructed a calibration method including background subtraction and calibration using stellar observations. Mg light curves at two true anomaly angles were obtained, which were in agreement with the Chamberlain model and a three‐dimensional numerical calculation. Comparing the Mg and calcium (Ca) radiances obtained by PHEBUS during the MSBs, the exospheric Mg atoms have a lower energy than the exospheric Ca atoms. This is consistent with the lower energy necessary for producing the Mg atoms produced by molecular photodissociation than for Ca atoms.

Based on coverage evaluation design method study of factor low-orbit infrared remote sensing constellation configuration

Abstract To satisfy the infrared detection coverage demands of Low Earth Orbit (LEO) satellites in global missile surveillance, we have devised a comprehensive evaluation system for global missile infrared remote sensing coverage performance. By referencing Walker’s extensive and uninterrupted global coverage constellation layout, we conducted a thorough analysis of various constellation configuration parameters. This analysis aimed to assess the coverage efficiency of differently configured LEO networking satellites. Following a detailed comparative analysis, we settled on an LEO infrared remote sensing constellation configuration featuring an orbit height of 1150 km and an orbit inclination of 60°. After an in-depth examination of the capabilities of the infrared remote sensing constellation and the characteristics of the detection zone, we constructed a Blind Spot Compensation Constellation. This was achieved by integrating four additional LEO satellites with a 0° orbit inclination to bolster coverage in low-latitude regions. Using our comprehensive coverage evaluation system, we rigorously evaluated the ground coverage capabilities of multiple constellations. Notably, the Blind Spot Compensation Constellation achieved impressive coverage, reaching 100%, and excelled particularly in the latitude belt of 20° or less. Although the Original Constellation performed better in the 40° latitude belt compared to the Blind Spot Compensation Constellation, it showed some deficiencies in coverage at a 50 km altitude. Specifically, it averaged 18.417 gaps per day, with a coverage rate slightly below 100%. However, it achieved full coverage at other altitudes. To validate our findings, we conducted scenario simulations. For missile targets, the Original Constellation offered a maximum coverage multiplicity of 6, with a total access duration of 4539.1 seconds. On the other hand, the Blind Spot Compensation Constellation boasted a maximum coverage multiplicity of 8, with a total access duration of 5465.9 seconds. Importantly, both constellations fully covered the missile’s entire 1056-second lifecycle, showcasing commendable performance. In conclusion, the LEO infrared remote sensing constellation and its complementary counterpart, developed and rigorously tested in this study, not only meet the demands of continuous global detection but also cater to the priority detection needs of diverse geographical regions.

Fast Fourier Transform (FFT) Application For Short-Term Earthquake Precursor Analysis Using Geomagnetic Data (Case Study of Kupang Geomagnetic Station, East Nusa Tenggara, Indonesia)

Abstract Earthquake (EQ) precursors have been identified from ULF geomagnetic enhancements related to a moderate EQ in Kupang, East Nusa Tenggara, Indonesia. Three components of geomagnetic data (X, Y, and Z) collected during January-June 2010 were analyzed. The EQ occurred on May 7, 2010, and its epicenter was 27.78 km from the KPG Geomagnetic Station. The magnitude and depth of the EQ were 5 and 11.3 km, respectively. This study investigated the energy of ULF geomagnetic signals in the frequency range of 0.03 to 0.04 Hz using SDR based on FFT. The results showed that the geomagnetic energy increased approximately three days before the EQ. Due to the significant magnitude and relative proximity of the EQ to the observation station, it can be concluded that the closer the geomagnetic station from the EQ source, the more likely it is to detect anomalies caused by the EQ. Despite the increase in geomagnetic energy, the Dst index which measures the global activity of the geomagnetic variation in low-latitude regions does not indicate any extraordinary global geomagnetic activity. This indicates that geomagnetic anomalies are most likely related to EQ events.

Nighttime ionospheric irregularity during intense geomagnetic storm events over the Europe-African longitudinal sector

Radio communication and navigation systems can be severely impacted by irregularities in the ionosphere. There is still much to learn about how geomagnetic storms affect the occurrence of these irregularities. Ionosphere studies in different regions, particularly the equatorial and low-latitudes, are necessary to enhance the forecasting of this phenomenon. This study investigates the effect of intense geomagnetic storm events of August 27, October 7 and December 22, 2015, on nighttime ionospheric irregularities. Data collected from the receivers of the Global Navigation Satellite Systems (GNSS) in specific longitudinal sector of 15∘W – 0∘, 0∘ – 15∘E, 15∘E – 30∘E and 30∘E – 45∘E, as well as from the Swarm constellations in the longitude range of 30∘W – 70∘E and the latitude range of 50∘S – 50∘N, have been used. The rate of change of the total electron content (TEC) index (ROTI) and the rate of change of the electron density index (RODI) were analyzed. In the main phases of the storms, at equatorial and low-latitude regions we observed ionospheric irregularities in the African longitudinal sectors of 15∘W – 0∘, 0∘ – 15∘E and 30∘E – 45∘E in the three storm events. The observed ionospheric irregularities were more pronounced in the western than eastern regions. These irregularities were possibly driven by the Prompt Penetration Electric Fields (PPEFs) that point east to west during nighttime. Ionospheric irregularities were inhibited in the selected storm periods over the middle latitudes in the African sector. In the longitudinal sector of 15∘E – 30∘E, we obtained inhibition of irregularity in the study periods. In the case of the top-side ionosphere, we observed enhanced and depleted electron density during the storm in the low latitude and equatorial regions. In the low latitude and equatorial regions, there were electron density fluctuations within the range of 15∘N and 15∘S, indicating significant top-side irregularities.

Global fishing patterns amplify human exposures to methylmercury

Global pollution has exacerbated accumulation of toxicants like methylmercury (MeHg) in seafood. Human exposure to MeHg has been associated with long-term neurodevelopmental delays and impaired cardiovascular health, while many micronutrients in seafood are beneficial to health. The largest MeHg exposure source for many general populations originates from marine fish that are harvested from the global ocean and sold in the commercial seafood market. Here, we use high-resolution catch data for global fisheries and an empirically constrained spatial model for seafood MeHg to examine the spatial origins and magnitudes of MeHg extracted from the ocean. Results suggest that tropical and subtropical fisheries account for >70% of the MeHg extracted from the ocean because they are the major fishing grounds for large pelagic fishes and the natural biogeochemistry in this region facilitates seawater MeHg production. Compounding this issue, micronutrients (selenium and omega-3 fatty acids) are lowest in seafood harvested from warm, low-latitude regions and may be further depleted by future ocean warming. Our results imply that extensive harvests of large pelagic species by industrial fisheries, particularly in the tropics, drive global public health concerns related to MeHg exposure. We estimate that 84 to 99% of subsistence fishing entities globally likely exceed MeHg exposure thresholds based on typical rates of subsistence fish consumption. Results highlight the need for both stringent controls on global pollution and better accounting for human nutrition in fishing choices.

Identification and Analysis of the Superoxide Dismutase (SOD) Gene Family and Potential Roles in High-Temperature Stress Response of Herbaceous Peony (Paeonia lactiflora Pall.).

The herbaceous peony (Paeonia lactiflora Pall.) plant is world-renowned for its ornamental, medicinal, edible, and oil values. As global warming intensifies, its growth and development are often affected by high-temperature stress, especially in low-latitude regions. Superoxide dismutase (SOD) is an important enzyme in the plant antioxidant systems and plays vital roles in stress response by maintaining the dynamic balance of reactive oxygen species (ROS) concentrations. To reveal the members of then SOD gene family and their potential roles under high-temperature stress, we performed a comprehensive identification of the SOD gene family in the low-latitude cultivar 'Hang Baishao' and analyzed the expression patterns of SOD family genes (PlSODs) in response to high-temperature stress and exogenous hormones. The present study identified ten potential PlSOD genes, encoding 145-261 amino acids, and their molecular weights varied from 15.319 to 29.973 kDa. Phylogenetic analysis indicated that PlSOD genes were categorized into three sub-families, and members within each sub-family exhibited similar conserved motifs. Gene expression analysis suggested that SOD genes were highly expressed in leaves, stems, and dormancy buds. Moreover, RNA-seq data revealed that PlCSD1-1, PlCSD3, and PlFSD1 may be related to high-temperature stress response. Finally, based on the Quantitative Real-time PCR (qRT-PCR) results, seven SOD genes were significantly upregulated in response to high-temperature stress, and exogenous EBR and ABA treatments can enhance high-temperature tolerance in P. lactiflora. Overall, these discoveries lay the foundation for elucidating the function of PlSOD genes for the thermotolerance of herbaceous peony and facilitating the genetic breeding of herbaceous peony cultivars with strong high-temperature resistance.

Impact of the high-speed solar wind stream over the low-latitude ionospheric system – a study combining Indian MOM and InSWIM observations

ABSTRACT In this study, we map the origin, acceleration, and propagation of the high-speed solar wind streams (HSS) and observe their impact on the low-latitude Earth’s ionosphere. Data from radio-sounding experiments conducted by the Indian Mars Orbiter Mission (MOM) from 2015 May 9–19 is analysed to understand the solar wind speed’s evolution at various helio-centric distances. The slope of the turbulence spectrum from 25 to 35 Rs was in the range of 0.2–0.4, indicative of the underdeveloped turbulence corresponding to the high-flow streams. It coincided with the appearance of the earth-facing coronal holes as observed in the coronal EUV images. The particle bulk velocity at L1 showed that the speeds began to rise from 400 km s−1 on May 11th–12th, reaching a peak of around 800 km s−1 on May13th–14th, followed by a gradual decrease to the average slow speeds. Geomagnetic disturbances during the same period manifested as a dip in the DST index values. The GNSS (Global Navigation Satellite System) data from the InSWIM (Indian network for Space Weather Impact Monitoring) network show an appreciable increase in the VTEC (vertical total electron content) of the ionosphere on disturbed days in entire low-latitude ionospheric region in the Indian sector. All these observed parameters correlate well with the HSS arrival. This is a unique study that connects the propagation of the HSS and its impact on near-Earth’s environment from the different vantage points in interplanetary space and proposes the application of Radio beacons to improve space weather forecasting.

Submicron Organic Aerosol Types in the Summertime Arctic: Mixing State, Geographic Distribution, and Drivers

AbstractDuring the 2017 summertime Arctic cruise observation campaigns, we measured over 290,000 individual submicron particles and clustered them into two inorganic classes (dominated by sea salt, accounting for 38.6% by number fraction) and five organic classes (dominated by natural and anthropogenic organics, 61.4%), presenting a distinct difference in geographic distribution. In the high Arctic and marginal ice zone (81.1–84.6°N) compared with the low Arctic (Chukchi Sea, Svalbard, and Iceland, <80°N), ocean‐derived organic aerosols were more prevalent (73.6% vs. 37.1%). Specifically, we found sharp contrasts in the geographic distributions of OC‐Ca (organics internally mixed with calcium, 29.0% vs. 9.4%) and OC‐S (organics internally mixed with sulfate, 3.2% vs. 21.4%). Utilizing an explainable machine learning technique, we inferred that OC‐Ca was driven by wind‐blown sea ice and/or sea ice floes and/or bubble bursting within sea ice leads under low wind speed conditions in the high Arctic, while OC‐S tended to associate with elemental carbon, sulfate, and higher temperatures, potentially originating from combustion emissions at low latitude regions.

Exploring Siamese network to estimate sea state bias of synthetic aperture radar altimeter

Sea state bias (SSB) is a crucial error of satellite radar altimetry over the ocean surface. For operational nonparametric SSB (NPSSB) models, such as two-dimensional (2D) or three-dimensional (3D) NPSSB, the solution process becomes increasingly complex and the construction of their regression functions pose challenges as the dimensionality of relevant variables increases. And most current SSB correction models for altimeters still follow those of traditional nadir radar altimeters, which limits their applicability to Synthetic Aperture Radar altimeters. Therefore, to improve this situation, this study has explored the influence of multi-dimensional SSB models on Synthetic Aperture Radar altimeters. This paper proposes a deep learning-based SSB estimation model called SNSSB, which employs a Siamese network framework, takes various multi-dimensional variables related to sea state as inputs, and uses the difference in sea surface height (SSH) at self-crossover points as the label. Experiments were conducted using Sentinel-6 self-crossover data from 2021 to 2023, and the model is evaluated using three main metrics: the variance of the SSH difference, the explained variance, and the SSH difference variance index (SVDI). The experimental results demonstrate that the proposed SNSSB model can further improve the accuracy of SSB estimation. On a global scale, compared to the traditional NPSSB, the multi-dimensional SNSSB not only decreases the variance of the SSH difference by over 11%, but also improves the explained variance by 5-10 cm2 in mid- and low-latitude regions. And the regional SNSSB also performs well, reducing the variance of the SSH difference by over 10% compared to the NPSSB. Additionally, the SNSSB model improves the computational efficiency by approximately 100 times. The favorable results highlight the potential of the multi-dimensional SNSSB in constructing SSB models, particularly the five-dimensional (5D) SNSSB, representing a breakthrough in overcoming the limitations of traditional NPSSB for constructing high-dimensional models. This study provides a novel approach to exploring the multiple influencing factors of SSB.

Observations of daytime topside ionospheric irregularities in the afternoon equatorial ionosphere

Previous observations show that the daytime irregularities (the fossil of nighttime irregularities) are mostly located in the low latitude region and at 10–14 LT. In this study, daytime topside ionospheric irregularities were observed along the longitude of ∼ 94oE by Swarms satellite in the afternoon equatorial ionosphere (about 15:00 LT) on 18 June 2020. Simultaneously, the F3 layer were observed in the bottomside ionosphere. Occurrences of F3 layer shows that there are disturbances on the zonal electric field. Multi-satellite observations show that the topside ionospheric irregularities did not occur in the morning equatorial ionosphere. Results indicate that afternoon ionospheric irregularities might be associated with the electrodynamic process of the plasma in the equatorial ionosphere. Simulations show that the combined effects of the disturbed zonal electric field and velocity shears in zonal plasma drift can be favorable to increase the occurrence rate of daytime ionospheric irregularities in the topside equatorial ionosphere.

Machine learning based storm time modeling of ionospheric vertical total electron content over Ethiopia

Geomagnetic storms can cause variations in the ionization levels of the ionosphere, which is commonly studied using the total electron content (TEC). TEC is a crucial parameter to identify the possible effects of ionospheric variations on satellite communication and navigation. This paper assesses the performance of light gradient boosting machine (LGB) and deep neural network (DNN) machine learning algorithms in modeling ionospheric vertical TEC (VTEC) during geomagnetic disturbances. GPS VTEC data for years 2011–2016 from 13 dual-frequency receiver stations over Ethiopia was utilized. Input parameters for the models were derived from the factors that influence VTEC, such as time, location, geomagnetic activity, solar activity, solar wind, and the interplanetary magnetic field. The LGB model improved the predictions of the DNN model from root mean squared error (RMSE), mean absolute percentage error (MAPE), and R2 values of 5.45 TECU, 21%, and 0.93 to 4.98 TECU, 18%, and 0.94 on the testing data, respectively. The two machine learning models significantly outperformed the International Reference Ionosphere (IRI 2020) model during the selected geomagnetic storm periods. This study could provide insight into the impacts of ionosphere variations on satellite communication and navigation systems in the low-latitude ionospheric region.

Tree Ring Blue Intensity-Based August Temperature Reconstruction for Subtropical Central China

Tree-ring blue intensity (BI) has the potential to provide information on past summer temperatures of a similar quality to that of tree-ring maximum latewood density and at a substantially reduced cost. To explore the applicability of BI in subtropical regions, the inverted BI for the earlywood, latewood, and the delta BI (DBI) parameters, together with tree-ring width of subalpine fir (Abies fargesii Franch.) in the Shennongjia area of China, were measured, and the corresponding chronologies were developed. The relationships of these chronologies with the monthly mean temperature and monthly precipitation were explored via correlation analysis. Results show that the DBI chronology is closely related to the temperature in August of the current year, indicating that BI, specifically delta BI, data are suitable for use in dendroclimatology studies in subtropical areas. The resultant mean temperature August reconstruction, based on DBI, explains 40.8% of the temperature variance and is robustly validated using independent periods from the calibration. This pilot study not only highlights the potential of DBI for temperature reconstruction in China but also offers valuable insights into historical climate variations in the Shennongjia region. Moreover, it shows the potential for utilizing such tree-ring data from low-latitude regions to derive past climate data in subtropical warm-humid zones.