Chlorophyll,calcite, and suspended sediment concentrations in the Bay of Bengal and the Arabian Sea at the river mouths

Chlorophyll and suspended sediment concentrations (SSC) and sea surface temperature (SST) are important parameters in assessing the productivity of coastal regions. Numerous rivers flow into the eastern (Ganga, Subernarekha, Mahanadi, Godavari, Krishna, Penner, and Kaveri) and western (Narmada, Tapti, and Indus) coasts of the Indian sub-continent. Using IRS P4 (Oceansat-1) Ocean Color Monitor (OCM) and Moderate Resolution Imaging Spectroradiometer (MODIS) data, we have retrieved chlorophyll, calcite, and SSC near the mouth of these rivers for the period during 2000–2004. The maxima of chlorophyll-a concentrations at the river mouth is much higher for the Himalayan and north India rivers (Ganga, Subernarekha, Mahanadi, and Indus) (10–14 mg/m³) compared to rivers in the southern parts of India (Kaveri and Penner) (∼4 mg/m³). The maxima of calcite concentration (∼45 moles/m³), chlorophyll (∼14 mg/m³), and sediment concentrations (∼9 g/m³) near river mouth are found to be influenced by river discharges (Ganga and Brahmaputra) during the monsoon season. The calcite concentration (∼45 moles/m³) at the mouth of Ganga river shows a major peak with the onset of monsoon season (June–July) followed by a maxima in chlorophyll-a with a time lag of 1–2 months. The Krishna, Kaveri, and Penner rivers show low chlorophyll concentrations (3–8 mg/m³), high calcite (0–40 moles/m³), and low SSC (<3 g/m³) compared to Narmada and Tapti rivers (chlorophyll-a 12–14 mg/m³, calcite 0–2 moles/m³, and SSC 13–19 g/m³). The Indus river shows similar behavior (maxima of chlorophyll ∼13 mg/m³ and SSC ∼8 g/m³) with respect to Ganga river except for high calcite concentration during winter months (∼25 moles/m³). The characteristics of the chlorophyll, calcite, and SSC at the mouth of these rivers show spatial and temporal variability along the eastern and westerns coasts of India which are found to differ widely. A comparison of the chlorophyll concentrations using OCM and MODIS data shows low chlorophyll concentrations in the Bay of Bengal as compared to the Arabian Sea.     

Contingency target assessment,trajectory design,and analysis for NASA’s NEA scout solar sail mission

The presented study examines contingency target selection and trajectory design for NASA’s Near-Earth Asteroid Scout mission under the assumption of a missed lunar gravity assist. Two previously considered asteroids are selected as potential targets for the given scenario based on favorable orbital characteristics for launch dates ranging from June 27, 2020 through July 26, 2020. Initially, a simplified circular restricted 3-body problem + ideal solar sail model is utilized to survey trajectory options for a month-long launch window. Selected solutions from this data set are then converged in an N-body ephemeris + non-ideal sail model. Results suggest that NEA Scout can still perform asteroid rendezvous mission under the missed lunar gravity assist scenario with new targets, 2019 GF1, 2018 PK21, and 2007 UN12, based on the target launch dates. Further target assessment is carried out for 165 days beyond the current June 27, 2020 launch date.     

Rio de la Plata estuarine system: Relationship between river flow and frontal variability

This paper deals with the application of SeaWIFS images to characterize spatial and temporal variability of fronts in the Rio de la Plata estuarine system over the period 2000–2003. We aim to depict the relationship between river outflow and variability of fronts’ loci on monthly to ENSO-related timescales and the influence of the winds along Rio de la Plata (axial winds) on the abrupt changes in frontal dynamics over synoptic timescales. During the studied period both La Niña (July 1999–June 2000) and El Niño (April 2002–May 2003) events induced significant displacements of fronts. Three distinct fronts were analyzed between river, estuarine, coastal and marine waters of the Rio de la Plata: Main Turbidity Front, Main Marine Front, and Secondary Marine Front. Their number, location and separation seem to be mainly related to river outflow and second, to fresh (>8 m/s) axial winds. During low discharge periods (i.e. summer time and/or La Niña events) these winds induce abrupt changes in the location of fronts (100–200 km) and greater separation between them over synoptic timescale, whereas during high river discharge or ENSO years some of the variability of fronts location is explained by the river’s outflow fluctuations, especially by the high variability of the River Uruguay discharge.     

Prediction of geosynchronous electron fluxes using an artificial neural network driven by solar wind parameters

There are hundreds of satellites operating at the geosynchronous (GEO) orbit where relativistic electrons can cause severe damage. Thus, predicting relativistic electron fluxes is significant for spacecraft safety. In this study, using GOES satellite data during 2011–2020, we propose two neural network models with two hidden layers to predict geosynchronous relativistic electron fluxes at two energy channels (>0.8 MeV and > 2 MeV). The number of input neurons of the two channels (>0.8 MeV and > 2 MeV) are determined to be 36 and 44, respectively. The > 0.8 MeV model has 22 and 9 neurons in the hidden layers, while the > 2 MeV model has 25 and 15 neurons in the hidden layers. The input parameters include the north–south component of the interplanetary magnetic field, solar wind speed, solar wind dynamic pressure and solar wind proton density. Through the analysis of different time delays, we determine that the optimal time delays of two energy channels (>0.8 MeV and > 2 MeV) are 8 days and 10 days, respectively. The training set and validation set (Jan 2011-Dec 2018) are divided by the 10-fold cross-validation method, and the remaining data (Jan 2019-Feb 2020) is used to analyze the model performance as a test set. The prediction results of both energy channels show good agreement with satellite observations indicated by low RMSE (～0.3 cm^-2sr^-1s^?1), high PE (～0.8) and CC (～0.9). These results suggest that only using solar wind parameters is capable of obtaining reasonable predictions of geosynchronous relativistic electron fluxes.     

Status of the Advanced Space-based Solar Observatory

The Advanced Space-based Solar Observatory (ASO-S) was formally approved at the end of 2017. In the past two years, ASO-S underwent its official Phase-B and Phase-C studies. The Phase-B study was successfully accomplished by the end of April 2019, and the Phase-C study is being now undertaken until August 2020. Then the flight model is planned to finish within 16 months. Around the end of 2021, ASO-S will be ready in the launch state. We briefly summarize the history of ASO-S, the phase-B studies, and the phase-C studies.      

Validation of non-linear split window algorithm for land surface temperature estimation using Sentinel-3 satellite imagery: Case study; Tehran Province,Iran

In recent years, land surface temperature (LST) has become critical in environmental studies and earth science. Remote sensing technology enables spatiotemporal monitoring of this parameter on large scales. This parameter can be estimated by satellite images with at least one thermal band. Sentinel-3 SLSTR data provide LST products with a spatial resolution of 1 km. In this research, direct and indirect validation procedures were employed to evaluate the Sentinel-3 SLSTR LST products over the study area in different seasons from 2018 to 2019. The validation method was based on the absolute (direct) evaluation of this product with field data and comparison (indirect) evaluation with the MODIS LST product and the estimated LST using the non-linear split-window (NSW) algorithm. Also, two emissivity estimation methods, (1) NDVI thresholding method (NDVI-THM) and (2) classification-based emissivity method (CBEM), were used to estimate the LST using the NSW method according to the two thermal bands of Sentinel-3 images. Then, the accuracy of these methods in estimating LST was evaluated using field data and temporal changes of vegetation, which the NDVI-THM method generated better results. For indirect evaluation between the Sentinel-3 LST product, MODIS LST product, and LST estimated using NSW, four filters based on spatial and temporal separates between pairs of pixels and pixel quality were used to ensure the accuracy and consistency of the compared pairs of a pixel. In general, the accuracy results of the LST products of MODIS and Sentinel-3, and LST estimated using NSW showed a similar trend for LST changes during the seasons. With respect to the two absolute and comparative validations for the Sentinel-3 LST products, summer with the highest values of bias (?1.24 K), standard deviation (StDv = 2.66 K), and RMSE (2.43 K), and winter with the lowest ones (bias of 0.14 K, StDv of 1.13 K, and RMSE of 1.12 K) provided the worst and best results for the seasons in the period of 2018–2019, respectively. According to both absolute and comparative evaluation results, the Sentinel-3 SLSTR LST products provided reliable results for all seasons on a large temporal and spatial scale over our studied area.     

Snow depth retrieval by using robust estimation algorithm to perform multi-SNR and multi-system fusion in GNSS-IR

Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technology provides a new means of snow depth detection. Multi-satellite and multi-Signal-to-Noise Ratio (SNR) provide more data for daily high-precision snow depth retrieval, but also face the problem of data fusion and effective utilization. Therefore, this study proposes a robust estimation algorithm based on multi-satellite and multi-SNR fusion applied to the observations of a GNSS station in Alaska. This study uses four solutions (S_avg, S_med, S_{RE_avg} and S_{RE_med}) to carry out multi-system fusion snow depth inversion and precision comparison research. The S_avg has more obvious disadvantages, which is not suitable for snow depth assessment. The S_{RE_avg} and S_{RE_med} have better snow depth retrieval effects in the snowy periods. The correlation coefficient (R), root mean square error (RMSE) and mean error (ME) of the calculated snow depth using the robust estimation algorithm with respect to the nearest in-situ measurements reached 0.759, 3.7 cm and ?1.4 cm, respectively. Compared with the S_med, the R is increased by 2.0 %, the RMSE corresponds to an improvement of 2.6 %. Moreover, the ME of the snow depth retrievals, as an indicator of the measurement bias, has significantly decreased by 6.7 %. The result also shows that the snow depth inversion by the robust estimation algorithm is more consistent with the in-situ measurements, further extending and advancing the optimal algorithm for snow depth retrieval.     

绳系系统轨道机动过程中的面内摆角抑制

摘要： 针对绳系卫星系统轨道机动过程中面内摆角抑制问题进行控制器设计.仅考虑面内摆角子系统下,针对绳系系统的动力学模型,提出了分层迭代非线性滑模控制方法.证明控制方法设计的控制律使系统所有状态渐近稳定.通过数学仿真验证方法的有效性和优势.     

Improved specular point prediction precision using gradient descent algorithm

Global Navigation Satellite Systems Reflectometry (GNSS-R) utilizes GNSS signals reflected off the Earth surface for remote sensing applications. Due to weak power of reflected signals, GNSS-R receiver needs to track reflected signals by open loop. The first step is to calculate the position of specular point. The specular point position error of the existing algorithm—Quasi-Spherical Earth (QSE) Approach—is about 3 km which may cause troubles in data post-processing. In this paper, gradient descent algorithm is applied to calculate position of specular point and the calculation is based on World Geodetic System 1984 (WGS 84) ellipsoid in geodetic coordinate. The benefit of this coordinate is that it is easy to investigate the effect of real surface’s altitude. Learning rate—the key parameter of the algorithm—is adaptively adjusted according to initial error, latitude and gradient descent rate. With self-adaptive learning rate strategy, the algorithm converges fast. Through simulation and test on Global Navigation Satellite System Occultation Sounder II (GNOS II), the performances of the algorithm are validated. The specular point position error of the proposed algorithm is about 10 m. The speed of the proposed algorithm is competitive compared with the existing algorithm. The test on GNOS II shows that the proposed algorithm has good real-time performance.     

基于动力学递推算法的绳系卫星系统刚柔耦合多体模型

利用动力学递推算法建立了空间绳系卫星系统(TSS)的铰接柔性杆动力学模型.所研究的绳系系统包含两颗刚体绳端卫星和一段连接两颗卫星的柔绳,柔绳离散为一系列球铰连接的弹性杆,考虑杆不均匀的纵向一维形变,并利用球铰的运动模拟柔绳的弯曲和扭转;然后基于递推算法推导得出了该刚柔混合离散模型的动力学方程.数值仿真结果表明:所建立的绳系卫星系统模型能够很好地模拟空间系绳的各向摆振和扭转,此外,递推算法的引入能够有效地减少离散模型动力学方程的维数,从而大幅减少计算量.      

10 Years of LAGEOS-1 and 15 years of LAGEOS-2 spin period determination from SLR data

Satellite Laser Ranging (SLR) stations measure distance to the satellites equipped with Corner Cube Reflectors (CCRs). These range measurements contain information about spin parameters of the spacecraft. In this paper we present results of spin period determination of two passive satellites from SLR data only: 10 years of LAGEOS-1 (10426 values), and 15 years of LAGEOS-2 (15580 values). The measurements have been made by standard 10 Hz SLR systems and the first 2 kHz SLR system from Graz (Austria). The obtained data allowed calculation of the initial spin period of the satellites: 0.61 s for LAGEOS-1 and 0.906 s for LAGEOS-2. Long time series of the spin period values show that the satellite’s slowing down rate is not constant but is oscillating with a period of 846 days for LAGEOS-1 and 578 days for LAGEOS-2. The results presented here definitely prove that the SLR is a very efficient technique able to measure spin period of the geodetic satellites.     

Cloud attenuation statistics from radiometric measurements over a tropical location Kolkata,India

The objective of this study is to investigate cloud attenuation at 30 GHz frequency using ground-based microwave radiometric observations at a tropical location, Kolkata. At higher frequencies and lower elevation angles, cloud attenuation is of major concern at a tropical location. The location experiences high value of liquid water path (LWP), which is responsible for cloud attenuation, during the Indian summer monsoon (ISM) and pre-monsoon season. Significant amount of cloud attenuation has been observed during monsoon season at 30 GHz. Two years observations of exceedance probability of cloud attenuation and worst month statistics are presented. The variation of cloud attenuation with frequencies for different elevation angles has also been investigated. The seasonal and diurnal patterns of cloud attenuation are examined. Cloud attenuation, inferred from radiometric measurements before rain commencement, has been compared to rain attenuation at Ku-band. Exceedance probabilities of cloud and rain attenuation have been compared.     

Effect of evaporation and solutocapillary-driven flow upon motion and resultant deposition of suspended particles in volatile droplet on solid substrate

Particle motion in a volatile droplet on a solid surface, especially the behavior of particles depositing in the vicinity of a solid–liquid–gas boundary line (contact line) is focused. This phenomenon is called the ‘coffee stain problem’. Motion and deposition of the particles suspended in distilled water droplets and distilled water–ethanol mixture droplets are discussed. The spatio-temporal particle motion is analyzed by the three-dimensional particle tracking velocimetry (3D PTV). A discussion of the morphology of the particles stuck to the solid surface after the dryout of the droplet is also given.     

Evaluation of rapid phase clock/bias products for PPP ambiguity resolution and its application to the M7.1 2019 Ridgecrest,California earthquake

Precise point positioning with ambiguity resolution (PPP-AR) is a useful tool for high-precision geodetic and geophysical applications, while phase bias products are the prerequisite to implement PPP-AR. Wuhan University has been providing the final (the best operationally post-processing solution based) phase clock/bias products with a latency of two weeks since March of 2019, while a dedicated open-source software package PRIDE PPP-AR is released to leverage these products for high-precision positioning. In order to satisfy some both time and precision critical applications, such as rapid earthquake response, Wuhan University also released rapid (with comparable quality but with much shorter delivery latency) phase clock/bias products with a latency of less than 24 h and updated PRIDE PPP-AR in July 2019. We first introduce the phase clock/bias generation and validation schemes and the maintenance of routine products provision. Then, with 14 days (July 2 to July 15 in 2019) of GPS data collected from 146 globally distributed IGS (International GNSS Service) stations, we evaluated the positioning performance of the rapid products with respect to their final counterparts. It is found that positioning precision of PPP-AR using rapid products is comparable to that using final products, especially in kinematic positioning mode. When rapid products are used, the RMS of PPP-AR in static mode with respect to IGS weekly solutions can reach 1.7 mm, 1.8 mm and 5.5 mm in the east, north and up components, respectively. Furthermore, the RMS of epoch-wise positions with respect to daily solutions for the east, north and up components are 0.51 cm, 0.57 cm and 1.51 cm for PPP-AR with rapid products in kinematic mode. It demonstrates that the rapid phase clock/bias products can sufficiently meet the precision requirement of most geodetic and geophysical applications yet with much shorter time delay. Finally, we study the July 6th M7.1 2019 Ridgecrest, California earthquake using the rapid phase clock/bias products and demonstrate their comparable performance against the final products.     

Quantitative contribution of climate change and anthropological activities to vegetation carbon storage in the Dongting Lake basin in the last two decades

The Dongting Lake Basin is an important hydrological regulation and flood storage area in the Yangtze River Basin, which plays an important role in maintaining regional ecological security. The watershed vegetation and its carbon sequestration capacity have changed dramatically due to climate change and human activities in the last two decades. In this paper, the monthly and annual vegetation net primary productivity (NPP) of the Dongting Lake basin during 2000 to 2020 was firstly estimated using the improved Carnegie-Ames-Stanford Approach (CASA) model. Then the multi-year NPP change trend and its significance were analyzed based on Theil-Sen median and Mann-Kendall method. Subsequently, the Hurst index was used to simulate the vegetation NPP persistence in the study area. Finally, the driving mechanisms of vegetation NPP changes in the study area were explored using partial correlation coefficients and residual analysis. The results demonstrated that: 1) The annual average NPP in the basin showed a fluctuating and increasing trend from 273.54 to 718.30 g C/m²·yr¹ during 2000 to 2020, and except for autumn, all seasons (spring, summer, winter) and annual NPP series showed an upward trend. The spatial distribution of vegetation NPP is characterized by an asymmetrical horseshoe shape in general, with high values in the west, south and east parts, and low values in the Lake area; 2) During the study years, about 84.38 % of the basin area showed a significant and extremely significant increase of NPP; 3) The future trend of vegetation NPP in the basin shows that the area of decrease (22.79 %) is more than the area of increase (11.35 %). The Chang-Zhu-Tan urban agglomeration will generally show a continuous and extremely significant reduction trend, while parts of Dongting Lake will show a continuous and extremely significant increase trend; 4) The correlation between solar radiation and NPP is stronger than the other two meteorological factors (precipitation and temperature). Temperature has a significant inhibitory effect on NPP, solar radiation has a significant promoting effect on NPP, and the effect of precipitation on NPP was relatively complicated. The relative importance of meteorological factors on vegetation NPP was ranked as follows: solar radiation > precipitation > temperature. The impacts of both climate change and human activities on NPP changes showed great spatial variability, and the positive contributions (89.81 % for climate change and 82.87 % for human activities) were both greater than the negative contributions.     

Application of support vector machine combined with K-nearest neighbors in solar flare and solar proton events forecasting

The support vector machine (SVM) combined with K-nearest neighbors (KNN), called the SVM-KNN method, is new classing algorithm that take the advantages of the SVM and KNN. This method is applied to the forecasting models for solar flares and proton events. For the solar flare forecasting model, the sunspot area, the sunspot magnetic class, and the McIntosh class of sunspot group and 10 cm solar radio flux are chosen as inputs; for the solar proton event forecasting model, the inputs include the longitude of active regions, the flux of soft X-ray, and those for the solar flare forecasting model. Detailed tests are implemented for both of the proposed forecasting models, in which the SVM-KNN and the SVM methods are compared. The testing results demonstrate that the SVM-KNN method provide a higher forecasting accuracy in contrast to the SVM. It also gives an increased rate of ‘Low’ prediction at the same time. The ‘Low’ prediction means occurrence of solar flares or proton events with predictions of non-occurrence. This method show promise for forecasting models of solar flare and proton events.     

Assessing the performance of BDS-3 for multi-GNSS static and kinematic PPP-AR

As of 2021, a total of four different GNSS constellations – namely, GPS, GLONASS, Galileo, and BDS-3 – can be used with Full Operational Capability (FOC). In this work, the contribution of BDS-3 FOC to GPS + GLONASS + Galileo (GRE) PPP-AR is investigated, considering the three different cut-off angles (7°, 30°, and 45°) and different lengths of static observation sessions (24-, 12-, 6-, 3-, 1-, 0.5-, 0.25-hour). The data of 31 IGS-MGEX stations is processed with GRE PPP-AR and GREC3 (GPS + GLONASS (using float mode) + Galileo + BDS-3) PPP-AR modes. The results showed that BDS-3 degraded the horizontal (except for 24-h sessions) and vertical accuracy of static GRE PPP-AR solutions regardless of the elevation cutoff angle and observation time. The kinematic results showed that BDS-3 significantly contributed to the accuracy of GRE kinematic PPP-AR for 30° and 45° cutoff angles. The convergence time analysis showed that BDS-3 only contributes to GRE kinematic PPP-AR for the vertical component.     

2021 Turkey mega forest Fires: Biodiversity measurements of the IUCN Red List wildlife mammals in Sentinel-2 based burned areas

Mega wildfires are one of the environmental disasters worldwide. This study evaluates the pre-fire species diversity and the indirect effects, including habitat loss for one of the largest wildfires in Manavgat (Antalya-Turkey) in 2021, with a two-step methodology. Here, (1) burnt areas in the Manavgat district (2021) were detected with remote sensing data from Sentinel-2A by delta Normalized Burn Ratio calculation for a selected area in Google Earth Engine, and (2) mammals' habitat vector data of International Union for Conservation of Nature (IUCN) Red List were integrated into Habitat and Biodiversity modelling of Terrset to analyze the alpha, beta, gamma diversity and Range Restriction Index for the wildfire region. In the total 4210 km² study area, 696 km² of the area was damaged by different fire severity; also, there were 56 mammal species' habitats here. These species include bats (i.e. Nyctalus leisleri), felids (i.e. Felis chaus), rodents (i.e. Rattus norvegicus) and large mammals (i.e. Ursus arctos). 88 % of these species are in IUCN's Least Concern category. The remaining classes are Near Threatened (3.7 %) and Vulnerable (7.4 %). This study also indicated that the burnt area's species richness does not totally consist of endemic species. Therefore, pre-fire species richness analyses of this study can be a base for further studies about the species' post-fire activity and occupancy.Furthermore, the 2021 mega wildfires show us the necessity of wildfire monitoring and risk studies in the entire Mediterranean ecosystem to evaluate the risks to the Sustainable Development Goals. Therefore, post-fire spatial data, fire migration monitorization, and recording of the species' activities should be performed temporally. In this way, the ability of wildlife's recovering, and the direct and indirect effects of the fire will be examined for ecosystems in the long term.     

Solar magnetic feature detection and tracking for space weather monitoring

We present an automated system for detecting, tracking, and cataloging emerging active regions throughout their evolution and decay using SOHO Michelson Doppler Interferometer (MDI) magnetograms. The SolarMonitor Active Region Tracking (SMART) algorithm relies on consecutive image differencing to remove both quiet-Sun and transient magnetic features, and region-growing techniques to group flux concentrations into classifiable features. We determine magnetic properties such as region size, total flux, flux imbalance, flux emergence rate, Schrijver’s R-value, R^∗ (a modified version of R), and Falconer’s measurement of non-potentiality. A persistence algorithm is used to associate developed active regions with emerging flux regions in previous measurements, and to track regions beyond the limb through multiple solar rotations. We find that the total number and area of magnetic regions on disk vary with the sunspot cycle. While sunspot numbers are a proxy to the solar magnetic field, SMART offers a direct diagnostic of the surface magnetic field and its variation over timescale of hours to years. SMART will form the basis of the active region extraction and tracking algorithm for the Heliophysics Integrated Observatory (HELIO).     

Boundary of nighttime ozone chemical equilibrium in the mesopause region: Improved criterion of determining the boundary from satellite data

A modified derivation of the criterion of nighttime ozone chemical equilibrium (NOCE) in the mesopause region is presented. According to 3D model calculations, the improved criterion reproduces the lower boundary of the equilibrium much better than its earlier version. Processing of the SABER/TIMED data of 2021 has shown that the modified criterion elevates the NOCE boundary by ～ 0.1–1.7 km, depending on latitude and season. The proposed method of determining the condition of chemical equilibrium can be used to analyse the equilibrium of many trace gases in the stratosphere and troposphere important for different practical applications.