Solar Phase Research Articles

Large Amplitude Fluctuations in the Alfvénic Solar Wind

Large amplitude fluctuations, often with characteristics reminiscent of large amplitude Alfven waves propagating away from the Sun, are ubiquitous in the solar wind. Such features are most frequently found within fast solar wind streams and most often at solar minimum. The fluctuations found in slow solar wind streams usually have a smaller relative amplitude, are less Alfvenic in character and present more variability. However, intervals of slow wind displaying Alfvenic correlations have been recently identified in different solar cycle phases. In the present paper we report Alfvenic slow solar wind streams seen during the maximum of solar activity that are characterized not only by a very high correlation between velocity and magnetic field fluctuations (as required by outwardly propagating Alfven modes) – comparable to that seen in fast wind streams – but also by higher amplitude relative fluctuations comparable to those seen in fast wind. Our results suggest that the Alfvenic slow wind has a different origin from the slow wind found near the boundary of coronal holes, where the amplitude of the Alfvenic fluctuations decreases together with decreasing the wind speed.

The Sun at TeV energies: Gammas, neutrons, neutrinos and a cosmic ray shadow

High energy cosmic rays reach the surface of the Sun and start showers with thousands of secondary particles. Most of them will be absorbed by the Sun, but a fraction of the neutral ones will escape and reach the Earth. Here we incorporate a new ingredient that is essential to understand the flux of these solar particles: the cosmic ray shadow of the Sun. We use Liouville’s theorem to argue that the only effect of the solar magnetic field on the isotropic cosmic ray flux is to interrupt some of the trajectories that were aiming to the Earth and create a shadow. This shadow reveals the average solar depth crossed by cosmic rays of a given rigidity. The absorbed cosmic ray flux is then processed in the thin Solar surface and, assuming that the emission of neutral particles by low-energy charged particles is isotropic, we obtain (i)a flux of gammas that is consistent with Fermi-LAT observations, (ii) a flux of 100–300 neutrons/(year m2) produced basically in the spallation of primary He nuclei, and (iii) a neutrino flux that is above the atmospheric neutrino background at energies above 0.1–0.6 TeV (depending on the solar phase and the zenith inclination). More precise measurements of the cosmic ray shadow and of the solar gamma flux, together with the possible discovery of the neutron and neutrino signals, would provide valuable information about the magnetic field, the cycle, and the interior of the Sun.

Mechanical Design and Analysis of Detector Head Assembly for Space bone High-Resolution Imaging Sensor

The imaging sensors employed in satellites are subjected to a wide range of vibratory loads induced during the launching phase. The effect of temperature change also needs to be looked upon while designing the structure of the imaging sensor as satellite passes through the solar and lunar phase. This project work goes into depth of challenges incurred during launching and in-orbit operation. The research includes development of lightweight structure, incorporating flexure interface to house detector head assembly (DHA) components. The design of flexural mount is a novel approach that not only arrests the deformation of the imaging sensor but also restricts structural stresses to affect the performance of the imaging sensor. This article showcases the assessment of three different mechanical designs of DHA through finite element simulation results computed in ANSYS workbench environment. The survivability of DHA structure has been checked under 55g quasi-static loading to simulate launch vibration along with 10°C thermal gradient corresponded to the in-service orbital motion. In this research work, AL6061-T6 and Kovar has been chosen for various design components of the DHA as they are space qualified materials. Though both material options showed similar performance, due to low density, ready availability and cost effectiveness leads to select Al6061-T6 material for the fabrication of DHA components.

Enhancement of the productivity for single solar still with ultrasonic humidifier combined with evacuated solar collector: An experimental study

Desalination of brackish and sea water with renewable energy source is an important economical solution for obtaining potable water. There are different techniques were used to improve the solar still productivity. So, this research deals with improving the solar still productivity by using ultrasonic waves, reflectors and phase change material. A single solar still was designed, fabricated and tested under the climate conditions of Alexandria, Egypt. The solar still has base dimensions of 1 m × 1 m and integrated with an evacuated solar collector of 200 l capacity. Six ultrasonic humidifiers were installed to strengthen the evaporation frequency of the water basin. A photovoltaic solar panel of 280 W was used to provide the power for ultrasonic humidifiers. An evacuated solar collector was used to provide solar still with hot sprayed water inside the solar still after 13:00 local time. Experimental tests have constructed to powerfully assess the daily productivity of fresh water during the three summer months under the same climate conditions. Four cases were studied to investigate the daily fresh water productivity at different embedded components with the solar still: phase change material; ultrasonic humidifiers and phase change material; evacuated solar collector and phase change material and the forth case is phase change material and ultrasonic humidifiers combined with evacuated solar collector. The results showed that the maximum daily productivity are 5.34 and 7.4 kg per day for 25 and 35 mm water depths respectively in case of using solar still with phase change material and ultrasonic humidifiers integrated with an evacuated solar still. The ultrasonic humidifier was influential in case of integrating evacuated solar collector and improved the daily productivity by 25 and 44% at water depths of 25 and 35 mm respectively.

Dayside cloud top structure of Venus retrieved from Akatsuki IR2 observations

We describe the dayside cloud top structure of Venus as retrieved from 93 images acquired at a wide variety of solar phase angles (0–120°) using the 2.02-μm channel of the 2-μm camera (IR2) onboard the Venus orbiter, Akatsuki, from April 4 to May 25, 2016. Since the 2.02-μm channel is located in a CO2 absorption band, the sunlight reflected from Venus allowed us to determine the cloud top altitude corresponding to unit aerosol optical depth at 2.02 μm. First, the observed solar phase angle dependence and the center-to-limb variation of the reflected sunlight in the region equatorward of 30° were used to construct a spatially averaged cloud top structure characterized by cloud top altitude zc, Mode 2 modal radius rg,2, and cloud scale height H, which were 70.4 km, 1.06 μm, and 5.3 km, respectively. Second, cloud top altitudes at individual locations were retrieved on a pixel-by-pixel basis with an assumption that rg,2 and H were uniform for the entire planet. The latitudinal structure of the cloud top altitude was symmetric with respect to the equator. The average cloud top altitude was 70.5 km in the equatorial region and showed a gradual decrease of ~2 km by the 45° latitude. It rapidly dropped at latitudes of 50–60° and reached 61 km in latitudes of 70–75°. The average cloud top altitude in the region equatorward of 30° showed negligible local time dependence, with changes up to 1 km at most. Local variations in cloud top altitude, including stationary gravity wave features, occurred within several hundreds of meters. Although long zonal or tilted streaky features poleward of ~45° were clearly identifiable, features in the low and middle latitudes were usually subtle. These did not necessarily appear as local variations at the cloud top level, where mottled and patchy UV patterns were observed, suggestive of convection and turbulence at the cloud top level.

Performance evaluation of IRI-2016 with GPS-derived TEC at the meridian of 110oE in China of 2014

The latest version of the International Reference Ionosphere (IRI-2016) is evaluated for ionospheric total electron content (TEC) over China during a high solar activity phase of 2014. TEC is derived from observations by the GNSS receiver network of Crustal Movement Observation Network of China (CMONOC). IRI-2016 uses the NeQuick option for the topside electron density profile. The comparisons shows that IRI-2016 underestimates GPS-TEC slightly in spring and winter, but overestimates slightly in summer and autumn at the mid-latitudes of 35oN-45oN. The deviation of TEC estimation is about 5 TECU at 35oN-45oN. As a whole, IRI-2016 underestimates GPS-TEC at the lower latitudes of 15oN-35oN, and the deviations of TEC estimation are about 4 TECU, 10 TECU, 26 TECU and 33 TECU in summer, autumn, winter and spring, respectively. The largest difference between IRI-TEC and GPS-TEC is about 50 TECU at the northern crest of equatorial ionization anomaly (EIA) in spring. There is an obvious winter anomaly for GPS-TEC, while it is not predicted by IRI-2016. Due to the influence of nighttime enhancement of ionosphere, the extreme latitudinal gradient of GPS-TEC appears after sunset in spring and winter, while it is not shown on that of IRI-TEC. Because of the equatorial fountain effect, the maximum time rate of GPS-TEC appears at the beginning of EIA (∼10:00–11:00 LT) in equinoxes, while it is not shown on that of IRI-TEC. The most rapid decrease of IRI-TEC appears after sunset (∼19:00 LT) in spring and winter, while GPS-TEC quickly decreases at ∼22:00 LT.

Quantifying the latitudinal representivity of in situ solar wind observations

Advanced space-weather forecasting relies on the ability to accurately predict near-Earth solar wind conditions. For this purpose, physics-based, global numerical models of the solar wind are initialized with photospheric magnetic field and coronagraph observations, but no further observation constraints are imposed between the upper corona and Earth orbit. Data assimilation (DA) of the available in situ solar wind observations into the models could potentially provide additional constraints, improving solar wind reconstructions, and forecasts. However, in order to effectively combine the model and observations, it is necessary to quantify the error introduced by assuming point measurements are representative of the model state. In particular, the range of heliographic latitudes over which in situ solar wind speed measurements are representative is of primary importance, but particularly difficult to assess from observations alone. In this study we use 40+ years of observation-driven solar wind model results to assess two related properties: the latitudinal representivity error introduced by assuming the solar wind speed measured at a given latitude is the same as that at the heliographic equator, and the range of latitudes over which a solar wind measurement should influence the model state, referred to as the observational localisation. These values are quantified for future use in solar wind DA schemes as a function of solar cycle phase, measurement latitude, and error tolerance. In general, we find that in situ solar wind speed measurements near the ecliptic plane at solar minimum are extremely localised, being similar over only 1° or 2° of latitude. In the uniform polar fast wind above approximately 40° latitude at solar minimum, the latitudinal representivity error drops. At solar maximum, the increased variability of the solar wind speed at high latitudes means that the latitudinal representivity error increases at the poles, though becomes greater in the ecliptic, as long as moderate speed errors can be tolerated. The heliospheric magnetic field and solar wind density and temperature show very similar behaviour.

On the Relationships Between Sunspot Number and Solar Radio Flux at 10.7 Centimeters

Regression analysis and neural network training procedures are used to study the relationship between sunspot number (SSN) and solar flux at 10.7 cm (F10.7). Measurements of SSN and F10.7 for the periods from December 1963 to January 2019 (including the periods from Solar Cycles 20 to 24) were used. The value of correlation coefficient between SSN and F10.7 for the entire data used in the study is 0.95, showing that the parameters are well correlated. Results from the study reveal that there are remarkable differences on the relationship between SSN and F10.7 during the four solar cycle phases of low (-activity), high (-activity), ascending, and descending. The relationships are identical for the ascending and descending phases when the SSNs are lower than about 150, but the regression curves diverge as the SSNs increase beyond that limit. A conspicuously changed relationship between SSN and F10.7 is also observed for years 2014 and 2015 in which the annual SSN-versus-F10.7 plots for those years are visibly above those of the prior years. The results indicate that F10.7 values can be predicted from SSNs using neural networks, with root-mean-square errors of about 13.68 solar flux units. Results from the neural network procedure also indicate that a newly introduced solar cycle phase index (defined to indicate the phase of the solar cycle in which given observations belong) was effective in improving the neural network predictions.

Ionospheric Modeling and Forecasting Services of GNSS

The study of ionospheric variability is vital for refining and predicts services of GNSS (Global Navigation Satellite System) applications. The GNSS service provides an explicitly obtainable resource GNSS information, goods and services in support of the earthly reference structure. GNSS is provides an Earth observation, navigation, positioning, timing and other applications that an assistance Society and Science. To investigate the variations in the daily averaged TEC (Total Electron Content) by taking several model components such as solar activity component, geomagnetic activity and periodic components at different latitudes ranging from 10˚N to 26˚N for the year 2018. The presented results would be useful to download, processing and analysis the IGS (International GNSS Service) data. MSSA model can reproduce quite well the observed values of GPS-TEC by utilizing only the first 4 singular modes and constitutes 99% of the total variance. The data is transformed into the singular values which are used for forecasting a noiseless time series. The proposed system results show that higher accuracy is achieved by MSSA (Multivariate Singular Spectrum Analysis) based model. It can also be noted that the training of MSSA is much faster and achieves higher learning accuracy, lowest training time. MSSA is effective even the space weather conditions are active during different solar phase periods.

Improving clean energy greenhouse heating with solar thermal energy storage and phase change materials

AbstractGreenhouses consume a great deal of energy to heat their building envelopes. The strategic integration of solar energy and thermal energy storage (TES) can help to boost energy performance and reduce the carbon emission in the sector. In this paper, the benefits of adding phase change materials (PCM) to the water tank of a solar heating system have been evaluated using the Transient System Simulation (TRNSYS) program. Initially, the hourly heating load of a reference greenhouse was evaluated using TRNSYS software. The results were validated with natural gas consumption data. The validated simulation was then used to investigate the impact of PCM on the performance of a large‐scale solar energy system. Four system configurations were evaluated; no PCM materials in the tank, then 20%, 40%, and 60% of the water tank volume occupied by PCM. Energy performance improvements of 10% to 14% were observed by increasing the proportion of PCM amounts over the baseline conventional system. Finally, an economic study was conducted to investigate the cost feasibility of different PCM concentrations. It was shown that PCM price, cost of natural gas, and carbon tax are the principal influence factors on the payback period.

Power improvement of finned solar photovoltaic phase change material system

Fins enabled Phase Change Material (FPCM) has potential to take away the thermal energy from photovoltaic (PV) and increase the efficiency. This study analyses the PV-FPCM arrangement and presents a mathematical model. The arrangement is studied under various azimuths of wind, its flow rates, temperature of surroundings, phase change temperature and dimensions of FPCM confinement. The duration of power improvement of PV using FPCM, power production, efficiency improvement and Power-Voltage (P–V) curves are reported. The outcomes convey that as azimuth of wind changes from 75° to 0°, the duration of power improvement elevates from 6.1 h to 7.3 h for 5 cm deep FPCM confinement. It increases from 4.9 h to 5.8 h for 4 cm deep FPCM confinement. Moreover, decrement in wind flow rate from 6 m/s to 1 m/s, contracts the duration of power improvement from 7.8 h to 6.1 h.

One-Day-Shock, Two-Days-Shock and Three-Days-Shocks foF2 Diurnal Variation with Solar Cycle Phases at Ouagadougou Station from 1966 to 1998. Comparison with IRI 2012 Predictions

The present work concerns foF2 time variation at Ouagadougou station for three solar cycles (from cycle 20 to cycle 22). We not only investigate solar cycle phase dependence under shock activity that is divided into one-shock-activity, two-shock-activity and three-shock-activity but also compare the IRI 2012 model values with the data carried out at Ouagadougou station. This study reveals that there is no one-day-shock during solar minimum phase. For the other solar cycle phases IRI 2012 reproduces the ionosphere electrodynamics at daytime except during the increasing phase. During night time the model is not suitable. The best subroutine under one-day-shock activity is URSI for increasing and decreasing phases. During the maximum phase it is CCIR. For two-days-shock activity IRI 2012 reproduces the ionosphere electrodynamics during the minimum and the increasing phases. The best subroutine is CCIR during the minimum phase and URSI for the other solar cycle phases. For three-days-shock activity IRI 2012 is not suitable. The best model is URSI for all solar cycle phases.

Application of Singular Spectrum Analysis Using Artificial Neural Networks in TEC Predictions for Ionospheric Space Weather

The prediction of the ionospheric state has become increasingly important as more and more terrestrial and space-based radiocommunication systems rely on the ionospheric space weather. This article presents a new ionospheric prediction model, named the singular spectrum analysis-artificial neural network (SSA-ANN) model. SSA is used as a preprocessing tool for the ionosphere total electron content (TEC) prediction based on the ANN approach. The hourly global positioning system (GPS)-TEC observations from the period of 2009–2017 at the Bangalore (13.02° N and 77.57° E) station are taken into account for analysis. The quick convergence of the SSA decomposition makes it possible to use the first four SSA modes to represent 99.57% of the total variance of the GPS-TEC dataset. The root mean square error between the observations and the SSA-ANN model TEC value is 1.40 TECU for the period of 2009–2017, and the correlation coefficient is 0.99. The performance of SSA-ANN is evaluated using autoregressive moving average (ARMA) and International Reference Ionosphere-16 (IRI-16) models in three different cases of solar phase periods, namely the ascending solar phase (ASP), high solar phase (HSP), and descending solar phase (DSP), and in different seasons. The SSA-ANN model predicts the absence of winter anomaly during the ASP period (2012), but the ARMA model and IRI models failed to predict the absence of the anomaly. The proposed SSA-NN model resulted in higher prediction accuracy and reduced training and testing times, which would be useful for the development of an ionospheric predicting system.

Study on enhancing heat transfer performance of spiral groove tube in phase change heat storage for solar energy

Based on the energy storage problem for solar energy utilization and the advantages of spiral groove tube heat exchanger, spiral groove tubes were used in the solar energy phase change heat storage. The thermal storage process of heat reservoir was simulated numerically. Firstly, the simulation method and the reliability of the used model are verified experimentally with smooth tube. Using spiral groove tube as water flow pipe and phase change material as heat storage medium, The three-dimensional model of heat storage was built by Gambit software and the grids were divided by ICEM. The heat storage process in the spiral groove tube and smooth tube heat storage were numerically simulated and the heat transfer enhancing effect was investigated. The influence of structural parameters such as groove pitch and groove depth on the heat storage process is simulated numerically and the influence rules are analyzed. The results show that the convective heat transfer intensity and heat transfer capability are enhanced when the smooth tubes are substituted by spiral groove tubes in the phase change heat storage and the heat storage time becomes shorter. In the range of this paper, the optimal structural parameters of spiral groove tube is groove pitch p=7mm and groove depth e=0.4mm.

Critical Frequency foF2 Variations at Korhogo Station from 1992 to 2001 Prediction with IRI-2012

In this paper we report the foF2 data measured at Korhogo station (Lat. 9.3° N; Long. 354.6° E; dip. 0.6° S) compared to predictions with IRI-2012 subroutine URSI and CCIR for different solar cycle phases (minimum, ascending, maximum, descending) and different geomagnetic activity classes (quiet, fluctuating, recurrent, shock). According to our investigations, predictions with IRI are in agreement with the measured data during daytime and show significant differences between them at night-time and especially before sunrise. Except at solar minimum, the gap between predictions and measured data are more appreciable during recurrent and shock conditions compared to quiet and fluctuating conditions. Our results also show that only URSI model expresses the signature of EXB drift phenomenon at solar maximum phase during the recurrent days and at ascending phase for fluctuating activity.

Responses of Multiday Oscillations in the Nighttime Thermospheric Temperature to Solar and Geomagnetic Activities Measured by Fabry‐Perot Interferometer in China

AbstractThe nighttime thermospheric temperature (~250 km) measured by FPI (Fabry‐Perot interferometer) at Xinglong (40.2°N, 117.4°E) station from 2010 to 2018 is used to investigate the responses of the multiday oscillations (periods of 27, 13.5, 9, and 7 days) in thermospheric temperature to oscillations in F10.7 and Ap index. The results show that (1) the 27‐, 13.5‐, 9‐, and 7‐day oscillations in the thermospheric temperature depend on solar phases. The 27‐day oscillations are predominant during solar maximum, while the 13.5‐, 9‐, and 7‐day oscillations are significant during solar ascending phase, and (2) the 27‐day oscillations in the thermospheric temperature are highly correlated (correlation coefficient >0.8) with the F10.7 and Ap index. Especially during solar maximum phase, the high‐correlation occurrence rate between the thermospheric temperature and F10.7 (Ap index) is up to 278.5 (191.0) days per year; (3) the 13.5‐, 9‐, and 7‐day oscillations are highly correlated with Ap index during the solar descending phase; and (4) the phase lags corresponding to the largest high‐correlation occurrence rates are mostly about 0.1π during specific solar phase.

Maximum Proton Trapping Energy in the Earth Radiation Belt

During the PAMELA satellite experiment started in 2006 onboard the Resurs-DK1 spacecraft (350–600 km, an inclination of 70°), cosmic ray charged particle fluxes in low near-Earth orbits were measured to the beginning of 2016. The data obtained during the experiment on high-energy proton (0.1–10 GeV) fluxes in the radiation belt made it possible to measure maximum proton trapping energies in various solar activity phases. The measurement results showed that the maximum proton trapping energy at L shells of 1.16–1.22 in the periods of both solar activity minimum (2009) and maximum (2014) was ∼2 GeV.

A Statistical Classifier for Historical Geomagnetic Storm Drivers Derived Solely From Ground‐Based Magnetic Field Measurements

Solar wind observations show that geomagnetic storms are mainly driven by interplanetary coronal mass ejections (ICMEs) and corotating or stream interaction regions (C/SIRs). We present a binary classifier that assigns one of these drivers to 7,546 storms between 1930 and 2015 using ground‐based geomagnetic field observations only. The input data consists of the long‐term stable Hourly Magnetospheric Currents index alongside the corresponding midlatitude geomagnetic observatory time series. This data set provides comprehensive information on the global storm time magnetic disturbance field, particularly its spatial variability, over eight solar cycles. For the first time, we use this information statistically with regard to an automated storm driver identification. Our supervised classification model significantly outperforms unskilled baseline models (78% accuracy with 26[19]% misidentified interplanetary coronal mass ejections [corotating or stream interaction regions]) and delivers plausible driver occurrences with regard to storm intensity and solar cycle phase. Our results can readily be used to advance related studies fundamental to space weather research, for example, studies connecting galactic cosmic ray modulation and geomagnetic disturbances. They are fully reproducible by means of the underlying open‐source software (Pick, 2019, http://doi.org/10.5880/GFZ.2.3.2019.003)

Multi wavelength optical broad band photometric properties of a representative sample of geostationary satellites

We present the results of multi-wavelength optical observations, using B, V, R and I band filters, of a sample of 61 active geostationary communications satellites, on 2015 July 9–11. These observations were done outside the glinting season, with a longitudinal solar angle smaller than 6° and a latitudinal solar phase angle of ~16.5°. This approach enabled us to determine the distribution of quiescent magnitudes and colors of these targets during a period of the night when they are expected to be the brightest. We present the distribution of magnitudes and colors of the sample. We find that the colors of these satellites are in general redder than the Solar spectrum, with a wide distribution of values (0.62<B-V<1.49,1.00<B-R<2.28,1.31<B-I<3.07,0.34<V-R<0.90,0.63<V-I<1.69,0.27<R-I<0.79). Satellites from different manufacturers are found to cluster around specific colors in color-color plots, indicating that this information can be used to identify different satellites and resolve cross tagging issues. We also investigate whether the colors of satellites change with time and find that in most cases there is no significant change to these properties as the satellites age.

Performance of NeQuick-2, IRI-Plas 2017 and GIM models over Ethiopia during varying solar activity periods

This paper investigates the performance of NeQuick-2, the latest version of International Reference Ionosphere IRI extended to the Plasmasphere (IRI-Plas 2017), and Global Ionospheric Map (GIM) models over four stations deployed in Ethiopia during medium, high, and low solar activity periods. The monthly and seasonal mean diurnal variations of Vertical Total Electron Content (VTEC) derived from NeQuick-2, IRI-Plas 2017 and GIM models were compared with the GPS-VTEC values in terms of Root-Mean-Square Errors (RMSE) and correlation coefficients (r). It was found that the monthly and seasonal mean diurnal VTEC variations agree fairly well with the GPS-VTEC at all stations although with some offsets. For the entire years of the study, the highest monthly mean VTEC variation is observed during equinox months, whereas minimum in the solstice months. The NeQuick-2 model monthly and seasonal mean VTEC output were generally better than IRI-Plas 2017 and GIM models output in most of the stations during medium solar activity year of 2012. For all models, the significant discrepancy (i.e, overestimations or underestimations) is observed during daytimes and seasons of high solar activities. In some cases, the IRI-Plas 2017 model displayed poor performance during medium and low solar activity periods, while it showed a better agreement for some stations (e.g. asos, armi, and bdmt) during high solar activity phase (especially in March equinox and December solstice). The performance of GIM model was good for most of the stations during low-solar activity year of 2016 and during the study years for adis, while it has poor performance during the periods of high solar activity year of 2014. All models correlated well, although GIM model was highly correlated with the GPS-VTEC value (r ≥0.99). The IRI-Plas 2017 model correlated better with the GPS-VTEC than NeQuick-2 model during the study years. Moreover, the performance of IRI-Plas 2017 model was better during high than low and medium periods of solar activity years. The GIM model has better performance for most stations (e.g. adis, asos, and bdmt) over the study region during low-solar activity period.