Changes in Irradiance and Illuminance on Earth Surface during 11-Year Solar Activity Cycle

2020 ◽  
pp. 61-66
Author(s):  
Alexander V. Leonidov
Keyword(s):  
Solar Activity ◽  
Solar Cycle ◽  
Solar Radiation ◽  
Visible Region ◽  
Earth Surface ◽  
Solar Cycles ◽  
Spectral Window ◽  
Solar Altitude ◽  
The Earth ◽  
Analytic Expression

The article formulates the analytic expression approximating the sequence of Gregorian 11-year solar cycles and the expression of solar activity within one cycle. The dependences of effective thermodynamic temperature of the Sun photosphere and the solar constant, and the solar illuminance constant at the upper border of Earth atmosphere on the year number within one solar cycle were obtained. The generalised analytic expression for integral transmittance of atmosphere (within its spectral window) on the Earth surface for the direct and diffuse components of solar radiation and their sums at different solar altitude angles is presented. The analytic expressions of dependences of irradiance and illuminance on the Earth surface within spectral window of atmosphere and within the visible region of solar radiation spectrum on the year number within a certain solar cycle at different solar altitude angles are obtained. The results of calculation of direct and diffuse components of irradiance and illuminance and their sums in the case of clear sky are presented for example. The proposed approach allows similar calculations to conduct for different types of sky cover.

Analytic Representation of Illuminance on the Earth Surface with Different Types and Conditions of Cloud Cover over the 11-Year Solar Activity Cycle

2021 ◽  
pp. 42-50
Author(s):  
Alexander V. Leonidov
Keyword(s):  
Solar Activity ◽  
Cloud Cover ◽  
Activity Cycle ◽  
Solar Activity Cycle ◽  
Earth Surface ◽  
Solar Altitude ◽  
The Earth ◽  
Different Types ◽  
Solar Altitude Angle ◽  
Construction Practice

The article describes the analytical expression approximating experimental data on daily natural illuminance on the Earth surface with different types and conditions of cloud cover over the 11-year solar activity cycle within the solar altitude angle range of 0 ° to 90 °. The values of the direct, diffused, and total illuminance on the Earth surface with different types and conditions of the cloud cover and, to some extent, of the substrate were defined and summarised in tables. The data presented may be used as part of the visual perception studies, light and engineering calculations, architecture and construction practice, etc.

Analytic Representation of Relation between Solar Altitude Angle and Local Time for Calculating Daylight Irradiance and Illuminance of the Earth Surface

2020 ◽  
pp. 34-38
Author(s):  
Alexander V. Leonidov
Keyword(s):  
Local Time ◽  
Analytic Form ◽  
Random Point ◽  
Analytic Representation ◽  
Earth Surface ◽  
Derived Relations ◽  
Solar Altitude ◽  
The Earth ◽  
Analytic Expression ◽  
Solar Altitude Angle

The analytic expression which sets relation between the solar altitude angle and local time at a random point of the Earth surface on a random day of a year is obtained. The obtained expression and derived relations allow one to conduct calculations of daylight irradiance and illuminance of the Earth surface in analytic form.

scholarly journals On the Prediction of Solar Cycles

Solar Physics ◽  
2021 ◽  
Vol 296 (1) ◽  
Author(s):  
V. Courtillot ◽  
F. Lopes ◽  
J. L. Le Mouël
Keyword(s):  
Solar Activity ◽  
Solar Cycle ◽  
Transfer Function ◽  
Singular Spectrum Analysis ◽  
Activity Cycle ◽  
Solar Activity Cycle ◽  
Planetary Motion ◽  
Data Sets ◽  
Solar Cycles ◽  
Jovian Planets

AbstractThis article deals with the prediction of the upcoming solar activity cycle, Solar Cycle 25. We propose that astronomical ephemeris, specifically taken from the catalogs of aphelia of the four Jovian planets, could be drivers of variations in solar activity, represented by the series of sunspot numbers (SSN) from 1749 to 2020. We use singular spectrum analysis (SSA) to associate components with similar periods in the ephemeris and SSN. We determine the transfer function between the two data sets. We improve the match in successive steps: first with Jupiter only, then with the four Jovian planets and finally including commensurable periods of pairs and pairs of pairs of the Jovian planets (following Mörth and Schlamminger in Planetary Motion, Sunspots and Climate, Solar-Terrestrial Influences on Weather and Climate, 193, 1979). The transfer function can be applied to the ephemeris to predict future cycles. We test this with success using the “hindcast prediction” of Solar Cycles 21 to 24, using only data preceding these cycles, and by analyzing separately two 130 and 140 year-long halves of the original series. We conclude with a prediction of Solar Cycle 25 that can be compared to a dozen predictions by other authors: the maximum would occur in 2026.2 (± 1 yr) and reach an amplitude of 97.6 (± 7.8), similar to that of Solar Cycle 24, therefore sketching a new “Modern minimum”, following the Dalton and Gleissberg minima.

Modeling Solar Radiation at the Earth Surface

2012 ◽  
pp. 127-179 ◽  
Author(s):  
Marius Paulescu ◽  
Eugenia Paulescu ◽  
Paul Gravila ◽  
Viorel Badescu
Keyword(s):  
Solar Radiation ◽  
Earth Surface ◽  
The Earth

Seasonal behavior of H component during solar cycle 24

2021 ◽  
Author(s):  
Yasmina Bouderba ◽  
Ener Aganou ◽  
Abdenaceur Lemgharbi
Keyword(s):  
Solar Activity ◽  
Solar Cycle ◽  
Horizontal Component ◽  
Low Latitude ◽  
Seasonal Behavior ◽  
The Earth ◽  
Earth Magnetic Field ◽  
Solar Cycle 24 ◽  
Minimum Solar Activity ◽  
Cycle 24

<p>In this work we will show the behavior of the horizontal component H of the Earth Magnetic Field (EMF) along the seasons during the period of solar cycle 24 lasting from 2009 to 2019. By means of  continuous measurements of geomagnetic components (X, Y) of the EMF, we compute the horizontal component H at the Earth’s surface. The data are recorded with a time resolution of one minute at Tamanrasset observatory in Algeria at the geographical coordinates of 22.79° North and 5.53° East. These data are available from the INTERMAGNET network. We find that the variation in amplitude of the hourly average of H component at low latitude changes from a season to another and it is greater at the maximum solar activity than at the minimum solar activity.</p><p><strong>Keywords:</strong> Solar cycle 24, Season, Horizontal component H. </p>

ESTABLISHING SOLAR ACTIVITY TREND FOR SOLAR CYCLES 21 – 24

2021 ◽  
Vol 44 ◽  
pp. 100-106
Author(s):  
A.K. Singh ◽  
◽  
A. Bhargawa ◽  
Keyword(s):  
Solar Activity ◽  
Solar Cycle ◽  
Sunspot Number ◽  
Cosmic Ray ◽  
Occurrence Rate ◽  
The Sun ◽  
Solar Cycles ◽  
Lyman Alpha ◽  
Rate Versus ◽  
Alpha Index

Solar-terrestrial environment is manifested primarily by the physical conditions of solar interior, solar atmosphere and eruptive solar plasma. Each parameter gives unique information about the Sun and its activity according to its defined characteristics. Hence the variability of solar parameters is of interest from the point of view of plasma dynamics on the Sun and in the interplanetary space as well as for the solar-terrestrial physics. In this study, we have analysed various solar transients and parameters to establish the recent trends of solar activity during solar cycles 21, 22, 23 and 24. The correlation coefficients of linear regression of F10.7 cm index, Lyman alpha index, Mg II index, cosmic ray intensity, number of M & X class flares and coronal mass ejections (CMEs) occurrence rate versus sunspot number was examined for last four solar cycles. A running cross-correlation method has been used to study the momentary relationship among the above mentioned solar activity parameters. Solar cycle 21 witnessed the highest value of correlation for F10.7 cm index, Lyman alpha index and number of M-class and X-class flares versus sunspot number among all the considered solar cycles which were 0.979, 0.935 and 0.964 respectively. Solar cycle 22 recorded the highest correlation in case of Mg II index, Ap index and CMEs occurrence rate versus sunspot number among all the considered solar cycles (0.964, 0.384 and 0.972 respectively). Solar cycle 23 and 24 did not witness any highest correlation compared to solar cycle 21 and 22. Further the record values (highest value compared to other solar three cycles) of each solar activity parameters for each of the four solar cycles have been studied. Here solar cycle 24 has no record text at all, this simply indicating that this cycle was a weakest cycle compared to the three previous ones. We have concluded that in every domain solar 24 was weaker to its three predecessors.

scholarly journals Breathing of heliospheric structures triggered by the solar-cycle activity

2003 ◽  
Vol 21 (6) ◽  
pp. 1303-1313 ◽  
Author(s):  
K. Scherer ◽  
H. J. Fahr
Keyword(s):  
Solar Wind ◽  
Solar Activity ◽  
Solar Cycle ◽  
Activity Cycle ◽  
Periodic Variation ◽  
Galactic Cosmic Rays ◽  
Activity Period ◽  
Solar Cycles ◽  
Interplanetary Physics ◽  
Ram Pressure

Abstract. Solar wind ram pressure variations occuring within the solar activity cycle are communicated to the outer heliosphere as complicated time-variabilities, but repeating its typical form with the activity period of about 11 years. At outer heliospheric regions, the main surviving solar cycle feature is a periodic variation of the solar wind dynamical pressure or momentum flow, as clearly recognized by observations of the VOYAGER-1/2 space probes. This long-periodic variation of the solar wind dynamical pressure is modeled here through application of appropriately time-dependent inner boundary conditions within our multifluid code to describe the solar wind – interstellar medium interaction. As we can show, it takes several solar cycles until the heliospheric structures adapt to an average location about which they carry out a periodic breathing, however, lagged in phase with respect to the solar cycle. The dynamically active heliosphere behaves differently from a static heliosphere and especially shows a historic hysteresis in the sense that the shock structures move out to larger distances than explained by the average ram pressure. Obviously, additional energies are pumped into the heliosheath by means of density and pressure waves which are excited. These waves travel outwards through the interface from the termination shock towards the bow shock. Depending on longitude, the heliospheric sheath region memorizes 2–3 (upwind) and up to 6–7 (downwind) preceding solar activity cycles, i.e. the cycle-induced waves need corresponding travel times for the passage over the heliosheath. Within our multifluid code we also adequately describe the solar cycle variations in the energy distributions of anomalous and galactic cosmic rays, respectively. According to these results the distribution of these high energetic species cannot be correctly described on the basis of the actually prevailing solar wind conditions.Key words. Interplanetary physics (heliopause and solar wind termination; general or miscellaneous) – Space plasma physics (experimental and mathematical techniques)

scholarly journals Solar Activity and Svalbard Temperatures

2011 ◽  
Vol 2011 ◽  
pp. 1-8 ◽  
Author(s):  
Jan-Erik Solheim ◽  
Kjell Stordahl ◽  
Ole Humlum
Keyword(s):  
Solar Activity ◽  
Solar Cycle ◽  
Winter Temperature ◽  
Positive Trend ◽  
Seasonal Temperature ◽  
Solar Cycles ◽  
Temperature Variations ◽  
Mean Temperature ◽  
Cent Level ◽  
Cycle 24

The long temperature series at Svalbard (Longyearbyen) show large variations and a positive trend since its start in 1912. During this period solar activity has increased, as indicated by shorter solar cycles. The temperature at Svalbard is negatively correlated with the length of the solar cycle. The strongest negative correlation is found with lags 10–12 years. The relations between the length of a solar cycle and the mean temperature in the following cycle are used to model Svalbard annual mean temperature and seasonal temperature variations. Residuals from the annual and winter models show no autocorrelations on the 5 per cent level, which indicates that no additional parameters are needed to explain the temperature variations with 95 per cent significance. These models show that 60 per cent of the annual and winter temperature variations are explained by solar activity. For the spring, summer, and fall temperatures autocorrelations in the residuals exist, and additional variables may contribute to the variations. These models can be applied as forecasting models. We predict an annual mean temperature decrease for Svalbard of °C from solar cycle 23 to solar cycle 24 (2009–20) and a decrease in the winter temperature of °C.

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