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11.
Prediction of sunspot cycle is a vital activity in space mission planning and various engineering decision making. In the present study, the sunspot cycle prediction has been carried out by a hybrid model which employs multivariate regression technique and the binary mixture of Laplace distribution (BMLD) function. The Expectation Maximization (EM) algorithm is being applied to the multivariate regression analysis to obtain a robust prediction of the sunspot cycle. Sunspot cycle 24 has been predicted using this technique. Multivariate regression model has been derived based on the available cycles 1 to 23. This model could predict cycle 24 as an average of previous cycles. Prediction from this model has been refined to capture the cycle characteristics such as bimodal peak at the high solar activity period by incorporating a predicted peak sunspot number from the BMLD model. This revised prediction has shown more accuracy in forecasting the major discrete features of sunspot cycle like maximum amplitude, the Gnevyshev gap, time duration from peak to peak amplitude, and the epoch of peak amplitude. This refined prediction shows that cycle 24 will be having a peak amplitude of 78 with an uncertainty of ±25. Moreover, the present forecast says that, cycle 24 will be having double peak with a strong second peak compared to the first peak. This hypothesis is found to be true with the realized data of cycle 24. Further, this techniques have been validated by predicting sunspot cycles 22 and 23. A preliminary level prediction of sunspot cycle 25 also been carried out using the technique presented here. Present study predicts that, cycle 25 also will be a modest cycle like the present cycle 24, and the peak amplitude may vary in a band of 75–95. 相似文献
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P. V. Hareesh Kumar S. Lekshmi P. S. V. Jagadeesh K. Anilkumar G. V. Krishnakumar A. D. Rao 《Marine Geodesy》2013,36(2-3):232-244
Time series of temperature and salinity collected from a station in the NE Arabian Sea during March, April, May, October, and November was utilized to explain the behavior of internal tides. Analysis revealed the existence of semi-diurnal internal tides and high frequency (HF) internal waves (IW). It was observed that the amplitudes of HF IWs were determined by the degree of stratification in the thermocline. Corresponding to an increase in the density gradient in thermocline (0.016 kg/m4 in April to 0.14 kg/m4 in October), the temperature fluctuations due to internal tides increased from <0.2°C to >1.5°C, respectively. Brunt-Vaiisala frequency also showed similar variations (～10 cph to 22 cph). Within the thermocline, semi-diurnal internal tides caused fluctuations of >10m in the isotherm depths. A linear regression equation was fitted to parameterize the amplitude of HF IWs and its upper frequency limit in terms of thermocline gradient. The IW and one-dimensional models simulated the presence of internal tides and diurnal cycling in the temperature field, respectively. Coupling of these models showed improvement in the simulation of temperature. 相似文献
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An algorithm is developed to find Weak Stability Boundary transfer trajectories to Moon in high fidelity force model using forward propagation. The trajectory starts from an Earth Parking Orbit (circular or elliptical). The algorithm varies the control parameters at Earth Parking Orbit and on the way to Moon to arrive at a ballistic capture trajectory at Moon. Forward propagation helps to satisfy launch vehicle’s maximum payload constraints. Using this algorithm, a number of test cases are evaluated and detailed analysis of capture orbits is presented. 相似文献
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The objective of the paper is to use the data collected along two meridional sections (45° E and 57°30′ E) during the austral
summer (January–March) 2004 to understand the influence of seabed topography across the Madagascar and Southwest Indian Ridges
on hydrographic parameters. The study was supplemented by World Ocean Circulation Experiment (WOCE) Conductivity-Temperature-Depth
data collected during February–March 1996 along 30° E, as well as Levitus climatology. A southward shift of 2° latitude (between
45° E and 57°30′ E) was recorded for the two predominant frontal structures, i.e., the Agulhas Return Front and Southern Subtropical
Front, which is attributed to the influence of seabed topography on hydrographic parameters. No significant spatial variation
of these fronts was noted between the 30° E and 45° E meridional sections. Between latitudes 31° S and 42° S, the temperature
and salinity structures show deepening over the ridges. The Antarctic Circumpolar Current core was detected between 40°15′ S
and 43° S. 相似文献
17.
This paper presents a new approach for describing the shape of 11-year sunspot cycles by considering the monthly averaged
values. This paper also brings out a prediction model based on the analysis of 22 sunspot cycles from the year 1749 onward.
It is found that the shape of the sunspot cycles with monthly averaged values can be described by a functional form of modified
binary mixture of Laplace density functions, modified suitably by introducing two additional parameters in the standard functional
form. The six parameters, namely two locations, two scales, and two area parameters, characterize this model. The nature of
the estimated parameters for the sunspot cycles from 1749 onward has been analyzed and finally we arrived at a sufficient
set of the parameters for the proposed model. It is seen that this model picks up the sunspot peaks more closely than any
other model without losing the match at other places at the same time. The goodness of fit for the proposed model is also
computed with the Hathaway – Wilson – Reichmann
measure, which shows, on average, that the fitted model passes within 0.47 standard deviations of the actual averaged monthly
sunspot numbers. 相似文献
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A stochastic prediction model for the sunspot cycle is proposed. The prediction model is based on a modified binary mixture
of Laplace distribution functions and a moving-average model over the estimated model parameters. A six-parameter modified
binary mixture of Laplace distribution functions is used for the modeling of the shape of a generic sunspot cycle. The model
parameters are estimated for 23 sunspot cycles independently, and the primary prediction-model parameters are derived from
these estimated model parameters using a moving-average stochastic model. A correction factor (hump factor) is introduced
to make an initial prediction. The hump factor is computed for a given sunspot cycle as the ratio of the model estimated after
the completion of a sunspot cycle (post-facto model) and the prediction of the moving-average model. The hump factors can be applied one at a time over the moving-average
prediction model to get a final prediction of a sunspot cycle. The present model is used to predict the characteristics of
Sunspot Cycle 24. The methodology is validated using the previous Sunspot Cycles 21, 22, and 23, which shows the adequacy
and the applicability of the prediction model. The statistics of the variations of sunspot numbers at high solar activity
are used to provide the lower and upper bound for the predictions using the present model. 相似文献
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