Solar Cycle Prediction Research Articles

Prediction of solar cycle 25: a non-linear approach

Prediction of solar cycle 25: a non-linear approach

An Updated Solar Cycle 25 Prediction With AFT: The Modern Minimum

AbstractOver the last decade there has been mounting evidence that the strength of the Sun's polar magnetic fields during a solar cycle minimum is the best predictor of the amplitude of the next solar cycle. Surface flux transport models can be used to extend these predictions by evolving the Sun's surface magnetic field to obtain an earlier prediction for the strength of the polar fields, and thus the amplitude of the next cycle. In 2016, our Advective Flux Transport (AFT) model was used to do this, producing an early prediction for Solar Cycle 25. At that time, AFT predicted that Cycle 25 will be similar in strength to the Cycle 24, with an uncertainty of about 15%. AFT also predicted that the polar fields in the southern hemisphere would weaken in late 2016 and into 2017 before recovering. That AFT prediction was based on the magnetic field configuration at the end of January 2016. We now have two more years of observations. We examine the accuracy of the 2016 AFT prediction and find that the new observations track well with AFT's predictions for the last 2 years. We show that the southern relapse did in fact occur, though the timing was off by several months. We propose a possible cause for the southern relapse and discuss the reason for the offset in timing. Finally, we provide an updated AFT prediction for Solar Cycle 25 that includes solar observations through January of 2018.

How Many Active Regions Are Necessary to Predict the Solar Dipole Moment?

Abstract We test recent claims that the polar field at the end of Cycle 23 was weakened by a small number of large, abnormally oriented regions, and investigate what this means for solar cycle prediction. We isolate the contribution of individual regions from magnetograms for Cycles 21, 22, and 23 using a 2D surface flux transport model, and find that although the top ∼10% of contributors tend to define sudden large variations in the axial dipole moment, the cumulative contribution of many weaker regions cannot be ignored. To recreate the axial dipole moment to a reasonable degree, many more regions are required in Cycle 23 than in Cycles 21 and 22 when ordered by contribution. We suggest that the negative contribution of the most significant regions of Cycle 23 could indeed be a cause of the weak polar field at the following cycle minimum and the low-amplitude Cycle 24. We also examine the relationship between a region’s axial dipole moment contribution and its emergence latitude, flux, and initial axial dipole moment. We find that once the initial dipole moment of a given region has been measured, we can predict the long-term dipole moment contribution using emergence latitude alone.

A prediction of the solar cycle 25

AbstractHere we report our recent prediction of the solar cycle 25 based on a newly developed scheme, which is used to investigate the predictability of the solar cycle over one cycle. The scheme is a combination of the empirical properties of solar cycles and a surface flux transport model to get the possible axial dipole moment evolution at a few years before cycle minimum, by which to get the subsequent cycle strength based on the correlation between the axial dipole moment at cycle minimum and the subsequent cycle strength. We apply this scheme to predict the large-scale field evolution since 2018 onwards. The results show that the northern polar field will keep on increasing, while the southern polar field almost keeps flat by the end of cycle 24. This leads to the cycle 25 strength of 125 ± 32, which is about 10% stronger than cycle 24 according to the mean value.

State-of-the-art of kinematic modeling the solar cycle

AbstractThe kinematic modeling of the solar convection zone remains the workhorse of the solar dynamo to understand the solar cycle. During the past several years, the major progress in understanding the solar cycle using kinematic models is as follows. (1). The Babcock-Leighton (BL) mechanism was confirmed to be at the essence of the solar cycle. (2). The scatter of sunspot tilt angles is identified as a major cause of solar cycle irregularities. (3). The important roles of the magnetic pumping in the dynamo process are recognized. (4). Some 3D kinematic BL type dynamo models have been developed. As a key part of the solar dynamo loop, the surface observable part of the BL mechanism makes the physics-based solar cycle prediction feasible. Including the effects of the tilt scatter on the polar field generation, the possible strength of the subsequent cycle can be predicted when a cycle starts for a few years.

Improvement of solar-cycle prediction: Plateau of solar axial dipole moment

Aims. We report the small temporal variation of the axial dipole moment near the solar minimum and its application to the solar cycle prediction by the surface flux transport (SFT) model. Methods. We measure the axial dipole moment using the photospheric synoptic magnetogram observed by the Wilcox Solar Observatory (WSO), the ESA/NASA Solar and Heliospheric Observatory Michelson Doppler Imager (MDI), and the NASA Solar Dynamics Observatory Helioseismic and Magnetic Imager (HMI). We also use the surface flux transport model for the interpretation and prediction of the observed axial dipole moment. Results. We find that the observed axial dipole moment becomes approximately constant during the period of several years before each cycle minimum, which we call the axial dipole moment plateau. The cross-equatorial magnetic flux transport is found to be small during the period, although the significant number of sunspots are still emerging. The results indicates that the newly emerged magnetic flux does not contributes to the build up of the axial dipole moment near the end of each cycle. This is confirmed by showing that the time variation of the observed axial dipole moment agrees well with that predicted by the SFT model without introducing new emergence of magnetic flux. These results allows us to predict the axial dipole moment in Cycle 24/25 minimum using the SFT model without introducing new flux emergence. The predicted axial dipole moment of Cycle 24/25 minimum is 60--80 percent of Cycle 23/24 minimum, which suggests the amplitude of Cycle 25 even weaker than the current Cycle 24. Conclusions. The plateau of the solar axial dipole moment is an important feature for the longer prediction of the solar cycle based on the SFT model.

Analysing Spotless Days as Predictors of Solar Activity from the New Sunspot Number

The use of the spotless days to predict the future solar activity is here revised based on the new version of the sunspot number index with a 24-month filter. Data from Solar Cycle (SC) 10 are considered because from this solar cycle the temporal coverage of the records is 100 %. The interrelationships of the timing characteristics of spotless days and their comparison with sunspot cycle parameters are explored, in some cases finding very strong correlations. Such is the case for the relationship between the minimum time between spotless days either side of a given solar maximum and the maximum time between spotless days either side in the previous solar minimum, with r = -0.91 and a p-value < 0.001. However, the predictions for SC 24 or 23 made by other authors in previous works using the spotless days as a predictor of solar activity are not good since it has not been fulfilled. Although there seems to be a pattern of strong correlation for some relationships between the parameters studied, prediction of future solar cycles from these parameters defined as functions of the spotless days should be made with caution because sometimes the estimated values are far from the observed ones. Finally, SC 23 seems to show a mode change, a break respect to the behavior of their previous solar cycles and more similar to SC 10-15.

Test on the predictions of solar cycle using the rising rate of monthly sunspot number

The period of about 11-year is the most significant quasi-periodic component in solar activity. The amplitude of the period is often used to indicate the activity intensity of a solar cycle. Solar activity affects the space weather, spaceflight and Earth climate. Solar physical scientists pay attention to studies of solar activity, and some geo-scientists are interested in the relationship between solar activity and some geophysical phenomena. So prediction of relative number of sunspots (SSN) has attracted the attention of many scientists in order to understand the activity of new solar cycle and study the variation of geophysical phenomena. Some prediction methods were used to predict the amplitude of the coming solar cycle, especially for the prediction of the amplitudes for solar cycles 22–24. The results show that only about 1/3 are better in many predictions, the relative predicted error is less than 20%. So it is still difficult to accurately predict the maximum of SSN. In 2000, the amplitude for solar cycle 23 was predicted using rising rate of SSN in earlier ascending phase of cycles by Han. The subsequent compare of actual maximum and prediction showed that the relative predicted error is about 15.2%. The motivation of this paper is to simply introduce how to use the method to predict the solar cycle 23, test the simulation prediction for solar cycle 24 using the new version SSN series (V2.0), and compare the results with those obtained by other researchers using different methods, in order to proof-test the ability of the method. The method uses regression analysis to calculate the rising rates of monthly smoothed SSN in initial stage of past solar cycles, and then calculate the quantitative relationship between the rising rates and corresponding maximums of the solar cycles using regression analysis again. Some tests show that they have high correlation when we use SSN in 1–24 months of initial stage of past solar cycles. Then we calculate the rising rate and use the rate to predict the amplitude of the coming solar cycle. The paper focuses on the simulative predictions of maximum amplitude for 22–24 cycles using the method and V2.0 SSN series. For the 3 cycles, predicted values of maximum amplitudes are 234.9, 191.9 and 134.1, they are in good agreement with the actual values, 212.5, 180.3, 116.4, and the relative prediction errors are about 10.6%, 6.4% and 15.2%, respectively. This shows that the prediction method has a certain application value possibly. Anyway, the studies of solar activity characteristics should be continually enhanced, as well as the studies of methods for predicting the solar activity in the future, to select relatively better prediction methods and improve the level of solar activity prediction. Meanwhile, the rising rate is obtained by the SSN in 1–24 months of the initial stage of a cycle, for the monthly smoothed SSN series, only at the 31st month after the beginning of a cycle can get smoothed values of 24 months and then to calculate rising rate. However, the rising stage is about 4–6 a, which makes the predicted leading time to be not long enough. The authors are considering the improvement of this method and to do more tests.

The HelMod Monte Carlo Model for the Propagation of Cosmic Rays in Heliosphere

AbstractThe heliospheric modulation model HelMod solves the transport-equation for Galactic Cosmic Ray propagation through the heliosphere down to Earth. It is based on a 2-D Monte Carlo approach that includes a general description of the symmetric and antisymmetric parts of the diffusion tensor, thus properly treating the particle drift effects as well as convection within the solar wind and adiabatic energy loss. The model was tuned in order to fit 1) the data observed outside the ecliptic plane at several distances from the Earth and 2) the spectra observed near the Earth for both, high and low solar activity periods. Great importance was given to description of polar regions of the heliosphere. We present the flux for protons, antiprotons and helium nuclei computed for solar cycle 23-24 in comparison with experimental observations and prediction for the full solar cycle 24.

DATA ASSIMILATION APPROACH FOR FORECAST OF SOLAR ACTIVITY CYCLES

ABSTRACT Numerous attempts to predict future solar cycles are mostly based on empirical relations derived from observations of previous cycles, and they yield a wide range of predicted strengths and durations of the cycles. Results obtained with current dynamo models also deviate strongly from each other, thus raising questions about criteria to quantify the reliability of such predictions. The primary difficulties in modeling future solar activity are shortcomings of both the dynamo models and observations that do not allow us to determine the current and past states of the global solar magnetic structure and its dynamics. Data assimilation is a relatively new approach to develop physics-based predictions and estimate their uncertainties in situations where the physical properties of a system are not well-known. This paper presents an application of the ensemble Kalman filter method for modeling and prediction of solar cycles through use of a low-order nonlinear dynamo model that includes the essential physics and can describe general properties of the sunspot cycles. Despite the simplicity of this model, the data assimilation approach provides reasonable estimates for the strengths of future solar cycles. In particular, the prediction of Cycle 24 calculated and published in 2008 is so far holding up quite well. In this paper, I will present my first attempt to predict Cycle 25 using the data assimilation approach, and discuss the uncertainties of that prediction.

Predictions of Solar Cycle 24: How are we doing?

AbstractPredictions of solar activity are an essential part of our Space Weather forecast capability. Users are requiring usable predictions of an upcoming solar cycle to be delivered several years before solar minimum. A set of predictions of the amplitude of Solar Cycle 24 accumulated in 2008 ranged from zero to unprecedented levels of solar activity. The predictions formed an almost normal distribution, centered on the average amplitude of all preceding solar cycles. The average of the current compilation of 105 predictions of the annual‐average sunspot number is 106 ± 31, slightly lower than earlier compilations but still with a wide distribution. Solar Cycle 24 is on track to have a below‐average amplitude, peaking at an annual sunspot number of about 80. Our need for solar activity predictions and our desire for those predictions to be made ever earlier in the preceding solar cycle will be discussed. Solar Cycle 24 has been a below‐average sunspot cycle. There were peaks in the daily and monthly averaged sunspot number in the Northern Hemisphere in 2011 and in the Southern Hemisphere in 2014. With the rapid increase in solar data and capability of numerical models of the solar convection zone we are developing the ability to forecast the level of the next sunspot cycle. But predictions based only on the statistics of the sunspot number are not adequate for predicting the next solar maximum. I will describe how we did in predicting the amplitude of Solar Cycle 24 and describe how solar polar field predictions could be made more accurate in the future.

Revisited sunspot numbers and prediction of solar cycle 25

Revisited sunspot numbers and prediction of solar cycle 25

Determination of Total Electron Content at Equatorial Region—Thailand Using Radio Occultation Technique

This paper investigates the total electron content (TEC) which is a major challenge to space and related industries, most especially in an equatorial region like Thailand within the geographical latitude 07°35'N - 20°17'N. This research was achieved using radio occultation data from COSMIC mission. The monthly, seasonal and annual TEC and electron density variation monitoring conducted during increasing solar activity from 2010 to 2013 due to changes and instability of ionospheric parameters. It was observed that electron density and TEC was predominant in summer season. Summer has the highest electron density and TEC values all through and the annual mean values keep on increasing within the period under consideration. In conclusion, ionospheric fluctuations and perturbations were observed to be at pick between the months of March and May. The results of the study demonstrated that ionospheric irregularities were steadily on the increase, confirming 24th solar cycle prediction by NASA and depended on many factors among the major ones which are located on the latitude, season and solar activity.

Operational Space Weather Services in National Space Science Center of Chinese Academy of Sciences

Operational Space Weather Services in National Space Science Center of Chinese Academy of Sciences

A proportional hazard model for storm occurrence risk

Severe Ionosphere magnetic storms are feared events for integrity and continuity of navigation systems such as EGNOS, the European SBAS (Satellite-Based Augmentation System) complementing GPS and an accurate modelling of this event probability is necessary. Our aim for the work presented in this paper is to give an estimation of the frequency of such extreme magnetic storms per time unit (year) throughout a solar cycle. Thus, we develop an innovative approach based on a proportional hazard model, inspired by the Cox model, with time dependent covariates. The number of storms during a cycle is supposed to be a non-homogeneous Poisson process. The intensity of this process could be expressed as the product of a baseline risk and a risk factor. Contrary to what is done in the Cox model, the baseline risk is one parameter of interest (and not a nuisance one), it is the intensity to estimate. As in Extreme Value Theory, all the high level events will be used to make estimation and the results will be extrapolated to the extreme level ones. After a precise description of the model, we present the estimation results and a model extension. A prediction for the current solar cycle (24th) is also proposed.

Long-term variations in the north–south asymmetry of solar activity and solar cycle prediction, III: Prediction for the amplitude of solar cycle 25

The combined Greenwich and Solar Optical Observing Network (SOON) sunspot group data during 1874–2013 are analysed and studied the relatively long-term variations in the annual sums of the areas of sunspot groups in 0°–10°, 10°–20°, and 20°–30° latitude intervals of the Sun’s northern and southern hemispheres. The variations in the corresponding north–south differences are also studied. Long periodicities in these parameters are determined from the fast Fourier transform (FFT), maximum entropy method (MEM), and Morlet wavelet analysis. It is found that in the difference between the sums of the areas of the sunspot groups in 0°–10° latitude intervals of northern and southern hemispheres, there exist ≈9-year periodicity during the high activity period 1940–1980 and ≈12-year periodicity during the low activity period 1890–1939. It is also found that there exists a high correlation (85% from 128 data points) between the sum of the areas of the sunspot groups in 0°–10° latitude interval of the southern hemisphere during a Qth year (middle year of 3-year smoothed time series) and the annual mean International Sunspot Number (RZ) of (Q+9)th year. Implication of these results is discussed in the context of solar activity prediction and predicted 50±10 for the amplitude of solar cycle 25, which is about 31% lower than the amplitude of cycle 24.

THE PREDICTABILITY OF ADVECTION-DOMINATED FLUX-TRANSPORT SOLAR DYNAMO MODELS

Space weather is a matter of practical importance in our modern society. Predictions of forecoming solar cycles mean amplitude and duration are currently being made based on flux-transport numerical models of the solar dynamo. Interested in the forecast horizon of such studies, we quantify the predictability window of a representative, advection-dominated, flux-transport dynamo model by investigating its sensitivity to initial conditions and control parameters through a perturbation analysis. We measure the rate associated with the exponential growth of an initial perturbation of the model trajectory, which yields a characteristic timescale known as the e-folding time τ e . The e-folding time is shown to decrease with the strength of the α-effect, and to increase with the magnitude of the imposed meridional circulation. Comparing the e-folding time with the solar cycle periodicity, we obtain an average estimate for τ e equal to 2.76 solar cycle durations. From a practical point of view, the perturbations analyzed in this work can be interpreted as uncertainties affecting either the observations or the physical model itself. After reviewing these, we discuss their implications for solar cycle prediction.

Prediction of Solar Cycle 24 Using Sunspot Number near the Cycle Minimum

Correlations between monthly smoothed sunspot numbers at the solar-cycle maximum [R max] and duration of the ascending phase of the cycle [T rise], on the one hand, and sunspot-number parameters (values, differences and sums) near the cycle minimum, on the other hand, are studied. It is found that sunspot numbers two – three years around minimum correlate with R max or T rise better than those exactly at the minimum. The strongest correlation (Pearson’s r=0.93 with P<0.001 and Spearman’s rank correlation coefficient r S=0.95 with P=9×10−12) proved to be between R max and the sum of the increase of activity over 30 months after the cycle minimum and the drop of activity over 30 or 36 months before the minimum. Several predictions of maximal amplitude and duration of the ascending phase for Solar Cycle 24 are given using sunspot-number parameters as precursors. All of the predictions indicate that Solar Cycle 24 is expected to reach a maximal smoothed monthly sunspot number (SSN) of 70 – 100. The prediction based on the best correlation yields the maximal amplitude of 90±12. The maximum of Solar Cycle 24 is expected to be in December 2013 – January 2014. The rising and declining phases of Solar Cycle 24 are estimated to be about 5.0 and 6.3 years, respectively. The minimum epoch between Solar Cycles 24 and 25 is predicted to be at 2020.3 with minimal SSN of 5.1 – 5.4. We predict also that Solar Cycle 25 will be slightly stronger than Solar Cycle 24; its maximal SSN will be of 105 – 110.

Using the Dipolar and Quadrupolar Moments to Improve Solar-Cycle Predictions Based on the Polar Magnetic Fields

The solar cycle and its associated magnetic activity are the main drivers behind changes in the interplanetary environment and Earth's upper atmosphere (commonly referred to as space weather and climate). In recent years there has been an effort to develop accurate solar cycle predictions, leading to nearly a hundred widely spread predictions for the amplitude of solar cycle 24. Here we show that cycle predictions can be made more accurate if performed separately for each hemisphere, taking advantage of information about both the dipolar and quadrupolar moments of the solar magnetic field during minimum.

SOLAR CYCLE PROPAGATION, MEMORY, AND PREDICTION: INSIGHTS FROM A CENTURY OF MAGNETIC PROXIES

The solar cycle and its associated magnetic activity are the main drivers behind changes in the interplanetary environment and the Earth's upper atmosphere (commonly referred to as space weather). These changes have a direct impact on the lifetime of space-based assets and can create hazards to astronauts in space. In recent years there has been an effort to develop accurate solar cycle predictions (with aims at predicting the long-term evolution of space weather), leading to nearly a hundred widely spread predictions for the amplitude of solar cycle 24. A major contributor to the disagreement is the lack of direct long-term databases covering different components of the solar magnetic field (toroidal vs.\ poloidal). Here we use sunspot area and polar faculae measurements spanning a full century (as our toroidal and poloidal field proxies), to study solar cycle propagation, memory, and prediction. Our results substantiate predictions based on the polar magnetic fields, whereas we find sunspot area to be uncorrelated to cycle amplitude unless multiplied by area-weighted average tilt. This suggests that the joint assimilation of tilt and sunspot area is a better choice (with aims to cycle prediction) than sunspot area alone, and adds to the evidence in favor of active region emergence and decay as the main mechanism of poloidal field generation (i.e. the Babcock-Leighton mechanism). Finally, by looking at the correlation between our poloidal and toroidal proxies across multiple cycles, we find solar cycle memory to be limited to only one cycle.