Prediction of the Maximum Amplitude and Timing of Sunspot Cycle 24

Solar Physics ◽  
2009 ◽  
Vol 260 (1) ◽  
pp. 225-232 ◽  
Author(s):  
Nipa J. Bhatt ◽  
Rajmal Jain ◽  
Malini Aggarwal
Keyword(s):  
Sunspot Cycle ◽  
Maximum Amplitude ◽  
Cycle 24

scholarly journals Estimating the maximum of the smoothed highest 3-hourly <i>a</i><i>a</i> index in 3 d by the preceding minimum for the solar cycle

2020 ◽  
Vol 38 (6) ◽  
pp. 1237-1245
Author(s):  
Zhanle Du
Keyword(s):  
Solar Cycle ◽  
Geomagnetic Activity ◽  
Sunspot Cycle ◽  
Maximum Amplitude ◽  
Maximum Intensity ◽  
Activity Intensity ◽  
Future Space ◽  
Cycle 24 ◽  
Ap Index ◽  
Aa Index

Abstract. Predicting the maximum intensity of geomagnetic activity for an upcoming solar cycle is important in space weather service and for planning future space missions. This study analyzed the highest and lowest 3-hourly aa index (aaH∕aaL) in a 3 d interval, smoothed by 363 d to analyze their variation with the 11-year solar cycle. It is found that the maximum of aaH (aaHmax) is well correlated with the preceding minimum of either aaH (aaHmin, r=0.85) or aaL (aaLmin, r=0.89) for the solar cycle. Based on these relationships, the intensity of aaHmax for solar cycle 25 is estimated to be aaHmax(25)=83.7±6.9 (nT), about 29 % stronger than that of solar cycle 24. This value is equivalent to the ap index of apmax(25)=47.4±4.4 (nT) if employing the high correlation between ap and aa (r=0.93). The maximum of aaL (aaLmax) is also well correlated with the preceding aaHmin (r=0.80). The maximum amplitude of the sunspot cycle (Rm) is much better correlated with high geomagnetic activity (aaHmax, r=0.79) than with low geomagnetic activity (aaLmax, r=0.37). The rise time from aaHmin to aaHmax is weakly anti-correlated to the following aaHmax (r=-0.42). Similar correlations are also found for the 13-month smoothed monthly mean aa index. These results are expected to be useful in understanding the geomagnetic activity intensity of solar cycle 25.

Reassessing the Predictions of Sunspot Cycle 24

2018 ◽  
Vol 13 (S340) ◽  
pp. 319-320
Author(s):  
Nipa J. Bhatt ◽  
Rajmal Jain
Keyword(s):  
Sunspot Number ◽  
Data Center ◽  
Activity Index ◽  
Sunspot Cycle ◽  
Prediction Method ◽  
Maximum Amplitude ◽  
Annual Maximum ◽  
Sunspot Minimum ◽  
Cycle 24 ◽  
Geomagnetic Activity Index

AbstractPredictions of sunspot cycle are important due to their space weather effects. Bhattet al.(2009) predicted sunspot cycle 24 (Maximum amplitude: 92.8±19.6; Timing:October 2012±4 months) using relative sunspot number (International Sunspot Number), and average geomagnetic activity indexaaconsidering 2008 as the year of sunspot minimum. Owing to the extended solar minimum till 2009, we re-examine our prediction model. Also, the newly calibrated international sunspot number reduces many discrepancies in the old dataset and is available from Solar Influences Data Center (SIDC) website. Considering 2009 as sunspot minimum year and newly calibrated international sunspot number, (i) The annual maximum amplitude of cycle 24 = 118.5±24.4 (observed = 113.3±0.1), (ii) A smoothed monthly mean sunspot number maximum in January 2014±4 months (observed in February 2014). Our prediction method appears to be a reliable indicator for the predictability of cycle 25.

scholarly journals Predicting the maximum <i>aa</i>/<i>Ap</i> index through its relationship with the preceding minimum

2020 ◽  
Author(s):  
Zhanle Du
Keyword(s):  
Correlation Coefficient ◽  
Geomagnetic Activity ◽  
Rise Time ◽  
Sunspot Cycle ◽  
Maximum Amplitude ◽  
Peak Time ◽  
Future Space ◽  
Cycle 24 ◽  
Ap Index ◽  
Aa Index

Abstract. Predicting the strength and peak time of geomagnetic activity for the ensuing cycle 25 is important in space weather service for planning future space missions. The minimum aa geomagnetic index around the solar minimum has been often used to predict the maximum amplitude of sunspot cycle, but seldom used to directly predict the maximum aa index. This study analyzed the relationships between the maxima and minima of both the geomagnetic aa and Ap indices for the 11-year cycle. The maximum aa index is found to be well correlated to the preceding minimum with a correlation coefficient of r = 0.860. As a result, the maximum aa index for the ensuing cycle 25 is predicted to be aamax(25) = 26.9 ± 2.6. This value is equivalent to Apmax(25) = 17.3 ± 1.8 ± 1.2 if employing the high correlation between aa and Ap (r = 0.939). The maximum Ap index is also found to be well correlated to the preceding minimum with a correlation coefficient of r = 0.862. Based on this correlation, the maximum Ap index is predicted to be a slightly higher value of Apmax(25) = 19.0 ± 1.6. The rise time of the aa (Ap) index for the 11-year cycle is found to be nearly uncorrelated to the following maximum, r = −0.16 (−0.17). If the data point for cycle 24 (which is far from others) were not considered, the rise time of the Ap index for the 11-year cycle would be weakly correlated to the following maximum, r = −0.404 at a confidence level of 62 %. The rise time for cycle 25 would be roughly estimated to be 89.9 ± 31.6 (months), implying that the geomagnetic activity for the ensuing cycle 25 would peak around April 2025 ± 32 months.

Cosmic Ray 11-Year Modulation for Sunspot Cycle 24

Solar Physics ◽  
2014 ◽  
Vol 290 (2) ◽  
pp. 635-643 ◽  
Author(s):  
H. S. Ahluwalia ◽  
R. C. Ygbuhay
Keyword(s):  
Sunspot Cycle ◽  
Cosmic Ray ◽  
Cycle 24

Predicting the start and maximum amplitude of solar cycle 24 using similar phases and a cycle grouping

2009 ◽  
Vol 9 (2) ◽  
pp. 133-136 ◽  
Author(s):  
Jia-Long Wang ◽  
Wei-Guo Zong ◽  
Gui-Ming Le ◽  
Hai-Juan Zhao ◽  
Yun-Qiu Tang ◽  
...  
Keyword(s):  
Solar Cycle ◽  
Maximum Amplitude ◽  
Solar Cycle 24 ◽  
Cycle 24

Current Forecast for Sunspot Cycle 24 Parameters

2010 ◽  
Author(s):  
H. S. Ahluwalia ◽  
R. C. Ygbuhay ◽  
M. Maksimovic ◽  
K. Issautier ◽  
N. Meyer-Vernet ◽  
...  
Keyword(s):  
Sunspot Cycle ◽  
Cycle 24

scholarly journals A Novel Bimodal Forecasting Model for Solar Cycle 25

2022 ◽  
Vol 924 (2) ◽  
pp. 59
Author(s):  
J. Y. Lu ◽  
Y. T. Xiong ◽  
K. Zhao ◽  
M. Wang ◽  
J. Y. Li ◽  
...  
Keyword(s):  
Solar Cycle ◽  
Goodness Of Fit ◽  
Moving Average ◽  
Sunspot Cycle ◽  
Missing Information ◽  
Geometric Information ◽  
Precursor Method ◽  
Peak Structure ◽  
Cycle 24 ◽  
Precursor Information

Abstract In this paper, a novel bimodal model to predict a complete sunspot cycle based on comprehensive precursor information is proposed. We compare the traditional 13 month moving average with the Gaussian filter and find that the latter has less missing information and can better describe the overall trend of the raw data. Unlike the previous models that usually only use one precursor, here we combine the implicit and geometric information of the solar cycle (peak and skewness of the previous cycle and start value of the predicted cycle) with the traditional precursor method based on the geomagnetic index and adopt a multivariate linear approach with a higher goodness of fit (>0.85) in the fitting. Verifications for cycles 22–24 demonstrate that the model has good performance in predicting the peak and peak occurrence time. It also successfully predicts the complete bimodal structure for cycle 22 and cycle 24, showing a certain ability to predict whether the next solar cycle is unimodal or bimodal. It shows that cycle 25 is a single-peak structure and that the peak will come in 2024 October with a peak of 145.3.

scholarly journals Sunspot numbers: Implications on Eastern African rainfall

2014 ◽  
Vol 110 (1/2) ◽  
pp. 1-5 ◽  
Author(s):  
Francis Gachari ◽  
David M. Mulati ◽  
Joseph N. Mutuku
Keyword(s):  
Sunspot Cycle ◽  
Total Rainfall ◽  
Sunspot Numbers ◽  
Predictive Skill ◽  
Solar Declination ◽  
Monthly Total ◽  
Current Maximum ◽  
Cycle 24 ◽  
Sahel Region ◽  
Greater Horn Of Africa

Following NASA’s prediction of sunspot numbers for the current sunspot cycle, Cycle 24, we now include sunspot numbers as an explanatory variable in a statistical model. This model is based on fitting monthly rainfall values with factors and covariates obtained from solar–lunar geometry values and sunspot numbers. The model demonstrates high predictive skill in estimating monthly values by achieving a correlation coefficient of 0.9 between model estimates and the measurements. Estimates for monthly total rainfall for the period from 1901 to 2020 for Kenya indicate that the model can be used not only to estimate historical values of rainfall, but also to predict monthly total rainfall. We have found that the 11-year solar sunspot cycle has an influence on the frequency and timing of extreme hydrology events in Kenya, with these events occurring every 5±2 years after the turning points of sunspot cycles. While solar declination is the major driver of monthly variability, sunspots and the lunar declinations play a role in the annual variability and may have influenced the occurrence of the Sahelian drought of the mid-1980s that affected the Sahel region including the Greater Horn of Africa. Judging from the reflection symmetry, the trend of the current maximum and the turning point of the sunspot minimum at the end of the Modern Maximum, with a 95% level of confidence, drought conditions similar to those of the early 1920s may reoccur in the year 2020±2.

scholarly journals Sunspot Cycle 24 and the Advent of Dalton-Like Minimum

2012 ◽  
Vol 2012 ◽  
pp. 1-5 ◽  
Author(s):  
H. S. Ahluwalia ◽  
R. C. Ygbuhay
Keyword(s):  
Temperature Change ◽  
20Th Century ◽  
21St Century ◽  
Sunspot Cycle ◽  
Historical Record ◽  
Global Temperature ◽  
Global Temperature Change ◽  
Cycle 24

Ahluwalia and Jackiewicz (2011) have predicted that sunspot cycle 24 will be only half as active as cycle 23, reaching its peak in May2013±6months. Here, we discuss the timeline for cycle 24 since its onset in December, 2008 and compare it to the timelines for the last ten cycles (14 to 23) of the 20th century; cycle 24 is rising the slowest. We speculate that cycle 24 may herald the onset of a Dalton-like minimum in the 21st century. The implications of this outcome on global temperature change and ensuing socioeconomic and political scenarios are discussed, on the basis of the historical record.

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