Sunspot cycle prediction using Warped Gaussian process regression

Gonçalves, Ítalo Gomes; Echer, E.; Frigo, Everton

doi:10.1016/j.asr.2019.11.011

Cited by 25 publications

(6 citation statements)

References 19 publications

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“…The recently complete solar cycle 24 is found to be very weak in terms of the solar and magnetospheric activity. There have been some studies that have predicted a trend for the solar activity entering in a period of a grand minimum or a Dalton type minimum (e.g., Gonçalves et al., 2020; Jiang & Cao, 2018; Upton & Hathaway, 2018; Wang, 2017, and references therein). If this really occurs, the weak cycle 24 leads us to expect a much lower solar wind energy input in the magnetosphere, and as a consequence a significant decrease in the geomagnetic activity.…”

Section: Discussionmentioning

confidence: 99%

Long‐Term Variations of the Geomagnetic Activity: A Comparison Between the Strong and Weak Solar Activity Cycles and Implications for the Space Climate

et al. 2021

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A large percentage of modern technical systems, from space communication satellites to ground-based power grids, is vulnerable to space weather (see Cannon et al., 2013; Lakhina et al., 2020, and references therein). Space weather includes everything from variations in the Sun, solar wind to their impacts on the interplanetary space, Earth, and other solar system bodies with varying magnetic and plasma properties (e.g., Echer et al., 2005; Hajra et al., 2020, and references therein). These are strongly modulated by the ∼11-year "Schwabe" cycle (Schwabe, 1844) when Sun's activity rises and falls. In addition to this oscillation, solar activity is reported to exhibit longer-scale modulations such as ∼80-90-year variation in the cycle amplitudes (Gleissberg, 1939), known as Gleissberg cycle (see Hathaway, 2015, for an excellent review on this topic). The long-term study of the space weather over time scales of several solar cycles is important for the knowledge of space climate (e.g., González Hernández et al., 2014;Mursula et al., 2007), which is the main focus of this present work.The solar wind-magnetosphere coupling and its relationship to geomagnetic disturbances are the most important aspects of the space research. The energy coupling process is mainly controlled by magnetic reconnection between the dayside geomagnetic field and interplanetary magnetic field (IMF) (Dungey, 1961). In this process, the northward geomagnetic field lines break upon encounter/contact with the (antiparallel) southward IMF in the dayside magnetopause current sheet where magnetic diffusion is significant. The "open" geomagnetic field lines connected with the IMF are transported down-tail across the polar cap by the solar wind flow and again reconnect at the far tail current sheet region. It may be mentioned that in the "closed magnetosphere" under northward IMF, the solar wind-magnetosphere energy coupling through

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Section: Discussionmentioning

confidence: 99%

Long‐Term Variations of the Geomagnetic Activity: A Comparison Between the Strong and Weak Solar Activity Cycles and Implications for the Space Climate

et al. 2021

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“…Solar activity is a primary factor driving global climate change [47][48][49]. Solar activity has a recurring cycle of about 11 years [50], and this cycle is related to the degree of drought [21,51]. Our study showed that the PDSI in the study site was strongly correlated with sunspots in some periods, e.g., a strong periodicity with cycles of 8-12 years existed during 1725-1750, 1760-1780, 1830-1840, and 1880-1960.…”

Section: Relationship Between Solar Activity the Little Ice Age And D...mentioning

confidence: 57%

A Framework on Analyzing Long-Term Drought Changes and Its Influential Factors Based on the PDSI

et al. 2022

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Drought is one of the most frequent and most widespread natural disasters worldwide, significantly impacting agricultural production and the ecological environment. An investigation of long-term drought changes and its influencing factors provides not only an understanding of historical droughts but also a scientific basis for the protection of future water resources. This study investigated the temporal characteristics of drought in a study site located in the center of Southwest China (SWC) over a 700-year period (AD 1300–2005) using the Palmer Drought Severity Index (PDSI). The linkage between drought and its influencing factors is discussed. An algorithm based on the random forest (RF) method was proposed to analyze the dynamic influence of the factors on drought. We also examined the linkages between the demise of two dynasties and historical drought events. The results showed that the study site was a drought-prone area in the study period and experienced a non-significant drying trend in all centuries, except for the 17th century; a total of 232 droughts were detected in the study site from AD 1300–2005. The wavelet spectrum of the PDSI series showed the existence of 4-, 8-, 16-, 32-, and 128-year-periods. A strong correlation existed between the sunspot numbers and the PDSI. The correlation of the period between the PDSI and El Niño-Southern Oscillation (ENSO) series in the same frequency domain was weak, while the ENSO exhibited a strong interaction with the PDSI in some time periods. The Pacific Decadal Oscillation (PDO) and PDSI had no resonance period in the low-frequency region, but there was a period of 80–130 years in the high-frequency region. The relative rates of influence of the ENSO, sunspot numbers, and PDO during AD 1700–1996 were 38.40%, 31.81%, and 29.8%, respectively. However, the mechanism of the interaction between droughts and the influential factors is complex, and the dominant factor changed over time. The analysis of long-term drought changes based on the PDSI series may provide clues to understand the development of historical events.

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“…For example, Rios and Tobar 39 utilized a slightly adjusted type of the Box-Cox transformation function and showed its effectiveness on real data, enforcing their predicted yearly sunspot numbers to be strictly positive. A similar application of warped GPs was presented by Gonc xalves et al 41 The authors estimated future sunspot numbers and enforced their predictions to be positive by using an integrated softplus function in their warping function.…”

Section: Warped Gpsmentioning

confidence: 96%

Warped Gaussian processes for predicting the degradation of aerospace structures

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Nasrollahi

et al. 2022

Structural Health Monitoring

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Gaussian processes (GPs) can be used to predict future states of a system with credible intervals when considering multiple previous trajectories for training. For example, predicting the degradation of mechanical structures is one application in which they have shown their usefulness. In modeling the system output as a GP, the output is presumed to be normally distributed—assuming the predictions to be defined from negative to positive infinity. However, this assumption does not hold in many applications as, for example, crack lengths and damage indices can only assume positive values. Moreover, several degradation trajectories for training are rare in real-world applications, and the current state of a monitored system, which is used to update the prediction, can often be not directly measured. This paper presents an approach that utilizes warped GPs for treating data that is not normally distributed while considering multiple degradation trajectories for training. The approach is successfully applied to two different crack propagation examples: first, an analytically computed pre-cracked infinite plate, and second, two equally manufactured aluminum structures that resemble a lower section of a wing. For the investigated aerospace structures, we use finite element (FE) simulations to generate multiple degradation trajectories for training. To estimate their hidden degradation states, we infer the current crack length from strain measurements by using Bayesian inference. The results show that the approach of warped GPs provides more accurate predictions than using standard ones for non-normally distributed data, as is the case for crack growth problems. The approach enables quick training of warped GPs while considering multiple training trajectories. Additionally, the crack lengths estimated from strain measurements agree well with the visually inspected ones. Ultimately, the presented approach enables estimating the current and future degradation states with credible intervals that can be used to improve maintenance scheduling.

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Sunspot cycle prediction using Warped Gaussian process regression

Cited by 25 publications

References 19 publications

Long‐Term Variations of the Geomagnetic Activity: A Comparison Between the Strong and Weak Solar Activity Cycles and Implications for the Space Climate

Long‐Term Variations of the Geomagnetic Activity: A Comparison Between the Strong and Weak Solar Activity Cycles and Implications for the Space Climate

A Framework on Analyzing Long-Term Drought Changes and Its Influential Factors Based on the PDSI

Warped Gaussian processes for predicting the degradation of aerospace structures

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