The Effect of Sunspot Activity on Earth's Extreme Climate

Shiyao Xu

Wuxi Furen Middle School, Wuxi, China

Keywords: Sunspots, ENSO, La Nina, Extreme Climate, ONI.

Abstract: The eastern equatorial Pacific Ocean experiences an oscillation of winds and sea surface temperatures known

as the El Nino-Southern Oscillation (ENSO), which is the most significant signal of inter-annual change in

the global climate system. This low-latitude air-sea interaction, manifested in the Southern Oscillation in the

atmosphere and the El Nino-La Nina transition in the ocean, has a profound impact on global weather patterns.

As an important indicator of solar activity, sunspot activity is closely related to the Earth's climate system and

may modulate ENSO events through various ways. The mechanism of sunspot activity affecting ENSO is

discussed in this paper. First, the effects of sunspots on the sun, Earth's climate and ENSO are analyzed. In

addition, the correlation between the number of sunspots and ONI was also analyzed, further revealing the

existence and correlation of this effect. The results are helpful to further understand the formation and

development mechanism of ENSO, and provide a new theoretical basis for improving the accuracy of ENSO

event prediction.

1 INTRODUCTION

At a distance of about 150 million kilometers, the Sun

is the closest star to Earth. The Sun continuously

emits 3.8× 10²⁶ joules/second of energy through

hydrogen fusion in its core, of which about 1.7×10¹

⁷ joules/second reaches the Earth, constituting

99.98% of the total energy received at the surface.

Solar activity can be divided into quiet periods and

active periods, which mainly include sunspots, flares,

solar prominences and coronal mass ejections. In the

eastern equatorial Pacific Ocean, there is a wind field

and sea surface temperature oscillation known as

ENSO (El Nino Southern Oscillation). The Southern

Oscillation in the sky and the ENSO transition in the

ocean serve as indicators of the low-latitude air-sea

interaction known as ENSO. Its formation and

development are the result of the interaction of many

factors, including the interaction between the ocean

and the atmosphere, the change of trade wind

direction, the change of sea surface temperature, the

difference of atmospheric pressure, Walker

circulation, Earth rotation and global climate change.

Many studies have shown that the Earth's extreme

climate is closely related to solar activity. In view of

this, this paper aims to explore the correlation

https://orcid.org/0009-0007-9989-6984

between sunspot activity and ENSO. The aim is to

deepen our understanding of the formation

mechanism of these extreme climates and provide

scientific basis for understanding and predicting

ENSO events.

1.1 Composition and Structure of the

Sun

The Sun is composed mainly of hydrogen and helium,

and these two elements make up the majority of the

Sun's total mass. Among other elements, it also

contains carbon, oxygen, neon, and iron. Although

there is no obvious barrier between the internal

material, which is primarily plasma, its density drops

exponentially with increasing altitude above the

photosphere. For ease, the solar radius is frequently

calculated using the distance between the sun's visible

surface and core (Den, 2023). Nuclear fusion occurs

all the time in the sun, and energy is diffused from the

inside to the outside. In this process, high-energy

particles such as gamma rays and neutrinos generated

by nuclear fusion will gradually decay into photons

of lower energy such as ultraviolet, visible light and

infrared light.

546

Xu, S.

The Effect of Sunspot Activity on Earth’s Extreme Climate.

DOI: 10.5220/0013829200004708

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 2nd International Conference on Innovations in Applied Mathematics, Physics, and Astronomy (IAMPA 2025), pages 546-551

ISBN: 978-989-758-774-0

The current research believes that the solar

structure is mainly divided into five layers, namely

core, radiation zone, convection zone, photosphere

and corona. Common solar activities mainly include

sunspots, flares, solar prominences, coronal mass

ejections, etc. These activities will have a certain

impact on space communications, power systems,

satellite operations, climate and so on.

1.2 Sunspot

Sunspots are a feature on the surface of the Sun,

proposed by Rudolf Wolf, usually located in the

photosphere and are the result of the upward push of

the intense magnetic flux inside the sun. Along this

flux, heat is heated in the upper photosphere and

chromosphere regions, usually in the form of light

spots and blotches--often referred to as active regions

(NOAA, 2025). These active areas are typically

where solar eruptions like solar flares and coronal

mass ejections occur. To ascertain and forecast the

solar cycle's advancement and, eventually, solar

activity, several organizations, like NASA and

NOAA, monitor sunspots (NASA, 2025).

The solar cycle is about 11 years, and the total

number of sunspots varies throughout the cycle.

According to the different number of sunspots can be

divided into solar minimum and solar maximum. The

former is characterized by a low number of sunspots,

while the latter is characterized by a high number of

sunspots. Sunspots can be used as a solar activity

indicator and as a possible source of violent solar

activity, including coronal mass ejections and flares.

Furthermore, the temperature of Earth may be

impacted by solar activity in the long run.

1.3 ENSO Phenomenon

ENSO is a wind field and sea surface temperature

oscillation that occurs in the eastern equatorial Pacific

Ocean. ENSO is a low-latitude sea-air interaction

phenomena that is indicated by the Southern

Oscillation in the atmosphere and the El Nino-La

Nina transition in the ocean (

Kessler, 2002). In the

Pacific Ocean close to the equator, the east has a low

temperature and the west a high one. The air in the

western Pacific Ocean is warm and humid, prevailing

updraft, becoming an area with extremely vigorous

convective activity, and also the most abundant

precipitation in the Pacific Ocean, while the eastern

Pacific Ocean is cold water, cold water makes the air

above it cool and dense, prevailing downdraft on the

ocean surface, more sunny and less cloudy weather.

This zonal circulation that flows east-west over the

low-latitude Pacific Ocean is called the Walker

circulation.

El Nino and La Nina are the two opposite phases

of ENSO, which exhibit different characteristics in

terms of the ocean and atmosphere. During El Nino,

the eastward expansion of warm surface water causes

the convection zone in the western tropical Pacific to

drift eastward. This resulted in increased rainfall,

decreased surface pressure and weakened trade winds

in the eastern Tropical Pacific, while west of the date

line, decreased rainfall and increased surface

pressure. At the same time, this phenomenon will also

cause and increase the global temperature abnormally

(

Philander, 1989). However, La Nina happens when

the equatorial Pacific's exceptionally powerful trade

winds push more warm water westward. It led to

exceptionally low SST in the equatorial Middle

Eastern Pacific Ocean, lower SST in the east, and

higher SST in the west. El Nino has the opposite

impact. This phenomenon will have a serious impact,

which may lead to a significant reduction in

agricultural production, and dry conditions also face

increased fire, which affects agricultural forest

planting and water supply reduction (

ESCAP and

Warning,2016

ENSO is a significant natural climate event that,

when combined, form a complex climate system that

alternately manifests and exhibits periodic

oscillations with a duration of roughly three to seven

years. The primary driving force behind the

complicated processes of ENSO creation is the

interplay between the ocean and atmosphere.

Southeast trade winds are often blown from east to

west from the equatorial Middle Eastern Pacific. The

western Pacific experiences warmer seas as a result

of these winds pushing warm water toward it, while

the eastern Pacific has cooler waters. When an El

Nino occurs, the winds weaken or even reverse,

which causes warm water to migrate from the western

to the eastern Pacific. Second, shifts in the ocean's

circulation are also significant determinants. Walker

circulation keeps the western Pacific Ocean's warm,

humid air ascending and the eastern Pacific Ocean's

cool water upwelling. Walker circulation deteriorates

during an El Nino, which reduces cold water

upwelling in the Eastern Pacific Ocean and

exacerbates the rise in SST.

The Effect of Sunspot Activity on Earth’s Extreme Climate

547

2 ANALYSIS OF THE

RELATIONSHIP BETWEEN

SUNSPOT ACTIVITY AND

ENSO

2.1 Influence of Sunspot Activity on the

Sun

One of the most significant indicators of solar activity

are sunspots, which are frequently associated with

violent phenomena like solar flares and coronal mass

ejections, which release massive amounts of

electromagnetic radiation and high-energy particles

into space, creating the solar wind. If sunspot activity

is high, solar radiation is increased, and if it is low,

solar radiation is diminished.

The formation of sunspots has a lot to do with the

sun's magnetic field. The Sun's magnetic field is not

evenly distributed, but can become extremely strong

in certain regions. These strong magnetic fields

inhibit the movement of the gas, which causes the

temperature in these places to cool down and form

sunspots.

2.2 Effects of Sunspot Activity on

Earth's Climate

Solar flares and coronal mass ejections (CMES),

which are common during sunspot activity, unleash

massive volumes of plasma and high-energy particles

towards Earth, creating the solar wind. Geomagnetic

storms are the result of interactions between the solar

wind and Earth's magnetic field. Changes in the

Earth's magnetic field during geomagnetic storms can

change air circulation patterns, which can have an

impact on the climate system (

Hathaway,2015).

There is a long-term relationship between sunspot

activity and Earth's climate. During periods of low

sunspot activity, Earth experienced a relatively cold

period known as the "Little Ice Age." During this

period, the earth's temperature dropped significantly,

rivers froze, and crop yields decreased.

The effect of sunspots on Earth's climate is

multifaceted, but this effect is relatively small and

complex. Sunspot activity indirectly affects the

Earth's climate system by changing the intensity of

solar radiation, ultraviolet radiation, solar wind and

geomagnetic activity.

2.3 Effects of Sunspot Activity on

ENSO

The core driving mechanism of ENSO is the variation

of the southeast trade winds in the equatorial Middle

East Pacific. Peak sunspot activity's enhanced

radiation alters the atmospheric pressure gradient and

heats the equatorial atmosphere, weakening trade

winds and encouraging the flow of warm water

eastward, which leads to El Nino. Conversely,

periods of low sunspot activity can lead to stronger

trade winds, pushing more warm water to pile up in

the western Pacific and intensifying cold water

upturning in the eastern Pacific, creating a La Nina.

There is a periodic relationship between sunspot

activity and ENSO. Sunspot activity has a cycle of

about 11 years, while ENSO phenomena typically

have a cycle of 2-7 years. It has been found that the

peak and trough years of sunspot activity have

significant effects on the intensity and frequency of

ENSO. During peak sunspot years, El Nino may

strengthen, while La Nina may weaken; Conversely,

in sunspot valley years, El Nino events may weaken

and La Nina events may strengthen.

3 SUNSPOT ACTIVITY AND

ENSO DATA ANALYSIS

3.1 Source of Data on Sunspot

Numbers

Sunspot Index and Long-term Solar Observations

(SILSO) is an important project of the Royal

Observatory of Belgium (ROB), Its history can be

traced back to the sunspot observation network

established by Rudolf Wolf at the Zurich Observatory

in 1849(

Clette,Svalgaard,Vaquero and Cliver,2014).

Early data collection relied primarily on visual

observations by observatories and amateur observers

worldwide, and calculated daily indices based on the

Wolff number formula:

()()

10 10Wk gsWk gs=+=+ (1)

In the early 20th century, due to data discontinuity

caused by insufficient coverage of observation

network, the predecessor institution of SILSO used

interpolation method and analogy method of activity

intensity of adjacent periods to fill the gap in data

(

Cliver and Ling, 2016).

Modern data acquisition system integrates multi-

source observation technology. Since 1995, the

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548

Michelson Doppler Imager (MDI) of the SOHO

satellite and the Helioseismic and Magnetic Imager

(HMI) of the SDO satellite have provided surface and

white light images 24 hours a day. To help correct the

weather disturbance error of ground-based

observation. SILSO also uses a dynamic cross-

calibration process to re-evaluate historical data using

modern high-resolution data.

Therefore, SILSO has built a relatively complete

database for recording sunspots. This paper takes it as

a reliable data source, and visualizes and analyzes the

public data in it. The data source is (

Royal Observatory

of Belgium, 2025).

3.2 Source of Data for Oceanic Nino

Index (ONI)

Sea Surface Temperature (SST) refers to the

temperature of the ocean surface, usually the water

temperature of the ocean surface (usually within 0.5

m depth). SST data is a very important basic data in

oceanography and climatology, widely used in

weather forecast, climate research, Marine ecosystem

research, fishery management and other fields. The

source of SST data is mainly obtained through

satellite remote sensing technology. The sensor on the

satellite measures the radiation temperature of the

ocean surface, and then inverts the SST.

The Nino 3.4 index is calculated based on the SST

anomalies for the region of Nino 3.4 (5°N-5°S,

120° W-170 ° W), subtracted from each month's

SST anomalies, which are usually based on 30-year

climate averages. The calculation formula is as

follows:

SST Exception SST SST= (2)

Where SST is SST value of this month;

SST is Revised monthly long term average SST;

：

The Oceanic Nino Index (ONI) is calculated using

the three-month sliding average of the SST anomalies

in the Nino 3.4 zone. The calculation formula is as

follows:

nnn

SST SST SST

Current Month ONI

−−

(3)

n-1

n-2

SST Exception Previous 2 Months;

SST is SST Exception Previous 1 Months;

SST is SST Exception Current Month;

Where: SST is

One of the major organizations involved in global

climate monitoring and forecasting, the National

Oceanic and Atmospheric Administration (NOAA),

uses the widely accepted and used criterion of ±0.5 °

C to assess El Nino and La Nina events.

An El Nino episode occurs when the ONI value is

at or above +0.5 °C for a minimum of five months.

A La Nina event occurs when the ONI value is at or

below -0.5 °C and lasts for at least five months,

according to the source (NOAA, 2025).

3.3 Data Preprocessing

The simple arithmetic average of the total number of

sunspots per day for every day of a given calendar

month is the monthly average number of sunspots.

The number of sunspots in the source data is

processed using moving average MA based on the

"March combination" in accordance with the standard

meteorological data processing procedure. The year,

month combination, and number of sunspots are

among the processed data components.

ONI downloads source data and has completed

the "March portfolio" moving average MA

processing. Data items include: Year, March

combination, ONI.

The above two groups of data were associated

with the same association condition as "year" and

"March combination". Delete irrelevant data items

from the results and get results that retain data from

1950 to 2024, which is called preprocessed data. Data

items include: year, March combination, number of

sunspots and ONI. Both sets of data have the same

time dimension, allowing for charting and data

correlation analysis.

3.4 Sunspot Count and ONI Charting

Using Python's matplotlib library, two sets of data are

presented on the same chart. The two groups of data

are visually displayed by graphical means (Figure 1)

in order to find the relationship between the two

groups of data. The horizontal coordinate represents

the time dimension of the "March combination", the

vertical axis of the principal coordinate represents the

number of sunspots, and the vertical axis of the

secondary coordinate represents ONI data. The red

graph illustrates the variations in ONI over time,

while the blue curve depicts the changes in sunspots.

Two horizontal red dashed lines are shown; the El

Nino threshold is at the top, while the La Nina

threshold is at the bottom.

From the figure 1, we can roughly observe that

when the number of sunspots is high and low, the

occurrence probability of ENSO phenomenon is

relatively high.

The Effect of Sunspot Activity on Earth’s Extreme Climate

549

Figure 1 Number of sunspots and ONI time chart

3.5 Sunspot Number and ONI

Correlation Analysis

Using Python's scipy library, the correlation between

the two sets of data is quantified. The purpose is to

find the strength of the correlation between the two

groups of data through statistical methods. Firstly,

ONI values in preprocessed data are discretized: ONI

values greater than 0.5 are adjusted to 1, ONI values

less than -0.5 are adjusted to -1, and ONI values

between -0.5 and 0.5 are adjusted to 0. Then, the

correlation strength of the two groups of data was

analyzed by statistical means, as in figure 2. In the

figure, the horizontal coordinate represents the

number of sunspots, and the vertical coordinate

represents the ONI discrete data. The correlation

coefficient value of the two groups of data is 0.1209,

and the p-value is 0.0003.

Figure 2 Analysis of the correlation between the number

of black suns and ONI

Statistics show that when the P-value is very small

(usually less than 0.05), it means that the null

hypothesis is rejected and the correlation between the

two variables is considered statistically significant.

The two sets of data have a p-value of 0.0003, which

is well below the cutoff point of 0.05. Consequently,

it may be said that there is a correlation between the

two sets of data.

A measure of the correlation between data is the

correlation coefficient (r). The range of values is [−

1,1]. There is no linear correlation when r=0, a totally

negative correlation when r=− 1, and a completely

positive correlation when r=1. Although the

correlation between the two data sets is small, it is

positive, as seen by the two groups' r=0.1209.

4 CONCLUSION

In this paper, the association between sunspot number

and ENSO data is merged, and the impacts of sunspot

activity on the sun, Earth climate, and ENSO are

examined and explained. The conclusion is that

although sunspot activity is not the determining factor

of ENSO, the two have a positive link, and the

sunspot number change may be utilized as an ENSO

reference factor to assist predict ENSO episodes more

accurately.

ENSO is often monitored with the help of easily

accessible indirect data. In addition to ONI, there are

examples such as Sea Surface Temperature (SST),

Ocean Heat Content (OHC), Southern Oscillation

Index (SOI), and Multivariate ENSO Index (MEI)

and other indicators. Due to the limited space and data

acquisition methods, this paper only conducted

comparative analysis of ONI data, and ONI's

emphasis on the characterization of surface sea

temperature in the East Pacific Ocean may weaken

the driving role of OHC (Ocean Heat Content) on

ENSO events. The conclusion of the data relationship

has certain limitations, which cannot accurately

explain the association between sunspot activity and

ENSO.

At the same time, due to the limitations of

research conditions, the open data of SILSO and

NOAA platforms were used for analysis. Although

the authority of the data was guaranteed, there were

limitations. For example, differences in observation

criteria between platforms (e.g., SILSO's historical

sunspot count is calibrated and revised multiple times,

while NOAA's ONI calculations rely on ERSSTv5

reanalysis data) can lead to systematic error

accumulation across databases.

As a key disturbance source of the global climate

system, ENSO affects human life, and the

improvement of its prediction accuracy is of great

significance to disaster prevention and reduction.

Although this study is limited by the lack of data

dimension and mechanism interpretation, the

combination of multidisciplinary collaboration, high-

precision observation and numerical simulation is

expected to reveal the deep link between solar activity

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550

and ENSO, and ultimately serve a more reliable

climate prediction system. If cross-platform real-time

data analysis can be established in the future, it is

expected to contribute to the construction of more

accurate prediction models, and serve the adaptation

management of human beings to extreme climates.

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