Paper finds solar activity explains climate change over past 200,000 years

A paper published in Earth and Planetary Science Letters finds solar activity was strongly correlated to climate change over the past 200,000 years. The paper reconstructs solar geomagnetic field strength using the 10Be isotope proxy of cosmic rays, which is inversely related to solar activity. The reconstruction in Figure 2 shows solar activity at the end of the record ["near present day"] was at some of the highest levels of the past 200,000 years, and solar geomagnetic field intensity approximately 3 times higher than during the ice age ~180,000 years ago.

Figure 4 below shows the strong correlation between solar activity [grey and black] and the climate change proxy [d18O in red] over the past 200,000 years. According to the author, "The marine δ18O [temperature proxy] record and solar modulation are strongly correlated at the 100,000 year timescale. It is proposed that variations in solar activity control the 100,000 year glacial–interglacial cycles." 

Thus, the paper appears to solve the mystery of what causes ice ages and glacial-interglacial cycles, which has remained unsolved due to the so-called 100,000 year problem of using Milankovitch Cycles to explain ice ages. That is, ice ages and glacial-interglacial cycles are primarily caused by changes in solar activity rather than solar insolation changes on the Northern and Southern Hemispheres as described by Milankovitch Cycles.

According to the author, 

"the geomagnetic field intensity appears to have varied by a factor of three over the last 200,000 years, with three excursions when the intensity became less than half the present value."  

"there are strong correlations between solar surface magnetic activity and climate at different timescales, which range from days through centuries. Whereas these observations have pointed to a causal relationship between solar activity and climate change, the details of of physical mechanism(s) still need to be worked out. It has been generally believed that the variations in solar magnetic activity lead to changes in total or ultraviolet irradiance of the Sun through the disc passage and evolution of sunspots and faculae, which, in turn, affects climate. Another posited mechanism through which solar activity could directly affect climate is via modulation of GCRs [Galactic Cosmic Rays], which induces cloud formation by inducing changes in the tropospheric ion production [Svensmark's theory]. If the changes in cosmic ray flux cause cloud cover variations, one would expect an inverse relationship between solar modulation and surface temperature, assuming that the proportion of low and high clouds remains constant. This is consistent with the observations in Figure 4 [below], although variations in irradiance could also affect climate by e.g. affecting ozone cover."

"In summary, it is evident that while there are strong correlations between solar activity and climate at different timescales, more work is needed towards finding mechanisms that change solar activity in the first place, and that explain the physical link between solar magnetism and climate." "The long term solar activity and the Earth's surface temperature appear to be directly related. The variations in solar activity may control the 100,000 year glacial-interglacial cycles providing a more tangible astronomical forcing than the estimated changes in solar insolation [Milankovitch Cycles] or cosmic dust accretion rates." 

Horizontal axis is thousands of years before the present. Solar geomagnetic activity is inversely related to galactic cosmic rays at Earth's surface, and thus inversely related to the cosmogenic isotope 10Be production.

Figure 4 shows the strong correlation between solar activity [grey and black] and the climate change proxy [d18O in red] over the past 200,000 years. According to the author, "The marine δ18O [temperature proxy] record and solar modulation are strongly correlated at the 100,000 year timescale. It is proposed that variations in solar activity control the 100,000 year glacial–interglacial cycles." 

Variations in solar magnetic activity during the last 200 000 years: is there a Sun–climate connection?

Mukul Sharma^, 

• Department of Earth Sciences, Dartmouth College, Hanover, NH 03755, USA

Abstract

The production of ¹⁰Be in the Earth’s atmosphere depends on the galactic cosmic ray influx that, in turn, is affected by the solar surface magnetic activity and the geomagnetic dipole strength. Using the estimated changes in ¹⁰Be production rate and the geomagnetic field intensity, variations in solar activity are calculated for the last 200 ka. Large variations in the solar activity are evident with the Sun experiencing periods of normal, enhanced and suppressed activity. The marine δ¹⁸O [temperature proxy] record and solar modulation are strongly correlated at the 100 ka timescale. It is proposed that variations in solar activity control the 100 ka glacial–interglacial cycles. However, the ¹⁰Be production rate variations may have been under-estimated during the interval between 115 ka and 125 ka and may have biased the results. Future tests of the hypothesis are discussed.

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100,000-year climate pattern linked to sun's magnetic cycles, according to a new analysis

Posted 06/06/02 Thanks to new calculations by a Dartmouth geochemist, scientists are now looking at the earth's climate history in a new light. Mukul Sharma, Assistant Professor of Earth Sciences at Dartmouth, examined existing sets of geophysical data and noticed something remarkable: the sun's magnetic activity is varying in 100,000-year cycles, a much longer time span than previously thought, and this solar activity, in turn, may likely cause the 100,000-year climate cycles on earth. This research helps scientists understand past climate trends and prepare for future ones. Published in the June 10 issue of Earth and Planetary Science Letters (Elsevier, volume 199, issues 3-4), Sharma's study combined data on the varying production rates of beryllium 10, an isotope found on earth produced when high-energy galactic cosmic rays bombard our atmosphere, and data on the past variations in the earth's magnetic field intensity. With this information, Sharma calculated variations in solar magnetic activity going back 200,000 years, and he noticed a pattern. Over the last 1 million years, the earth's climate record has revealed a 100,000-year cycle oscillating between relatively cold and warm conditions, and Sharma's data on the sun's magnetic activity corresponded to the earth's ice age history. "Surprisingly, it looks like solar activity is varying in longer time spans than we realized," says Sharma. "We knew about the shorter cycles of solar activity, so maybe these are just little cycles within a larger cycle. Even more surprising is the fact that the glacial and interglacial periods on earth during the last 200,000 years appear to be strongly linked to solar activity." Sharma's calculations suggest that when the sun is magnetically more active, the earth experiences a warmer climate, and vice versa, when the sun is magnetically less active, there is a glacial period. Right now, the earth is in an interglacial period (in between ice ages) that began about 11,000 years ago, and as expected, this is also a time when the estimated solar activity appears to be high. Beryllium 10 is useful for studying the geology from hundreds of thousands of years ago mainly because it has a half-life of about one and a half million years. In addition, there are two key factors that have affected beryllium 10 production over the last 200,000 years: the earth's magnetic field and the sun's magnetic activity. When there are high-intensity solar magnetic storms, more charged particles are interacting with cosmic rays, and less beryllium 10 is produced. Likewise, the earth's magnetic field changes the flux of cosmic rays into and out of the atmosphere. Since the production rate of beryllium 10 and earth's magnetic field intensity are known for the last 200,000 years, Sharma could calculate solar magnetic activity for this time period. "I took sets of existing, independent data and made new comparisons and calculations," says Sharma. Then he went a step further to make a connection with the history of ice ages by looking at oxygen isotopes in the oceans, which reveal the history of how much ice was at the poles and are therefore a measure of average global surface temperature. "I compared the estimated past variations in the solar activity with those of the oxygen isotopes in the ocean. Although there is a strong relationship between solar activity and oxygen isotopic variations, it is too early to say exactly what is the mechanism though which the sun is influencing the terrestrial climate." One explanation of the 100,000-year cycle was offered by the Milankovitch Theory of Ice Ages in the 1940s, which suggested that the cyclical variations in the earth's orbit around the sun result in the earth receiving varying amounts of solar radiation that, in turn, control the climate. This explanation is under dispute because the variations of the solar energy in relation to the changes in orbit are very small. Other current research focuses on past variations in the sun's irradiance, or heat intensity (as opposed to the magnetic activity). Sharma notes that more analysis is needed to test his theory. "I've only looked at 200,000 years. My calculations need to be verified for a million years, for instance. Plus, regarding the current global warming debate, it still needs to be examined if the role of solar activity will exacerbate the rising temperatures that result from carbon dioxide buildup in the atmosphere." This work was supported by Dartmouth College, the Max Planck Institute and by a grant from the National Science Foundation.

Related: 

New paper finds ice ages explained even with constant levels of CO2

New paper finds climate change & CO2 levels explained as a function of lagged solar activity

A new paper under open review for Earth System Dynamics finds Holocene climate change can be explained on the basis of lagged responses to changes of solar activity. According to the author,

This paper analyzes the lagged responses of the Earth’s climate system, as part of cosmic-solar-terrestrial processes. Firstly, we analyze and model the lagged responses of the Earth’s climate system, previously detected for geological and orbital scale processes, with simple non-linear functions, and we estimate a correspondent lag of ~1600-yr for the recently detected ~9500-yr scale solar recurrent patterns. Secondly, a recurrent and lagged linear influence of solar variation on volcanic activity and carbon dioxide (CO2) has been assessed for the last millennia, and extrapolated for future centuries and millennia. As a consequence we found that, on one side, the recent CO2 increase can be considered as a lagged response to solar activity, and, on the other side, the continental tropical climate signal during late Holocene can be considered as a sum of three lagged responses to solar activity, through direct, and indirect (volcanic and CO2), influences with different lags of around 40, 800 and 1600 years. 

Note the ~1600 year lag of response to solar activity is essentially the same as the well-known ~1500 year "never-ending climate cycle" identified by numerous peer-reviewed, published papers.

Note also the paper explains CO2 levels on the basis of a lagged function of solar activity, due to variations in solar heating of the oceans, and ocean in-gassing and out-gassing of CO2, not as a result of the ~4% CO2 contribution from mankind. 

The paper shows the (noisy) 1600-year climate cycle in the ice core 10Be proxy of solar activity of the past 1800 years peaked in the 1900's. The orange lines are modeled on the basis of a function of three lagged compenents of solar activity cycles and is currently on a downswing until ~2100, indicating potentially cooler Earth temperatures ahead. 

According to the author, "we propose the global ocean circulation processes, that include the well known meridional overturning circulation, and the thermohaline circulation, as a global mechanism capable of explaining the lagged forcing (volcanic activity & CO2) and continental tropical climate responses to solar activity variations."

The Earth’s climate system recurrent & multi-scale lagged responses: empirical law, evidence, consequent solar explanation of recent CO2 increases & preliminary analysis

Jorge Sánchez-Sesma

Received: 18 Aug 2016 – Accepted: 31 Aug 2016 – Published: 07 Sep 2016

Abstract. This paper analyzes the lagged responses of the Earth’s climate system, as part of cosmic-solar-terrestrial processes. Firstly, we analyze and model the lagged responses of the Earth’s climate system, previously detected for geological and orbital scale processes, with simple non-linear functions, and we estimate a correspondent lag of ~1600-yr for the recently detected ~9500-yr scale solar recurrent patterns. Secondly, a recurrent and lagged linear influence of solar variation on volcanic activity and carbon dioxide (CO2) has been assessed for the last millennia, and extrapolated for future centuries and millennia. As a consequence we found that, on one side, the recent CO2 increase can be considered as a lagged response to solar activity, and, on the other side, the continental tropical climate signal during late Holocene can be considered as a sum of three lagged responses to solar activity, through direct, and indirect (volcanic and CO2), influences with different lags of around 40, 800 and 1600 years. Thirdly, we find more examples of this ~1600-yr lag, associated with oceanic processes throughout the Holocene, manifested in the mineral content of SE Pacific waters, and in a carbon cycle index, CO3, in the Southern Atlantic. Fourthly, we propose the global ocean circulation processes, that include the well known meridional overturning circulation, and the thermohaline circulation, as a global mechanism capable of explaining the lagged forcing (volcanic activity & CO2) and continental tropical climate responses to solar activity variations. Finally, some conclusions are provided for the lagged responses of the Earth's climate system with their influences and consequences on present and future climate, and implications for climate modelling are preliminarily analyzed.

New paper finds Indian climate is influenced by solar activity

A paper published today in Advances in Space Research finds "Indian climate appears to be influenced by solar variability" and the "mechanism for the Sun–climate relationship may be related solar polarity also." The authors conclude,

"Comparison of the relationships between the Indian temperature anomalies and solar activity (SSN) provides evidence favouring a mechanism that depends not only on the level of sunspot activity but also on solar polarity."

and in turn show that this may be related to Svensmark's cosmic ray theory of climate [one of many solar amplification mechanisms described in the scientific literature]:

"Reversal in the polarity of the solar polar magnetic field takes place near the solar activity maximum in each solar cycle, and the large-scale interplanetary magnetic field is an extension of the solar polar magnetic field in space (Smith et al., 1978). It is also known that the large-scale structure of the interplanetary magnetic field is of basic importance for the long-term modulation of galactic cosmic rays (Venkatesan and Badruddin, 1990, Kudela et al., 2000 and Badruddin et al., 2007). There are indications that long-term variability in cosmic ray intensity influences the Earth’s climate (Svensmark and Friis-Christensen, 1997, Kirkby, 2007 and Rao, 2011). Thus, we have studied the Sun–climate relationship by averaging the data over the time scales of solar polarity epoch (peak to peak SSN). Averaged over this time scale, we found a significant improvement in correlation between and temperature anomalies as compared to decadal and solar activity cycle timescales."

Advances in Space Research

Volume 54, Issue 8, 15 October 2014, Pages 1698–1703

Study of the influence of solar variability on a regional (Indian) climate: 1901–2007

• O.P.M. Aslam, 
• Badruddin^, 

 Show more

DOI: 10.1016/j.asr.2014.06.019

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Highlights

•

Influence of solar variability on the Indian climate has been studied.

•

Indian climate appears to be influenced by solar variability.

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Mechanism for Sun–climate relationship may be related solar polarity also.

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Abstract

We use Indian temperature data of more than 100 years to study the influence of solar activity on climate. We study the Sun–climate relationship by averaging solar and climate data at various time scales; decadal, solar activity and solar magnetic cycles. We also consider the minimum and maximum values of sunspot number (SSN) during each solar cycle. This parameter SSN is correlated better with Indian temperature when these data are averaged over solar magnetic polarity epochs (SSN maximum to maximum). Our results indicate that the solar variability may still be contributing to ongoing climate change and suggest for more investigations.

Keywords

• Sun–climate relationship; 
• Global warming; 
• Indian climate; 
• Solar activity

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1. Introduction

The long-term increase in the globally averaged yearly mean temperatures registered in the 20th century has raised the question as to what part, if any, of the observed changes can be attributed to human influence and what part, if any, can be attributed to natural phenomena? A measure of natural phenomenon, the sunspot number (SSN) is a solar activity index with long data record. It is frequently used when studying long-term phenomena like climate change, though it may not be the most appropriate index (Georgieva and Kirov, 2006).

The term global warming is now popularly used to refer the recent reported increase in the mean surface temperature of the Earth; this increase being attributed to increasing human activity, and in particular to the increased contribution of greenhouse gases (Carbon dioxide, Methane and Nitrous oxide) in the atmosphere. However, there is a dissenting view of global warming science too, which is at odds with this view of the cause of global warming (see, Khandekar et al., 2005). The physical mechanism of the greenhouse gases has been understood whereas the mechanism of solar influence on weather and climate requires more detailed study (Stozhkov, 2003 and Gray et al., 2010).

Observations over the last century have shown that the climate at most places on our globe has changed considerably. The extent to which these changes result from human and/or natural forcing is a subject of intense study (e.g., Solanki and Krivova, 2003, Hiremath, 2009, Mufti and Shah, 2011, Rao, 2011 and Ahluwalia, 2012). One reason is that both human influences on the environment (e.g., anthropogenic CO₂ in the atmosphere) and solar activity increased considerably over the last century. This covariance hampers isolation of their separate effects. Moreover, the climatic impacts of several forcing factors are still insufficiently understood.

The solar–climate relationship is currently a matter of a fierce debate. Despite the increasing evidence of its importance, solar–climate variability is likely to remain controversial until a physical mechanism is established. Nevertheless, it is important to identify the primary forcing agents since they provide the fundamental reason why the climate changed. A key issue of climate change is to identify the forcing and their relative contributions.

The Sun can have obvious effect on climate change; its radiation is the main energy source for the outer envelopes of our planet. Nevertheless, there is a long-standing controversy on whether solar variability can significantly generate climate change, and how this might occur. Eddy (1976) initiated the modern study of this topic by pointing out that the Maunder Minimum (1645–1715) in sunspot activity corresponded to the oldest excursion of the Little Ice Age (1450–1850). Subsequent studies related to the solar influence on the Earth’s temperature are quite extensive (see, Eddy, 1976, Reid, 1987, Friis-Christensen and Lassen, 1991,Carslaw et al., 2002, Shaviv and Viezer, 2003, de Jager, 2005, de Jager and Usoskin, 2006, Usoskin and Kovaltsov, 2006, Haigh, 2007, Kirkby, 2007, Gray et al., 2010, Beig, 2011, Singh et al., 2011 and Hady, 2013, and references therein), indicating the importance of the problem and that there are many issues that require further investigations. There are indications from recent and past research (e.g., see Lockwood et al., 2011 and Maghrabi and Al Dajani, 2014; and references therein) that some regional climates will be more susceptible to solar changes.

2. Methodology

In this article, we study the solar influence on climate using a climate (temperature) and a solar activity (sunspot) parameter. We used Indian monthly surface temperature data (all India maximum and minimum) anomalies for the period 1901–2007. All India monthly maximum (Tmax) and minimum (Tmin) surface temperature data sets for the period 1901–2007 are available through Indian Institute of Tropical Metrology’s (IITM’s) data archival (http://www.tropmet.res.in/). This data archival contains data of 107 years (each year have 12 monthly values), generated at IITM using instrumental meteorological records of the India Meteorological Department (IMD). They used climatological normals of monthly mean maximum and minimum temperatures for the period 1951–80 for 388 well-spread stations from the monthly weather records of the India Meteorological Department (IMD, 1999). The procedure adopted for monthly all India maximum and minimum temperature data generation has been explained (see, Kothawale and Rupa Kumar, 2005;ftp://103.251.184.5/pub/data/txtn/README.pdf). We have calculated the anomalies in all India maximum (dTmax) and minimum (dTmin) temperature using this monthly temperature data. We have calculated the mean-yearly temperature by taking average over 12 months (January–December). Average of yearly-mean temperature for the period 1951–80 is taken as reference; we calculated the deviation (anomaly in temperature) in yearly-mean temperature of individual years. Using the anomalies in all India maximum and minimum temperature we also calculated anomalies in average temperature [i.e., dTav = (dTmax + dTmin)/2].

Sunspot number is the solar activity parameter available and well documented on monthly and yearly average basis for continuous long periods of time (http://solarscience.msfc.nasa.gov/). The relationship between the anomalies in Indian temperature and SSN has been studied at various time scales relevant for extracting some physical meaning to the Sun–climate relationship.

3. Results and discussion

Fig. 1 shows the sunspot variations from the beginning of the last century. To start with, we have studied the relationship between the decadal averages of sunspot number () and temperature anomalies (, , and (see, Fig. 2a). We observe that, averaged over decadal time scale, there is some correspondence between the solar and climate parameters. However, this correspondence is poor during the last decade of the 20th century and the beginning years (2001–2007) of this century.

Fig. 1. 

Variation of the annual average sunspot numbers (SSN) from 1901 to 2012.

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Fig. 2. 

Variation of the SSN and temperature anomalies of Indian temperature for (a) ‘decadal average’ for the period 1901–2007, (b) the ‘SSN Peak to peak averages’ for the period 1905–2007.

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A Schwabe (solar activity) cycle period may range from 9 to 17 years, measured from one sunspot minimum to the next sunspot minimum, with an average period of 11 years. The Schwabe cycle is the most prominent periodicity in solar activity. It may be more useful to consider the solar cycle average, instead of decadal average, for the study of the relationship between solar activity and climate. Both the durations and the amplitudes of different solar cycles are quite variable (see Fig. 1). Therefore, we performed an analysis to study the Sun–climate relationship for solar cycle averages. We find that relationship between the solar cycle averaged sunspot number () and temperature anomalies is not much different from that observed on the decadal average scale (see, Table 1). Results of correlation analysis between SSN and temperature anomalies at various time scales are tabulated in Table 1, showing value of correlation coefficients (R) along with p-value and confidence interval for confidence level of 95%. The probability of error that is involved in accepting our observed result is represented by p-value, i.e., smaller the p-value, stronger the validity of the observed result (e.g., a p-value of 0.05 indicate that there is a 5% probability that the relation between parameters found in our study is a chance of occurrence). Confidence interval provides a range of possible R values which is likely to include an unknown population. Confidence interval includes zero means the correlation is not significant at the given level of confidence (95%).

Table 1.

Result of correlation analysis between sunspot number (SSN) and temperature anomalies at various time scales.

Time scale			Correlation coefficient
SSN	Temperature	Total periods	dTmax				dTmin				dTav
			R	p-Value	Confidence interval of R for confidence level of 95%		R	p-Value	Confidence interval of R for confidence level of 95%		R	p-Value	Confidence interval of R for confidence level of 95%
					Lower limit	Upper limit			Lower limit	Upper limit			Lower limit	Upper limit
Decadal average	Same period average	1901–2000	0.61	0.0611	−0.032	0.896	0.63	0.0509	0.001	0.902	0.74	0.0144	0.207	0.934
		1901–2007⁎	0.36	0.2768	−0.306	0.789	0.33	0.3216	−0.336	0.776	0.38	0.2490	−0.285	0.798
Solar cycle average	Same period average	1901–1995	0.49	0.1806	−0.256	0.871	0.53	0.1422	−0.207	0.883	0.75	0.0199	0.171	0.944
		1901–2007⁎	0.30	0.3997	−0.406	0.782	0.29	0.4163	−0.415	0.778	0.35	0.3215	−0.359	0.803
SSN peak to peak average	Same period average	1905–1999	0.79	0.0113	0.265	0.954	0.67	0.0483	0.011	0.923	0.89	0.0013	0.552	0.977
		1905–2007⁎	0.68	0.0305	0.088	0.917	0.56	0.0923	−0.108	0.880	0.69	0.0272	0.107	0.920
Max SSN in solar cycle	Solar cycle average	1901–1995	0.39	0.2994	−0.370	0.837	0.65	0.0581	−0.025	0.918	0.72	0.0287	0.107	0.936
		1901–2007⁎	0.26	0.4163	−0.415	0.778	0.41	0.2393	−0.296	0.826	0.38	0.2787	−0.328	0.815
Minimum SSN at the beginning of the cycle	Solar cycle average	1901–1995	0.90	0.0009	0.586	0.979	−0.03	0.9389	−0.681	0.647	0.80	0.0096	0.290	0.956
		1901–2007⁎	0.73	0.0165	0.186	0.931	0.05	0.8909	−0.598	0.659	0.54	0.1071	−0.136	0.873
Solar magnetic cycle average	Average of same period	1905–1999	0.84	0.1600	−0.163	0.989	0.64	0.0634	−0.042	0.915	0.88	0.1200	−0.010	0.992
		1905–2007⁎	0.68	0.2066	−0.506	0.976	0.53	0.1151	−0.150	0.869	0.47	0.4244	−0.704	0.956

⁎

Including data points of recent period (available up to 2007).

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Reversal in the polarity of the solar polar magnetic field takes place near the solar activity maximum in each solar cycle, and the large-scale interplanetary magnetic field is an extension of the solar polar magnetic field in space (Smith et al., 1978). It is also known that the large-scale structure of the interplanetary magnetic field is of basic importance for the long-term modulation of galactic cosmic rays (Venkatesan and Badruddin, 1990, Kudela et al., 2000 and Badruddin et al., 2007). There are indications that long-term variability in cosmic ray intensity influences the Earth’s climate (Svensmark and Friis-Christensen, 1997, Kirkby, 2007 and Rao, 2011). Thus, we have studied the Sun–climate relationship by averaging the data over the time scales of solar polarity epoch (peak to peak SSN). Averaged over this time scale, we found a significant improvement in correlation between and temperature anomalies as compared to decadal and solar activity cycle timescales (see Table 1 and Fig. 2b).

Georgieva et al. (2012) recently studied the influence of solar poloidal and solar toroidal-related solar activities on the atmospheric circulation. The highest value of sunspots in a solar cycle, SSN_max, is considered as a proxy for the toroidal field strength (de Jager, 2005). Since the amplitudes of solar activity (SSN_max) in different cycles are quite variable, ranging from ∼50 to ∼200 (see Fig. 1). Moreover, the lowest activity (SSN_min) in the beginning of each cycle is also somewhat variable; we also looked at the relationship between SSN_max of each solar cycle and cycle-averages of temperature anomalies, as well as between SSN_min at the beginning of each cycle and cycle averages of temperature anomalies. The correlations in these two cases are, in general, lower than those found when averaged over peak to peak sunspot periods (see Table 1).

It is well known that the number of sunspots increases and then decreases in approximately 11-year intervals. The 11-year sunspot cycle is actually a 22-year cycle in the solar magnetic field, with sunspots showing the same hemispheric magnetic polarity on alternate 11-year cycles; polarity reversal taking place around solar maximum. Therefore, we have looked for the relationship between the SSN and the temperature anomalies averaged over the solar magnetic cycles. In this case the correlation of with temperature anomalies is somewhat lower as compared to that when averaged over only one polarity epoch. Thus, when averaged over each solar polarity epoch (sunspot maximum to maximum), the relationship between the sunspot number and temperature anomaly is found to be the best among all those discussed above.

The question of a definite relation between temperature and the solar activity is still a matter of debate. Our results, however, indicate that some relationship does exist.

Sunspot cycle 23 was unusual (e.g., see Aslam and Badruddin, 2012 and Hady, 2013, and references therein), the current sunspot minimum has been unusually long, and with more than 670 days without sunspots through June 2009. The solar wind is reported to be in a unique low energy state since space measurements began nearly 40 years ago (Fisk and Zhao, 2009 and Livingston and Penn, 2009). Unfortunately, all India temperature data (Tmax, Tmin) is not available to us after 2007; it would be very interesting to look for Sun–climate relationship during cycle 24.

4. Conclusions

Comparison of the relationships between the Indian temperature anomalies and solar activity (SSN) provides evidence favouring a mechanism that depends not only on the level of sunspot activity but also on solar polarity. In spite of the evidences found during the most part of the past century, the latest temperature rise in the 1990’s (especially during solar cycle 23) is difficult to comprehend from most of the discussed results. However, on the solar polarity scale (sunspot maximum to maximum), there are some indications, from the data up to 2007, that a link between solar activity and climate can still be accounted for, and this connection will be watched with curiosity during the current solar cycle 24 and later periods.