Impacts of sunspot number and Geomagnetic aa-index on climate of Wet Zone West Africa during solar cycles 22–24

Abstract

Using the facilities at Heliophysics Science Division of NASA Goddard Space Flight Center, Greenbelt, MD, USA, we attempted to investigate the impact of solar magnetic activities on the climate of Wet Zone West Africa. The solar activity data namely, Sunspot Number (SSN) was obtained from the Royal Observatory of Belgium, Brussels; and Geomagnetic aa-index was obtained from World Data Center, Kyoto, Japan. Surface Air Temperature (SAT) and Rainfall data [for Port Harcourt in Nigeria and Abidjan in Cote D’Ivoire] were obtained from the HadCRUT-4 project of Climate Research Unit of University of East Anglia, United Kingdom. Firstly, we carried out Time Series Analysis of SSN and Geomagnetic aa-index spanning from 1950 to 2016. Secondly, we performed Regression Analysis on both solar activity data and climate variables to estimate the impact of solar magnetic activity on the Wet Zone West African climate. The Time Series Analysis showed that SSN variation was in-phase with Geomagnetic aa-index in all the solar cycles studied. Thus, Geomagnetic aa-index can be used as a proxy for studying solar magnetic activities. Performance of Regression Analysis showed that SSN regressed on SAT and Rainfall amounted to an average of 0.49 and 0.02% respectively throughout Solar Cycles 22–24. Furthermore, a regression of Geomagnetic aa-index on SAT and Rainfall yielded an average of 0.145 and 0.125% respectively. Our models showed that the variability of SAT and Rainfall in Wet Zone West Africa during Solar Cycles 22–24 are far less than 1%. Hence, the influence of SSN and Geomagnetic aa-index on SAT and Rainfall is less than 1%; and could cause ‘very small’ effect. These weak impacts are proofs that the variability of SAT and Rainfall were most probably not effected by SSN and Geomagnetic aa-index. Consequently, the variability of SAT and Rainfall in Wet Zone West Africa could not be attributed to SSN and Geomagnetic aa-index. We therefore, attempt to conclude that climate variability in Wet Zone West Africa is most probably not driven by solar magnetic activity, but could be attributed to anthropogenic activities.

Possible Linkages of Hydrological Variables to Ocean–Atmosphere Signals and Sunspot Activity in the Upstream Yangtze River Basin

“…Previous studies have confirmed that the variability of solar activity influences global climate on various timescales [22,24,25], with negative anomalies of SST in equatorial Pacific during high solar activity years [26]. Sea temperature varies in-phase with an 11-year solar activity cycle [27][28][29], which could force the Pacific decadal variability [22]. Solar activity maxima and minima refer to periods of maximum and minimum sunspot counts, with a solar cycle spanning from one sunspot minimum to the next [27]; hence, sunspot number is a possible indicator of solar activity associated with climate.…”

“…Solar activity has an average cycle with a duration of approximately 11 years [22,25,27]. The solar activity data, i.e., sunspot number (SSN), was obtained from the Royal Observatory of Belgium, Brussels (https://wwwbis.sidc.be/silso/datafiles, accessed on 7 August 2021), which is calculated from Equation (1) [27]:…”

“…Sea temperature varies in-phase with an 11-year solar activity cycle [27][28][29], which could force the Pacific decadal variability [22]. Solar activity maxima and minima refer to periods of maximum and minimum sunspot counts, with a solar cycle spanning from one sunspot minimum to the next [27]; hence, sunspot number is a possible indicator of solar activity associated with climate. Gaining a comprehensive understanding of the effects of oceanic-atmospheric climate anomalies and solar activity on temporal variability of precipitation and streamflow in specific watersheds is of great significance for hydrological simulation, climate change and risk management as well as for addressing water-resource-related issues [3,30,31].…”

Incidence of Galactic Cosmic Ray Fluxes at Polar and Middle Latitude Regions

“…Propagation of GCR is highly modulated by the structure of geomagnetic fields (Perry, 2007). A study conducted by Hanson and Okeke, (2021) revealed an in-phase variation pattern between Sunspot Number and Geomagnetic aaindex; and deduced that the latter can be used as a proxy for studying solar magnetic activities. Paudel (2014) described possible way for utilization of GCR particles for energy generation to meet humanity energy need.…”

“…Ross and Chaplin, 2019;Shuai et al, 2021;Hanson and Okeke, 2021) have utilized GCR data generated at Thule (and other NM Stations including Newark, McMurdo and South Pole), hosted at Bartol Research Institute, University of Delaware, USA; and Geomagnetic aa index hosted by World Data Center, Kyoto, Japan. The Regression of GCR on Geomagnetic aa index in Thule revealed that an increase in Geomagnetic aa-index by 1 [nT] resulted to a decrease in GCR by15.4.8 [Counts]…”