Elsevier

Advances in Space Research

Volume 55, Issue 1, 1 January 2015, Pages 106-112
Advances in Space Research

The relationship between the Quasi Biennial Oscillation and Sunspot Number

https://doi.org/10.1016/j.asr.2014.09.035Get rights and content

Highlights

  • The relation between the QBO and SSN is investigated with a multiple regression model.

  • There is a positive relation between QBO- and SSN for solar maximum.

  • There is a negative relation between QBO- and SSN for solar minimum.

  • We observed that the variation of QBO up to maximum 16 m/s is due to SSN.

Abstract

In this study, the relationship between the monthly mean values of the Quasi Biennial Oscillation (QBO) measured at 10 hPa and 70 hPa altitudes and Sunspot Number (SSN) for solar maxima and solar minima conditions is analyzed. Before applying the model for the statistical analysis of the study, the stationary of the variables is investigated by using the unit root test. Existence of a long-term relationship between the variables is also investigated by using the co-integration test. Positive and negative relationships between SSN and QBO obtained for 10 hPa and 70 hPa are observed for the solar maxima and the solar minima, respectively. The explainable effects of the SSN on the QBO at 10 hPa altitude are greater than those at 70 hPa. When the calculated coefficients are analyzed, it is observed that the variation of QBO up to 16 m/s is due to SSN. The rest of at least 34 m/s are seen to be based on the other variables.

Introduction

The Quasi-Biennial Oscillation (QBO) is a quasi-periodic oscillation of the equatorial regional wind between easterlies and westerlies in the tropical stratosphere with a mean period of 28–29 months (Heaps et al., 2000). The QBO generally emerges in the equatorial region and moves with a velocity of approximately 30 m/s in the east (negative sign) and 20 m/s in the west (positive sign) (see Fig. 1 and Fig. 2). Although maximum amplitude of the QBO is generally at the level of 10 hPa, it varies from 100 hPa to 2 hPa (Baldwin et al., 2001).

Several solar indices have been developed to describe the amount of solar disturbances occurring at any given time and location. One of the most important solar indices is the Sunspot Numbers (SSN) (see Fig. 1 and Fig. 2). SSN is a solar index that measures the total number of sunspots and groups of sunspots on the surface of the sun. SSN decreases and increases over a period of approximately 11 years (Banks and Kockarts, 1973, Tascione, 1994, Whitten and Poppoff, 1971).

Labitzke (1987) and Labitzke and van Loon (1988) originally discover a signature of the 11-year solar cycle (SC) in polar stratospheric temperatures stratified according to the easterly or westerly phase of the equatorial QBO. Since then, this possible solar-QBO-stratosphere/troposphere relationship has been intensively investigated in numerous observational and modeling studies (e.g., Baldwin and Dunkerton, 1989, Hamilton, 2002, Mayr et al., 2003, Soukharev and Hood, 2001). Salby and Callaghan (2000) suggest that the solar signature observed in stratospheric records, grouped according to QBO phase, may be caused, at least in part, by an 11-year solar cycle modulation of the equatorial QBO itself. Particularly, they have found that the duration of the westerly QBO phase in the middle stratosphere varies in a systematic pattern resembling the curve of the 11-year solar cycle.

Because of the major role of the QBO in determining interannual variability of the stratosphere, such a modulation, if present, could significantly assist in explaining the unexpectedly large amplitudes of apparent solar cycle variations in the equatorial stratosphere (Soukharev and Hood, 2001). This QBO-SC relationship has been re-examined and confirmed more recently by several authors using reanalysis data (Van Loon and Labitzke, 2000, Labitzke, 2001, Labitzke, 2004, Labitzke, 2005, Salby and Callaghan, 2000, Labitzke et al., 2006, Lu et al., 2009). A direct modulation of the equatorial QBO descent rates by the SC has been proposed (McCormack, 2003, McCormack et al., 2007, Lu et al., 2009). However, it is not clear which of these, if any, is the dominant mechanism for the QBO-SC interaction (Lu et al., 2009).

The aim of the study is to statistically define the effect of SSN on QBO. The solar maxima and minima conditions are chosen for investigating the relationship between SSN and QBO. The statistical analysis used in this study, Results and Discussion and Conclusions are presented in Sections 2 The statistical analysis, 3 Results and discussions, 4 Conclusion.

Section snippets

The statistical analysis

In statistics, a multiple regression model is used to collect the observations of well-defined data items obtained through repeated measurements over time. Therefore, this statistical analysis is used to forecast and estimate the possible future cases in the related series by utilizing the estimates for the factor components. In this study, the multiple regression model is used to investigate the relationship between QBO and SSN obtained for solar maxima and solar minima cases of the solar

Results and discussions

The statistical model given in Section 2 is applied to investigate the relationship between QBO and SSN. The monthly mean values of QBO are obtained from Canton Island (02.46°S–171.33°W) for the period of 01/1953–07/1967, Gan Maldives (00.41°S–73.09°E) for the period of 08/1967–12/1975, and Singapore (01.22°N, 103.55°E) for the period of 01/1976–09/2011 (data available at http://strat-www.met.fu-berlin.de). SSN values in the solar maxima and solar minima periods are obtained for January 1977

Conclusion

In this study, the relationship between SSN for solar maxima and minima and QBO is investigated by using the multiple regression model. It is observed that QBO at 10 hPa is affected more than at 70 hPa by SSN for both solar maxima and minima. For solar maxima, SSN has a positive relationship with QBO at both 10 hPa and 70 hPa. The coefficients of this relationship for solar maxima are observed to be smaller than for solar minima at both two QBO heights. The relationship coefficient at the two QBO

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