Abstract
Abstract. We employ JRA-55 (Japanese 55-year Reanalysis), a recent second-generation global reanalysis providing data of high quality in the stratosphere, to examine whether a distinguishable effect of geomagnetic activity on Northern Hemisphere stratospheric temperatures can be detected. We focus on how the statistical significance of stratospheric temperature differences may be robustly assessed during years with high and low geomagnetic activity. Two problems must be overcome. The first is the temporal autocorrelation of the data, which is addressed with a correction of the t statistics by means of the estimate of the number of independent values in the series of correlated values. The second is the problem of multiplicity due to strong spatial autocorrelations, which is addressed by means of a false discovery rate (FDR) procedure. We find that the statistical tests fail to formally reject the null hypothesis, i.e. no significant response to geomagnetic activity can be found in the seasonal-mean Northern Hemisphere stratospheric temperature record.
Highlights
There is a large interest in the potential climate impact of geomagnetic activity
We focus on wintertime stratospheric temperatures between 200 and 1 hPa, a prerequisite for possible surface impacts associated with electron precipitation (EEP)-related changes in ozone concentrations
At 5 hPa, the area with significant differences covers most of the Northern Hemisphere in JJA, but, as can be seen from the analysis of the Durbin–Watson test, the summer season exhibits a large temporal autocorrelation
Summary
There is a large interest in the potential climate impact of geomagnetic activity. One of the main mechanisms by which geomagnetic activity is thought to affect the middle atmosphere is through the production of nitrogen oxides (NOx), either by the continuous precipitation of auroral electrons penetrating into the lower thermosphere (Sinnhuber et al., 2012) or by the more episodic precipitation of higher energy electrons into the mesosphere (Andersson et al, 2014; Päivärinta et al, 2016). By compositing separately on the basis of Ap and f10.7, S09 obtained different samples of seasonal-mean data for years with high geomagnetic activity and for years with low geomagnetic activity. They computed the SAT differences of the seasonal means (December, January and February – DJF; March, April and May – MAM; June, July and August – JJA; and September, October and November – SON) between the two samples and employed a t test based on the set of daily means (Annika Seppälä, personal communication, 2018) used to compute the seasonal averages to discriminate against a null hypothesis of no effect.
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