New paper finds another solar amplification mechanism by which the Sun controls climate

A paper published today in Environmental Research Letters finds another potential solar amplification mechanism by which changes in solar UV activity over 11-year solar cycles are amplified to large-scale effects upon climate via modulations of the North Atlantic Oscillation [NAO]. 

The authors model a mechanism whereby large changes (up to 100%) in solar UV over solar cycles affect heating rates of the upper stratosphere, which in turn affect winds and temperature gradients in the troposphere, and heat storage in North Atlantic Ocean. This results in a lagged effect of 3-4 years in the amplitude of the North Atlantic Oscillation, which in turn affects Arctic sea ice extent, other ocean oscillations, the jet stream, and weather patterns around the globe. The paper corroborates several others demonstrating solar influence upon the NAO, as well as other ocean oscillations. 

According to the authors,

Numerous studies have suggested an impact of the 11 year solar cycle on the winter North Atlantic Oscillation (NAO), with an increased tendency for positive [NAO signals to occur at maxima of the solar cycle, and negative NAO signals to occur at minima of the solar cycle]. Climate models have successfully reproduced this solar cycle modulation of the NAO, although the magnitude of the effect is often considerably weaker than implied by observations.  

A leading candidate for the mechanism of solar influence is via the impact of ultraviolet radiation variability on heating rates in the tropical upper stratosphere, and consequently on the meridional temperature gradient and zonal winds...On reaching the troposphere this produces a response similar to the winter NAO. Recent analyses of observations have shown that solar cycle–NAO link becomes clearer approximately three years after solar maximum and minimum. Previous modelling studies have been unable to reproduce a lagged response of the observed magnitude. 

In this study, the impact of solar cycle on the NAO is investigated using an atmosphere–ocean coupled climate model. We show that the model produces significant NAO responses peaking several years after extrema of the solar cycle, persisting even when the solar forcing becomes neutral. This confirms suggestions of a further component to the solar influence on the NAO beyond direct atmospheric heating and its dynamical response. Analysis of simulated upper ocean temperature anomalies confirms that the North Atlantic Ocean provides the memory of the solar forcing required to produce the lagged NAO response. These results have implications for improving skill in decadal predictions of the European and North American winter climate.

A simulated lagged response of the North Atlantic Oscillation to the solar cycle over the period 1960–2009

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M B Andrews 1, J R Knight 1 and L J Gray 2
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M B Andrews et al 2015 Environ. Res. Lett. 10 054022
doi:10.1088/1748-9326/10/5/054022Published 22 May 2015

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Abstract

Numerous studies have suggested an impact of the 11 year solar cycle on the winter North Atlantic Oscillation (NAO), with an increased tendency for positive (negative) NAO signals to occur at maxima (minima) of the solar cycle. Climate models have successfully reproduced this solar cycle modulation of the NAO, although the magnitude of the effect is often considerably weaker than implied by observations. A leading candidate for the mechanism of solar influence is via the impact of ultraviolet radiation variability on heating rates in the tropical upper stratosphere, and consequently on the meridional temperature gradient and zonal winds. Model simulations show a zonal mean wind anomaly that migrates polewards and downwards through wave–mean flow interaction. On reaching the troposphere this produces a response similar to the winter NAO. Recent analyses of observations have shown that solar cycle–NAO link becomes clearer approximately three years after solar maximum and minimum. Previous modelling studies have been unable to reproduce a lagged response of the observed magnitude. In this study, the impact of solar cycle on the NAO is investigated using an atmosphere–ocean coupled climate model. Simulations that include climate forcings are performed over the period 1960–2009 for two solar forcing scenarios: constant solar irradiance, and time-varying solar irradiance. We show that the model produces significant NAO responses peaking several years after extrema of the solar cycle, persisting even when the solar forcing becomes neutral. This confirms suggestions of a further component to the solar influence on the NAO beyond direct atmospheric heating and its dynamical response. Analysis of simulated upper ocean temperature anomalies confirms that the North Atlantic Ocean provides the memory of the solar forcing required to produce the lagged NAO response. These results have implications for improving skill in decadal predictions of the European and North American winter climate.

1. Introduction

The variability of the Sun's output influences the heating of the stratosphere via the absorption of ultraviolet (UV) by ozone (Haigh1994, Gray et al 2009). Observational studies of the influence of the 11 year solar cycle show warm temperature anomalies in the equatorial upper stratosphere at solar maximum compared to solar minimum (Frame and Gray 2010, Mitchell et al 2014). Significant changes in the extratropical atmospheric circulation have been linked to these temperature anomalies (Kodera 1995, Kodera and Kuroda 2002), and this is supported by modelling studies (e.g. Matthes et al 2004, 2006, Ineson et al 2011). One of the mechanisms for 'top-down' solar influence (Gray et al 2010) involves equatorial stratospheric warm anomalies at solar maximum which increases the mean meridional temperature gradient, resulting in an increase in the mean Westerly wind in the mid-latitude stratosphere. This positive zonal wind anomaly is then amplified by forcing from planetary waves propagating upwards from the troposphere. Along with meridional advection, this wave feedback causes the poleward and downward migration and amplification of the wind anomaly to the mid- and high-latitude lower stratosphere, where it is able to influence tropospheric circulation. The resulting surface response involves sea-level pressure changes at solar maximum which are very similar to the positive phase of the Arctic Oscillation (AO), with anomalous low pressure over the North Pole bordered by anomalous high pressure in mid-latitudes (Thompson and Wallace 1998). Conversely, at solar minimum, a negative AO response results from reduced stratospheric meridional temperature gradients and the downward and poleward propagation of negative zonal wind anomalies. This top-down mechanism occurs on seasonal timescales since planetary wave propagation in the stratosphere is limited to the winter half-year.

This 'top-down' mechanism cannot explain the recently identified lag of approximately 3 years between solar maximum (minimum) and an increased tendency of a positive (negative) North Atlantic Oscillation (NAO) signal superimposed on the intrinsic year-to-year NAO variability (Gray et al 2013). The ability of the climate system to produce a multi-year lag in the winter NAO response necessitates the persistence of solar signals within the climate system from one winter to the next. Scaife et al (2013) showed that the North Atlantic Ocean is a prime candidate for the source of the lag. Model simulations have demonstrated that the sub-surface North Atlantic Ocean can be influenced by NAO changes related to the internal variability of stratospheric circulation (Reichler et al2012) and changes in multidecadal solar irradiance (Menary and Scaife 2014). On interannual timescales, Scaife et al (2013) presented a mechanism involving coupled atmosphere–ocean feedbacks. The NAO is known to be correlated with a tripole pattern in the North Atlantic sea-surface temperatures (SST), (Visbeck et al 2003), which extends below the surface into the ocean mixed layer. Due to the seasonal cycle in surface heat and turbulent fluxes, the mixed-layer-depth (MLD) is deeper in winter than in summer. This suggests that a winter sub-surface ocean signal, linked to solar variability, could persist by being isolated underneath the shallower summer mixed layer from the modifying influence of surface fluxes from the atmosphere. In autumn, as the summer mixed-layer erodes and the deeper winter mixed layer becomes established, any sub-surface solar signal would reconnect with the surface, giving it the potential to influence the atmosphere. This sequestration and re-emergence of signals from one winter to the next has been shown to operate in other contexts (Alexander et al 1999, Timlin et al 2002, Deser et al 2003, Taws et al 2011), and would give rise to a forcing of the NAO by the ocean (Rodwell and Folland 2002). Hanawa and Sugimoto (2004) identified several regions of re-emergence including areas of the North Atlantic relevant to this study. Scaife et al (2013) argue that a weak solar-related AO/NAO signal could build up over a number of years in the tripole region of the North Atlantic Ocean and feedback onto the atmosphere to produce a peak in the NAO signal after a few years.

Several studies have examined the simulated NAO response to solar forcings. Gray et al (2013) and Mitchell et al (2015) showed that Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations were unable to reproduce the observed NAO response. On the other hand, Ineson et al (2011) were able to simulate a realistic amplitude of the NAO response by imposing a higher level of variability in UV-band irradiance. They reproduced the UV-induced 'top-down' mechanism, connecting the upper-stratosphere and the tropospheric NAO. The simulations from Ineson et al (2011) were further analysed by Scaife et al (2013), who showed that the implied ocean–atmosphere coupling in the model used by Ineson et al (2011) was too weak to produce the observed delay.

In this study we use historical simulations of the period 1960–2009 with CMIP5 evolving forcings to explore the influence of solar variability on the NAO. This is different to the experiments of Ineson et al (2011) which use constant forcings within their solar maximum and solar minimum scenarios. We use two ensembles, the first with solar irradiance held constant and the second with time-varying spectrally resolved solar variability. The difference in response of the ensembles should reveal the influence of the varying solar cycle on the atmosphere and oceans.

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Figure 1. (a) Time-series of imposed TSI anomaly (black line), and UV-band irradiance anomaly (dashed blue line) with respect to the 1960–2009 mean. (b) Composites of upper stratospheric zonal mean temperature (dashed red line) and DJF NAO-index (black line) as a function of lag with respect to solar maximum minus solar minimum. The upper stratospheric temperature is calculated as the annual average of the region bounded by 0.5–5 hPa (approximately 40–55 km), and 30 °S–30 °N. The NAO-index is defined as the DJF surface pressure difference between the Azores and Iceland. The points where the NAO-index is significant at the 95% level are highlighted with squares.

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Summary

We have investigated the NAO response to solar variability using a state-of-the-art atmosphere–ocean coupled model. Historical ensembles for the period 1960–2009 were performed with constant and time-varying solar irradiance. Analysis of the differences between the ensembles was performed to identify solar cycle responses in the atmosphere and ocean. The results demonstrate tropical upper stratospheric heating in response to the imposed UV change at solar maximum compared to solar minimum, and confirm the results of Ineson et al (2011), showing a subsequent surface winter NAO response via a 'top-down' mechanism. The response of the NAO peaks 3–4 years following the extreme phase of the solar cycle. This finding is consistent with a recent re-evaluation of observed responses to the solar cycle (Gray et al 2013) which shows the largest NAO signal at a similar lag. The in-phase response of the Aleutian Low is also in agreement with observational analyses.

We diagnose the source of the NAO lag in the model by examining its surface and sub-surface solar responses in the North Atlantic Ocean. We find evidence for amplification of 'top-down' solar-related NAO changes via an ocean feedback over a period of several years, as suggested by Scaife et al (2013). This feedback is analysed by examining solar cycle responses in the different nodes of the North Atlantic tripole SST pattern, as this pattern reflects NAO–ocean coupling. The Northern and Middle nodes of the tripole show temperature responses in the surface and sub-subsurface ocean with a similar lag to the NAO. The Southern node, however, does not show any lag. In the Middle node we find re-emergence of solar signals imprinted on the ocean from the previous winter. By remaining intact below the shallow ocean mixed-layer that forms in summer, these signals can re-emerge in winter and reinforce the 'top-down' forcing of the NAO via coupling with the atmosphere. This mechanism is not evident in the Northern and Southern nodes. The simulated re-emergence in the North Atlantic Ocean causes an accumulation of the solar signal, allowing the NAO to grow over several years. This growth is limited by the reversal of the solar cycle, resulting in a lag approximately equal to one quarter of its period. Although we do not explicitly demonstrate here that the growth in the NAO response arises through feedback from the solar SST signal in the Middle node the existence of this feedback is supported by previous studies (Rodwell and Folland 2002, Timlin et al 2002) that show the influence of tripole SSTs on the NAO.

The NAO (Hurrell et al 2003) is a key mode of regional climate variability that strongly influences the wintertime weather of Northern Europe and Eastern North America. The ability to reproduce the lagged NAO response to solar forcing in atmosphere–ocean coupled models offers the possibility of increased NAO predictability and hence skill in seasonal forecasts (Scaife et al 2014) and decadal forecasts up to a few years ahead (Smith et al 2012).