Decadal windstorm activity in the North Atlantic-European sector and its relationship to the meridional overturning circulation in an ensemble of simulations with a coupled climate model
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The relationship between decadal variations in the North Atlantic meridional overturning circulation (MOC) and North Atlantic/Western European windstorm activity during the extended winter season is studied. According to an ensemble of three 240-year long simulations performed with the ECHAM5-MPIOM model, periods of high decadal windstorm activity frequently occur in the years following a phase of weak MOC (i.e. when the MOC starts to recover). These periods are characterised by a distinctive pattern in the mixed layer ocean heat content (OHC). A positive anomaly is located in the region 45°N−52°N/35°W−16°W (west of France). Negative anomalies are located to the North and South. The signal can be detected both in the heat content of the oceanic mixed layer and in the sea surface temperatures. Its structure is consistent with anomalously enhanced baroclinic instability in the region with the strong negative OHC gradient (30°W−10°W/45°N−60°N), which eventually produces a higher probability of windstorms.
KeywordsDecadal variability Windstorms MOC
Skillful decadal climate forecasts for the North Atlantic and Europe are of high scientific interest, but the research on this subject is still at an early stage. The North Atlantic is known to exhibit decadal to multidecadal variability. Moreover, the North Atlantic has been identified as one of the regions where decadal predictability is likely to exist (Latif et al. 2006, and references therein).
Windstorm activity in the North Atlantic/Western European region, being one of the major hazards for this region, is exhibiting pronounced decadal variability (e.g., Donat et al. 2011; Wang et al. 2009). Decades with especially high windstorm activity are associated with enormous monetary losses as for example seen during the 1990’s. It is of interest to investigate, if and how the decadal variations in windstorm activity over the North Atlantic and European sector can be related to low-frequency variations in the North Atlantic.
Previous studies have already investigated the influence of the ocean on the mean state of the atmosphere, for example on the storm track (i.e. bandpass-filtered variance in the 500 hPa height field) and on the North Atlantic Oscillation (NAO). It is known that windstorms, NAO and the storm track are related. The position of the storm track is influenced by the phase of the NAO, with a positive NAO being associated with a more northerly storm track (e.g. Hurrell and van Loon 1997), a higher number of extreme cyclones (e.g. Pinto et al. 2009) as well as a higher number of windstorms affecting northern Europe (e.g. Donat et al. 2010a). The relationship between the NAO and European windstorms is, however, not linear. Most storm days are associated with a moderately positive phase of the NAO (Donat et al. 2010a). The NAO typically peaks two days prior to the time of maximum destructiveness and exhibits an anomalous shift of its low-pressure centre towards the east (Hanley and Caballero 2012).
With regard to the ocean, previous studies have used a variety of parameters to describe the ocean’s state. Some studies are based on sea surface temperatures (SSTs) and their anomalies in the North Atlantic or the tropics (e.g. ENSO). Other studies focus on ocean dynamics and consider the state of the thermohaline or Atlantic meridional overturning circulation (MOC), which is commonly determined by zonally integrating the Atlantic stream function (e.g. Pohlmann et al. 2013). Some studies also investigate the influence of the North Atlantic gyre circulation, which seems to play a less important role for the atmospheric winter variability than the MOC (Gastineau et al. 2013).
A relationship between SSTs in the North Atlantic Ocean and the storm track has been established in several studies analysing idealised model simulations (Brayshaw et al. 2008, 2011; Wilson et al. 2009; Nakamura et al. 2008). The authors agree that the location and strength of the storm track is influenced by SST anomalies. Introducing a meridional SST gradient in the western North Atlantic region associated with the Gulf Stream enhances the storm track downstream.
The response of the atmosphere to Atlantic MOC variability has been analysed by Gastineau and Frankignoul (2012) using six global climate models. An intense MOC is followed by a weak NAO and a southward shift of the storm track consistent with a horseshoe shaped anomaly in the SSTs. The lag between the MOC and the atmospheric response varies between 4 and 9 years depending on the model. Woollings et al. (2012) relate simulated changes of the storm track under climate change conditions to the weakening of the MOC anticipated in response to increasing greenhouse-gas concentrations, using 22 coupled climate models. A complete shutdown of the MOC in the Met Office Unified Model (HadCM3) results in an intensification and eastward extension of the North Atlantic storm track (Brayshaw et al. 2009).
Even though most investigations see an effect of the ocean variability on the atmosphere, there is still no consensus regarding the significance of this effect. For the seasonal to interannual time scale observations suggest that the influence of the extratropical atmosphere on the ocean is higher than the influence of the ocean on the atmosphere (e.g. Cayan 1992; Kushnir et al. 2006; Kwon et al. 2010). Still, some influence of the ocean on the atmosphere can also be detected (Frankignoul and Kestenare 2005; Renggli et al. 2011).
On the decadal to multidecadal time scale the atmospheric response to the ocean variability seems to be more significant than for the shorter time scales due to the ocean’s thermal inertia and relative slow dynamics (Bjerknes 1964; Delworth et al. 1993; Latif 1998). Several authors have studied the link between North Atlantic ocean variability and the NAO on the decadal time scale and found that the state of the NAO can be reconstructed/predicted to some extent from North Atlantic SSTs (e.g., Rodwell et al. 1999; Sutton and Hodson 2003; Eden et al. 2002). Model results suggest that the decadal variations at the ocean surface can be caused by low frequency variations in the ocean circulation, e.g. the MOC (Gastineau et al. 2013). In addition, the seasonal cycle of mixed layer depth can induce winter to winter memory of SST anomalies (Deser et al. 2010, and references therein).
Even for the low-frequency time scale there is evidence for atmospheric variability to influence the ocean. Latif et al. (2004) found that multidecadal variations in the MOC lag multidecadal changes in the NAO by about a decade. In the MPIOM ocean model, which is used for this study, internally generated (30-year variability) and coupled ocean-atmosphere variations (60-year variability) in the MOC co-exist (Zhu and Jungclaus 2008).
In this paper the possible influence of decadal variations in the ocean circulation on windstorm activity in the North Atlantic-European sector is investigated. In contrast to previous studies described in the literature we focus on extremes (i.e. windstorms) rather than the mean state (e.g. storm track or NAO). Studies on the relation of extreme and moderate cyclones indicate that there is a difference in the spatial distribution (Pinto et al. 2009).
A potential chain of mechanisms producing decadal windstorm variability is suggested and assessed: Decadal variations in the Atlantic MOC affect the ocean heat transport and lead to anomalies in the ocean heat content (OHC) and the SSTs. Characteristic anomaly patterns, which are associated with the MOC variations have the potential to enhance atmospheric baroclinicity. This creates favourable conditions for the development of extreme cyclones and can increase the decadal windstorm activity. In accordance to most other studies investigating reasons for decadal variability this investigation is based on model simulations as there is a lack of adequate long term observational time series.
2 Data and method
The investigation is based on three 240-year long simulations with the ECHAM5-MPIOM model (e.g., Roeckner et al. 2006; Jungclaus et al. 2006). The simulations cover the period 1860–2100 and have been forced with observed greenhouse gas concentrations between 1860 and 2000 and with SRES A1B scenario concentrations afterwards. The choice of the model was motivated by an intensive comparison between models and observations performed within the ENSEMBLES project (http://www.ensembles-eu.org). In particular, it was shown that both winter storm activity simulated by this model for present day greenhouse gas forcing, and its change under increasing greenhouse gas concentrations are close to the multi model ensemble mean of the 7 models investigated in the project (Ulbrich et al. 2008; Donat et al. 2010b). Moreover, the ECHAM5-MPIOM model simulates the most important source for decadal variations in the Atlantic, the MOC, especially well (Collins et al. 2006).
Windstorms are identified using a method developed by Leckebusch et al. (2008). The 10 m wind field is scanned for grid boxes in which the wind speed exceeds the local 98th percentile. The use of this percentile has been demonstrated to be useful in the context of reproducing observed losses from windstorms (e.g., Klawa and Ulbrich 2003). Adjoining grid boxes with extreme wind speeds form a cluster. The clusters are then tracked in time by using a nearest neighbour approach. Only the wind tracks, which last at least 18 h (4 time steps archived from the model runs) and cover an area of at least 217,000 km2 per time step (corresponding to 5 grid boxes at the equator) are kept. In the context of this study, North Atlantic windstorm activity is defined as the number of extreme wind tracks per extended winter season (October-March) crossing the region 45°W−20°E/45°N−70°N (see rectangle in Fig. 9).
In order to analyse variations in the Atlantic MOC, the annual mean of the meridional overturning stream function is determined and a MOC index constructed using the maximum values in the North Atlantic (below 500 m and north of 28°N) as suggested by Yoshimori et al. (2009).
The term “decadal” commonly refers to the 10–30 year time scale (Meehl et al. 2009). In this paper we separate variability on the decadal time scale by applying a 10–35 year band pass filter (Doblas-Reyes and Déqué 1997) to the time series of storm activity, MOC and OHC. This also removes long-term trends caused by the increasing greenhouse gas concentrations in the climate change simulations. Unless stated otherwise the following results are all based on these filtered time series.
3 Relationship between windstorm activity and the ocean circulation
3.1 The MOC and windstorm activity
Wavelet analysis (Torrance and Compo 1998) applied to the unfiltered but normalised and detrended time series, confirms that the MOC and the windstorm activity time series include variability in the the 10–35 year period range, which differs statistically significant from white noise (not shown). In particular, all runs exhibit periods with significant variability around 30 years and around 60 years, in line with the results of Zhu and Jungclaus (2008), who also reported MOC variability with periods around 30 and 60 years in the MPIOM model. The simulations analysed here additionally include variability with shorter periods (around 10 and 20 years), which reaches statistically significant levels in 2 out of the 3 simulations.
Cross spectral analysis between the two unfiltered time series shows coherence on the decadal time scale for all runs with values up to 0.7, which is statistically significant on the 95 % level for 2 out of the 3 simulations (not shown).
3.2 OHC and SSTs
Variations in the MOC can alter the heat transport in the ocean. Resulting anomalies in the ocean heat content may influence the atmosphere via the SSTs. The following subsection investigates, whether high decadal windstorm activity is associated with characteristic anomalies in the upper level OHC and SSTs in the North Atlantic region.
In order to further test the robustness of our results a number of sensitivity tests have been conducted. Using the OHC of the upper 500 m instead of the upper 300 m leads to approximately the same OHC anomaly pattern.
The correlation coefficients obtained using seasonal mean instead of annual mean OHC values have been determined for all seasons and were found to be almost identical to those using annual means. This is due to the fact that the OHC anomalies are already present in the months prior to the occurrence of the winter storms and indicates that the OHC anomalies are not solely a response to the atmospheric windstorm forcing.
3.3 The link between the MOC and OHC
Variability in the MOC of the ECHAM5-MPIOM model has been analysed by Zhu and Jungclaus (2008). They identified two distinct periods of approximately 60 years and of approximately 30 years. While the 60 year period was identified as an coupled atmosphere-ocean mode, the 30 year oscillation is an ocean internal mode as it also exists when the ocean model is forced using a climatological mean atmosphere. Moreover, Zhu and Jungclaus (2008) demonstrate that the years following the negative phase of the 30 year MOC mode are associated with an upper ocean temperature signal, very similar to the one presented in Fig. 5. When the MOC is weak less heat reaches the sub-polar basin causing negative anomalies there. Warm surface water is located east of Newfoundland. When the MOC recovers the warm surface water is transported eastwards, leading to positive SST (and upper level OHC) anomalies along the NAC, while the sub-polar basin is still cold.
3.4 Observational support
Validation of the results against observations is difficult, as reliable long-term atmospheric and oceanic time series, which are needed to investigate decadal variability, are not existing. At this point, we therefore only attempt to answer the question whether observations of the recent past support or contradict the model results. The analysis is based on the period from 1959 to 2006, which is the time span commonly covered by the analysed data sets. Windstorm frequency in the region 45°W−20°E/45°N−70°N is determined using the method described in Sect. 2 using NCEP reanalysis data (Kalnay et al. 1996). Band pass filtering leaves 2 distinct periods with high decadal wind storm activity with maxima in 1973 and in 1991. A minor maximum occurs in 1982.
4 Mechanism translating ocean temperature anomalies into storms
The SST anomalies west of the British Isles, developing during the transition of the MOC from a weak to a strong phase, are associated with an increased meridional temperature gradient. This is consistent with an increase of atmospheric baroclinic instability in this region due to heat transfer anomalies. The heat transfer over the region is mostly directed from the ocean into the atmosphere and most pronounced during the cold season, when the temperature contrast between the ocean and the atmosphere is highest (Liu et al. 1979; Yu and Weller 2007).
It is known that variations in the strength of the MOC are caused by changes in the density structure of the North Atlantic, which are due to fluctuations in salinity and temperature. For the decadal variations in the MPIOM model Zhu and Jungclaus (2008) find that the strongest contribution comes from temperature fluctuations. They also show that a weak North-South density gradient is followed by a weak MOC with a time lag of about 2 years and a weak North Atlantic Current with a time lag of about 3 years. At the time of the MOC minimum warm near surface temperature anomalies appear east of Newfoundland and are advected eastward when the MOC recovers. Consistent with these results, the mixed layer OHC anomalies associated with enhanced decadal wind activity, we find in our study, develop 1–3 years after the slowest period of the MOC and resemble the near surface temperature anomalies shown by Zhu and Jungclaus (2008).
The SST and OHC anomalies are already present in the months before the winter storms occur (see Sect. 3.2)
The study by Zhu and Jungclaus (2008) suggest that MOC variations with an approx. period of 30 years, which are included in the 10–35 year period range we have analysed in this study, are an ocean internal mode of the ECHAM5-MPIOM.
An index time series of the decadal OHC variations explains about 10–30 % of the decadal storm variability in the North East Atlantic. This number is modest compared to the 52 % of variability explained in the United State’s multidecadal drought frequency by the combined influence of the Atlantic Multidecadal and Pacific Decadal Oscillation (McCabe et al. 2004), but still useful to better understand the observed decadal windstorm variability. As decadal variations in the MOC are believed to be potentially predictable (Pohlmann et al. 2013; Matei et al. 2012; Collins et al. 2006; Griffies and Bryan 1997), our model-based results suggest that the decadal variations of North Atlantic storm activity may also be to some extent predictable.
Observations seem to support the results of this study, but the available observational time series are too short for robust conclusions. Further support of the results may come in the future, from the analysis of simulations of other coupled ocean atmosphere climate models.
We are greatful for funding of this work by EQECAT, Paris and by the Federal Ministry of Education and Research in Germany (BMBF) through the research programme MiKlip (FKZ: 01LP1104A). Additional funding has been received from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007-2013) under REA Grant agreement No. PCIG11-GA-2012-322208. We thank Dominik Renggli, Tim Kruschke and Henning Rust for valuable discussions and technical support. We would also like to thank the two anonymous reviewers for their comments, which helped to improve the manuscript.
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