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Termpaper writing for MSc Biogeochemistry and pollutant dynamics, ETH Zurich. Nina Bachmann, HS 2007. The North Atlantic Oscillation (NAO) Research, mechanisms and future outlook Contents Abstract 1 1. Introduction 2 2. History and trends in NAO research 3 3. Temporal structure of NAO 4 4. Spatial Structure of NAO 5 5. Dynamics and possible mechanisms of NAO 8 6. Influences of NAO on Europe 10 7. Simulations of future NAO development 13 8. Conclusions and Outlook 14 References 16 Abstract The North Atlantic Oscillation (NAO) phenomenon describes the varying strength of two atmospheric pressure systems lying over the subpolar and the subtropical region of the North Atlantic. The variability in the strengh of this pressure gradient can be expressed by an Index, which gets positive if the pressure systems are well established and negative when the pressure gradient between them is weaker. Especially during northern hemisphere winter (December to March), the NAO has a strong influence on weather conditions in Europe: A positive phase of NAO causes high precipitation and mild temperatures in Northern Europe which indirectly influences for example the European biosphere or the amount of snow in the Alps. Therefore, predictability of NAO is of high interest for meteorologists. Unfortunatly, it is still unclear which mechanisms are driving NAO. Due to this, short-term predictability has been impossible so far. In view at climate change, long-term modeling of future NAO development became the focus of recent NAO research. Some models indicate an upward trend of NAO Index towards higher positive values, which would have severe effects on European weather conditions. Here, actual knowledge and future possible trends in NAO research are discussed, with a focus on the consequences for the European continent. Nina Bachmann, D-UWIS, [email protected] 1. 2 Introduction The analysis of pressure fields shows that their variability always exhibit certain patterns, which are called variability patterns or modi (Brönnimann, 2005). The North Atlantic Oscillation (NAO) is one of the most prominent patterns of atmospheric circulation variability and is the only atmospheric mode, which can be observed during the whole year in the northern hemisphere (Hurrell et al., 2003). The NAO consists of opposing variations of barometric pressure over the subpolar and the subtropical region of the North Atlantic (IPCC, 2007). In general, there is a high pressure system over the subtropical region near the Azores, and a low pressure situation over the subpolar region near Iceland (Wanner et al., 2001). The strength of the pressure gradient between the two so-called centres of action varies with time within stronger and weaker phases. The measure for this variation, the NAO Index, gets positive in a stronger phase with a high pressure gradient and negative in phases with a weaker pressure gradient (Brönnimann, 2005). The pressure difference between the Azores and Iceland is associated with westerly winds across the Atlantic into Europe, and as the pressure gradient fluctuates, the strength of the westerly winds also varies. This has a high importance for weather and climate in the whole North Atlantic region: With western winds, mild and humid air is transported from the Atlantic into Europe and determines temperature and precipitation, especially during northern hemisphere wintertime from December to March (Hurrell and Dickson, 2004). Thompson et al. (2000) showed, that for the winter months from 1968 to 1997, NAO (or NAM, see below) accounts for 1.6°C of the 3.0°C warming in Eurasian surface temperatures (IPCC, 2007). There were also significant effects on ocean heat content, sea ice, ocean currents and ocean heat transport (IPCC, 2007). That means, understanding the processes that govern NAO variability is important for weather and climate predictability and is therefore of high priority, especially in the context of global climate change (Hurrell et al., 2003). The definition of an Index for NAO to relate the variability of two centres of action is only one possibility to explain a variability modus. Another is a more statistical approach where time series and spatial patterns are analysed through main component analysis. Through this approach, another variability pattern, the Arctic Oscillation (AO) or Northern Hemispheric Annular Mode (NAM) is defined. Despite of the different definition approaches, the NAO and the AO/NAM show a similar spatial pattern, but AO/NAM has a third center of action in the pacific and the surface land pressure in the polar region is more important than for NAO, where the polar low is equally weighted like the subtropical high (Brönnimann, 2005). It is still an open question, whether NAO and AO/NAM are the same phenomena or whether NAO and AO/NAM are not only different definitions but also different concepts. The suggestion that they are different concepts would also mean, that the underlying processes for both wouldn‘t be the same (Hurrell et al., 2003). Here, only the NAO is adressed, for further information the reader is referred to Wallace (2000). In the following section, there is a short overview about history of NAO research, followed by a more detailled description of the temporal and spatial structure of the phenomena. In chapter 5, different mechanisms which might be forcing NAO are discussed. Chapter 6 gives informations about the consequences of NAO for European climate and weather conditions, whereas Chapters 7 and 8 discuss future NAO development and trends in NAO research. Nina Bachmann, D-UWIS, [email protected] 2. 3 History and trends in NAO research The NAO phenomenon was first discovered through the observation of different weather and climate conditions during winter. The occurrence of periods with mild winters and others with severe winters lead to descriptions of NAO-related weather observations already several hundert years ago. In the nineteenth century, more data became available and researchers began to investigate temperature series in the northern hemisphere. The focus of most meteorologists and climatologists at that time was mainly on forecasting weather and therefore more on data observation of the phenomenon than on understanding its physical processes (Wanner et al., 2001). One of the most cited researchers from the early 20th century in todays NAO related studies is G.T. Walker. With his statistical research of pressure data he found three modes which dominate world weather. In his paper from 1924 he defined the terms North Atlantic Oscillation, North Pacific Oscillation and Southern Oscillation (Walker, 1924). Walkers concept of NAO became very popular, and a few years later Walker and Bliss (1932) constructed the first quantitative measure for the strength of NAO, a NAO Index. This first Index involves several temperature and pressure data from Europe and North America and can be calculated through a rather complex, iterative statistical procedure. Until today, Walkers and Bliss‘ NAO Index was adapted several times, but it‘s principle remained the same (see chapter 3). In the 1960s, new, more dynamical and less descriptive theoretical concepts of climate variability in the Atlantic-European region were developed. Bjerknes (1964) reviewed ocean-atmosphere interactions in relation to North Atlantic climate variability. He mentioned that heat exchange in the atmosphere and sea surface temperatures (SSTs) must play an important role for the NAO. In addition, the interaction dynamics of the atmosphere circulation and pressure centres over land were described by leading meteorologists of that time (for example Lorenz, 1967). In the 1970s and 1980s some important studies were made which lead to more detailled knowledge about the NAO concept. Van Loon and Rogers (1978) for example found, based on Bjerkes‘ research, significant correlations between atmosphere circulation and sea surface temperature and Barnston and Livezey (1987) showed, that the NAO is the only circulation pattern in the northern hemisphere which is found in every month in the year, although it‘s quite weak in European summer time. In the 1990s, researchers focused on climate modelling with respect on the NAO anomalies. With a publication by Hurrell (1995), the interest in NAO and its influence on climate increased rapidly. Hurrell related the NAO phenomenon with temperature and pressure variability over Europe in a interannual to decadal timescale. He also defined a new Index for NAO, which is todays most used NAO Index in climate research (see chapter 3 for more details). More research has been done in the following years on reconstructing NAO Indexes on larger timescales, in order to explain low frequency or short-term atmospheric variability over the Atlantic-European area. Most recently, the role of NAO in climate change was discussed, an overview about this is given in chapter 7 and 8. Nina Bachmann, D-UWIS, [email protected] 3. 4 Temporal structure of NAO A measure for the state of the NAO is an Index called the North Atlantic Oscillation Index (NAO Index). There are several ways to calculate this Index, depending on the statistical analysis of meterological parameters used (Wanner et al., 2001). The NAO Index which was defined by Hurrell (1995) for example, uses weather data from Stykkisholmur (Iceland) and Lisbon (Portugal): Sea level pressure data are normalized to „normal“ pressure, which is defined through mean sea level pressure over several years. The normalization gives the anomaly of the actual pressure compared to normal pressure. The normalized pressures of Iceland is then subtracted from the normalized pressure of Portugal. The NAO Index gets positive for example, if there is a lower than normal pressure over Iceland, respectively a higher than normal pressure over Portugal, or if both anomalies occur (Hurrell et al., 2003). The „Hurrell-Index“ has the advantage, that it can be calculated back to the XIX century, because weather data from more than 100 years are available from the two weather stations which allows the construction of time series of NAO Index (Wanner et al., 2001). The actualized time series of NAO Index for the winter months calculated by Hurrell (1995) and updated until 2003 is shown figure 1. 6.00 NAO Index 1864 – 2007 4.00 2.00 0.00 -2.00 -4.00 18 64 18 69 18 74 18 79 18 84 18 89 18 94 18 99 19 04 19 09 19 14 19 19 19 24 19 29 19 34 19 39 19 44 19 49 19 54 19 59 19 64 19 69 19 74 19 79 19 84 19 89 19 94 19 99 20 04 -6.00 year Figure 1: Updated NAO wintertime Index from 1864 to 2007 with value of NAO Index on y-axis (Hurrell, 1995; new data available from www.cgd.ucar.edu/cas/jhurrell/indices.html). There are several observations about NAO which can be driven from this time series (Hurrell, 1995): The NAO has a kind of „memory“, it shows a so-called interannual variability. This means, that NAO remains often more than one year in the same phase before it changes again. Furthermore, the changes from positiv to negative values often seem to happen on longer timescales, which is referred to as interdecadal variability. For example, the Index from 1940 until about 1965 shows a decreasing trend, while from then on, NAO Index values seem to increase until about 1995 (Hurrell, 1995). Nina Bachmann, D-UWIS, [email protected] 4. 5 Spatial Structure of the NAO The NAO Index can be used to express whether the pressure anomalies betweeen the two pressure centres are high or low: If the Index is positiv, the NAO is said to be in its positive phase (NAO+) and if the pressure anomalies are low, there is a negative (NAO-) phase. One must consider, that this is a simplified model of the states of NAO, because it implies that these two phases are static and bipolar. In reality, the strength of the phases can differ a lot from each other, which is expressed by a wide range of values for the NAO Index. The aggregation of all the different phases to only two phases, a NAO+ and a NAO– phase, is used due to the weather and climate characteristics, which are similar for all states of NAO which have a positive or a negative NAO Index value (Wanner et al., 2001). In this section, the characteristics of NAO+ and NAO– phases are discussed. 4.1 NAO+ phase The characteristic of a NAO+ phase is a well developed Icelandic Low and an Azores High. As air always flows from higher to lower pressure, the pressure gradient between the two regions causes stronger than normal westerlies from the eastern Atlantic towards the European continent (see figure 2). Atlantic air is wet and mild and in winters with NAO+ phases, precipitation and temperatures in northern Europe are therefore higher than normal. In contrary, Southern Europe tends to be drier and colder in NAO+ winters due to the extension of the Azores High (Wanner et al., 2001). The influence of NAO is not limited to Europe only. The well established Icelandic Low leads to strong northerly winds over Greenland and northeastern Canada. This causes a decrease in land and sea surface temperatures over the northwestern Atlantic (Hurrell et al., 2003). Northern Canada is like northern Europe drier and colder during a NAO+ winter. On the other hand, the Icelandic Low extends over northern Siberia, where it causes warmer and more humid weather compared to normal Siberian conditions. This affects river runoff and sea-ice extension: If NAO stays several winters in its positive phase, sea ice boundary extends farther south at the coast of Canada, while the sea ice boundary of Siberian ice lies more northern than normal. Sea-ice extension affects salinity, which in turn affects ocean circulation, at least on longer timescales: The global thermohaline circulation variability seems to be synchronized with interdecadal NAO variations (Hurrell et al., 2003). During a NAO+ phase, the salinity at the coast of Canada is higher than normal due to the increased sea ice extension (see figure 2). In this case, the dense and cool water sinks down more rapidely than in NAO– phases. Delworth and Dixon (2000) suggest, that increased deep water formation in the North Atlantic region at the coast of Canada could delay the slowing down of the thermohaline circulation, which was projected by global climate warming scenarios. Figure 2 gives an overview of the important processes and of heat and water fluxes which are dominant during a NAO+ phase. Nina Bachmann, D-UWIS, [email protected] 354 HEINZ WANNER ET AL. Figure 9a. Graphical representation of the two modes or states of the NAO, based on discussions with different researchers and a review of different papers. Surfaces mark SSTs and sea-ice extension, arrows show the flow systems in ocean, atmosphere and rivers, blue and red lines indicate near surface sea level pressures and white rectangles describe characteristic climate conditions or Figure 2: Schematic NAO+ phase. important processes. (a) Positive mode, (b) Negative Icelandic low and Azores high are well established [big Lmode. and H], other, smaller high pressure centres over the continents are shown as well [H]. As air always flows from higher to lower pressure, the large pressure difference between Azores High and Icelandic Low c causes stronger than normal westerlies [blue-green arrow] towards northern Europe. The Azores High also gives rise to stronger than normal esterlies [yellow arrow] from North Africa towards the Atlantic. Sea surface temperature anomalies as well as sea-ice are marked with colored areas [orange: warm bluegrey: cold; light blue: sea-ice extension]. The possible relationship between sea surface temperatures, sea-ice and NAO is discussed in chapter 5. Ocean circulation could also play an important role for NAO [orange arrow for warm water transport; blue arrow for cold water transport; light-blue arrows for under-ice circulation]. River runoff anomalies which are directly forced by higher or lower precipitation due to NAO are also shown [blue arrows over land in polar region]. Characterisitc climatological conditions or important processes of the hydrological cycle are marked by white rectangles and are further explained in the text. (From Wanner et al., 2001). 6 Nina Bachmann, D-UWIS, [email protected] 4.2 7 NAO– phase During a NAO– phase, there is normally still a Icelandic Low and a Azores High, but both are rather weak. Therefore, the westerlies are reduced. Almost all characteristics which were described for NAO+ are inversed during a NAO– phase and should therefore not be discussed here again (more details in chapter 4.1). Very rarely, the pressure distribution is reversed, that means there is high pressure over Iceland and low pressure over Azores. The NAO Index is then very negative, and there is an easterly wind over Eastern Atlantic. This was the case in January 1881, 1918 and 1963. This „inversed“ pressure gradients led to extremely severe winters, where, in Switzerland for example, several big lakes were frozen on the surface. NORTH ATLANTIC OSCILLATION – CONCEPTS AND STUDIES 355 Figure 9b. Figure 3: Schematic NAO– phase. Same symbols as in figure 2. (From Wanner et al., 2001). Nina Bachmann, D-UWIS, [email protected] 5. 8 Dynamics and possible mechanisms of NAO There are different possible mechanisms for the NAO. It‘s still unclear, if the NAO is purely an atmospheric phenomenon, or if the ocean-atmosphere interactions like thermohaline circulation, sea surface temperature variability or sea-ice are influencing the NAO or if these factors are rather influenced by the NAO (Hurrell et al., 2006). The answer to this questions can be found through modelling of NAO. The type of data input to the models can be varied, for example sea surface temperature time series of the past 100 years can be used to generate a simulated NAO. Then, the simulated NAO variability is compared to the observed variability. The percentage of how much variability is explained by the model can then tell about the importance of the input data for NAO fluctuations. 5.1 Atmospheric processes NAO can be simulated with atmospheric general circulation models (AGCMs), which are fed with climatological variables like insolation, sea surface temperature, sea ice and snow cover which are the model‘s boundary conditions. As climatological variables, these forcing fields contain no signal of the NAO. Nevertheless, the spatial pattern and the amplitude of NAO Index anomalies are well simulated, which shows that the NAO is not imposed onto the atmosphere by external forcing. Therefore, NAO must be caused by intrinsic forcing of the atmosphere, its land-sea distribution and nonlinear dynamics, at least on short time scales of 10 days (Feldstein, 2000). But if this would be the only reason for the NAO phenomen, this would still not explain interdecadal trends and interannual variability shown be NAO Index time series. „At present, there is no consensus on the process or processes that are most likely responsible for the enhanced interannual variability of the NAO.“ (Hurrell et al., 2006). One theory is, that on longer time scales, the lower stratosphere influences the troposphere, but how exactly this would cause the flow anomalies in the troposphere, remains still unexplained. 5.2 Ocean influence On longer time scales, the NAO could be influenced by the Atlantic ocean, but the inverse pathway, that the NAO influences the ocean is also possible: Hurrell et al. (2003) concluded, that Atlantic Ocean responses to the NAO, because the changes in surface wind patterns through NAO has an influence on heat transfer and freshwater exchange on Atlantic surface, which could alter the thermohaline and horizontal circulation. This would explain the interdecadal sea surface temperature anomalies, which were observed over the last 100 years and correspond to NAO pressure fluctuations: The subtropical gyre warmed below 1000 meters, and the subpolar gyre cooled, which is consistent with a predominantly positive phase of the NAO (IPCC, 2007). At the same time, trends in salinity towards freshening in the subpolar regions and increased salinity in the subtropics were observed (IPCC, 2007) and can also be related to NAO influenced sea-ice and water flow processes which are explained in chapter 4.1. Since the 1995s, there has been a return to warmer and more saline waters in the subpolar regions, which coincidences with a slight Nina Bachmann, D-UWIS, [email protected] 9 decrease of NAO Indexvalues. But this return to saltier water has not been long enough to change the long-term global trend, which indicates a water freshening of the relatively fresher regions (IPCC, 2007). As mentioned, the other way is also possible: Sea surface temperature fluctuations could force turbulent heat fluxes at ocean surface, which would have a direct effect on atmospheric boundary layer. Rodwell et al. (1999) argue, that evaporation, precipitation and atmospheric heating processes depend on sea surface temperature of the Atlantic. They showed, that about 50% of the amplitude of the long-term variability in the wintertime NAO index can be explained through an AGCM, which is fed by sea surface temperatures (Rodwell et al., 1999; Hurrell et al., 2006). Czaja and Frankignoul (1999) have also demonstrated, that North Atlantic sea surface temperature anomalies are followed by anomalies in the atmospheric circulation (IPCC, 2007). In conclusion, it‘s still unclear, whether the ocean is the dominant factor for NAO variability, or if NAO is influencing the ocean on the other hand. Similarly, the role of sea ice and land snow cover is still unclear: the influence could take place in the atmosphere-land or in the land-atmosphere way. A ocean-influenced or sea-ice influenced NAO would make predictability of future NAO behaviour easier and is therefore an important part of actual NAO discussion among researchers (see chapter 8). 2–4 °C below ng from Scanpe to the Black ween 50% and ndinavia and the western Africa, by coner than usual, cken Spain. his was a comthat had prens since the transitions in ? The study by is issue2 offers d rainfall variave long been North Atlantic NAO is often nce in sea-level ssure adjusted n Iceland and of the winteratmospheric en two states: differ from one regional presand the Azores sea-level presther result in and direction, and heat and e Atlantic and 1,3–5 . No wonhave long been he NAO ahead .2 numerically onsisting of a ribe the largef momentum, more heuristic cale processes ormation, pret the land and g work, some he seasonally he top of the carbon-diox- ww.nature.com evolution does not depend on initial condi- climate prediction. For this purpose, tions. Thus they are not meant to predict the atmospheric models must be sensitive to the actual evolution of the atmosphere but prescribed extratropical SST distribution. D-UWIS, most [email protected] 10 rather to depict, in a statistical sense,Nina the Bachmann, pat- However, attempts to simulate the tern and strength of atmospheric variability. atmospheric response to extratropical SST In Rodwell and colleagues’ study, how- anomalies have been frustrating, yielding ever, actual SST values over the entire world model-specific results that are inconsistent ocean Influences are used, prescribed to follow their and generally weak7,10. In what constitutes a 6. of NAO on Europe observed monthly states between 1870 and breakthrough in this research, Rodwell et al. 1997. If atmospheric variability in this model have produced strong evidence for a synintegration is temporally synchronized with chronicity between model-simulated and observations, the cause is in the ocean. observed NAO fluctuations, resulting from NAO pressure is the variations cause for stronger or weaker westerlies, depending on the strength Over most ofdistribution the world ocean, specifying realistic SST variability in the of pressure anomalies, by the NAOextratropical Index. The transport of moisture in SST depend largely onexpressed heat exchange with North Atlantic Ocean. and mild air through the atmosphere, sothe are south shapedeastern by atmosDoes thisEurope bring uscauses closerchanges to predicting the these westerlies and from Atlantic towards in temperature, pre7,8 pheric variability NAO and its effect on Europe’s climate? Only . The ocean itself remains cipitation and storminess over Europe (Rodwell et al., 1999). Figure 4 shows temperature and rainpassive, sluggishly accommodating fast- up to a point. In the extratropics atmospherfall anomalies during toindifferent NAOheat phasesicinand Europe. SST anomalies evolve together, which changing fluctuations atmospheric flux to form large-scale SST anomalies. There are only a few examples of an active oceanic role in SST variability, the most a makes it difficult to specify the SST field ahead of time. This poses a considerable obstacle to a prediction algorithm based on b Winter 1994—95 Winter 1995—96 1010 1025 1015 1020 1000 Low 1020 1025 1015 High 1035 High 1030 1010 Low 1030 Low 1005 - 1015 1010 1020 1025 High High 1015 1015 1010 1010 Low 1010 Figure 1 Swings of the North Atlantic Oscillation from one phase to the other affect European climate. Figure 4: a. NAO+ phase and b. NAO- phase. White contours depict the seasonal mean sea-level pressure a, During the winter 1994–95, the respectively Icelandic low-pressure andcolder Azoresthan high-pressure regions in were field; regions in red of and blue were warmer and normal; regions green and brown both more intense than usual. In this positive phase of the NAO, strong westerly winds (arrow) respectively experienced higher and lower rainfall than normal. Stronger westerlies during a NAO+ phase steereda) Atlantic winter storms eastward and brought unusually (figure is marked with a grey arrow (from Kushnir, 1999). wet conditions to northern Europe and warm temperatures all the way into Siberia. The western Mediterranean was dry and northern Africa cool. b, In the winter of 1995–96 the NAO swung into its negative phase. A weak North Atlantic pressure system led to reduced Atlantic influence over northern Europe, with less rainfall and much colder temperatures. Over the Iberian Peninsula and northern Africa drought gave way to excess Through it‘s influence on European weather conditions, NAO is steering indirectly the whole Eurorainfall, as winter storms moved freely into the Mediterranean. (Contours depict the seasonal mean pean biosphere. Menzel et al., (2005) showed through the analysis of plant phenology sea-level pressure field; regions in red and blue were respectively warmer and colder than normal; data sets, that the progress ofand season, change from springhigher to summer, is rainfall highly than depending regions in green brownthe respectively experienced and lower normal.)on NAO state: in ye- ars with a positive NAOMagazines Index, theLtd progress of season from west to the east of Europe was clearly © 1999 Macmillan 289 pronounced, while in years with a negative NAO Index the progress was depending on other factors and showed a more north to south component. The variability in NAO causes the annual variability in season progress. George et al. (2004) analysed the direct and indirect effects of NAO weather conditions on four lakes in Britain from data which was recorded between 1961 and 1997. Especially the changes of lake conditions in the two smaller lakes, Esthwaite Water and Blelham Tarn, could directly be correlated to NAO Index variation (see figure 5). Through the comparison of meteorological measurements and NAO Index, they found that in years with positive NAO Index, winter weather conditions in Britain Nina Bachmann, D-UWIS, [email protected] 11 were extremly mild and wet. Therefore, biosphere activity was increased during this years, which caused a higher nitrate assimilation in the surrounding catchment of the lakes, and therefore a reduced import of nitrate in the water through leaching processes. Moreover, through higher precipitation in wet winters, washing out of chlorophyll in lakes with small retention time was increased, leading to a reduced growth of phytoplankton in spring. The influence of the NAO index on four lakes 771 Fig. 8 AnFigure overview5:Correlation of the site-specific recorded with the NAOI. The horizontal dashed shows P ¼ 0.05. of correlations NAO Index and different parameters measured in lines british lakes. Horizonal dashed line shows P=0.05. From the left to the right: Water temperature surface and bottom, dissolved reactive phosphorus, nitrate concentration, chlorophyll a, phytoplankton (Asterionella). 2 Indirect(temperature) – where the and effects of concentration the NAO are (negabiological variables. A striking of these Highest correlation of NAOfeature Index with physical parameters nitrate mediated by a chain of interactions in system relationships is the systematic change recorded in tivly correlated). Biological variables response is weaker and also differs more between thethe lakes due to difunder investigation; the ‘non-significant’ relationships identified the 2004). ferent biological systems (from Georgefor et al., 3 Integrated – where the NAO influences the DRP, the biomass of phytoplankton and the timing of ecosystem in a cumulative way. the Asterionella maxima. In each case, the calculated In this paper, we have assembled examples that coefficients formed an ordered sequence that either illustrate both the direct and indirect effects of the ranged from values close to zero to significant positive NAO on the long-term variations recorded in the or negative values or from a weak negative values to a Beniston (1997) compared snow records of Swiss Alps to the phase of NAO. A country like SwitzerEnglish lakes. A notable feature of the direct effects is significant positive correlation. These differential land is sensitive changes in snow amount andstrength duration: which the of Its the electricity correlationsproduction, noted between theis based responses demonstrate thattoeach lake ‘integrates’ the temperature of the lakes and the status of the NAO. differentmostly elements of the climate signal in functionally on hydro-power, its Tourism industry and mountain ecosystems, they all depend on snowfound that the thermal effects of differentrich ways. In some cases, such as the year-to-year winter seasons. Warm winters tend to beLivingstone drier than(2000) the norm (Rebetez, 1996). Additionally, the the NAO were particularly pronounced in northern variations in the water temperature, the effect is snow melts faster if the are milder (Beniston, 1997). In the high altitudes Europe but the correlations reported here for of theSwitzermediated by the direct response to temperatures a single meteoroland, mild winterssuch are as often bythe persistent high pressure a positive English Lakes are justsituations, as strong asassociated those notedwith at high logical variable. In others, the caused timing of latitudes. The chemical effects noted hereIndex provide a Asterionella maximum, the effect is more complex NAO Index. The relationship betweenand pressure anomalies in Zurich and the NAO is shown in good example of the indirect effects of the NAO on may be mediated by variations in the wind speed, the figure 6. A positive NAO Index almost always leads to snow spareness in the alpine regions (Benisthe flux of nutrients from the surrounding catchment. underwater light climate and the flushing effects of ton, 1997). The most wide-ranging effect was that noted for the heavy rain. residual concentration of winter nitrate and appeared In a recent review, Ottersen et al. (2001) suggest that to be relatively independent of the nature of the lake. the ecological effects of the NAO can be classified into The DRP and biological effects recorded in the two three categories: smaller lakes were also indirect but more site-specific. 1 Direct – where there is a very clear connection Variations in atmospheric features, like the NAO, between the response and a particular climatic variare now widely used as proxy indicators of regional able; ! 2004 Blackwell Publishing Ltd, Freshwater Biology, 49, 760–774 Nina Bachmann, D-UWIS, [email protected] 288 12 MARTIN BENISTON NAO index 3 = Forecast Error (FE) RPSS (%) = = Terciles = Figure 6: Time Series of wintertime (December to February) pressure anomalies for the NAO Index and for Zurich, Switzerland. A positive NAO Index mostly causes higher than normal pressure in Zurich, representative for the opressure Leading principal component of North Atlantic (20 N-80oN, anomalies 40oE-90oW)in the Swiss Alps. Longer mean sea level pressure. phases with high pressure Mean difference between forecast and actual values for 1972/3-2005/6. anomalies during winter Rank Probability Skill Score = percentage improvement in Rank Probability give raise to higher temScore over 1972/3-2005/6 climate norm. peratures in higher alpine The standard way of dividing the NAO into three categories each having the regions and therefore less same probability (33.3%) of occurrence. These categories are below-normal snow amount in the Alps (lower tercile), near-normal (middle tercile) and above-normal (upper1997). tercile). (from Beniston, Figure 4. Time series of the North Atlantic Oscillation index and surface pressure in Zürich. European Winter Temperature, Precipitation and Windspeed Verification of persistent highas pressure in Switzerland, sometimes asso-influences European winter TheObserved winter episodes 2006/2007 may serve an actual example of how NAO ciated with blocking in the formal sense of the term, are most often accompanied Northern Europe experienced a warm, wet and windy winter with temperatures over(1995; 2oC weather conditions. The value of the NAO Index for the winter 2006/07 calculated by Hurrell by large average, positive departures of temperature; are also linked to extended periods above and windspeed and they precipitation over 40%isabove thehigh 1971/2-2000/1 climate updated on www.cgd.ucar.edu/cas/jhurrell ) wastaken +2.80, which a quite positive NAO Index. of low or negligible precipitation. These two factors together, as the main norm (Figure 1). Southern parts of Europe tended to be drier and less windy than normal, During on thissnow, winter, Northern experienced warm,times wet of and windy winter with temperatures controls explain much ofEurope the observed sparsenessa during positive consistent with a positive NAO index. Our forecasts did not verify well this year, predicting NAO indices. of more than 2 Degrees above average (Saunders and Lea, 2007). Windspeed and precipitation were near average precipitation, temperature windspeed for Europe. Figure 5 illustrates the relationship betweenand average annual snow duration This underprediction is over 40% thelarge climate norm between and 2000/01. In contrary, was partly dueabove to the underprediction of1971/72 the CRU Had we Southern predictedEurope the CRU for various depth thresholds at the three climatological sites NAO (which index. have been drier less perfectly windy than normal (see figure 7).in general, smoothed using a five-point filter for the sake of clarity) and the smoothed average the correct windspeed, NAOand index our forecasts would, have predicted wintertime (DJF: December, January and February mean) pressure field as mea- the magnitude of these temperature and precipitation patterns but would have underpredicted sured in Zürich for the 50-year period. Different snow duration thresholds have anomalies. been chosen to illustrate the correspondance between shifts in snow duration with shifts in surface pressure. The figure highlights two periods during the record when average pressures increased and peaks exceeded the 1951–1980 climatological mean value, i.e., from 1967–1975 and since 1980. The latter period of the record has been the longest this century where pressure has remained largely above the 30-year climatological average. It is seen that whenever pressures rise, the snow-pack responds by decreasing in duration (and depth, not shown here). This is particularly visible since 1982 in Davos and Montana, already to some extent for the 50-cm threshold (particularly since 1980) but more so for snow-depth thresholds exceeding 100 cm. For example, with the strengthening of the wintertime mean surface pressure field in the 1980s, periods with 150 cm of snow or more at Davos have all but disappeared since 1985 and at Montana since 1990. There have been other extended periods where snow  Figure 7:Weather conditions during december 2006, january and february 2007. Farbscale shows the difference from long time mean (1971/72 – 2000). Left: Surface temperature anomalies in degrees; Right: Precipitation anomalies in percent (from Saunders and Lea, 2007). Figure 1. Observed anomalies in 2m air temperature, accumulated precipitation and 10m wind speed across Europe for the 2006/7 winter. These maps are computed using monthly NCEP/NCAR global re-analysis project Nina Bachmann, D-UWIS, [email protected] 7. 13 Simulations of future NAO development NAO and its answer to climate change (or influence on climate change) has been one of the most important topic in all recent NAO studies. The rise of temperatures in northern Europe during the last years can to some part been linked to NAO behaviour (Hurrell, 1996). It would be important to understand NAO for understanding global climate change, and therefore todays research effort is focused mainly on predictability and modelling of NAO phenomena. As already mentioned in chapter 3, an intesification of NAO, namely a trend towards higher positive NAO Index values has been observed over the past few decades, which caused higher temperatures and higher precipitation over Europe (Hurrell, 1995). This upward trend might be unique in earth history, although this is not yet clear (Hurrell, 1995; Thompson et al., 2000) and recent NAO Index values show a more decreasing trend. Osborn et al. (1999) tried to model decadal NAO Index trend with atmospheric climate models. This modelling predicted a decrease in NAO Index. But instead of a decrease, the observations showed an increase of NAO Index. It could be that the model isn‘t able to simulate recent NAO Index development correctly, because it doesn‘t include for example natural variablity of solar radiation and troposphere-stratosphere interactions. Another possibility is, that recent NAO Index development was forced by external factors, namely by anthropogenic climate warming. In the 4th assessment report of the International Panel on Climate Change (IPCC, 2007) the authors state that many simulations project a decrease in arctic sea level pressure in the 21st century (see figure 8). This would lead to an increase of the NAO Index, which was confirmed by half of the simulation models investigated by Osborn (2004) and Kuzmina et al. (2005). Although the magnitude of the modelled pressure trends varies largely (IPCC, 2007), none of the models calculated an increasing pressure trend, which makes lower arctic sea level pressure and therefore a higher index very probable (Miller et al., 2006; IPCC, 2007). Furthermore, climate models simulations for NAO with regard to troposhperic processes project an increased index in response to increasing CO2 concentraGlobal Climate Projections tions, although this response is not that large and it‘s magnitude depends on the model (Stephenson et al., 2006; IPCC, 2007). Figure 8: Simulated mean sea level pressure by atmospheric general circulation models. The value „0“ indicates todays sea level pressures, values above or below indicate an increased respectively decreased mean sea level pressure by the end of the 21st century (2080-2099). For the arctic region, the simulations show a decrease and for the Azores region a slight increase of about 1 hPa. Therefore, the NAO Indexwould shift towards more positive values (from IPCC, 2007). Nina Bachmann, D-UWIS, [email protected] 8. Conclusions and Outlook 8.1 Conclusions 14 The temporal and geographic pattern of the big pressure systems over the North Atlantic is well understood. NAO describes the phenoma, that the magnitude of these pressure systems‘ strength oscillates, and the NAO Index can describe this oscillation quite well. Timeseries of the NAO Index were calculated back to a time span of several hundred years to identify possible regularities in the pressure fluctuation. Furthermore, there is a consensus among researchers, that NAO significantly influences climate conditions in the whole North Atlantic region. In this context, NAO recently got of high interest in climate research (see chapter 7) regarding todays anthropogenic climate change disscussion. As NAO influences European temperatures and precipitation, as well as it influences the whole North Atlantic climate, knowledge about this phenomena is important for climate change modeling. As discussed in chapter 7, recent modelling of NAO showed an increasing trend of the NAO Index towards more positive values during the 21th century. This would lead to a mild and humid climate in Europe, which is consistent with climate change simulations that focus on other climate-driving factors like for example green house gas emissions. The prediction of the models are therefore assumed to be quite reliable, altough they differ largely in magnitude. 8.2 Outlook Athough the research about NAO already started at the beginning of the 20th century, a lot of open questions are still unanswered. The problem in NAO research is that progress depends mainly on the use of reliable models. Until now, Atmospheric-Ocean General Circulation Models (AOGCMs) have been fed with different parameters like for example sea surface temperatures to simulate NAO, but so far, there aren‘t any models which are specifically adapted for NAO (Osborn, 2004). To improve NAO models, all processes which drive NAO must be included in the right way. This means that the models must also be extended to the stratosphere in order to include troposphere-stratosphere interactions. Until now, it isn‘t even clear which are the mechanisms driving NAO (see chapter 4.1 and 6). To improve NAO modeling, it is first of all important to know all the underlying processes for NAO, which should be possible with todays AOGCMs. Once all the processes which drive NAO are defined, models for each of these have to be coupled to create a model which is specifically adapted for NAO. With this new NAO model, several open questions could be investigated further: - Sea surface temperature variation seems to be closely related to long-term NAO variations (Rodwell et al., 1999). If other mechanisms can be excluded from being responsible for NAO, this is an advantage regarding predictability of NAO: If the Ocean, especially sea surface temperature influences NAO, predictability is possible as there are already projection methods for Nina Bachmann, D-UWIS, [email protected] 15 changes in sea surface temperature (for example: Sutton and Allen, 1997). Therefore, it is considered essential to make sea surface temperature predictions more reliable in the near future (Hurrell et al., 2004; IPCC, 2007). - It is important to know how increasing CO2 concentrations in the atmosphere have an influence on NAO. Although models simulated a response of NAO Index to higher concentrations (see chapter 7), not every model showed a strong increase in NAO Index, but some of them did. It‘s essential to investigate, if NAO would react with increasing Index values on higher greenhouse gas concentrations. - If NAO Index reaches more and more positive values in the 21st century as predicted by several authors (IPCC, 2007), it would have a strong effect on European weather phenoma. For European economists and politics the amplitude of this weather effects must been known to take in account for example more severe stroms or higher precipitation. 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