Article

Spatial variability in winter NAO-wind speed relationships in western Europe linked to concomitant states of the East Atlantic and Scandinavian patterns: Variability of Winter Wind Speeds in Response to NAO, EA and SCA

Wiley
Quarterly Journal of the Royal Meteorological Society
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Abstract

The 3-hourly gridded ERA-Interim climate reanalysis dataset, spanning 1979 to 2013, was used to investigate the spatial stationarity of the previously documented relationships between wind speeds and the NAO state in Europe. Over much of western Europe, wind speeds were found to be affected strongly by the concomitant states of the secondary and tertiary atmospheric teleconnections, namely the East Atlantic (EA) and the Scandinavian (SCA) patterns. These modify the geographic positions of the NAO dipole and modulate the influence of the NAO on wind statistics on regional scales, producing non-stationarities in the NAO-wind speed relationships. The interactions of these teleconnections play an important role in modifying wind speeds within Europe. Finally, systematic north-south changes in the Weibull distribution scale and shape parameters are documented along the western margin of Europe, as a function of different states of the NAO, the EA and the SCA. These effects influence both monthly averaged wind speeds and the statistical distributions of 3-hourly wind data, implying strong impacts on wind energy resources and expected wind power production. The results have implications for regional to continent-scale long-term planning of windfarm siting to minimise the impact of resource intermittency.

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... Furthermore, the response of power systems to these patterns across Europe has recently been studied, with a focus on the North Atlantic Oscillation (NAO) [e.g. 22,[30][31][32][33]. ...
... Although the maximum average number of days at a country level is 3, and only for a few combinations of WR and month, figure 4 shows smaller regions where we expect compound events 5 days a month in January and February associated with blocking conditions. Overall, figure 4 supports what previous studies have found: (a) that large-scale circulation patterns influence the energy demand [22,30,31] and the wind power generation over Europe [22,32,33,43], and (b) that blocking patterns are associated with anomalous cold and low-wind speed conditions over Northern and Central Europe, which, in turn, increase the demand and reduce the wind power generation [22,30,33,[43][44][45]. ...
... Although the maximum average number of days at a country level is 3, and only for a few combinations of WR and month, figure 4 shows smaller regions where we expect compound events 5 days a month in January and February associated with blocking conditions. Overall, figure 4 supports what previous studies have found: (a) that large-scale circulation patterns influence the energy demand [22,30,31] and the wind power generation over Europe [22,32,33,43], and (b) that blocking patterns are associated with anomalous cold and low-wind speed conditions over Northern and Central Europe, which, in turn, increase the demand and reduce the wind power generation [22,30,33,[43][44][45]. ...
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A transition to renewable energy is needed to mitigate climate change. In Europe, this transition has been led by wind energy, which is one of the fastest growing energy sources. However, energy demand and production are sensitive to meteorological conditions and atmospheric variability at multiple time scales. To accomplish the required balance between these two variables, critical conditions of high demand and low wind energy supply must be considered in the design of energy systems. We describe a methodology for modeling joint distributions of meteorological variables without making any assumptions about their marginal distributions. In this context, Gaussian copulas are used to model the correlated nature of cold and weak-wind events. The marginal distributions are modeled with logistic regressions defining two sets of binary variables as predictors: four large-scale weather regimes and the months of the extended winter season. By applying this framework to ERA5 data, we can compute the joint probabilities of co-occurrence of cold and weak-wind events on a high-resolution grid (0.25 deg). Our results show that a) weather regimes must be considered when modeling cold and weak-wind events, b) it is essential to account for the correlations between these events when modeling their joint distribution, c) we need to analyze each month separately, and d) the highest estimated number of days with compound events are associated with the negative phase of the North Atlantic Oscillation (3 days on average over Finland, Ireland, and Lithuania in January, and France and Luxembourg in February) and the Scandinavian Blocking pattern (3 days on average over Ireland in January and Denmark in February). This information could be relevant for application in sub-seasonal to seasonal forecasts of such events.
... Long-term solar forcing does not, however, have an impact on North Atlantic Oscillation (NAO) (Ortega et al. 2015;Maycock et al. 2015), but instead, the East Atlantic pattern (EA) (Sjolte et al. 2018), the secondary mode of atmospheric circulation in the North Atlantic region. On the other hand, reanalysis data suggest wind speeds over western Europe are affected by the EA modulating the influence of the NAO (westerlies) on regional wind patterns (Zubiate et al. 2017). Thus, when NAO and EA have opposite indices there are positive wind anomalies over Ireland, the UK and central Europe (Zubiate et al. 2017). ...
... On the other hand, reanalysis data suggest wind speeds over western Europe are affected by the EA modulating the influence of the NAO (westerlies) on regional wind patterns (Zubiate et al. 2017). Thus, when NAO and EA have opposite indices there are positive wind anomalies over Ireland, the UK and central Europe (Zubiate et al. 2017). As such, decadal-scale variations of surface wind may be influenced by the variability in the dominant spatial climate patterns in the region, which define the main climate modes, for example the NOA, EA and Scandinavian pattern, Atlantic Multidecadal Variability (Zeng et al. 2019;Hernández et al. 2020). ...
... orbital parameters, greenhouse gases concentration and feedback mechanisms). In particular, deepening our understanding of how solar-modulated modes of climate variability can trigger regional differences, which could have important influences on the spatial distribution of wind anomalies and impacts of extreme weather events, in the North Atlantic-European region (Zubiate et al. 2017). ...
Article
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Understanding atmospheric response to radiative forcing, including the intensity and distribution of wind patterns is critical as this might have important implications in the coming decades. Long-term episodes of reduced solar activity (i.e. Grand Solar Minima, GSM) have triggered rapid climate change in the past, recorded in proxy-based records, including varved sediments from Meerfelder Maar, Germany, where the Homeric GSM (~2800 years ago) was studied. This study reconstructs windy conditions during the same GSM from Diss Mere, another varved record in England, to support the solar-wind linkage in the North Atlantic-European region. We use diatoms as proxies for windiness and support the palaeolimnological and palaeoclimate interpretation with a multi-proxy chironomids and pollen) evidence. The diatom assemblage documents a shift from Pantocsekiella ocellata dominance to Stephanodiscus parvus and Lindavia comta, indicating a shift to more turbulent waters from ~2767 ± 28, linked to increased windiness. This shift is synchronous with changes in 14C production, linked to solar activity changes during the GSM. Both proxy records reflect a rapid and synchronous atmospheric response (i.e. stronger winds) at the onset and during the GSM in the North Atlantic and continental Europe. In order to test whether this solar-wind linkage is consistent during other GSMs and to understand the underlying climate dynamics, we analyse the wind response to solar forcing at the two study sites during the Little Ice Age, a period that includes several GSMs. For this, we have used a reconstruction based on a 1200-year-long simulation with an isotope-enabled climate model. Our study suggests that wind anomalies in the North Atlantic-European sector may relate to an anomalous atmospheric circulation in response to long-term solar forcing leading to north-easterlies modulated by the East Atlantic pattern.
... Previous research has shown that meteorological conditions and their variability have a strong impact on energy-related parameters and thus influence wind and solar power supply [7][8][9][10]. Large-scale weather patterns have a significant impact on surface conditions [33][34][35], e.g., blocked regimes and related high-pressure systems are known to be associated with low wind power production [12,[36][37][38][39]. Aside from their impact on wind speed, synoptic-scale circulations can also significantly affect cloud cover and hence surface solar radiation [40][41][42][43][44] and solar power production [12,45]. ...
... This will be discussed further in the next section. Amongst the various synoptic-scale weather phenomena which have been shown to strongly affect wind power generation in western Europe [36,[59][60][61], blocking of high-pressure systems (and the absence of westerly airflow into Europe) can result in extended periods of low production and periods of Dunkelflaute [36][37][38][39]. ...
... This will be discussed further in the next section. Amongst the various synoptic-scale weather phenomena which have been shown to strongly affect wind power generation in western Europe [36,[59][60][61], blocking of high-pressure systems (and the absence of westerly airflow into Europe) can result in extended periods of low production and periods of Dunkelflaute [36][37][38][39]. ...
Article
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In the coming decades, the European energy system is expected to become increasingly reliant on non-dispatchable generation such as wind and solar power. Under such a renewable energy scenario, a better characterization of the extreme weather condition ‘Dunkelflaute’, which can lead to a sustained reduction of wind and solar power, is important. In this paper, we report findings from the very first climatological study of Dunkelflaute events occurring in eleven countries surrounding the North and Baltic Sea areas. By utilizing multi-year meteorological and power production datasets, we have quantified various statistics pertaining to these events and also identified their underlying meteorological drivers. It was found that almost all periods tagged as Dunkelflaute events (with a length of more than 24 h) are in November, December, and January for these countries. On average, there are 50–100 h of such events happening in each of these three months per year. The limited wind and solar power production during Dunkelflaute events is shown to be mainly driven by large-scale high-pressure systems and extensive low-cloud coverage. Even though the possibility of simultaneous Dunkelflaute events in neighboring countries can be as high as 30–40%, such events hardly occur simultaneously in all the eleven countries. Through an interconnected EU-11 power system, the mean frequency of Dunkelflaute drops from 3–9% for the individual countries to approximately 3.5% for the combined region, highlighting the importance of aggregating production over a wide area to better manage the integration of renewable energy generation.
... Amongst these, the most important for the climate of Western Europe is the North Atlantic Oscillation (NAO), which accounts for about 40% of the variance of the SLP field in winter [5]. Its influence on air temperature, precipitation and wind speed in eastern North America and Western Europe on an inter-annual time scale has been widely recognised [6,7]. The NAO consists of a meridional dipole of sea-level pressure between the Icelandic Low and the Azores High that controls the location and intensity of western flows in the North Atlantic. ...
... The NAO directs the patterns and extremes of temperature, precipitation, snow cover and wind in Europe, especially during the winter, although its effects can spread throughout the subsequent seasons of the year [8]. Other atmospheric pressure patterns can modulate and cause temporary unseasonality in the relationships between the NAO index and climatic variables in Europe, particularly the East Atlantic pattern (EA), a low-pressure monopole to the West of Ireland located at approximately 55 • N and 20-35 • W [9] and representing about 16% of the variance of the SLP field [7]. ...
... This behaviour, of intensified (reduced) anomalies when the two modes have the same (different) sign, has already been explained by Comas-Bru and McDermott [29]. Zubiate et al. [7] found similar behaviour in their study looking at the influence of the EA and NAO modes on wind speed in the IP, as did Bastos et al. [8] in their behavioural analysis of the PDSI index for each of the 4 combined EA-NAO phases. ...
Article
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The combined influence of the North Atlantic Oscillation (NAO) and the East Atlantic (EA) patterns on the covariability of temperatures and precipitation in 35 stations of the Iberian Peninsula during the period 1950–2019 is analysed in this work. Four EA-NAO composites were defined from teleconnection patterns’ positive and negative phases: EA+NAO+, EA+NAO-, EA-NAO+ and EA-NAO-. Daily data of maximum and minimum temperature were used to obtain seasonal means (TX and TN, respectively), and the covariability of these variables with accumulated seasonal rainfall (R) was studied comparing results obtained for different NAO and EA composites. Main results indicate slight differences in the spatial coverage of correlation coefficients between R and temperature variables, except in spring when the generalised negative relationship between R and TX under EA+NAO+ and EA-NAO- disappears under EA-NAO+ and EA+NAO- composites. This result may be useful to interpret and discuss historical reconstructions of the Iberian climate.
... [8]. Other atmospheric pressure patterns can modulate and cause temporary unseasonality in the relationships between the NAO index and climatic variables in Europe, particularly the East Atlantic pattern (EA), a low-pressure monopole to the West of Ireland located at approximately 55°N and 20-35°W [9], and representing about 16% of the variance of the SLP field [7]. ...
... Amongst these, the most important for the climate of Western Europe is the North Atlantic Oscillation (NAO), which accounts for about 40% of the variance of the SLP field in winter [5]. Its influence on air temperature, precipitation and wind speed in eastern North America and Western Europe on an inter-annual time scale has been widely recognized [6][7]. The NAO consists of a meridional dipole of sea-level pressure between the Icelandic Low and the Azores High that controls the location and intensity of western flows in the North Atlantic. ...
... As far as we know, only a few papers have studied the possible influence of atmospheric circulation patterns on temperature and precipitation covariability: Beniston and Goyette [49] studied the local influence of NAO on combined temperature and precipitation modes in Switzerland, and López-Moreno et al. [2] used a similar methodology to study combined modes of temperature and precipitation in mountainous areas of the Mediterranean Basin. Luoto and Nevalainen [50], using proxy data from northern Europe, studied changes in the temperature-precipitation ratio over the past two millennia, and their relationship to the NAO phases, identifying warm-dry (cold-humid) periods in areas where the positive (negative) phase of the NAO predominated; Zubiate et al. [7] studied the combined influence of NAO and EA patterns on climate variability in Western Europe, and Sánchez-López et al. [31] analysed the role of the NAO, EA and their interactions, on the climate variability observed in the IP over the past 2000 years. ...
Preprint
The combined influence of the North Atlantic Oscillation (NAO) and the East Atlantic (EA) patterns on the covariability of temperatures and precipitation in 35 stations of the Iberian Peninsula during the period 1950-2019 is analysed in this work. Four EA-NAO composites were defined from teleconnection patterns positive and negative phases: EA+NAO+, EA+NAO-, EA-NAO+, and EA-NAO-. Daily data of maximum and minimum temperature were used to obtain seasonal means (TX, and TN, respectively), and the covariability of these variables with accumulated seasonal rainfall (R) was studied comparing results obtained for different NAO and EA composites. Main results indicate slight differences in the spatial coverage of correlation coefficients between R and temperature variables, except in spring when the generalized negative relationship between R and TX under EA+NAO+ and EA-NAO- disappears under EA-NAO+ and EA+NAO- composites. This result may be useful to interpret and discuss historical reconstructions of Iberian climate.
... Several previous studies have recognized the strong links between the North Atlantic Oscillation (NAO) (Walker et al., 1932;Lamb et al., 1987;Hurrell, 1995) -the most relevant EATC-and surface temperature, wind speed or precipitation anomalies over Europe on interannual timescales (Trigo et al., 2002;Scaife et al., 2008;Hurrell et al., 2009;Burningham and French, 2013;Svensson et al., 2015). However, more recent studies (Moore and Renfrew, 2012;Comas-Bru and McDermott, 2014;Zubiate et al., 2017;Comas-Bru and Hernández, 2018;Hall and Hanna, 2018;Rust et al., 2015) have shown that taking into account the second, third and fourth modes of variability -namely the East Atlantic (EA), East Atlantic/Western Russia (EAWR) and the Scandinavian (SCA) patterns-greatly improves the representation of the variability and our understanding of the impacts on surface climate. Each teleconnection is composed of a fixed spatial pattern and an associated index (a time series) that describes the evolution of its amplitude and phase. ...
... The interplay of the EATCs exerts a strong impact on climates at different spatio-temporal scales and has important ecological, economical and societal impacts (e.g. Jerez et al., 2013;Bastos et al., 2016;Zubiate et al., 2017). ...
Article
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The goal of this analysis is the better understanding of how the large-scale atmospheric patterns affect the renewable resources over Europe and to investigate to what extent the dynamical predictions of the large-scale variability might be used to formulate empirical prediction of local climate conditions (relevant for the energy sector). The increasing integration of renewable energy into the power mix is making the electricity supply more vulnerable to climate variability, therefore increasing the need for skillful weather and climate predictions. Forecasting seasonal variations of energy relevant climate variables can help the transition to renewable energy and the entire energy industry to make better informed decision-making. At seasonal timescale climate variability can be described by recurring and persistent, large-scale patterns of atmospheric pressure and circulation anomalies that interest vast geographical areas. The main patterns of the North Atlantic region (Euro Atlantic Teleconnections, EATCs) drive variations in the surface climate over Europe. We analyze reanalysis dataset ERA5 and the multi-system seasonal forecast service provided by Copernicus Climate Change Service (C3S). We found that the observed EATC indices are strongly correlated with surface variables. However, the observed relationship between EATC patterns and surface impacts is not accurately reproduced by seasonal prediction systems. This opens the door to employ hybrid dynamical-statistical methods. The idea consists in combining the dynamical seasonal predictions of EATC indices with the observed relationship between EATCs and surface variables. We reconstructed the surface anomalies for multiple seasonal prediction systems and benchmarked these hybrid forecasts with the direct variable forecasts from the systems and also with the climatology. The analysis suggests that hybrid methodology can bring several improvements to the predictions of energy relevant Essential Climate Variables.
... NAO manifests itself as a meridional dipole of sea-level pressure between two centres of action, Iceland and the Azores, and occurs in two phases, a positive phase associated with mild and rainy winters in northern Europe, and a negative phase associated with increased precipitation in southern Europe (Hurrell 1995;Trigo, Osborn, and Corte-Real 2002). The EA pattern consists of a monopole of mean sea-level pressure to the south of Iceland and west of the United Kingdom, near 52.5 o N, 22.5 o W ( Barnston and Livezey 1987;Zubiate et al. 2017). The EA pattern is known to influence the climate variability of Western Europe (Murphy and Washington 2001) and plays an important role in the strength and location of the NAO (Moore, Pickart, and Renfrew 2011; Moore and Renfrew 2012). ...
Article
Aim Macaronesian cloud forests are insular ecosystems subjected to local environmental variability, but the responses of their tree species to climate variations have never been studied. Our aim was to assess how the variation in environmental conditions associated with the geographical location of several islands in three Macaronesian archipelagos affects the growth patterns and drought‐resistance of the dominant cloud forests trees. Location Azores, Madeira and Canary archipelagos. Portugal and Spain. Taxon Lauraceae, Aquifoliaceae, Clethraceae, Oleaceae, Rosaceae and Cupressaceae. Methods We assessed variations in the radial growth response of 10 cloud forest tree species from 18 populations on 5 islands along a geographical gradient in Macaronesia. We quantified the influence of local climatic variables and North Atlantic Oscillation (NAO) and East Atlantic Pattern (EA) circulation patterns on tree growth and how drought events affected to the resistance, recovery and resilience indices estimated for these species. Results Trees from the same island showed similar growth patterns, particularly in islands with marked hydric stress. In Madeira and the Canary Islands, radial growth was mainly determined by water availability, winter NAO negatively affected growth and droughts caused abrupt narrow growth‐ring width. In the Azores, the effect of the EA was positive, as it increased temperature and relative humidity and promoted growth. Trees from wetter environments demonstrated higher growth resistance to drought, while trees from drier sites showed faster growth recovery after drought events. Main Conclusions Homogeneous growth patterns among species from the same island suggested that the radial growth of trees in cloud forests is mostly determined by local environmental conditions, which are more important for their growth than phenotypic traits. The variability in water availability determined by a latitudinal geographical gradient throughout the Macaronesian region influenced both the climatic response of the trees and their resilience to drought.
... Thus, many studies have analysed the influence of the NAO on wind supply and temperature-related demand, and confirmed that it affects average wind energy generation (Bett et al., 2013;Brayshaw, Troccoli, et al., 2011;Burningham & French, 2012;Ely et al., 2013;Zubiate et al., 2016), power demand (Ely et al., 2013) and even electricity prices (Curtis et al., 2016). While the majority of studies have looked at average supply and demand conditions, less work has been done on individual, daily, extreme events and their effects on the power system. ...
Article
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Britain's power system has shifted towards a major contribution from wind energy. However, wind is highly variable, and exceptionally low wind events can simultaneously occur with cold conditions, which increase demand. These conditions can pose a threat for the security of energy supply. Here we use bias‐corrected wind supply data and the estimated temperature‐related part of demand to analyse events of potential weather‐related energy shortfall based on the historic meteorological record. We conduct sensitivity studies with varying scenarios of Britain's total wind energy capacity and the temperature sensitivity of national demand. These scenarios are estimates for present‐day conditions as well as potential future changes of the power system. We apply a new methodology to estimate the potential severity of an event for the power system, and analyse the atmospheric conditions associated with the most severe events. We find that events of potentially severe shortfall are relatively rare and short‐lived, and often occur with an atmospheric pattern broadly resembling a negative North Atlantic Oscillation. This broad tendency emerges from a wide range of individual daily weather patterns that cause cold and still conditions. With an increase in wind capacity, it is likely that severe events will become rarer, although the most severe days of the record are relatively insensitive to changes in wind supply and temperature sensitivity of demand under our assumptions.
... 1350-1450 AD) to the late LIA (1450 AD to 1900 AD) represents a change to colder conditions (Figs. 2 b, 3 b d) reflecting a strong change in the local climate. This transition is likely related to a shift from EA + to EA − , even under strong negative NAO conditions (Mellado-Cano et al., 2019;Zubiate et al., 2017). These findings suggest that the cold and wet conditions during the latter part of the LIA (Fig. 3 d) can be associated with the southward position of the jet stream under a weakened polar vortex (Mellado-Cano et al., 2019). ...
Article
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Predicting the environmental impact of climate change in extremely sensitive areas, like western Iberia, requires an understanding of the long-term interactions between climate and vegetation. Here we present a novel high-temporal resolution multiproxy analysis, including plant-wax n-alkane isotope data, pollen analysis, macrocharcoal identification, chironomid and diatom records of sediments from a mountain lake in central Portugal. We examined the evolution of the Atlantic and Mediterranean climate influences over the last two millennia, exploring their connection with major atmospheric patterns and impacts on the climatic signal and vegetation dynamics in this understudied region. During the Roman Period (RP; ca. -200 – 500 AD), the study area was characterized by grass dominance, with high temperatures indicated by chironomid composition and microcharcoal content. The increase in plant-wax δ2H values during this period suggests a shift from wet to dry conditions. The Early Middle Ages (EMA; ca. 500–900 AD) were characterized by colder and a transition to wetter conditions, as indicated by the vegetation and plant-wax n-alkane isotope data. The Medieval Climate Anomaly (MCA; ca. 900–1300 AD) was generally warm, with a short initial lake level drop. This period exhibits the maximum expansion of the Mediterranean forest over the last 2 ka and possibly proximal moisture sources. During the Little Ice Age (LIA; 1300–1850 AD), a reduction of the Mediterranean forest and a strong depletion of plant-wax δ2H values suggest cold and wet conditions with strong influence of remote Atlantic moisture, with the coldest and wettest phase of the last 2 ka detected between 1550 and 1900 AD. The post-LIA period, from 1900 AD onwards, shows a change to the present warmer and drier conditions, in a highly anthropized landscape. We also demonstrate that major changes in climate have influenced vegetation patterns, with these changes mainly controlled by large-scale atmospheric dynamics. This underscores the sensitivity of western Iberian ecosystems to climate shifts, enriches the current regional understanding of climate-vegetation interplay, and offers valuable insights for future climate change projections.
... Wind power production in the United Kingdom has been demonstrated to be strongly related to teleconnection patterns (Brayshaw et al. 2011;Zubiate et al. 2017;van der Wiel et al. 2019;Bloomfield et al. 2020b). During the period in which this wind drought event occurred, the North Atlantic Oscillation (NAO) index (Hurrell et al. 2003) showed mainly negative values, which explains the persistent anticyclonic circulation over the British Isles and the low wind speeds. ...
Article
In 2021, the energy sector was put at risk by extreme weather in many different ways: North America and Spain suffered heavy winter storms that led to the collapse of the electricity network; California specifically experienced heavy droughts and heatwave conditions, causing the operations of hydropower stations to halt; floods caused substantial damage to energy infrastructure in central Europe, Australia and China throughout the year, and unusual wind drought conditions decreased wind power production in the United Kingdom by almost 40% during summer. The total economic impacts of these extreme weather events are estimated at billions of USD. Here we review and assess in some detail the main extreme weather events that impacted the energy sector in 2021 worldwide, discussing some of the most relevant case studies and the meteorological conditions that led to them. We provide a perspective on their impacts on electricity generation, transmission and consumption, and summarize estimations of economic losses.
... The manifestation of that pattern obtained by EOF analysis is still debated, and descriptions somewhat differ. Thus, some describe it as a north-south dipole extending across the North Atlantic (often referred to as a southward shifted NAO pattern), while other descriptions emphasise a monopole field south of Iceland and west of Ireland 41,[43][44][45][46] . Regardless, the main action centre of the EA pattern extends along the nodal line of the NAO. ...
Article
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The impact of tropical sea surface temperatures (SSTs) on the signal of geopotential heights (GH200) over the North Atlantic-European (NAE) region is analysed from the aspects of seasonality, the contribution of individual tropical basins and midlatitude North Atlantic, El Niño-Southern Oscillation (ENSO) effect and spatial pattern of the atmospheric response. For this purpose, ensembles of targeted numerical simulations with SST forcing prescribed in various ocean basins are performed and examined. A clear atmospheric response is obtained in the late winter months. The strongest signal is linked to ENSO events during late winter. The competitive influences of individual tropical basins are indicated. At the same time, the superposition effect of the extratropical North Atlantic SSTs, which is established through the modulation of storm tracks, is demonstrated. Both, the modelled signal and the NOAA-CIRES-DOE 20th Century Reanalysis variance reveal the ENSO signature as a pattern in the North Atlantic projecting onto the East Atlantic pattern.
... Weather regimes modulate surface weather in continent-size regions and on multi-day to weekly time scales (Büeler et al., 2021). Thereby, weather regimes cause substantial multi-day variability in the European energy sector (van der Wiel et al., 2019b;Zubiate et al., 2017), in particular wind power (Grams et al., 2017). ...
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Renewable power generation from wind and solar energy is strongly dependent on the weather. To plan future sustainable energy systems that are robust to weather variability, a better understanding of why and when periods of low wind and solar power output occur is valuable. We call such periods of low wind speed and insolation “Dunkelflauten”, the German word for “dark wind lulls”. In this article, we analyse the meteorological conditions during Dunkelflauten in Germany by applying the concept of weather regimes. Weather regimes are quasi‐stationary, recurrent and persistent large‐scale circulation patterns that explain multi‐day atmospheric variability (5–15 days). We use a regime definition that allows us to distinguish four different types of blocked regimes, characterized by high‐pressure situations in the North Atlantic‐European region. We find that Dunkelflauten in Germany occur mainly in winter when the solar power output is low due to the seasonal cycle of solar irradiance and wind power output drops for several consecutive days. A high‐pressure system over Germany, associated with the European Blocking regime, is responsible for most of the Dunkelflauten. Dunkelflauten during the Greenland Blocking regime are associated with colder temperatures than usual, causing higher electricity demand, and would present a particular challenge as space heating becomes electrified in the future. Furthermore, we show that Dunkelflauten occur predominantly when a weather regime is well established and persists longer than usual. Our study provides novel insight into the occurrence and meteorological characteristics of Dunkelflauten, which is essential for planning resilient energy systems and supporting grid operators to prepare for potential shortages in supply.
... Weather regimes modulate surface weather in continent size regions and on multi-day to weekly time scales (Büeler et al., 2021). Thereby, weather regimes cause substantial multi-day variability on the European energy sector (Zubiate et al., 2017;van der Wiel et al., 2019b) in particular wind power (Grams et al., 2017). ...
Preprint
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Renewable generation from wind and solar power is strongly weather-dependent. To plan future sustainable energy systems that are robust to this variability, a better understanding of why and when periods of low wind and solar power output occur is valuable. We call such periods of low wind and solar power output `Dunkelflauten', the German word for dark wind lulls. In this article, we analyse the meteorological conditions during Dunkelflauten in Germany by applying the concept of weather regimes. Weather regimes are quasi-stationary, recurrent, and persistent large-scale circulation patterns which explain multi-day atmospheric variability (5-15 days). We use a regime definition that allows us to distinguish four different types of blocked regimes, characterised by high pressure situations in the North Atlantic-European region. We find that in Germany, Dunkelflauten mainly occur in winter when the solar power output is anyway low and when the wind power output drops for several consecutive days. A high-pressure system over Germany, associated with the European Blocking regime, is responsible for most of the Dunkelflauten. Dunkelflauten during the Greenland Blocking regime are associated with colder temperatures than usual, causing higher electricity demand and presenting a particular challenge as space heating demand electrifies in future. Furthermore, we show that Dunkelflauten occur predominantly when a weather regime is well-established and persists longer than usual. Our study provides novel insight on the occurrence and meteorological characteristics of Dunkelflauten, which is essential for planning resilient energy systems and supporting grid operators to prepare for potential shortages in supply.
... Studies of the seasonal forecast skill of the NAO now show agreement that there is predictability of the NAO index at lead times of 2-4 months, calculated with different methods and in various data sets (Athanasiadis et al. 2017;Baker et al. 2018;Domeisen et al. 2018;Dunstone et al. 2016;Hansen et al. 2019;Scaife et al. 2014;Weisheimer et al. 2017Weisheimer et al. , 2019. Besides the NAO, other dominant large-scale patterns are of interest for European weather (Zubiate et al. 2017), for example, the Scandinavian Pattern (SCA: Barnston and Livezey 1987;Bueh and Nakamura 2007) and the East-Atlantic Pattern (EA: Nesterov 2009;Wallace and Gutzler 1981). ...
Article
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Severe winter windstorms are amongst the most damaging weather events for Europe and show significant interannual variability. While surface variables (temperature, precipitation) have been successfully predicted for some time now, predictability of severe windstorms caused by extra-tropical cyclones remains less well explored. This study investigates windstorm prediction skill of the UK Met Office Global Seasonal Forecast System Version 5 (GloSea5) for the Northeast-Atlantic and European region. Based on an objective Lagrangian tracking of severe, damage relevant windstorms, three storm parameters are analysed: windstorm frequency and two intensity measures. Firstly, skill based on direct tracking of simulated windstorms is diagnosed. Significant positive skill for storm frequency and intensity is found over an extended area at the downstream end of the storm track, i.e., from the UK to southern Scandinavia. The skill for frequency agrees well with previous studies for older model versions, while the results of event-based intensity are novel. Receiver Operating Characteristic Curves for three smaller regions reveal significant skill for high and low storm activity seasons. Second, skill of windstorm characteristics based on their multi-linear regressions to three dominant large-scale circulation patterns [i.e., the North Atlantic Oscillation (NAO), the Scandinavian Pattern (SCA), and the East-Atlantic Pattern (EA)] are analysed. Although these large-scale patterns explain up to 80% of the interannual variance of windstorm frequency and up to 60% for intensity, the forecast skill for the respectively linear-regressed windstorms do not show systematically higher skill than the direct tracking approach. The signal-to-noise ratio of windstorm characteristics (frequency, intensity) is also quantified, confirming that the signal-to-noise paradox extends to windstorm predictions.
... We used the NAO, EA, and SCAND indices as circulation patterns. According to various authors, they impact the air temperatures and precipitation in Eastern Europe [80][81][82][83]. The analysis of the impacts of the large-scale processes in the oceans-atmosphere system showed that the NAO index has a strong positive and statistically significant correlation with the warm compound indices (WD and WW) in the northern part of Eastern Europe in winter. ...
Article
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The spatial distribution of compound extremes of air temperature and precipitation was studied over the territory of Eastern Europe for the period 1950–2018. Using daily data on air temperature and precipitation, we calculated the frequency and trends of the four indices—cold/dry (CD), cold/wet (CW), warm/dry (WD) and warm/wet (WW). The connection between these indices and large-scale patterns in the ocean–atmosphere system, such as the North Atlantic Oscillation (NAO), the East Atlantic (EA) and Scandinavia (SCAND) patterns, was also studied. The positive and statistically significant trends in the region were observed for the warm extremes (especially the WW index) in all seasons, with maximum values in the winter season, while negative trends were obtained for the cold extremes. The NAO index has a strong positive and statistically significant correlation with the warm compound indices (WD and WW) in the northern part of Eastern Europe in winter like the EA pattern, but with smaller values. The spatial distribution of the correlation coefficients between compound extremes and the SCAND index in the winter season is opposite to the correlation coefficients with the NAO index.
... This complexity explains partly the poor agreement in the southern stations, between the timing of the storm surge season and the atmospheric events (Fig. 5b). Indeed, the NAO represents only the major mode of variability, but 4 climate regimes are generally used to describe the North Atlantic atmospheric variability 28,34,37 . Two of them are the NAO+ and NAO− regimes, the two others correspond to a strong anticyclonic ridge over Scandinavia ("Blocking" regime) and over the North Atlantic ("Atlantic Ridge" regime). ...
Article
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Along the European coasts, changes in the timing of the storm surge season are analyzed. Using 10 long-term tide gauges located in western Europe, a consistent spatio-temporal shift emerged in the storm surge season between 1950 and 2000. Temporal shifts are positive (later events) in the North, negative (earlier events) in the South. Extreme surge events occurred about 4 days/decade later in northern Europe, and 5 days/decade earlier in southern Europe. Such a tendency is similar to the one already reported for European river floods between 1960 and 2010. In northern Europe, extreme surges are known to occur during the positive North Atlantic Oscillation phase (NAO+). Identified spatio-temporal shifts likely trace that NAO+ storms tend to occur later between 1950 and 2000. A new index measuring the timing of the NAO+ and NAO− persistent situations is shown to help capture this spatial distribution in the timing of the storm surge seasons.
... During winter, a positive SCA phase results in increased precipitation over southern Europe and the United Kingdom, and decreased precipitation over Scandinavia [45]. Like the EA, the SCA can affect the location and strength of the Azores High and Icelandic Low dipoles [40], subsequently influencing climatic variables such as temperature, rainfall and windspeed [44,46]. Rainfall deviations as a result of the phase of the SCA also propagate to streamflow in Scandinavia [33]. ...
Article
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It has long been understood that the North Atlantic Oscillation (NAO) is a key driver of regional climate in Great Britain and across Europe. However, studies have also noted that there is spatio-temporal variability in NAO-rainfall signatures which arguably limits its practical inclusion in water management. In this study we quantify, at high spatio-temporal resolution, the influence of a broader set of atmospheric circulations on monthly precipitation. Using Standardised Precipitation Indices for the Integrated Hydrological Unit (IHU) Groups of Great Britain we apply univari-ate and multivariate regression models to understand the potential of five atmospheric circulation indices to explain precipitation variability. As far as we are aware this represents the first high spatial and temporal resolution analysis quantifying the influence of a broad set of atmospheric circulations , both individually and in combination. We highlight the influence of each circulation and establish that the NAO only partially explains precipitation variability, especially in the southern regions and during the summer months, where circulations, such as the East Atlantic Pattern, also have an important influence. In summary, we suggest that there is significant explanatory value in looking beyond the NAO when seeking to understand hydroclimatological variability in Great Brit-ain, and there is potential for future work to explore how this understanding can translate into the practical application of atmospheric circulation indices in water management.
... Changes in wind direction and wind speed on the Irish shelf in certain years may have altered the regional stability of the shelf edge current, and potentially enhanced cross-shelf exchange (Hill 1995;Huthnance 1995;Porter et al. 2018), enabling the transport of P. noctiluca from offshore waters onto the shelf in those years (Figure 4.4). Moreover, a negative phase of the NAO index (low atmospheric pressure difference between the Subtropical High and the Subpolar Low) and a positive phase of the EAP index (high atmospheric pressure difference between the central North Atlantic and Western Europe) are both associated with lower wind speed in the North East Atlantic, especially when these two situations cooccur (Zubiate et al. 2017). This may explain why these climatic indices had significant effects on the variability of P. noctiluca presence from mixed effects models. ...
Thesis
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Gelatinous zooplankton are a natural and globally important group of marine organisms, as they provide regulating, provisioning and supporting services to ecosystems. However, gelatinous zooplankton are still a major issue for human activities in several parts of the world, and there is concern that in these regions, the abundance of gelatinous zooplankton may be increasing over time. Added uncertainty comes from the lack of information for the abundance of gelatinous zooplankton at a regional level, particularly in offshore waters, and for gelatinous mesozooplankton that are < 2 cm in size. This thesis sought to improve these knowledge gaps by generating two decade-long datasets for the abundance and diversity of two poorly represented groups of gelatinous zooplankton in the Celtic Seas region of the North East Atlantic (NEA), using fisheries surveys as a research platform. To generate baseline information for gelatinous mesozooplankton species in the Celtic Seas, we identified two fisheries research surveys that were actively collecting zooplankton samples in the region, that could be re-analysed for gelatinous mesozooplankton. However, the net methods used to sample zooplankton on the two types of fisheries survey were different. To evaluate whether each net type (i.e. a Gulf VII sampler and a ring net) estimated the abundance and diversity of gelatinous mesozooplankton similarly, simultaneous deployments of the Gulf VII and ring net were made at 15 sites in July 2017 in Irish and UK shelf waters, and their gelatinous catches were compared. The difference in the estimates of gelatinous mesozooplankton abundance and taxon richness of the Gulf VII and the ring net samples were not significant. This confirmed that zooplankton samples from these two fisheries surveys could be re-analysed to generate a novel long-term data set for gelatinous mesozooplankton in the Celtic Seas. Using zooplankton samples from the two aforementioned fisheries surveys, species abundance data was generated for gelatinous mesozooplankton in the Celtic Sea for seven summers over a 13-year period (2007 – 2019). Total abundance was highly variable each summer, but did not increase or decrease linearly over time. However, subtle compositional changes occurred interannually, including a gradual shift in the abundance ratio of two siphonophore species Muggiaea atlantica and Agalma elegans. Holoplanktonic species dominated the abundance of the gelatinous mesozooplankton community (93.27%) and their abundance was negatively associated with sea surface temperature in July (represented by the position of the 16°C isotherm), and this was underpinned by natural climate variability (represented by the Eastern Atlantic Pattern index). Importantly, these findings suggest that gelatinous mesozooplankton abundance in the Celtic Sea may be lower as a consequence of future ocean warming. The aggregations of one oceanic jellyfish, Pelagia noctiluca, have negatively affected the aquaculture industry in the NEA, especially in Ireland and Scotland. Despite this, there is very little long-term information for their abundance and distribution in the NEA. To investigate the frequency and scale of P. noctiluca aggregations in this region, we collected semi-quantitative data for this species from an autumn-winter fisheries survey, which deployed 1,948 trawls over 11 years (2008 – 2018) covering most of the Celtic Seas. P. noctiluca was present on the Irish shelf in every year of the study (which is much higher than the historical record), and large aggregations of this warm-temperate species occurred in 5 of 11 years, as isolated events. When aggregations occurred, the highest by-catch density was recorded in the northern Irish shelf (maximum catch of P. noctiluca was 195 kg in 2009). P. noctiluca occurrence and abundance was related to wind patterns and two modes of hydroclimatic variability (the North Atlantic Oscillation index and the Eastern Atlantic Pattern index), which could reflect changes in advective processes that transport offshore populations onto the Irish shelf. A recent increase in the occurrence of P. noctiluca detected in the present work may pose a rising threat to coastal enterprise in the North East Atlantic, namely the aquaculture industry. Together, the present work revealed that different groups of gelatinous zooplankton species displayed different trends in abundance over time in the NEA, and this was likely a result of differences in specific biological traits such as life history type, geographical distribution and temperature preference. The diversity of trends (and associated mechanisms) described here further emphasises the complexity and diversity of gelatinous zooplankton, and the need to study this group of organisms at a high taxonomic resolution and over regional or sub-regional scales.
... The strength of windstorms is undoubtedly crucial for the salinity dynamics of the Baltic Sea. Zubiate et al. (2016) characterized the variability of wind speed and distribution as a function of the NAO and the current states of the secondary (EA) and tertiary (SCA) patterns of the SLP variability over Europe. A strong correlation at monthly timescales has been found between the NAO positive phase and wind speed in northern Europe. ...
Article
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In the Baltic Sea, salinity and its large variability, both horizontal and vertical, are key physical factors in determining the overall stratification conditions. In addition to that, salinity and its changes also have large effects on various ecosystem processes. Several factors determine the observed two-layer vertical structure of salinity. Due to the excess of river runoff to the sea, there is a continuous outflow of water masses in the surface layer with a compensating inflow to the Baltic in the lower layer. Also, the net precipitation plays a role in the water balance and consequently in the salinity dynamics. The salinity conditions in the sea are also coupled with changes in the meteorological conditions. The ecosystem is adapted to the current salinity level: a change in the salinity balance would lead to ecological stress for flora and fauna, as well as related negative effects on possibilities to carry on sustainable development of the ecosystem. The Baltic Sea salinity regime has been studied for more than 100 years. In spite of that, there are still gaps in our knowledge of the changes in salinity in space and time. An important part of our understanding of salinity is its long-term changes. However, the available scenarios for the future development of salinity are still uncertain. We still need more studies on various factors related to the salinity dynamics. Among others, more knowledge is needed, e.g., from meteorological patterns at various space scales and timescales as well as mesoscale variability in precipitation. Also, updated information on river runoff and inflows of saline water is needed to close the water budget. We still do not understand the water mass exchange accurately enough between North Sea and Baltic Sea and within its sub-basins. Scientific investigations of the complicated vertical mixing processes are additionally required. This paper is a continuation and update of the BACC (Baltic Assessment of Climate Change for the Baltic Sea Region) II book, which was published in 2015, including information from articles issued until 2012. After that, there have been many new publications on the salinity dynamics, not least because of the major Baltic inflow (MBI) which took place in December 2014. Several key topics have been investigated, including the coupling of long-term variations of climate with the observed salinity changes. Here the focus is on observing and indicating the role of climate change for salinity dynamics. New results on MBI dynamics and related water mass interchange between the Baltic Sea and the North Sea have been published. Those studies also included results from the MBI-related meteorological conditions, variability in salinity, and exchange of water masses between various scales. All these processes are in turn coupled with changes in the Baltic Sea circulation dynamics.
... We used the NAO, EA, and SKA indices as circulation modes. According to various authors, they impact the air temperatures and precipitation rates in Eastern Europe (Zubiate et al. 2017;Tsanis and Tapoglou 2019;Cio et al. 2015;Mikhailova and Yurovsky 2016, etc). The analysis of the impacts of the largescale processes in oceans-atmosphere system showed that the NAO index has a strong positive and statistically signi cant correlation with the WD and WW indices of compound extremes in the northern part of Eastern Europe in winter. ...
Preprint
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The spatial distribution of compound extremes of air temperature and precipitation was studied over the territory of Eastern Europe for the period 1950–2018 during winter and spring. Using daily data on air temperature and precipitation, we calculated the frequency and trends of the four indices – cold/dry, cold/wet, warm/dry and warm/wet. Also, we studying the connection between these indices and large-scale processes in the ocean-atmosphere system such as North Atlantic Oscillation, East Atlantic Oscillation and Scandinavian Oscillation. The results have shown that positive trends in the region are typical of the combinations with the temperatures above the 75th percentile, i.e., the warm extremes in winter and spring. Negative trends were obtained for the cold extremes. Statistically significant increase in the number of days with warm extremes was observed in the northern parts of the region in winter and spring. The analysis of the impacts of the large-scale processes in oceans-atmosphere system showed that the North Atlantic Oscillation index has a strong positive and statistically significant correlation with the warm indices of compound extremes in the northern part of Eastern Europe in winter, while the Scandinavian Oscillation shows the opposite picture.
... Summer NAO trends also affect the Arctic climate as assessed in Sections 3.4.1 and 9.4.1. The NAO is associated with storms or periods of persistent mild winds and dry/sunny spells affecting availability and power consumption (Jerez et al., 2013;Zubiate et al., 2017). ...
Chapter
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This Annex describes the fundamental features of the main modes of large-scale climate variability assessed across chapters in the AR6 WGI report. Modes are defined as recurrent space-time structures of variability of the climate system with intrinsic spatial patterns, seasonality and timescales. They can arise through the dynamical characteristics of the atmospheric circulation but also through coupling between the ocean and the atmosphere, with some interactions with land surfaces and sea ice. The variability of the climate system at ocean- or continental-basin scales, and in particular on seasonal-to-multidecadal timescales, can be described to a large extent by the occurrence and often combination of several modes of climate variability which lead to local impacts and remote responses through teleconnection processes on top of externally forced trends. More precisely, the concept of “teleconnection” refers to the ability of modes of variability to relate climate in remote regions through associated atmospheric or oceanic pathways. Regional climate variations are thus the complex outcome of local physical processes, such as thermodynamical and land-atmosphere feedback processes, and non-local large-scale phenomena.
... The strength of windstorms is undoubtedly crucial for the salinity dynamics of the Baltic Sea. Zubiate et al. (2016) characterized the variability of wind speed and distribution as a function of the NAO and the current states of the secondary (EA) and tertiary (SCA) patterns of the SLP variability over Europe. A strong correlation at monthly time scales has been found between the NAO positive phase and wind speed in northern Europe. ...
Preprint
Full-text available
In the Baltic Sea, salinity and its large variability, both horizontal and vertical, are key physical factors in determining the overall stratification conditions. In addition to that, salinity and its changes also have large effects on various ecosystem processes. Several factors determine the observed two-layer vertical structure of salinity. Due to the excess of river runoff to the sea, there is a continuous outflow of water masses in the surface layer with a compensating inflow to the Baltic in the lower layer. Also, the net precipitation plays a role in the water balance and consequently in the salinity dynamics. The salinity conditions in the sea are also coupled with the changes in the meteorological conditions. The ecosystem is adapted to the current salinity level: a change in the salinity balance would lead to ecological stress of flora and fauna, and related negative effects on possibilities to carry on sustainable development of the ecosystem. The Baltic Sea salinity regime has been studied for more than 100 years. In spite of that, there are still gaps in our knowledge of the changes of salinity in space and time. An important part of our understanding of salinity are its long-term changes. However, the available scenarios for the future development of salinity are still inaccurate. We still need more studies on various factors related to salinity dynamics. Among others more knowledge is needed, e.g. from meteorological patterns in various space and time scales and mesoscale variability in precipitation. Also, updated information on river runoff and inflows of saline water is needed to close the water budget. We still do not understand accurately enough the water mass exchange between North Sea and Baltic Sea and within its sub-basins. Scientific investigations of the complicated vertical mixing processes are additionally required. This paper is a continuation and update of the BACC II book which was published in 2015, including information from articles issued until 2012. After that, there have been many new publications on the salinity dynamics, not least because of the Major Baltic Inflow which took place in December 2014. Several key topics have been investigated, including the coupling of long-term variations of climate with the observed salinity changes. Here the focus is on observing and indicating the role of climate change for salinity dynamics. New results of MBI-dynamics and related water mass interchange between the Baltic Sea and the North Sea have been published. Those studies also included results from the MBI-related meteorological conditions, variability in salinity and exchange of water masses between various scales. All these processes are in turn coupled with changes in the Baltic Sea circulation dynamics.
... In this work, four Euro-Atlantic Teleconnection (EATC) indices (namely the North Atlantic Oscillation (NAO), East Atlantic (EA), East Atlantic/Western Russia (EAWR) and Scandinavian Pattern (SCA)) are employed as predictors to anticipate near-surface wind speed conditions in Europe. Those teleconnection indices are strongly 55 related to wind speed conditions in Europe (Zubiate et al., 2017) and wind power generation (Yang et al., 2020), and have been recently shown to be predictable . Since the downscaled predictions combine a dynamical forecast of a circulation variable and a statistical relationship with a second variable of interest, they are referred to as hybrid predictions (see Chapter 2 in WMO (2020)), to differentiate them from purely statistical seasonal forecasts that employ ob-60 served values of potential forcing fields to derive the predictions (Kämäräinen et al., 2019). ...
Article
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This work provides a new methodology based on a statistical downscaling with a perfect prognosis approach to produce seasonal predictions of near-surface wind speeds at the local scale. Hybrid predictions combine a dynamical prediction of the four main Euro-Atlantic Teleconnections (EATC) and a multilinear statistical regression, which is fitted with observations and includes the EATC as predictors. Once generated, the skill of the hybrid predictions is assessed at 17 tall tower locations in Europe targeting the winter season. For comparative purposes, hybrid predictions have also been produced and assessed at a pan-European scale, using the ERA5 100-metre wind speed as the observational reference. Overall, results indicate that hybrid predictions outperform the dynamical predictions of near-surface wind speeds, obtained from five prediction systems available through the Climate Data Store of the Copernicus Climate Change Service. The performance of a multi-system ensemble prediction has also been assessed. In all cases, the enhancement is particularly noted in northern Europe. By being more capable of anticipating local wind speed conditions in higher quality, hybrid predictions will boost the application of seasonal predictions outside the field of pure climate research. Full article in Open Access: https://iopscience.iop.org/article/10.1088/1748-9326/abe491
... Central Europe, including the UK and Northern Germany, is vulnerable to wind storm damage due to intense North Atlantic extratropical cyclones [108]. As extratropical cyclones grow on the baroclinicity associated with the midlatitude jet stream [109], intense cyclones are favoured by a strong and zonally extended North Atlantic jet, as found for positive values of the North Atlantic Oscillation (NAO) [110,111]. Severe European wind storm damage particularly took place in the 1990s, a decade of persistent positive NAO [112], and the possibility of a longer-term GHG-induced upward trend remains open but debated [108,113]. In the future projections, climate models indicate a strengthening of the mean westerlies in Central Europe [114]. ...
Article
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Purpose of Review Atmospheric circulation exerts a strong control on regional climate and extremes. However, projections of future circulation change remain uncertain, thus affecting the assessment of regional climate change. The purpose of this review is to describe some key cases where regional precipitation and windiness strongly depend on the mid-latitude atmospheric circulation response to warming, and summarise this into alternative plausible storylines of regional climate change. Recent Findings Recent research has enabled to better quantify the importance of dynamical aspects of climate change in shaping regional climate. The cold season precipitation response in Mediterranean-like regions is identified as one of the most susceptible impact-relevant aspects of regional climate driven by mid-latitude circulation changes. A circulation-forced drying might already be emerging in the actual Mediterranean, Chile and southwestern Australia. Increasing evidence indicates that distinct regional changes in atmospheric circulation and European windiness might unfold depending on the interplay of different climate drivers, such as surface warming patterns, sea ice loss and stratospheric changes. Summary The multi-model mean circulation response to warming tends to show washed-out signals due to the lack of robustness in the model projections, with implications for regional changes. To better communicate the information contained within these projections, it is useful to discuss regional climate change conditionally on alternative plausible storylines of atmospheric circulation change. As progress continues in understanding the factors driving the response of circulation to global warming, developing such storylines will provide end–to–end and physically self-consistent descriptions of plausible future unfoldings of regional climate change.
... More recently, the amplitude of this internal variability has been attributed to the influence of other North Atlantic modes of climate variability [i.e., the East Atlantic (EA) and Scandinavian (SCA) patterns], which would thereby modulate the strength and location of the NAO dipole from annual to multidecadal scales [21][22][23] . The EA pattern is structurally similar to the NAO, being defined as a north-south dipole with SLP anomaly centres, spanning the entire North Atlantic Ocean 3,24 , or a well-defined SLP monopole south of Iceland and west of Ireland 4,22,23,25 . Compared with the nodal lines of the NAO pattern, the anomaly centres of the EA pattern are displaced to the southeast 26 . ...
Article
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The North Atlantic Oscillation (NAO) is the major atmospheric mode that controls winter European climate variability because its strength and phase determine regional temperature, precipitation and storm tracks. The NAO spatial structure and associated climatic impacts over Europe are not stationary making it crucial to understanding its past evolution in order to improve the predictability of future scenarios. In this regard, there has been a dramatic increase in the number of studies aimed at reconstructing past NAO variability, but the information related to decadal-scale NAO evolution beyond the last millennium is scarce and inconclusive. We present a new 2,000-year multi-annual, proxy-based reconstruction of local NAO impact, with associated uncertainties, obtained by a Bayesian approach. This new local NAO reconstruction is obtained from a mountain lacustrine sedimentary archive of the Iberian Peninsula. This geographical area is not included in previous NAO reconstructions despite being a widely used region for instrumental-based NAO measurements. We assess the main external forcings (i.e., volcanic eruptions and solar activity) on NAO variability which, on a decadal scale, show that a low number of sunspots correlate to low NAO values. By comparison with other previously published NAO reconstructions in our analyses we can test the stationarity of the solar influence on the NAO signal across a latitudinal gradient based on the position of the employed archives for each NAO reconstruction. Inconclusive results on the volcanic forcing on NAO variability over decadal time-scales indicates the need for further studies. Moreover, we highlight the potential role of other North Atlantic modes of variability (i.e., East Atlantic pattern) on the non-stationary behaviour of the NAO throughout the Common Era, likely via solar forcing.
Preprint
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The application of AI forecasts to wind power generation is an important emerging topic for the energy sector. Wind power was responsible for approximately 23% of the total European electricity generated in 2019. Wind generation in Germany currently accounts for about 40% of the country's total power generation, while the offshore wind farms in the UK create almost 50% of the total energy in winter. In this study, 100-m wind forecasts provided by FourCastNetv2-small (FCNv2), an AI-driven weather prediction model (AIWP), are investigated and compared against ECMWF HRES forecasts for the same period, verified against ERA5. The performance of FCNv2 in predicting wind events is evaluated, focusing on a strong wind case over the North Sea on 13 March 2023 and an extended analysis between October 2022 and March 2023. FCNv2 performs well at forecasting both weak and strong wind conditions, especially at long lead times over five days. However, it tends to underestimate high wind speeds, producing smooth wind fields that lack sharp gradients. This smoothing effect arises from the use of root mean square error during training and limits FCNv2's skill in predicting extremes at longer lead times. As FCNv2 is trained to reproduce 100-m winds from the ERA5 reanalysis, this gives it an unfair advantage over physical models. However, this advantage is lost through the nonlinear relationship between wind speed and turbine efficiency, making HRES forecasts of wind energy more skilful at all lead times. Finally, potential improvements and pitfalls are discussed-including use of a fractional skill score during model training, bias correction for AIWP output, and correct handling of results over complex orography. Despite some limitations, AIWPs like FCNv2 show the potential to complement traditional NWP models in specific forecasting applications.
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Monitoring sandy shoreline evolution from years to decades is critical to understand the past and predict the future of our coasts. Optical satellite imagery can now infer such datasets globally, but sometimes with large uncertainties, poor spatial resolution, and thus debatable outcomes. Here we validate and analyse satellite-derived-shoreline positions (1984–2021) along the Atlantic coast of Europe using a moving-averaged approach based on coastline characteristics, indicating conservative uncertainties of long-term trends around 0.4 m/year and a potential bias towards accretion. We show that west-facing open coasts are more prone to long-term erosion, whereas relatively closed coasts favor accretion, although most of computed trends fall within the range of uncertainty. Interannual shoreline variability is influenced by regionally dominant atmospheric climate indices. Quasi-straight open coastlines typically show the strongest and more alongshore-uniform links, while embayed coastlines, especially those not exposed to the dominant wave climate, show weaker and more variable correlation with the indices. Our results provide a spatial continuum between previous local-scale studies, while emphasizing the necessity to further reduce satellite-derived shoreline trend uncertainties. They also call for applications based on a relevant averaging approach and the inclusion of coastal setting parameters to unravel the forcing-response spectrum of sandy shorelines globally.
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The jellyfish Pelagia noctiluca form extensive aggregations in the Mediterranean Sea that can exert top-down control on prey and cause mass-mortalities in fish farms. The description of extensive aggregations of P. noctiluca in the northeast Atlantic in 2007 coupled with a subsequent mortality event of farmed salmon in Northern Ireland prompted further investigation of the species in this region. We collected standardised P. noctiluca biomass from 1938 fisheries trawls over 11 years (2008–2018) covering ~200,000 km2 of northeast Atlantic shelf seas. While a linear trend in P. noctiluca was not identified, the mean annual biomass exhibited significant fluctuations, with particularly elevated levels in 2009, 2013, 2014 and 2016 (0.05, 0.02, 0.01 and 0.02 kg ha 1, respectively). Mean biomass was higher in the northern (0.028 kg ha 1) and western portions (0.005 kg ha 1) of the study area compared to the southwestern (0.003 kg ha 1) and southeastern portions (0.001 kg ha 1). A binomial generalised linear mixed model of P. noctiluca biomass data indicated that higher P. noctiluca occurrence was driven by a positive Eastern Atlantic Pattern index (strongest effect), south-easterly winds, a negative North Atlantic Oscillation index and lower sea-surface temperatures (weakest effect). The fixed effects accounted for 36.81% of the variance in P. noctiluca occurrence data, while a random year effect further explained an additional 24.06% of the variance. These conditions may destabilise the European Slope Current in autumn-winter which promotes the transport of P. noctiluca from oceanic sources onto the northeast Atlantic shelf. Our findings represent a dramatic shift in our understanding of this species in the northeast Atlantic which may have significant ecological impacts, from predation on fish eggs and larvae to providing food for oceanic sunfish.
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Plain Language Summary The North Atlantic Oscillation (NAO) is the most dominant weather pattern over the North Atlantic‐European sector with profound influence on regional climate. The NAO pattern describes the changes in a low‐pressure system over Iceland and a high‐pressure system over the Azores, which are commonly known as the NAO centers of action. However, the NAO centers of action are not always fixed in these two locations, but show spatial movement over time. In this study, we compare the winter weather patterns over the North Atlantic region from the last millennium to future scenarios in climate models with reanalysis products and paleoclimate reconstructions. We find that models generally can capture the spatial structure of the NAO very well but with little changes in its location and shape over time in contrast to historical reanalysis. These biased NAO patterns in climate models can shift the modeled regional temperature and precipitation patterns associated with the NAO. This remains a challenge for the reliability of future climate projections over the North Atlantic region.
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This study presents the simulated response of regional climate and the oxygen isotopic composition of precipitation (δ18Op) to different along-strike topographic evolution scenarios. These simulations are conducted to determine if the previously hypothesized diachronous surface uplift in the Western and Eastern Alps would produce δ18Op signals in the geologic record that are sufficiently large and distinct to be detected using stable isotope paleoaltimetry. We present a series of topographic sensitivity experiments conducted with the water-isotope-tracking atmospheric general circulation model (GCM) ECHAM5-wiso. The topographic scenarios are created from the variation of two free parameters, (1) the elevation of the Western–Central Alps and (2) the elevation of the Eastern Alps. The results indicate Δδ18Op values (i.e., the difference between δ18Op values at the low- and high-elevation sites) of up to -8 ‰ along the strike of the Alps for the diachronous uplift scenarios, primarily due to changes in orographic precipitation and adiabatic lapse rate driven localized changes in near-surface variables. These simulated magnitudes of Δδ18Op values suggest that the expected isotopic signal would be significant enough to be preserved and measured in geologic archives. Moreover, the simulated slight δ18Op differences of 1 ‰–2 ‰ across the low-elevation sites support the use of the δ–δ paleoaltimetry approach and highlight the importance of sampling far-field low-elevation sites to differentiate between the different surface uplift scenarios. The elevation-dependent rate of change in δ18Op (“isotopic lapse rate”) varies depending on the topographic configuration and the extent of the surface uplift. Most of the changes are significant (e.g., -1.04 ‰ km-1 change with slope error of ±0.09 ‰ km-1), while others were within the range of the statistical uncertainties (e.g., -0.15 ‰ km-1 change with slope error of ±0.13 ‰ km-1). The results also highlight the plausible changes in atmospheric circulation patterns and associated changes in moisture transport pathways in response to changes in the topography of the Alps. These large-scale atmospheric dynamics changes can complicate the underlying assumption of stable isotope paleoaltimetry and therefore require integration with paleoclimate modeling to ensure accurate reconstruction of the paleoelevation of the Alps.
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The prediction skill of sub‐seasonal forecast models is evaluated for seven year‐round weather regimes in the Atlantic–European region. Reforecasts based on models from three prediction centers are considered and verified against weather regimes obtained from ERA‐Interim reanalysis. Results show that predicting weather regimes as a proxy for the large‐scale circulation outperforms the prediction of raw geopotential height. Greenland blocking tends to have the longest year‐round skill horizon for all three models, especially in winter. On the other hand, the skill is lowest for the European blocking regime for all three models, followed by the Scandinavian blocking regime. Furthermore, all models struggle to forecast flow situations that cannot be assigned to a weather regime (so‐called no regime), in comparison with weather regimes. Related to this, variability in the occurrence of no regime, which is most frequent in the transition seasons, partly explains the predictability gap between transition seasons and winter and summer. We also show that models have difficulties in discriminating between related regimes. This can lead to misassignments in the predicted regime during flow situations in which related regimes manifest. Finally, we document the changes in skill between model versions, showing important improvements for the ECMWF and NCEP models. This study is the first multi‐model assessment of year‐round weather regimes in the Atlantic–European domain. It advances our understanding of the predictive skill for weather regimes, reveals strengths and weaknesses of each model, and thus increases our confidence in the forecasts and their usefulness for decision‐making.
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The spatial and temporal variations of wet and dry spells may be related to large‐scale climatic indices. To date, no comprehensive study has been conducted on Iran's spatial and temporal variations of wet and dry spells. To fill this gap, 14 wet/dry spell indices were calculated for 512 rain gauges across Iran from 1985 to 2016. The modified non‐parametric Mann–Kendall test was then used to examine the temporal variations of wet and dry spell indices. Whether any relationships between spell indices and 13 large‐scale climatic indicators existed was determined. The maps showing the degree of correlation between wet/dry spell indices and two climatic indicators that reflect short‐ and long‐term El Niño oscillation were presented. The results demonstrated that precipitation typically occurs in bursts of 1 or 2 days in length, with most of the annual precipitation coming from a few exceptionally heavy or extreme events. Most dry spells in Iran occur from 6 to 27 days or longer. The length, frequency, and intensity of wet spells declined in southern Iran while expanding in northern Iran. However, extreme wet spells have intensified significantly across the country. When El Niño occurs, Iran experiences wetter weather. However, long‐term oscillations in sea‐surface temperatures in the Pacific Ocean are found to be significantly correlated with wet/dry spells, outperforming those obtained for shorter periods. A smaller portion of the country showed a significant correlation in extreme spell indices, though.
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Plain Language Summary Predicting the most likely weather patterns ahead of the autumn and winter can be very useful for resilience planning. To date, skillful forecasts have only been possible for the most common pattern of winter atmospheric variability over the North Atlantic and European region, called the North Atlantic Oscillation (“NAO”), with no significant skill for the second pattern, called the East Atlantic Pattern (“EAP”). Using seasonal predictions from a range of coupled ocean—atmosphere models, we demonstrate significant skill in the EAP, in late autumn and early winter. The associated temperature and precipitation variability across western Europe is also skilfully predicted. We further show that skill shifts from the EAP to the NAO over the autumn to winter and reflects the evolving influence of the El Niño South Oscillation, a large‐scale atmosphere‐ocean feature of the tropical Pacific. However, climate models underestimate the magnitude of the predictable signal of the EAP, as found previously for the NAO. Resolving this error would further improve seasonal predictions of the late autumn and early winter period.
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As offshore wind power is continuously integrated into the electric power systems in around the world, it is critical to understand its variability. Weather regimes (WRs) can provide meteorological explanations for fluctuations in wind power. Instead of relying on traditional large-scale circulation WRs, this study focuses on assessing the dependency of wind resources on WRs in the tailored region clustered based on the finer spatial scale. For this purpose, we have applied self-organizing map algorithm (SOM) to cluster atmospheric circulations over the South China Sea (SCS) and characterized wind resources for the classified WRs. Results show that WRs at mesoscale can effectively capture weather systems driving wind power production variability, especially on multi-day timescale. Capacity factor reconstruction during four seasons illustrates that WRs highly influence most areas in winter and southern part of SCS in summer, and WRs can serve as a critical source of predicting the potential of wind resources. In addition, we further qualify the wind power intermittency and complementarity under different WRs, which have not been assessed associated with WRs. During WRs with changeable atmosphere conditions, the high complementarity over coastal areas can reduce the impact of intermittency on wind power generation. The proposed approach is able to be implemented in any region and may benefit wind resource evaluation and characterization.
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Long‐term variations in maximum gust speeds have been analyzed using wind measurements recorded at St Mary's, Isles of Scilly, UK, and possible drivers of recent changes have been investigated. A rigorous homogenization procedure has been applied to the wind records to remove discontinuities mainly caused by non‐climatic changes. Trends in magnitude of the homogenized annual and monthly maximum gust speeds have been subsequently estimated. A significant (p < 0.10) decreasing trend of −0.102 m s⁻¹/10 years is exhibited by the annual maximum gust speeds over the period 1928–2011, while a non‐significant (p > 0.10) positive trend characterizes the entire period 1928–2020 of wind measurements. A turning point has been detected in the monthly maximum gust speed series in 2012, followed by a trend reversal. Distinctive differences in the gust trend pattern have been observed among the seasons, with increasing trend in summer, and winter gust speeds exhibiting decline in 1969–2011 and strengthening since 2012. Variations in the monthly maximum gust speeds appear closely related to changes in air temperature and latitudinal pressure gradients. Furthermore, the monthly maximum gust speeds show significant correlation with the main oceanic‐atmospheric circulation patterns in the North Atlantic region. A synergistic effect among the phases of the dominant patterns of climate variability appears to explain the observed decline and recovery trends in winter gusts. Summer gust speeds show a positive correlation with the global land‐ocean temperature deviations from the corresponding 1951–1980 base period mean.
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A transition to renewable energy is needed to mitigate climate change. In Europe, this transition has been led by wind energy, which is one of the fastest growing energy sources. However, energy demand and production are sensitive to meteorological conditions and atmospheric variability at multiple time scales. To accomplish the required balance between these two variables, critical conditions of high demand and low wind energy supply must be considered in the design of energy systems. In addition, large-scale weather regimes impact the weather conditions at the surface. For instance, the negative phase of the North Atlantic Oscillation and the Scandinavian Blocking pattern are associated with cold and weak-wind events in Northern Europe. We describe a methodology for modeling joint distributions of meteorological variables without making any assumptions about their marginal distributions. In this context, the concept of Gaussian copulas is used to model the correlated nature of cold and weak-wind events. The marginal distributions are modeled with logistic regressions defining two sets of binary variables as predictors: the weather regimes and the months of the extended winter season. By applying this framework to ERA5 data, we can compute the joint probabilities of co-occurrence of cold and weak-wind events on a high-resolution grid (0.25 deg). Our results indicate that we can expect cold and weak-wind compound events on more than 10%10 \% of the days in the regimes defined by the negative phase of the North Atlantic Oscillation and the Scandinavian Blocking in January and February. This information could be relevant for application in sub-seasonal to seasonal forecasts of such events.
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European winter weather is dominated by several low‐frequency teleconnection patterns, the main ones being the North Atlantic Oscillation, East Atlantic, East Atlantic/Western Russia, and Scandinavian patterns. We analyze the century‐long ERA‐20C reanalysis and ASF‐20C seasonal hindcast data sets and find that these patterns are subject to decadal variability and fluctuations in predictive skill. Using indices for determining periods of extreme cold or warm temperatures, we establish that the teleconnection patterns are, for some regions, significantly correlated or anti‐correlated to cold or heat waves. The seasonal hindcasts are however only partly able to capture these relationships. There do not seem to be significant changes to the observed links between large‐scale circulation patterns and extreme temperatures between periods of higher and lower predictive skill.
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With growing amounts of wind and solar power in the electricity mix of many European countries, understanding and predicting variations of renewable energy generation at multiple timescales is crucial to ensure reliable electricity systems. At seasonal scale, the balance between supply and demand is mostly determined by the large-scale atmospheric circulation, which is uncertain due to climate change and natural variability. Here we employ four teleconnection indices, which represent a linkage between atmospheric conditions at widely separated regions, to describe the large-scale circulation at seasonal scale over Europe. For the first time, we relate each of the teleconnections to the wind and solar generation anomalies at country and regional level and we show that dynamical forecasts of the teleconnection indices allow predicting renewable generation at country level with positive skill levels. This model unveils the co-variability of wind and solar generation in European countries through its common dependence on the general circulation and the state of the teleconnections.
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Atmospheric-oceanic circulations (teleconnections) have an important influence on regional climate. In Great Britain, the North Atlantic Oscillation (NAO) has long been understood as the leading mode of climate variability, and its phase and magnitude have been found to influence regional rainfall in previous research. The East Atlantic Pattern (EA) is also increasingly recognised as being a secondary influence on European climate. In this study we use high resolution gridded rainfall and Standardised Precipitation Index (SPI) time series data for Great Britain to map the monthly rainfall signatures of the NAO and EA over the period January 1950-December 2015. Our analyses show that the influence of the two teleconnections varies in space and time with distinctive monthly signatures observed in both average rainfall/SPI-1 values and incidences of wet/dry extremes. In the winter months the NAO has a strong influence on rainfall and extremes in the northwestern regions. Meanwhile, in the southern and central regions stronger EA-rainfall relationships are present. In the summer months opposing positive/negative phases of the NAO and EA result in stronger wet/dry signatures which are more spatially consistent. Our findings suggest that both the NAO and EA have a prominent influence on regional rainfall distribution and volume in Great Britain, which in turn has implications for the use of teleconnection forecasts in water management decision making. We conclude that accounting for both NAO and EA influences will lead to an enhanced understanding of both historic and future spatial distribution of monthly precipitation.
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Renewable energy has a key role to play in the transition towards a low‐carbon society. Despite its importance, relatively little attention has been focused on the crucial impact of weather and climate on energy demand and supply, or the generation or operational planning of renewable technologies. In particular, to improve the operation and longer‐term planning of renewables, it is essential to consider seasonal and subseasonal weather forecasting. Unfortunately, reports that focus on these issues are not common in scientific literature. This paper presents a systematic review of the seasonal forecasting of wind and wind power for the Iberian Peninsula and the Canary Islands, a region leading the world in the development of renewable energies (particularly wind) and thus an important illustration in global terms. To this end, we consider the scientific literature published over the last 13 years (2008–2021). An initial search of this literature produced 14,293 documents, but our review suggests that only around 0.2% are actually relevant to our purposes. The results show that the teleconnection patterns (North Atlantic Oscillation [NAO], East Atlantic [EA] and Scandinavian [SCAND]) and the stratosphere are important sources of predictability of winds in the Iberian Peninsula. We conclude that the existing literature in this crucial area is very limited, which points to the need for increased research efforts, that could lead to great returns. Moreover, the approach and methods developed here could be applied to other areas for which systematic reviews might be either useful or necessary.
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With the role of surface winds in the generation of ocean waves, secondary microseisms induced by ocean wave-wave interactions represent a unique interconnection between the solid Earth, the ocean and global atmospheric circulation patterns. In this study, temporal changes in the ocean generated seismic wavefield in Northeast Atlantic are monitored offshore West of Ireland using ocean bottom seismometers located on top of a thick sedimentary basin. Comparisons with numerical seismic simulations and ocean wave model hindcast data suggest those variations are correlated with changing patterns in ocean wave-wave interactions closely linked to secondary microseism generation areas. Here we show how those changes, accentuated by the specific structure of the Irish offshore margin, reveal the signature of the North Atlantic Oscillation (NAO) in the Earth’s background seismic wavefield. In the North Atlantic, secondary microseism sources likely fluctuate with the changing storm track in response to variations in the NAO.
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Although gelatinous zooplankton are an important component of marine ecosystems, gelatinous mesozooplankton that are <2 cm are underrepresented in monitoring programmes. Here, the interannual variability of gelatinous mesozooplankton abundance and diversity was estimated from 167 zooplankton net samples that were collected in the Celtic Sea during seven fisheries surveys between 2007 and 2019 and analysed alongside environmental parameters. Compositional changes occurred interannually, including an overturn in the abundance ratio of two siphonophores (Muggiaea atlantica and Agalma elegans). Analysis of annual mean gelatinous abundance revealed no linear trend over time (Spearman, r = −0.09, p = 0.287); however, the interannual abundance varied by a factor of 33 (minimum mean abundance in 2013 = 7.36 ± 4.86 individuals m−3; maximum in 2017 = 244.82 ± 84.59 individuals m−3). Holoplanktonic taxa dominated the abundance of the gelatinous community (93.27%) and their abundance was negatively associated with summer sea surface temperature (represented by the 16°C isotherm in July), and the Eastern Atlantic Pattern index 3 months prior (April). Our data suggest that gelatinous mesozooplankton in the Celtic Sea may become less abundant with further ocean warming, and further highlight the need to monitor gelatinous mesozooplankton with a high taxonomic resolution moving forward.
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The observed surface wind speed (SWS) has declined over the past four decades over China, which have has been examined from a climatological perspective. However, the SWS is highly variable and is dependent on the weather regime (WR). This study investigates the variability of winter SWS under six typical WRs and assesses the variability at the synoptic to decadal time scales. Our results reveal that the WRs impose important impacts on the spatial pattern and inter‐annual variability of SWS over China. The Siberian high pressure exerts an important influence on the WR occurrence over Eastern Asia and affects the SWS variations, with more prominent impacts at the decadal time scale. The Aleutian low pressure exhibits weak inter‐annual correlations with the SWS under all WRs but reveals closer decadal connections under certain WRs. However, WRs can not sufficiently explain the decreasing trend of SWS from 1980 to 2017.
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Utilizing the Community Atmosphere Model, version 4 (CAM4), the influence of sudden Arctic sea-ice thinning on North Atlantic Oscillation (NAO) events is investigated on a sub-seasonal time scale. First, the control simulation with CAM4 using prescribed daily boundary conditions produces realistic descriptions for the frequency and evolution of NAO events. Second, sensitivity experiments are then conducted to investigate the impact of sudden Arctic sea-ice thinning on NAO events. Numerical results show that the NAO has obvious responses to sudden sea-ice thinning over 10 days. Finally, the NAO responses to sudden sea-ice thinning are related to the positions of the NAO event. Further diagnostic analysis reveals that when the poleward centre of a positive NAO event is located west (east) of Greenland, cold (warm) advection would be induced because of the sudden sea-ice thinning along with the northward (southward) wind. This cooling (warming) causes the air to contract (expand) and further results in a decrease (increase) in the geopotential height and sea level pressure fields, which corresponds to a positive NAO (negative NAO) response. The results of this investigation show that the response of atmospheric circulation to boundary conditions is determined by both boundary condition changes and the atmospheric circulation regime, which provides an understanding of the effect on an NAO event of sudden sea-ice thinning on a sub-seasonal time scale.
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Seasonal forecast systems have demonstrated significant skill in forecasting the winter North Atlantic Oscillation (NAO) in recent years. This skill is a result of influences that have remote origins, such as the El Niño-Southern Oscillation or the stratospheric Quasi-Biennial Oscillation. Here we assess the role of the tropical troposphere and the extra-tropical stratosphere in driving North Atlantic-European wintertime sea level pressure, using numerical experiments in which conditions in these regions are constrained to be similar to observational reanalyses. We show that both of these remote regions play a role in influencing surface circulation. In particular, the East Atlantic Pattern-the second most important mode of regional winter variability after the NAO-is linked to convective anomalies in the tropical Atlantic. Tropical and stratospheric influences are shown to lead to the reproduction of observed large-scale pressure patterns in the majority of winters, but often by a single driver rather than a blend of both. We argue that while stratospheric influences are well represented, tropical influences are underrepresented in winter predictions. These results highlight tropical Atlantic predictability as an important focus for further research.
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Atmospheric circulation patterns that prevail for several consecutive days over a specific region can have consequences for the wind energy sector as they may lead to a reduction of the wind power generation, impacting market prices or repayments of investments. The main goal of this study is to develop a user‐oriented classification of atmospheric circulation patterns in the Euro‐Atlantic region that helps to mitigate the impact of the atmospheric variability on the wind industry at seasonal timescales. Particularly, the seasonal forecasts of these frequencies of occurrence can be also beneficial to reduce the risk of the climate variability in wind energy activities. K‐means clustering has been applied on the sea level pressure from the ERA5 reanalysis to produce a classification with three, four, five and six clusters per season. The spatial similarity between the different ERA5 classifications has revealed that four clusters are a good option for all the seasons except for summer when the atmospheric circulation can be described with only three clusters. However, the use of these classifications to reconstruct wind speed and temperature, key climate variables for the wind energy sector, has shown that four clusters per season are a good choice. The skill of five seasonal forecast systems in simulating the year‐to‐year variations in the frequency of occurrence of the atmospheric patterns is more dependent on the inherent skill of the sea level pressure than on the number of clusters employed. This result suggests that more work is needed to improve the performance of the seasonal forecast systems in the Euro‐Atlantic domain to extract skilful forecast information from the circulation classification. Finally, this analysis illustrates that from a user perspective it is essential to consider the application when selecting a classification and to take into account different forecast systems.
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This study presents a climatology and trend analysis of reference crop evapotranspiration (ETo) over continental Spain and the Balearic Islands. Geographic features of the study region play a substantial role in the climatology of ETo. The highest values (in excess of 1,200 mm y⁻¹) are found at lower elevations in the south, while the lowest values (less than 900 mm y⁻¹) are found in the highest elevations in the north. A deep analysis reveals: (a) a low interannual variability; (b) summer accumulates more than 50% of annual values; and (c) the radiative component contribution is higher than 50%. A positive long‐term trend (1961–2014) has been detected for most of the study area, but showing contrasting situations when shorter periods (20–30 years) are analysed. A short initial period of negative trend was followed by a longer period of a positive trend. We argue that global dimming/brightening played a role in this process, as these two contrasting periods are clearly guided by the radiative component. A seasonal analysis of the trends reveals that spring and summer are the seasons showing the long‐term positive trends. Interestingly, a monthly analysis shows that spring trends are guided by March and April and summer trends are mostly guided by June, which is the month showing the highest relative changes. This could have important consequences for agriculture and natural ecosystems since this month represents the start of the summer (dry) period.
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Large-scale climate patterns control variability in the global carbon sink. In Europe, the North-Atlantic Oscillation (NAO) influences vegetation activity, however the East-Atlantic (EA) pattern is known to modulate NAO strength and location. Using observation-driven and modelled data sets, we show that multi-annual variability patterns of European Net Biome Productivity (NBP) are linked to anomalies in heat and water transport controlled by the NAO-EA interplay. Enhanced NBP occurs when NAO and EA are both in negative phase, associated with cool summers with wet soils which enhance photosynthesis. During anti-phase periods, NBP is reduced through distinct impacts of climate anomalies in photosynthesis and respiration. The predominance of anti-phase years in the early 2000s may explain the European-wide reduction of carbon uptake during this period, reported in previous studies. Results show that improving the capability of simulating atmospheric circulation patterns may better constrain regional carbon sink variability in coupled carbon-climate models.
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The North Atlantic Oscillation (NAO) is known to influence precipitation δ18O (δ18Op) through its control on air temperature and on the trajectory of the westerly winds that carry moisture onto Europe during boreal winters. Hence, paleoclimate studies seeking to reconstruct the NAO can exploit the δ18O signal that is commonly preserved in natural archives such as stalagmites, ice cores, tree rings and lake sediments. However, such reconstructions should consider the uncertainties that arise from non-stationarities in the δ18Op-NAO relationship. Here, new insights into the causes of these temporal non-stationarities are presented for the European region using both observations (GNIP database) and the output of an isotope-enabled general circulation model (ECHAM5-wiso). The results show that, although the East Atlantic (EA) pattern is generally uncorrelated to δ18Op during the instrumental period, its polarity affects the δ18Op-NAO relationship. Non-stationarities in this relationship result from spatial shifts of the δ18Op-NAO correlated areas as a consequence of different NAO/EA combinations. These shifts are consistent with those reported previously for NAO-winter climate variables and the resulting non-stationarities mean that δ18O-based NAO reconstructions could be compromised if the balance of positive and negative NAO/EA states differs substantially in a calibration period compared with the period of interest in the past. The same approach has been followed to assess the relationships between δ18Op and both winter total precipitation and winter mean surface air temperature, with similar results. Crucially, this study also identifies regions within Europe where temporal changes in the NAO, air temperature and precipitation can be more robustly reconstructed using δ18O time series from natural archives, irrespective of concomitant changes in the EA.
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Climate data can be used in simulations to estimate the output of wind turbines in locations where meteorological observations are not available. We perform the most comprehensive evaluation of the NCEP CFSR reanalysis model hourly wind speed hindcasts to date, and the first for the UK, by correlating the data against 264 onshore and 12 offshore synoptic weather stations, over a period of 30 years. The correlation of CFSR data to in situ measurements is similar to alternative approaches used in other studies both onshore and offshore. We investigate the impact of the topography, land use and mean wind speed on the onshore locations for the first time. The analysis of these spatial factors shows that CFSR represents the variety of terrain over UK well, and that the worst correlated sites are those at the highest elevations.
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With a rapidly increasing fraction of electricity generation being sourced from wind, extreme wind power generation events such as prolonged periods of low (or high) generation and ramps in generation, are a growing concern for the efficient and secure operation of national power systems. As extreme events occur infrequently, long and reliable meteorological records are required to accurately estimate their characteristics.Recent publications have begun to investigate the use of global meteorological “reanalysis” data sets for power system applications, many of which focus on long-term average statistics such as monthly-mean generation. Here we demonstrate that reanalysis data can also be used to estimate the frequency of relatively short-lived extreme events (including ramping on sub-daily time scales). Verification against 328 surface observation stations across the United Kingdom suggests that near-surface wind variability over spatiotemporal scales greater than around 300 km and 6 h can be faithfully reproduced using reanalysis, with no need for costly dynamical downscaling.A case study is presented in which a state-of-the-art, 33 year reanalysis data set (MERRA, from NASA-GMAO), is used to construct an hourly time series of nationally-aggregated wind power generation in Great Britain (GB), assuming a fixed, modern distribution of wind farms. The resultant generation estimates are highly correlated with recorded data from National Grid in the recent period, both for instantaneous hourly values and for variability over time intervals greater than around 6 h. This 33 year time series is then used to quantify the frequency with which different extreme GB-wide wind power generation events occur, as well as their seasonal and inter-annual variability. Several novel insights into the nature of extreme wind power generation events are described, including (i) that the number of prolonged low or high generation events is well approximated by a Poission-like random process, and (ii) whilst in general there is large seasonal variability, the magnitude of the most extreme ramps is similar in both summer and winter.An up-to-date version of the GB case study data as well as the underlying model are freely available for download from our website: http://www.met.reading.ac.uk/∼energymet/data/Cannon2014/.
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Until recently, long range forecast systems showed only modest levels of skill in predicting surface winter climate around the Atlantic basin and associated fluctuations in the North Atlantic Oscillation at seasonal lead times. Here we use a new forecast system to assess seasonal predictability of winter north Atlantic climate. We demonstrate that key aspects of European and North American winter climate and the surface North Atlantic Oscillation are highly predictable months ahead. We demonstrate high levels of prediction skill in retrospective forecasts of the surface North Atlantic Oscillation, winter storminess, near surface temperature and wind speed; all of which have high value for planning and adaptation to extreme winter conditions. Analysis of forecast ensembles suggests that while useful levels of seasonal forecast skill have now been achieved, key sources of predictability are still only partially represented and there is further untapped predictability.
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Much of the twentieth century multidecadal variability in the relationship between North Atlantic Oscillation (NAO) and winter climate over the North Atlantic–European sector can be linked to the combined effects of the NAO and either the East Atlantic pattern (EA) or the Scandinavian pattern (SCA). Our study documents how different NAO–EA and NAO–SCA combinations influence winter climatic conditions (temperature and precipitation) as a consequence of NAO dipole migrations. Using teleconnectivity maps, we find that the zero-correlated line of the NAO–winter-climate relationship migrates southwards when the EA is in the opposite phase to the NAO, related to a southwestwards migration of the NAO dipole under these conditions. Similarly, a clockwise movement of the NAO–winter-climate correlated areas occurs when the phase of the SCA is opposite to that of the NAO, reflecting a clockwise movement of the NAO dipole under these conditions. Our study provides new insights into the causes of spatial and temporal nonstationarity in the climate–NAO relationships, particularly with respect to winter precipitation. Furthermore, interannual variability in the north–south winter precipitation gradient in the UK appears to reflect the migration of the NAO dipole linked to linear combinations of the NAO and the EA. The study also has important implications for studies of the role of the NAO in modulating the wind energy resource of the UK and Ireland, as well as for the selection of locations for terrestrial proxy archive reconstruction of past states of the NAO. Copyright © 2013 Royal Meteorological Society
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The North Atlantic Oscillation (NAO) is one of the most important modes of variability in the global climate system and is characterized by a meridional dipole in the sea level pressure field, with centers of action near Iceland and the Azores. It has a profound influence on the weather, climate, ecosystems, and economies of Europe, Greenland, eastern North America, and North Africa. It has been proposed that around 1980, there was an eastward secular shift in the NAO's northern center of action that impacted sea ice export through Fram Strait. Independently, it has also been suggested that the location of its southern center of action is tied to the phase of the NAO. Both of these attributes of the NAO have been linked to anthropogenic climate change. Here the authors use both the one-point correlation map technique as well as empirical orthogonal function (EOF) analysis to show that the meridional dipole that is often seen in the sea level pressure field over the North Atlantic is not purely the result of the NAO (as traditionally defined) but rather arises through an interplay among the NAO and two other leading modes of variability in the North Atlantic region: the East Atlantic (EA) and the Scandinavian (SCA) patterns. This interplay has resulted in multidecadal mobility in the two centers of action of the meridional dipole since the late nineteenth century. In particular, an eastward movement of the dipole has occurred during the 1930s to 1950s as well as more recently. This mobility is not seen in the leading EOF of the sea level pressure field in the region.
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The wind power generated during winter months 1999–2003 at several wind farms in the northeastern Iberian Peninsula is investigated through the application of a statistical downscaling. This allows for an improved understanding of the wind power variability and its relationship to the large scale atmospheric circulation. It is found that 97 % of the variability of this non-climatic variable is connected to changes in the atmospheric circulation. The methodological uncertainty associated with multiple configurations of the statistical downscaling method replicates well the observed variability of the wind power, an indication of the robustness of the methodology to changes in the model set up. In addition, the use of the statistical model is extended out of the observational period providing an estimation of the long-term variability of wind power throughout the twentieth century. The extended wind power reconstruction shows large inter-annual and multidecadal variability. Alternative approaches to calibrate the empirical downscaling model using actual wind power observations have also been investigated. They involve the estimation of wind power changes from downscaled wind values and make use of several transfer functions based on the linearity between wind and wind energy. The performance of the latter approaches is similar to the direct downscaling of wind power and may allow wind power production estimations even in the absence of historical wind turbine records. These results can be of great interest for deriving medium/long term impact-oriented energy assessments, especially when wind power observations are missing as well as in the context of climate change scenarios.
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All year long, massive airborne plumes of desert dust from the Sahara and surrounding regions are exported to the North Atlantic Ocean and the Mediterranean Sea. The mass of African dust transported in the atmosphere is large--about one billion tonnes per year--and it has been suggested that the wind-blown dusts have a substantial influence on the regional radiative budget. Here we use daily satellite observations of airborne dusts to obtain an 11-year regional-scale analysis of dust transport out of Africa. The substantial seasonal variability over the Atlantic Ocean and Mediterranean Sea can be explained by the synoptic meteorology. Interannual variations in dust transport are similar over both regions, and are well correlated with the climatic variability defined by the North Atlantic Oscillation. This large-scale climatic control on the dust export is effected through changes in precipitation and atmospheric circulation over the regions of dust mobilization and transport. Such natural variability is so large that it is difficult to resolve any antrophogenic influences on atmospheric dust loads, such as those due to desertification or land-use changes. It seems likely that the North Atlantic Oscillation will also affect the distribution--and radiative influence--of other aerosols.
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The North Sea 10-m wind speed (WS10) climate is compared and related to circulation patterns based on the sea level pressure (SLP) extracted from three reanalysis and one high-resolution model dataset. The mean magnitude and the trends of WS10 depend considerably on the selected reanalysis. The variability of WS10 among the three reanalysis datasets is highly correlated in the recent period (1980-2000) but less so in the past period (1960-1980). The WS10 over the North Sea is well represented by the relatively low reanalysis resolution when compared to the high-resolution WS10 model data partially owing to the high spatial correlation of WS10. Exceptions are observed only at the coastal areas. The dominant mode of WS10 explains coherent variability of WS10 over the North Sea and is related to a SLP pattern similar to the North Atlantic oscillation (NAO). The increase of the magnitude of the dominant WS10 pattern is related to the increase of the magnitude of the NAO-like SLP pattern from 1960s to mid-1990s. The second dominant WS10 pattern—a dipole in WS10 to the north and south of Great Britain—is related to the differences in SLP between Scandinavia and Iceland. The relation between the second WS10 and SLP patterns is more prominent in the recent period. The extreme WS10 in the German Bight is related to the low SLP over Scandinavia. The extreme WS10 is strongly increasing from the early 1980s to the beginning of 1990s, which is not observed in the corresponding SLP time series over Scandinavia.
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ERA-Interim is the latest global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). The ERA-Interim project was conducted in part to prepare for a new atmospheric reanalysis to replace ERA-40, which will extend back to the early part of the twentieth century. This article describes the forecast model, data assimilation method, and input datasets used to produce ERA-Interim, and discusses the performance of the system. Special emphasis is placed on various difficulties encountered in the production of ERA-40, including the representation of the hydrological cycle, the quality of the stratospheric circulation, and the consistency in time of the reanalysed fields. We provide evidence for substantial improvements in each of these aspects. We also identify areas where further work is needed and describe opportunities and objectives for future reanalysis projects at ECMWF.
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Greenland ice-core data have revealed large decadal climate variations over the North Atlantic that can be related to a major source of low-frequency variability, the North Atlantic Oscillation. Over the past decade, the Oscillation has remained in one extreme phase during the winters, contributing significantly to the recent wintertime warmth across Europe and to cold conditions in the northwest Atlantic. An evaluation of the atmospheric moisture budget reveals coherent large-scale changes since 1980 that are linked to recent dry conditions over southern Europe and the Mediterranean, whereas northern Europe and parts of Scandinavia have generally experienced wetter than normal conditions.
Article
The study of the wind power output variability comprises different time scales. Among these, low-frequency variations can substantially modify the performance of a wind power plant during its lifetime. In recent years, other temporal scales such as the short-term variability or the climatological conditions of wind and the corresponding generated power have been investigated in depth. However, the study of longer decadal and multidecadal variations is still in its early stages.In this work, the wind power output long-term variability is analysed for two locations in Spain, during the period 1871–2009. This is attained by computing the annual wind speed probability density functions derived from an ensemble of atmospheric sea level pressure data set through a statistical downscaling based in evolutionary algorithms. Results reveal significant trends and periodicities in multidecadal bands including 13, 25 and 46 years, as well as significant differences among both sites. The impact of the leading large-scale circulation patterns (NAO, EA, SCAND and AMO) on wind power output and its stationarity is analysed. Results on both locations show non-stationary significant and opposite seasonal couplings with these forcings. Finally, the long-term variability of the reconstructed Weibull parameters of the annual wind speed distributions is used to derive a linear model to estimate the annual wind power.
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This paper describes recent variations of the North Atlantic eddy-driven jet stream and analyzes the mean response of the jet to anthropogenic forcing in climate models. Jet stream changes are analyzed both using a direct measure of the near-surface westerly wind maximum and using an EOF-based approach. This allows jet stream changes to be related to the widely used leading patterns of variability: the North Atlantic Oscillation (NAO) and East Atlantic (EA) pattern. Viewed in NAO-EA state space, isolines of jet latitude and speed resemble a distorted polar coordinate system, highlighting the dependence of the jet stream quantities on both spatial patterns. Some differences in the results of the two methods are discussed, but both approaches agree on the general characteristics of the climate models. While there is some agreement between models on a poleward shift of the jet stream in response to anthropogenic forcing, there is still considerable spread between different model projections, especially in winter. Furthermore, the model responses to forcing are often weaker than their biases when compared to a reanalysis. Diagnoses of jet stream changes can be sensitive to the methodologies used, and several aspects of this are also discussed.
Article
An estimation of the monthly wind energy output for the period 1999–2003 at five wind farms in northeastern Spain was evaluated. The methodology involved the calculation of wind speed histograms and the observed average wind power versus wind relation obtained from hourly data. The energy estimation was based on the cumulated contribution of the wind power from each wind speed interval. The impact of the Weibull distribution assumption as a substitute of the actual histogram in the wind energy estimation was evaluated. Results reveal that the use of a Weibull probability distribution has a moderate impact in the energy calculation as the largest estimation errors are, on average, no larger than 10% of the total monthly energy produced. However, the evaluation of the goodness of fit through the χ ² statistics shows that the Weibull assumption is not strictly substantiated for most of the sites. This apparent discrepancy is based on the partial cancellation of the positive and negative departures of the Weibull fitted and the actual wind frequency distributions. Further investigation of the relation between the χ ² and the error contribution exposes a tendency of the Weibull distribution to underestimate (overestimate) the observed histograms in the lower and upper (intermediate) wind speed intervals. This fact, together with the larger wind power weight over the highest winds, results in a systematic total wind energy underestimation. Copyright © 2008 John Wiley & Sons, Ltd.
Article
Contemporaneous correlations between geopotential heights on a given pressure surface at widely separated points on earth, referred to as teleconnections in this paper, are studied in an attempt to identify and document recurrent spatial patterns which might be indicative of standing oscillations in the planetary waves during the Northern Hemisphere winter, with time scales on the order of a month or longer. A review of existing literature on the subject reveals the existence of at least four such patterns: the North Atlantic and North Pacific Oscillations identified by Walker and Bliss (1932). a zonally symmetric seesaw between sea level pressures in polar and temperature latitudes, first noted by Lorenz (1951), and what we will refer to as the Pacific/North American pattern, which has been known to operational long-range forecasters in this country since the 1950's. A data set consisting of NMC monthly mean sea level pressure and 500 mb height analyses for a 15-year period is used as a basis fo...
Article
An outline of the concept of the North Atlantic Oscillation (NAO), along with some of its history is presented. This is followed by a brief presentation of the results and implications of an encouraging new application of the NAO to a regional climate problem-the interannual variation of Moroccan winter-semester precipitation. That precipitation is shown to be inversely related to the concurrent state of the NAO, and the relationship is relatively strong by the standards of recent research into the mechanisms of tropical and subtropical precipitation fluctuations. It is suggested that the NAO is of particular significance for the important issue of the long-range prediction of Moroccan (and probably also Spanish, Portuguese, and Algerian) winter precipitation, and that further research on this subject is warranted. Several specific recommendations in the latter regard are made.
Article
Over recent years there has been an increasing deployment of renewable energy generation technologies, particularly large-scale wind farms. As wind farm deployment increases, it is vital to gain a good understanding of how the energy produced is affected by climate variations, over a wide range of time-scales, from short (hours to weeks) to long (months to decades) periods.By relating wind speed at specific sites in the UK to a large-scale climate pattern (the North Atlantic Oscillation or “NAO”), the power generated by a modelled wind turbine under three different NAO states is calculated. It was found that the wind conditions under these NAO states may yield a difference in the mean wind power output of up to 10%. A simple model is used to demonstrate that forecasts of future NAO states can potentially be used to improve month-ahead statistical forecasts of monthly-mean wind power generation.The results confirm that the NAO has a significant impact on the hourly-, daily- and monthly-mean power output distributions from the turbine with important implications for (a) the use of meteorological data (e.g. their relationship to large-scale climate patterns) in wind farm site assessment and, (b) the utilisation of seasonal-to-decadal climate forecasts to estimate future wind farm power output. This suggests that further research into the links between large-scale climate variability and wind power generation is both necessary and valuable.Highlights► Power output from wind turbines is sensitive to wind speed. ► The affect of large-scale atmospheric circulation (NAO) on UK wind is investigated. ► Slow (monthly) changes in NAO state are shown to affect turbine output by up to 10%. ► Monthly turbine power output forecasts are improved using simple NAO predictions.
Article
Western Europe has experienced a sequence of unusually cold winters culminating in December 2010, which was the coldest December in the United Kingdom for over 100 years. The North Atlantic Oscillation (NAO) is the most important indicator of the climate of the North Atlantic and Western Europe. However, in this article, we argue that the record cold temperatures in December 2010 cannot be explained by appeal to the NAO alone. Rather we show that the consideration of another atmospheric teleconnection pattern, the East Atlantic (EA) pattern, provides for a more robust explanation as to why December 2010 was so cold. Copyright © 2011 Royal Meteorological Society
Article
Much of the atmospheric variability in the North Atlantic sector is associated with variations in the eddy-driven component of the zonal flow. Here we present a simple method to specifically diagnose this component of the flow using the low-level wind field (925–700 hpa ). We focus on the North Atlantic winter season in the ERA-40 reanalysis. Diagnostics of the latitude and speed of the eddy-driven jet stream are compared with conventional diagnostics of the North Atlantic Oscillation (NAO) and the East Atlantic (EA) pattern. This shows that the NAO and the EA both describe combined changes in the latitude and speed of the jet stream. It is therefore necessary, but not always sufficient, to consider both the NAO and the EA in identifying changes in the jet stream.The jet stream analysis suggests that there are three preferred latitudinal positions of the North Atlantic eddy-driven jet stream in winter. This result is in very good agreement with the application of a statistical mixture model to the two-dimensional state space defined by the NAO and the EA. These results are consistent with several other studies which identify four European/Atlantic regimes, comprising three jet stream patterns plus European blocking events. Copyright © 2010 Royal Meteorological Society
Article
Three methods for calculating the parameters of the Weibull wind speed distribution for wind energy analysis are presented: the maximum likelihood method, the proposed modified maximum likelihood method, and the commonly used graphical method. The application of each method is demonstrated using a sample wind speed data set, and a comparison of the accuracy of each method is also performed. The maximum likelihood method is recommended for use with time series wind data, and the modified maximum likelihood method is recommended for use with wind data in frequency distribution format.
Article
An analysis of the frequency of cyclones and surface wind velocity for the Euro-Atlantic sector is performed by means of an objective methodology. Monthly and seasonal trends of cyclones and wind speed magnitude are computed and trends between 1960 and 2000 evaluated. Results reveal a significant frequency decrease (increase) in the western Mediterranean (Greenland and Scandinavia), particularly in December, February, and March. Seasonal and monthly analysis of wind magnitude trends shows similar spatial patterns. We show that these changes in the frequency of low-pressure centers and the associated wind patterns are partially responsible for trends in the significant height of waves. Throughout the extended winter months (October-March), regions with positive (negative) wind magnitude trends, of up to 5 cm/s/year, often correspond to regions of positive (negative) significant wave height trends. The cyclone and wind speed trends computed for January-March are well matched by the corresponding trends in significant wave height, with February being the month with the highest trends (negative south of lat 50 degrees N up to -3 cm/year, and positive up to 5 cm/year just north of Scotland). Trends in European precipitation are assessed using the Climatic Research Unit data set. The results of the assessment emphasize the link with the corresponding tendencies of cyclone frequencies. Finally, it is shown that these changes are associated, to a large extent, with the preferred phases of major large-scale atmospheric circulation modes, particularly with the North Atlantic Oscillation, the eastern Atlantic pattern, and the Scandinavian pattern.
Article
Four weather regimes occurring over the Atlantic area and their preferred precursors and successors are identified. The first pattern exhibits the typical European blocking dipole, the second one represents an enhanced zonal flow, the third one consists of a positive anomaly over Greenland, and the last one is characterized by a ridge over the eastern Atlantic Ocean. The backward and forward memory times of the different regimes are established. Preferred precursor and successor patterns are identified as the maxima of the composite probability densities of the anomalies occurring before the onsets and after the breaks. The preferred transitions between regimes are also examined. The systematic aspect of this study gives rise to multiple applications, especially for case and composite studies on model prediction errors.
Article
Bridging the traditional gap between the spatio-temporal scales of weather and climate is a significant challenge facing the atmospheric community. In particular, progress in both medium-range and seasonal-to-interannual climate prediction relies on our understanding of recurrent weather patterns and the identification of specific causes responsible for their favoured occurrence, persistence or transition. Within this framework, I here present evidence that the main climate intra-seasonal oscillation in the tropics-the Madden-Julian Oscillation (MJO)-controls part of the distribution and sequences of the four daily weather regimes defined over the North Atlantic-European region in winter. North Atlantic Oscillation (NAO) regimes are the most affected, allowing for medium-range predictability of their phase far exceeding the limit of around one week that is usually quoted. The tropical-extratropical lagged relationship is asymmetrical. Positive NAO events mostly respond to a mid-latitude low-frequency wave train initiated by the MJO in the western-central tropical Pacific and propagating eastwards. Precursors for negative NAO events are found in the eastern tropical Pacific-western Atlantic, leading to changes along the North Atlantic storm track. Wave-breaking diagnostics tend to support the MJO preconditioning and the role of transient eddies in setting the phase of the NAO. I present a simple statistical model to quantitatively assess the potential predictability of the daily NAO index or the sign of the NAO regimes when they occur. Forecasts are successful in approximately 70 per cent of the cases based on the knowledge of the previous approximately 12-day MJO phase used as a predictor. This promising skill could be of importance considering the tight link between weather regimes and both mean conditions and the chances of extreme events occurring over Europe. These findings are useful for further stressing the need to better simulate and forecast the tropical coupled ocean-atmosphere dynamics, which is a source of medium-to-long range predictability and is the Achilles' heel of the current seamless prediction suites.
Article
The seasonality and persistence of the major modes of interannual variability in the low-frequency atmospheric circulation were studied using orthogonally rotated principle component analysis (RPCA) of Northern Hemisphere 1-month mean 700 mb heights. The twice-daily data for the 1950-1984 period were used. Winter results are similar to those of other recent RPCA and teleconnection studies. The strongest summer pattern is the North Atlantic Oscillation, which is also the strongest winter pattern; it systematically contracts northward in summer and expands southward in winter, being the only pattern found for every month of the year. The robustness of the RPCA results was examined through consistency with results of other studies and of adjacent month solutions within this study, as well as by replicating the results using 3-month and 10-day means of 700-mb height. It is concluded that the RPCA method provides a physically meaningful and statistically stable product with the simplicity of teleconnection patterns but with superior pattern choice and depiction.
European Wind Atlas. Published for the Commission of European Communities, Directorate-General of Science
  • I Troen
  • E L Petersen
Troen I, Petersen EL, Commission of the European Communities. 1989. European Wind Atlas. Published for the Commission of European Communities, Directorate-General of Science, Research and Development: Brussels, by Risø National Laboratory: Roskilde, Denmark.