Relationships between the North Atlantic Oscillation index and temperatures in Europe in global climate models

2012 ◽  
Vol 57 (1) ◽  
pp. 138-153 ◽  
Author(s):  
Romana Beranová ◽  
Jan Kyselý
Keyword(s):  
North Atlantic Oscillation ◽  
North Atlantic ◽  
North Atlantic Oscillation Index ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
The North ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

North Atlantic Oscillation

2017 ◽  
Author(s):  
Edward Hanna ◽  
Thomas E. Cropper
Keyword(s):  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
The Arctic ◽  
Energy Output ◽  
Jet Stream ◽  
The North ◽  
The North Atlantic

Many variations in the weather in the European and North Atlantic regions are linked with changes in the North Atlantic Oscillation (NAO). The NAO is measured using a south-minus-north index of atmospheric surface pressure variation across the North Atlantic and is closely connected with changes in the North Atlantic atmospheric polar jet stream and wider changes in atmospheric circulation. The physical, human, and biological impacts of NAO changes extend well beyond weather and climate, with major economic, social, and environmental effects. The NAO index based on barometric pressure records now extends as far back as 1850, based on recent work. Although there are few significant overall trends in monthly or seasonal NAO (i.e., for the whole record), there are many shorter-term multidecadal variations. A prominent increase in the NAO between the 1960s and 1990s was widely noted in previous work and was thought to be related to human-induced greenhouse gas forcing. However, since then this trend has reversed, with a significant decrease in the summer NAO since the 1990s and a striking increase in variability of the winter—especially December—NAO that has resulted in four of the six highest and two of the five lowest NAO Decembers occurring during 2004–2015 in the 116-year record, with accompanying more variable year-to-year winter weather conditions over the United Kingdom. These NAO changes are related to an increasing trend in the Greenland Blocking Index (GBI; equals high pressure over Greenland) in summer and a significantly more variable GBI in December. Such NAO and related jet stream and blocking changes are not generally present in the current generation of global climate models, although recent process studies offer insights into their possible causes. Several plausible climate forcings and feedbacks, including changes in the sun’s energy output and the Arctic amplification of global warming with accompanying reductions in sea ice, may help explain the recent NAO changes. Recent research also suggests significant skill in being able to make seasonal NAO predictions and therefore long-range weather forecasts for up to several months ahead for northwest Europe. However, global climate models remain unclear on longer-term NAO predictions for the remainder of the 21st century.

scholarly journals Significant Extremal Dependence of a Daily North Atlantic Oscillation Index (NAOI) and Weighted Regionalised Rainfall in a Small Island Using the Extremogram

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 2989
Author(s):  
Luis Angel Espinosa ◽  
Maria Manuela Portela ◽  
Rui Rodrigues
Keyword(s):  
North Atlantic Oscillation ◽  
North Atlantic ◽  
North Atlantic Oscillation Index ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Statistical Dependence ◽  
Small Island ◽  
Extremal Dependence ◽  
Rain Gauges

Extremal dependence or independence may occur among the components of univariate or bivariate random vectors. Assessing which asymptotic regime occurs and also its extent are crucial tasks when such vectors are used as statistical models for risk assessment in the field of Climatology under climate change conditions. Motivated by the poor resolution of current global climate models in North Atlantic Small Islands, the extremal dependence between a North Atlantic Oscillation index (NAOI) and rainfall was considered at multi-year dominance of negative and positive NAOI, i.e., −NAOI and +NAOI dominance subperiods, respectively. The datasets used (from 1948–2017) were daily NAOI, and three daily weighted regionalised rainfall series computed based on factor analysis and the Voronoi polygons method from 40 rain gauges in the small island of Madeira (∼740 km2), Portugal. The extremogram technique was applied for measuring the extremal dependence within the NAOI univariate series. The cross-extremogram determined the dependence between the upper tail of the weighted regionalised rainfalls, and the upper and lower tails of daily NAOI. Throughout the 70-year period, the results suggest systematic evidence of statistical dependence over Madeira between exceptionally −NAOI records and extreme rainfalls, which is stronger in the −NAOI dominance subperiods. The extremal dependence for +NAOI records is only significant in recent years, however, with a still unclear +NAOI dominance.

Rainfall Variability and Trend Analysis of Multiannual Rainfall in Romanian Plain

2017 ◽  
Vol 17 (2) ◽  
pp. 124-144 ◽  
Author(s):  
Zeineddine Nouaceur ◽  
Ovidiu Murărescu ◽  
George Murătoreanu
Keyword(s):  
North Atlantic Oscillation ◽  
Central Europe ◽  
North Atlantic ◽  
El Nino ◽  
Southern Oscillation ◽  
Global Climate ◽  
El Nino Southern Oscillation ◽  
The North ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

AbstractThe IPCC climate models predict, for the Central Europe, are for climate changes, being seen variability of temperature, with a growing trend of 1-2,5° C (with 1° C for alpine zone – Carpathians and 2-2,5° C for plains). Current observations in the Romanian plain are not consistent, with an existence of a multiannual variability of temperature and precipitations depending on cyclonal and anti-ciclonal activity. The research is based on calculation of reduced centered index, also the graphical chronological method in information processing (MGCTI) of „Bertin Matrix” type, to show current trends of the spatio-temporal variability of precipitation in the context of global climate change. These are in line with the movement of air masses in Europe in general, and implicitly in Romania, with particular regard to the southern region of the country where the Romanian Plain. The variability of short-term global climate is generally associated with coupling phases of oceanic and atmospheric phenomena including El Niño Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). While El Niño Southern Oscillation (ENSO) affects climate variability in the world, the North Atlantic Oscillation (NAO) is the climate model dominant in the North Atlantic region. The latter cyclic oscillation whose role is still under debate could explain the variability of rainfall in much of the, central Europe area, and support the hypothesis of a return of the rains marking the end of years of drought in Romanian plain. Faced with such great changes that today affect the central Europe region and given the complexity of spatial and temporal dimensions of the climatic signal, a more thorough research of causes and retroactions would allow for a better understanding of the mechanisms behind this new trend.

scholarly journals Quantifying the rarity of extreme multi-decadal trends: how unusual was the late twentieth century trend in the North Atlantic Oscillation?

2021 ◽  
Author(s):  
R. Eade ◽  
D. B. Stephenson ◽  
A. A. Scaife ◽  
D. M. Smith
Keyword(s):  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Serial Correlation ◽  
Climate Models ◽  
Climate Indices ◽  
Positive Trend ◽  
Climate Trends ◽  
The North ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

AbstractClimate trends over multiple decades are important drivers of regional climate change that need to be considered for climate resilience. Of particular importance are extreme trends that society may not be expecting and is not well adapted to. This study investigates approaches to assess the likelihood of maximum moving window trends in historical records of climate indices by making use of simulations from climate models and stochastic time series models with short- and long-range dependence. These approaches are applied to assess the unusualness of the large positive trend that occurred in the North Atlantic Oscillation (NAO) index between the 1960s to 1990s. By considering stochastic models, we show that the chance of extreme trends is determined by the variance of the trend process, which generally increases when there is more serial correlation in the index series. We find that the Coupled Model Intercomparison Project (CMIP5 + 6) historical simulations have very rarely (around 1 in 200 chance) simulated maximum trends greater than the observed maximum. Consistent with this, the NAO indices simulated by CMIP models were found to resemble white noise, with almost no serial correlation, in contrast to the observed NAO which exhibits year-to-year correlation. Stochastic model best fits to the observed NAO suggest an unlikely chance (around 1 in 20) for there to be maximum 31-year NAO trends as large as the maximum observed since 1860. This suggests that current climate models do not fully represent important aspects of the mechanism for low frequency variability of the NAO.

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