Evaluation of the North Atlantic Oscillation as simulated by a coupled climate model

1999 ◽  
Vol 15 (9) ◽  
pp. 685-702 ◽  
Author(s):  
T. J. Osborn ◽  
K. R. Briffa ◽  
S. F. B. Tett ◽  
P. D. Jones ◽  
R. M. Trigo
Keyword(s):  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Climate Model ◽  
Coupled Climate Model ◽  
The North ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

scholarly journals European Climate Extremes and the North Atlantic Oscillation

2008 ◽  
Vol 21 (1) ◽  
pp. 72-83 ◽  
Author(s):  
Adam A. Scaife ◽  
Chris K. Folland ◽  
Lisa V. Alexander ◽  
Anders Moberg ◽  
Jeff R. Knight
Keyword(s):  
North Atlantic Oscillation ◽  
North Atlantic ◽  
General Circulation ◽  
Climate Model ◽  
Circulation Model ◽  
Extreme Weather Events ◽  
The North ◽  
Weather Events ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

Abstract The authors estimate the change in extreme winter weather events over Europe that is due to a long-term change in the North Atlantic Oscillation (NAO) such as that observed between the 1960s and 1990s. Using ensembles of simulations from a general circulation model, large changes in the frequency of 10th percentile temperature and 90th percentile precipitation events over Europe are found from changes in the NAO. In some cases, these changes are comparable to the expected change in the frequency of events due to anthropogenic forcing over the twenty-first century. Although the results presented here do not affect anthropogenic interpretation of global and annual mean changes in observed extremes, they do show that great care is needed to assess changes due to modes of climate variability when interpreting extreme events on regional and seasonal scales. How changes in natural modes of variability, such as the NAO, could radically alter current climate model predictions of changes in extreme weather events on multidecadal time scales is also discussed.

Applying machine learning for drought prediction using a large ensemble of climate simulations

2021 ◽  
Author(s):  
Elizaveta Felsche ◽  
Ralf Ludwig
Keyword(s):  
Machine Learning ◽  
Regional Climate Model ◽  
North Atlantic Oscillation ◽  
North Atlantic ◽  
North Atlantic Oscillation Index ◽  
Climate Model ◽  
Regional Climate ◽  
The North ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

<p>There is strong scientific and social interest to understand the factors leading to extreme events in order to improve the management of risks associated with hazards like droughts. Recent events like the summer 2018 drought in Germany already had severe und unexpected impacts, e.g. forest fires and crop failures; in order to increase preparedness robust prediction tools are  urgently required. In this study, machine learning methods are applied to predict the occurrence of a drought with lead times of one to three months. The approach takes into account a list of thirty atmospheric and soil variables<strong> </strong>as predictor input parameters from a single regional climate model initial condition large ensemble (CRCM5-LE). The data was produced the context of the ClimEx project by Ouranos with the Canadian Regional Climate Model (CRCM5) driven by 50 members of the Canadian Earth System Model (CanESM2) for the Bavarian and Quebec domains.</p><p>Drought occurrence was defined using the Standardized Precipitation Index. The training and test datasets were chosen from the current climatology (1955-2005) for the Munich and Lisbon subdomain within the CRCM5-LE. The best performing machine learning algorithms managed to obtain a correct classification of drought or no drought for a lead time of one month for around 60 % of the events of each class for the both domains. Explainable AI methods like feature importance and shapley values were applied to gain a better understanding of the trained algorithms. Physical variables like the North Atlantic Oscillation Index and air pressure one month before the event proved to be of high importance for the prediction. The study showed that better accuracies can be obtained for the Lisbon domain, due to the stronger influence of the North Atlantic Oscillation Index on Portugal’s climate.</p>

scholarly journals Influence of the North Atlantic oscillation on the atmospheric levels of benzo[a]pyrene over Europe

2021 ◽  
Author(s):  
Pedro Jiménez-Guerrero ◽  
Nuno Ratola
Keyword(s):  
Spatial Pattern ◽  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Transport Model ◽  
Regional Scale ◽  
The South ◽  
Climatic Fluctuations ◽  
The North ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

AbstractThe atmospheric concentration of persistent organic pollutants (and of polycyclic aromatic hydrocarbons, PAHs, in particular) is closely related to climate change and climatic fluctuations, which are likely to influence contaminant’s transport pathways and transfer processes. Predicting how climate variability alters PAHs concentrations in the atmosphere still poses an exceptional challenge. In this sense, the main objective of this contribution is to assess the relationship between the North Atlantic Oscillation (NAO) index and the mean concentration of benzo[a]pyrene (BaP, the most studied PAH congener) in a domain covering Europe, with an emphasis on the effect of regional-scale processes. A numerical simulation for a present climate period of 30 years was performed using a regional chemistry transport model with a 25 km spatial resolution (horizontal), higher than those commonly applied. The results show an important seasonal behaviour, with a remarkable spatial pattern of difference between the north and the south of the domain. In winter, higher BaP ground levels are found during the NAO+ phase for the Mediterranean basin, while the spatial pattern of this feature (higher BaP levels during NAO+ phases) moves northwards in summer. These results show deviations up to and sometimes over 100% in the BaP mean concentrations, but statistically significant signals (p<0.1) of lower changes (20–40% variations in the signal) are found for the north of the domain in winter and for the south in summer.

Polar motion and the North Atlantic Oscillation

1997 ◽  
Vol 42 (11) ◽  
pp. 927-931 ◽  
Author(s):  
Yonghong Zhou ◽  
Dawei Zheng ◽  
Benjamin Fong Chao
Keyword(s):  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Polar Motion ◽  
The North ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

scholarly journals Global drivers effect in multi-annual variability of runoff

2014 ◽  
Vol 62 (3) ◽  
pp. 169-176 ◽  
Author(s):  
Miriam Fendeková ◽  
Pavla Pekárová ◽  
Marián Fendek ◽  
Ján Pekár ◽  
Peter Škoda
Keyword(s):  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Coherence Function ◽  
Climatic Conditions ◽  
Base Flow ◽  
Quasi Biennial Oscillation ◽  
The North ◽  
The North Atlantic ◽  
The North Atlantic Oscillation ◽  
Biennial Oscillation

Abstract Changes in runoff parameters are very important for Slovakia, where stream-flow discharges, being supplied by precipitation and groundwater runoff, are preferentially influenced by climatic conditions. Therefore, teleconnections between runoff parameters, climate parameters and global atmospheric drivers such as North Atlantic Oscillation, Southern Pacific Oscillation, Quasi-biennial oscillation and solar activity were studied in the Nitra River Basin, Slovakia. Research was mostly based on records of 80 years (1931-2010) for discharges and baseflow, and 34 years for groundwater heads. Methods of autocorrelation, spectral analysis, cross-correlation and coherence function were used. Results of auto- correllograms for discharges, groundwater heads and base flow values showed a very distinct 11-year and 21-year periodicity. Spectrogram analysis documented the 11-year, 7.8-year, 3.6-year and 2.4-year periods in the discharge, precipitation and air temperature time series. The same cycles except of 11-years were also identified in the long-term series of the North Atlantic Oscillation and Southern Pacific Oscillation indices. The cycle from approximately 2.3 to 2.4-years is most likely connected with Quasi-biennial oscillation. The close negative correlation between the North Atlantic Oscillation winter index and the hydrological surface and groundwater parameters can be used for their prediction within the same year and also for one year in advance.

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