scholarly journals Impact of Eurasian autumn snow on the winter North Atlantic Oscillation in seasonal forecasts of the 20<sup>th</sup> century

2021 ◽  
Author(s):  
Martin Wegmann ◽  
Yvan Orsolini ◽  
Antje Weisheimer ◽  
Bart van den Hurk ◽  
Gerrit Lohmann

Abstract. As the leading climate mode of wintertime climate variability over Europe, the North Atlantic Oscillation (NAO) has been extensively studied over the last decades. Recently, studies highlighted the state of the Eurasian cryosphere as a possible predictor for the wintertime NAO. However, missing correlation between snow cover and wintertime NAO in climate model experiments and strong non-stationarity of this link in reanalysis data is questioning the causality of this relationship. Here we use the large ensemble of Atmospheric Seasonal Forecasts of the 20th Century (ASF-20C) with the European Centre for Medium-Range Weather Forecasts model, focusing on the winter season. Besides the main 110-year ensemble of 51 members, we investigate a second, perturbed ensemble of 21 members where initial (November) land conditions over the Northern Hemisphere are swapped from neighboring years. The Eurasian snow/NAO linkage is examined in terms of a longitudinal snow depth dipole across Eurasia. Subsampling the perturbed forecast ensemble and contrasting members with high and low initial snow dipole conditions, we found that their composite difference indicates more negative NAO states in the following winter (DJF) after positive west to east snow cover gradients at the beginning of November. Surface and atmospheric forecast anomalies through the troposphere and stratosphere associated with the anomalous positive snow dipole consist of colder early winter surface temperatures over Eastern Eurasia, an enhanced Ural ridge and increased vertical energy fluxes into the stratosphere, with a subsequent negative NAO-like signature in the troposphere. We thus confirm the existence of a causal connection between autumn snow patterns and subsequent winter circulation in the ASF-20C forecasting system.

2021 ◽  
Vol 2 (4) ◽  
pp. 1245-1261
Author(s):  
Martin Wegmann ◽  
Yvan Orsolini ◽  
Antje Weisheimer ◽  
Bart van den Hurk ◽  
Gerrit Lohmann

Abstract. As the leading climate mode of wintertime climate variability over Europe, the North Atlantic Oscillation (NAO) has been extensively studied over the last decades. Recently, studies highlighted the state of the Eurasian cryosphere as a possible predictor for the wintertime NAO. However, missing correlation between snow cover and wintertime NAO in climate model experiments and strong non-stationarity of this link in reanalysis data are questioning the causality of this relationship. Here we use the large ensemble of Atmospheric Seasonal Forecasts of the 20th Century (ASF-20C) with the European Centre for Medium-Range Weather Forecasts model, focusing on the winter season. Besides the main 110-year ensemble of 51 members, we investigate a second, perturbed ensemble of 21 members where initial (November) land conditions over the Northern Hemisphere are swapped from neighboring years. The Eurasian snow–NAO linkage is examined in terms of a longitudinal snow depth dipole across Eurasia. Subsampling the perturbed forecast ensemble and contrasting members with high and low initial snow dipole conditions, we found that their composite difference indicates more negative NAO states in the following winter (DJF) after positive west-to-east snow depth gradients at the beginning of November. Surface and atmospheric forecast anomalies through the troposphere and stratosphere associated with the anomalous positive snow dipole consist of colder early winter surface temperatures over eastern Eurasia, an enhanced Ural ridge and increased vertical energy fluxes into the stratosphere, with a subsequent negative NAO-like signature in the troposphere. We thus confirm the existence of a causal connection between autumn snow patterns and subsequent winter circulation in the ASF-20C forecasting system.


2016 ◽  
Vol 69 (3) ◽  
pp. 229-238 ◽  
Author(s):  
A Marchane ◽  
L Jarlan ◽  
A Boudhar ◽  
Y Tramblay ◽  
L Hanich

2008 ◽  
Vol 21 (1) ◽  
pp. 72-83 ◽  
Author(s):  
Adam A. Scaife ◽  
Chris K. Folland ◽  
Lisa V. Alexander ◽  
Anders Moberg ◽  
Jeff R. Knight

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.


2015 ◽  
Vol 15 (9) ◽  
pp. 2069-2077 ◽  
Author(s):  
D. Burić ◽  
J. Luković ◽  
B. Bajat ◽  
M. Kilibarda ◽  
N. Živković

Abstract. More intense rainfall may cause a range of negative impacts upon society and the environment. In this study we analysed trends in extreme ETCCDI (Expert Team on Climate Change Detection and Indices) rainfall indices in Montenegro for the period between 1951 and 2010. Montenegro has been poorly studied in terms of rainfall extremes, yet it contains the wettest Mediterranean region known as Krivošije. Several indices of precipitation extremes were assessed including the number of dry days and rainfall totals in order to identify trends and possible changes. A spatial pattern relationship between extreme rainfall indices and the North Atlantic Oscillation has also been examined. The results generally suggest that the number of days with precipitation decreased while rainfall intensity increased, particularly in south-western parts of the country. A slight tendency towards intense rainfall events is suggested. The examined rainfall indices and North Atlantic Oscillation over Montenegro seemed to be directly linked to changes in one of the major large-scale circulation modes such as the NAO pattern that is particularly evident during the winter season.


2011 ◽  
Vol 42 (1) ◽  
pp. 30-39 ◽  
Author(s):  
Dariusz Wrzesiński ◽  
Rafał Paluszkiewicz

The article presents regional differences in the impact that the North Atlantic Oscillation (NAO) exerts on the flow of European rivers. The impact is determined by temporal variations in the strength of relations expressed by coefficients of correlation between monthly or seasonal NAO indices and discharges recorded at 510 river profiles. The results of the correlation analysis were arranged using Ward’s method of hierarchical grouping. The classification of river profiles thus obtained made it possible to distinguish seven regions differing in the nature of the dependence between streamflow and the intensity of the NAO. The most statistically significant positive correlations are displayed by the rivers of Fennoscandia, Denmark and the northwest part of the British Isles in the winter period, while the most significant negative correlations (also in winter) are recorded for streams of the Mediterranean Basin, western France and the southeast of England. In the southeast part of the Baltic Sea drainage basin, significant positive correlations of streamflow with the NAO indices can be observed in the winter season and negative correlations are observed in spring.


2009 ◽  
Vol 22 (2) ◽  
pp. 364-380 ◽  
Author(s):  
Hai Lin ◽  
Gilbert Brunet ◽  
Jacques Derome

Abstract Based on the bivariate Madden–Julian oscillation (MJO) index defined by Wheeler and Hendon and 25 yr (1979–2004) of pentad data, the association between the North Atlantic Oscillation (NAO) and the MJO on the intraseasonal time scale during the Northern Hemisphere winter season is analyzed. Time-lagged composites and probability analysis of the NAO index for different phases of the MJO reveal a statistically significant two-way connection between the NAO and the tropical convection of the MJO. A significant increase of the NAO amplitude happens about 5–15 days after the MJO-related convection anomaly reaches the tropical Indian Ocean and western Pacific region. The development of the NAO is associated with a Rossby wave train in the upstream Pacific and North American region. In the Atlantic and African sector, there is an extratropical influence on the tropical intraseasonal variability. Certain phases of the MJO are preceded by the occurrence of strong NAOs. A significant change of upper zonal wind in the tropical Atlantic is caused by a modulated transient westerly momentum flux convergence associated with the NAO.


2021 ◽  
Vol 8 (1) ◽  
pp. 45
Author(s):  
Graciela González ◽  
Amílcar Calzada ◽  
Alejandro Rodríguez

There have been several advances in understanding the North Atlantic Oscillation (NAO), but there are still uncertainties regarding its level of influence on the tropical climate. That is why this work determines the influence of the NAO on the main hydrometeorological events that affected Cuba in the 1999–2016 period. To comply with this, a regression analysis is carried out in the CurveExpert software where the combined influence of the NAO and El Niño-Southern Oscillation on hydrometeorological events is also examined. It was found that the NAO exerts a greater influence on Cuba when it is in its negative phase during the winter season.


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

2006 ◽  
Vol 19 (6) ◽  
pp. 1032-1041 ◽  
Author(s):  
Martin P. King ◽  
Fred Kucharski

Abstract The low-frequency covariabilities of tropical sea surface temperature (SST) and the North Atlantic Oscillation (NAO) during twentieth-century winters are investigated by maximum covariance analysis (MCA) using reanalysis data. It was found that the positive NAO phase is positively correlated to an increase in tropical SST, especially during the recent decades. The western tropical Pacific SST displays high correlation with the NAO throughout the whole of the twentieth century. For this ocean region, the MCA homogeneous map has a SST spatial pattern with meridional gradients. It was also found that a cooling of tropical Atlantic SST is correlated with positive NAO. The influence of the tropical Atlantic SST on the NAO is strongest during the pre-1960s period.


2021 ◽  
Author(s):  
Elizaveta Felsche ◽  
Ralf Ludwig

&lt;p&gt;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 &amp;#160;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&lt;strong&gt; &lt;/strong&gt;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.&lt;/p&gt;&lt;p&gt;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&amp;#8217;s climate.&lt;/p&gt;


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