scholarly journals Interannual variability of winter precipitation in the European Alps: relations with the North Atlantic Oscillation

2008 ◽  
Vol 5 (4) ◽  
pp. 2045-2065 ◽  
Author(s):  
E. Bartolini ◽  
P. Claps ◽  
P. D'Odorico

Abstract. The European Alps rely on winter precipitation for various needs in terms of hydropower and other water uses. Major European rivers originate from the Alps and rely on winter precipitation and the consequent spring snow melt for their summer base flows. Understanding the fluctuations in winter rainfall in this region is crucially important to the study of changes in hydrologic regime in streams and rivers, as well as to the management of their water resources. Despite the recognized relevance of winter precipitation to the water resources of the Alps and surrounding regions, the magnitude and mechanistic explanation of interannual precipitation variability in the Alpine region remain unclear and poorly investigated. Here we use gridded precipitation data from the CRU TS 1.2 to study the interannual variability of winter alpine precipitation. We found that the Alps are the region with the highest interannual variability in winter precipitation in Europe. This variability cannot be completely explained by large scale climate patterns such as the AO, NAO or the EA-WR, even though regions below and above the Alps demonstrate connections with these patterns. Significant trends were detected only in small areas within this region, and were of opposite sign between the eastern and western part of the Alps.

2009 ◽  
Vol 13 (1) ◽  
pp. 17-25 ◽  
Author(s):  
E. Bartolini ◽  
P. Claps ◽  
P. D'Odorico

Abstract. The European Alps rely on winter precipitation for various needs in terms of hydropower and other water uses. Major European rivers originate from the Alps and depend on winter precipitation and the consequent spring snow melt for their summer base flows. Understanding the fluctuations in winter rainfall in this region is crucially important to the study of changes in hydrologic regime in river basins, as well as to the management of their water resources. Despite the recognized relevance of winter precipitation to the water resources of the Alps and surrounding regions, the magnitude and mechanistic explanation of interannual precipitation variability in the Alpine region remains unclear and poorly investigated. Here we use gridded precipitation data from the CRU TS 1.2 to study the interannual variability of winter alpine precipitation. We found that the Alps are the region with the highest interannual variability in winter precipitation in Europe. This variability cannot be explained by large scale climate patterns such as the Arctic Oscillation (AO), North Atlantic Oscillation (NAO) or the East Atlantic/West Russia (EA/WR), even though regions below and above the Alps demonstrate connections with these patterns. Significant trends were detected only in small regions located in the Eastern part of the Alps.


2007 ◽  
Vol 135 (10) ◽  
pp. 3587-3598 ◽  
Author(s):  
William M. Frank ◽  
George S. Young

Abstract This paper examines the interannual variability of tropical cyclones in each of the earth’s cyclone basins using data from 1985 to 2003. The data are first analyzed using a Monte Carlo technique to investigate the long-standing myth that the global number of tropical cyclones is less variable than would be expected from examination of the variability in each basin. This belief is found to be false. Variations in the global number of all tropical cyclones are indistinguishable from those that would be expected if each basin was examined independently of the others. Furthermore, the global number of the most intense storms (Saffir–Simpson categories 4–5) is actually more variable than would be expected because of an observed tendency for storm activity to be correlated between basins, and this raises important questions as to how and why these correlations arise. Interbasin correlations and factor analysis of patterns of tropical cyclone activity reveal that there are several significant modes of variability. The largest three factors together explain about 70% of the variance, and each of these factors shows significant correlation with ENSO, the North Atlantic Oscillation (NAO), or both, with ENSO producing the largest effects. The results suggest that patterns of tropical cyclone variability are strongly affected by large-scale modes of interannual variability. The temporal and spatial variations in storm activity are quite different for weaker tropical cyclones (tropical storm through category 2 strength) than for stronger storms (categories 3–5). The stronger storms tend to show stronger interbasin correlations and stronger relationships to ENSO and the NAO than do the weaker storms. This suggests that the factors that control tropical cyclone formation differ in important ways from those that ultimately determine storm intensity.


Author(s):  
Minhua Ling ◽  
Hongbao Han ◽  
Xingling Wei ◽  
Cuimei Lv

Abstract The Huang-Huai-Hai Plain is an important commercial grain production base in China. Understanding the temporal and spatial variations in precipitation can help prevent drought and flood disasters and ensure food security. Based on the precipitation data for the Huang-Huai-Hai Plain from 1960 to 2019, this study analysed the spatiotemporal distribution of total precipitation at different time scales using the Mann–Kendall test, the wavelet analysis, the empirical orthogonal function (EOF), and the centre-of-gravity model. The results were as follows: (1) The winter precipitation showed a significant upward trend on the Huang-Huai-Hai Plain, while other seasonal trends were not significant. (2) The precipitation on the Huang-Huai-Hai Plain shows a zonal decreasing distribution from southeast to northwest. (3) The application of the EOF method revealed the temporal and spatial distribution characteristics of the precipitation field. The cumulative variance contribution rate of the first two eigenvectors reached 51.5%, revealing two typical distribution fields, namely a ‘global pattern’ and a ‘north-south pattern’. The ‘global pattern’ is the decisive mode, indicating that precipitation on the Huang-Huai-Hai Plain is affected by large-scale weather systems. (4) The annual precipitation barycentres on the Huang-Huai-Hai Plain were located in Jining city and Taian city, Shandong Province, and the spatial distribution pattern was north-south. The annual precipitation barycentres tended to move southwest, but the trend was not obvious. The annual precipitation barycentre is expected to continue to shift to the north in 2020.


2021 ◽  
Author(s):  
Elena Vyshkvarkova ◽  
Olga Sukhonos

Abstract 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.


2018 ◽  
Vol 31 (6) ◽  
pp. 2511-2532 ◽  
Author(s):  
Clio Michel ◽  
Annick Terpstra ◽  
Thomas Spengler

Polar mesoscale cyclones (PMCs) are automatically detected and tracked over the Nordic seas using the Melbourne University algorithm applied to ERA-Interim. The novelty of this study lies in the length of the dataset (1979–2014), using PMC tracks to infer relationships to large-scale flow patterns, and elucidating the sensitivity to different selection criteria when defining PMCs and polar lows and their genesis environments. The angle between the ambient mean and thermal wind is used to distinguish two different PMC genesis environments. The forward shear environment (thermal and mean wind have the same direction) features typical baroclinic conditions with a temperature gradient at the surface and a strong jet stream at the tropopause. The reverse shear environment (thermal and mean wind have opposite directions) features an occluded cyclone with a barotropic structure throughout the entire troposphere and a low-level jet. In contrast to previous studies, PMC occurrence features neither a significant trend nor a significant link with the North Atlantic Oscillation and the Scandinavian blocking (SB), though the SB negative pattern seems to promote reverse shear PMC genesis. The sea ice extent in the Nordic seas is not associated with overall changes in PMC occurrence but influences the genesis location. Selected cold air outbreak indices and the temperature difference between the sea surface and 500 hPa (SST − T500) show no robust link with PMC occurrence, but the characteristics of forward shear PMCs and their synoptic environments are sensitive to the choice of the SST − T500 threshold.


2019 ◽  
Vol 58 (4) ◽  
pp. 645-661 ◽  
Author(s):  
Vahid Rahimpour Golroudbary ◽  
Yijian Zeng ◽  
Chris M. Mannaerts ◽  
Zhongbo Su

AbstractKnowledge of the response of extreme precipitation to urbanization is essential to ensure societal preparedness for the extreme events caused by climate change. To quantify this response, this study scales extreme precipitation according to temperature using the statistical quantile regression and binning methods for 231 rain gauges during the period of 1985–2014. The positive 3%–7% scaling rates were found at most stations. The nonstationary return levels of extreme precipitation are investigated using monthly blocks of the maximum daily precipitation, considering the dependency of precipitation on the dewpoint, atmospheric air temperatures, and the North Atlantic Oscillation (NAO) index. Consideration of Coordination of Information on the Environment (CORINE) land-cover types upwind of the stations in different directions classifies stations as urban and nonurban. The return levels for the maximum daily precipitation are greater over urban stations than those over nonurban stations especially after the spring months. This discrepancy was found by 5%–7% larger values in August for all of the classified station types. Analysis of the intensity–duration–frequency curves for urban and nonurban precipitation in August reveals that the assumption of stationarity leads to the underestimation of precipitation extremes due to the sensitivity of extreme precipitation to the nonstationary condition. The study concludes that nonstationary models should be used to estimate the return levels of extreme precipitation by considering the probable covariates such as the dewpoint and atmospheric air temperatures. In addition to the external forces, such as large-scale weather modes, circulation types, and temperature changes that drive extreme precipitation, urbanization could impact extreme precipitation in the Netherlands, particularly for short-duration events.


2016 ◽  
Author(s):  
Luca Pozzoli ◽  
Srdan Dobricic ◽  
Simone Russo ◽  
Elisabetta Vignati

Abstract. Winter warming and sea ice retreat observed in the Arctic in the last decades determine changes of large scale atmospheric circulation pattern that may impact as well the transport of black carbon (BC) to the Arctic and its deposition on the sea ice, with possible feedbacks on the regional and global climate forcing. In this study we developed and applied a new statistical algorithm, based on the Maximum Likelihood Estimate approach, to determine how the changes of three large scale weather patterns (the North Atlantic Oscillation, the Scandinavian Blocking, and the El Nino-Southern Oscillation), associated with winter increasing temperatures and sea ice retreat in the Arctic, impact the transport of BC to the Arctic and its deposition. We found that the three atmospheric patterns together determine a decreasing winter deposition trend of BC between 1980 and 2015 in the Eastern Arctic while they increase BC deposition in the Western Arctic. The increasing trend is mainly due to the more frequent occurrences of stable high pressure systems (atmospheric blocking) near Scandinavia favouring the transport in the lower troposphere of BC from Europe and North Atlantic directly into to the Arctic. The North Atlantic Oscillation has a smaller impact on BC deposition in the Arctic, but determines an increasing BC atmospheric load over the entire Arctic Ocean with increasing BC concentrations in the upper troposphere. The El Nino-Southern Oscillation does not influence significantly the transport and deposition of BC to the Arctic. The results show that changes in atmospheric circulation due to polar atmospheric warming and reduced winter sea ice significantly impacted BC transport and deposition. The anthropogenic emission reductions applied in the last decades were, therefore, crucial to counterbalance the most likely trend of increasing BC pollution in the Arctic.


2020 ◽  
Vol 59 (2) ◽  
pp. 317-332
Author(s):  
Nicky Stringer ◽  
Jeff Knight ◽  
Hazel Thornton

AbstractRecent advances in the skill of seasonal forecasts in the extratropics during winter mean they could offer improvements to seasonal hydrological forecasts. However, the signal-to-noise paradox, whereby the variability in the ensemble mean signal is lower than would be expected given its correlation skill, prevents their use to force hydrological models directly. We describe a postprocessing method to adjust for this problem, increasing the size of the predicted signal in the large-scale circulation. This reduces the ratio of predictable components in the North Atlantic Oscillation (NAO) from 3 to 1. We then derive a large ensemble of daily sequences of spatially gridded rainfall that are consistent with the seasonal mean NAO prediction by selecting historical observations conditioned on the adjusted NAO forecasts. Over northern and southwestern Europe, where the NAO is strongly correlated with winter mean rainfall, the variability of the predicted signal in the adjusted rainfall forecasts is consistent with the correlation skill (they have a ratio of predictable components of ~1) and are as skillful as the unadjusted forecasts. The adjusted forecasts show larger predicted deviations from climatology and can be used to better assess the risk of extreme seasonal mean precipitation as well as to force hydrological models.


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