Low-frequency atmospheric variability patterns and synoptic types linked to large floods in the lower Ebro River basin

2022 ◽  
pp. 1-47
Keyword(s):  
Sea Level ◽  
Multivariable Analysis ◽  
Low Frequency ◽  
Atmospheric Variability ◽  
Sea Level Pressure ◽  
Ebro River ◽  
Level Pressure ◽  
Instrumental Period ◽  
Major Floods ◽  
Future Outcomes

Abstract This study analyzes the atmospheric variability that caused the largest floods affecting the town of Tortosa in the mouth of the Ebro River (northeast Iberian Peninsula). The Tortosa flood database and flood marks in the nearby town of Xerta are used to define the more relevant flooding episodes (discharges > 2900 m3s−1) of the 1600-2005 period. We explore the atmospheric variability based on low-frequency patterns and synoptic types applying a multivariable analysis to grids at sea-level pressure and geopotential at 500 hPa provided by the 20th Century V3 Reanalysis Project for the instrumental period (since 1836). Output from the Last Millennium Ensemble Project was used to analyze the sea-level pressure over the pre-instrumental period (before 1836). Our analysis includes 33 flood episodes. Four synoptic types are related to floods in Tortosa since 1836, characterized by low-pressure systems that interact with the Mediterranean warm air-mass and promote the atmosphere destabilization. Flooding in Tortosa is related to relative high values of solar activity, positive Northern Hemisphere temperature anomalies and NAO in positive phase. This indicates that the major floods are related to zonal atmospheric circulations (west to east cyclone transfer). During winter, the main impact of the floods is located at the western part of the basin, while the Pyrenean sub-basins are affected during autumn. The major finding is that similar flood behavior is detected since 1600, improving our understanding of past climates, enhancing the knowledge base for some aspects and impacts of climate change and reducing uncertainty about future outcomes.

scholarly journals Changes in atmospheric variability in a glacial climate and the impacts on proxy data: a model intercomparison

2009 ◽  
Vol 5 (3) ◽  
pp. 489-502 ◽  
Author(s):  
F. S. R. Pausata ◽  
C. Li ◽  
J. J. Wettstein ◽  
K. H. Nisancioglu ◽  
D. S. Battisti
Keyword(s):  
Sea Level ◽  
North Atlantic ◽  
Climate Models ◽  
Atmospheric Variability ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
The North ◽  
Surface Climate ◽  
Leading Mode ◽  
The North Atlantic Oscillation

Abstract. Using four different climate models, we investigate sea level pressure variability in the extratropical North Atlantic in the preindustrial climate (1750 AD) and at the Last Glacial Maximum (LGM, 21 kyrs before present) in order to understand how changes in atmospheric circulation can affect signals recorded in climate proxies. In general, the models exhibit a significant reduction in interannual variance of sea level pressure at the LGM compared to pre-industrial simulations and this reduction is concentrated in winter. For the preindustrial climate, all models feature a similar leading mode of sea level pressure variability that resembles the leading mode of variability in the instrumental record: the North Atlantic Oscillation (NAO). In contrast, the leading mode of sea level pressure variability at the LGM is model dependent, but in each model different from that in the preindustrial climate. In each model, the leading (NAO-like) mode of variability explains a smaller fraction of the variance and also less absolute variance at the LGM than in the preindustrial climate. The models show that the relationship between atmospheric variability and surface climate (temperature and precipitation) variability change in different climates. Results are model-specific, but indicate that proxy signals at the LGM may be misinterpreted if changes in the spatial pattern and seasonality of surface climate variability are not taken into account.

scholarly journals Reconstruction of high resolution atmospheric fields for Northern Europe using analog-upscaling

2012 ◽  
Vol 8 (5) ◽  
pp. 1681-1703 ◽  
Author(s):  
F. Schenk ◽  
E. Zorita
Keyword(s):  
High Resolution ◽  
Sea Level ◽  
Climate Model ◽  
Regional Climate ◽  
Low Frequency ◽  
Climate Simulation ◽  
Northern Europe ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Realistic Situation

Abstract. The analog method (AM) has found application to reconstruct gridded climate fields from the information provided by proxy data and climate model simulations. Here, we test the skill of different setups of the AM, in a controlled but realistic situation, by analysing several statistical properties of reconstructed daily high-resolution atmospheric fields for Northern Europe for a 50-yr period. In this application, station observations of sea-level pressure and air temperature are combined with atmospheric fields from a 50-yr high-resolution regional climate simulation. This reconstruction aims at providing homogeneous and physically consistent atmospheric fields with daily resolution suitable to drive high resolution ocean and ecosystem models. Different settings of the AM are evaluated in this study for the period 1958–2007 to estimate the robustness of the reconstruction and its ability to replicate high and low-frequency variability, realistic probability distributions and extremes of different meteorological variables. It is shown that the AM can realistically reconstruct variables with a strong physical link to daily sea-level pressure on both a daily and monthly scale. However, to reconstruct low-frequency decadal and longer temperature variations, additional monthly mean station temperature as predictor is required. Our results suggest that the AM is a suitable upscaling tool to predict daily fields taken from regional climate simulations based on sparse historical station data.

scholarly journals Interannual to decadal variability within and across the major Eastern Boundary Upwelling Systems

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Giulia Bonino ◽  
Emanuele Di Lorenzo ◽  
Simona Masina ◽  
Doroteaciro Iovino
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Sea Level ◽  
Low Frequency ◽  
Global Ocean ◽  
Thermocline Depth ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Eastern Boundary ◽  
Low Frequency Variability

AbstractClimate variability and climate change in Eastern Boundary Upwelling Systems (EBUS) affect global marine ecosystems services. We use passive tracers in a global ocean model hindcast at eddy-permitting resolution to diagnose EBUS low-frequency variability over 1958–2015 period. The results highlight the uniqueness of each EBUS in terms of drivers and climate variability. The wind forcing and the thermocline depth, which are potentially competitive or complementary upwelling drivers under climate change, control EBUS low-frequency variability with different contributions. Moreover, Atlantic and Pacific upwelling systems are independent. In the Pacific, the only coherent variability between California and Humboldt Systems is associated with El Niño Southern Oscillation. The remaining low-frequency variance is partially explained by the North and South Pacific expressions of the Meridional Modes. In the Atlantic, coherent variability between Canary and Benguela Systems is associated with upwelling trends, which are not dynamically linked and represent different processes. In the Canary, a negative upwelling trend is connected to the Atlantic Multi-decadal Oscillation, while in the Benguela, a positive upwelling trend is forced by a global sea level pressure trend, which is consistent with the climate response to anthropogenic forcing. The residual variability is forced by localized offshore high sea level pressure variability.

scholarly journals Effect of Synoptic Systems on the Variability of the North Atlantic Oscillation

2005 ◽  
Vol 133 (10) ◽  
pp. 2894-2904 ◽  
Author(s):  
Ulrike Löptien ◽  
Eberhard Ruprecht
Keyword(s):  
North Atlantic Oscillation ◽  
Sea Level ◽  
North Atlantic ◽  
Low Frequency ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
The North ◽  
Low Frequency Variability ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

Abstract The North Atlantic Oscillation (NAO) represents the dominant mode of atmospheric variability in the North Atlantic region. In the present study, the role of the synoptic systems (cyclones and anticyclones) in generating the NAO pattern is investigated. To study the intermonthly variations of the NAO, NCEP–NCAR reanalysis data are used, and for the interdecadal variations the results of a 300-yr control integration under present-day conditions of the coupled model ECHAM4/OPYC3 are analyzed. A filtering method is developed for the sea level pressure anomalies. Application of this method to each grid point yields the low-frequency variability in the sea level pressure field that is due to the synoptic systems. The low-frequency variability of the filtered and the original data are in high agreement. This indicates that the low-frequency pressure variability, and with it the variability of the NAO, is essentially caused by the distribution of the synoptic systems. The idea that the distribution of the synoptic systems is the cause of the variation of the NAO is confirmed by high correlation between the latitudinal position of the polar front over the North Atlantic and the NAO index. Since most of the low-frequency variability in sea level pressure can be explained through the distribution of the synoptic systems, the NAO seems to be a reflection of the distribution of the synoptic systems, rather than the source for variations in the cyclone tracks.

scholarly journals Varied Expressions of the Hemispheric Circulation Observed in Association with Contrasting Polarities of Prescribed Patterns of Variability*

2004 ◽  
Vol 17 (21) ◽  
pp. 4245-4253 ◽  
Author(s):  
R. Quadrelli ◽  
J. M. Wallace
Keyword(s):  
Sea Level ◽  
Intraseasonal Variability ◽  
Low Frequency ◽  
Nonlinear Behavior ◽  
Zonal Flow ◽  
Gulf Of Alaska ◽  
Eastern United States ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Teleconnection Patterns

Abstract The low-frequency (>5 day period) variability observed within four different subsets of the climatology (H1, L1, H2, and L2) as defined by the high and low index polarities of the two leading principal components (PCs) of the sea level pressure field is compared, with emphasis on distinctive flow configurations and teleconnection patterns. The analysis is based on wintertime 500-hPa height, sea level pressure, and 1000–500-hPa thickness fields derived from the NCEP–NCAR reanalyses for the period of record, 1958–99. “Spaghetti diagrams” display specified contours for ensembles of individual 10-day mean charts extracted from the four different subsets of the climatology. In L1, 10-day mean maps (weak zonal flow at latitudes ∼55°N) exhibit larger undulations in the barotropic component of the flow than those in H1, implying larger particle displacements and deeper penetration of Arctic air masses, particularly into Europe and the eastern United States. Maps in H2 and L2, separated in accordance with the Pacific–North American (PNA)-like second mode, exhibit quite different kinds of planetary wave patterns. The L2 subset (characterized by a retracted Pacific jet) exhibits greater variability over the Gulf of Alaska and over northern Europe. Cold air outbreaks in Europe occur more frequently in L1 than H1, and over western North America, they occur more frequently in L2 than H2. The cold anomalies associated with low polarities of both PCs are observed more frequently than expected based on linear correlation; within the individual subsets of the climatology there are suggestions of multiple circulation regimes; teleconnection patterns for the subsets of the climatology are also discernibly different. These results constitute evidence of nonnormal or nonlinear behavior of 5- and 10-day mean fields and provide indications of how the intraseasonal variability depends on the mean state of the flow in which it is embedded.

Reconstructing Sea Level Pressure Variability via a Feature Tracking Approach

2015 ◽  
Vol 72 (1) ◽  
pp. 487-506 ◽  
Author(s):  
Sergey Kravtsov ◽  
I. Rudeva ◽  
Sergey K. Gulev
Keyword(s):  
Sea Level ◽  
Large Scale ◽  
Large Fraction ◽  
Storm Track ◽  
Low Frequency ◽  
Time Variability ◽  
Reconstruction Technique ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Wide Range

Abstract The aim of this paper is to quantify the contribution of synoptic transients to the full spectrum of space–time variability of sea level pressure (SLP) in middle latitudes. In previous work by the authors it was shown that tracking cyclones and anticyclones in an idealized atmospheric model allows one to reconstruct a surprisingly large fraction of the model’s variability, including not only synoptic components, but also its large-scale low-frequency component. Motivated by this result, the authors performed tracking of cyclones and anticyclones and estimated cyclone and anticyclone size and geometry characteristics in the observed SLP field using the 1948–2008 NCEP–NCAR reanalysis dataset. The reconstructed synoptic field was then produced via superimposing radially symmetrized eddies moving along their actual observed trajectories. It was found that, similar to earlier results for an idealized model, the synoptic reconstruction so obtained accounts for a major fraction of the full observed SLP variability across a wide range of time scales, from synoptic to those associated with the low-frequency variability (LFV). The synoptic reconstruction technique developed in this study helps elucidate connections between the synoptic eddies and LFV defined via more traditional spatiotemporal filtering. In particular, we found that the dominant variations in the position of the zonal-mean midlatitude jet are synonymous with random ultralow-frequency redistributions of cyclone and anticyclone trajectories and, hence, is inseparable of that in the storm-track statistics.

scholarly journals Multi-decadal variability in seasonal mean sea level along the North Sea coast

Ocean Science ◽  
2018 ◽  
Vol 14 (6) ◽  
pp. 1491-1501 ◽  
Author(s):  
Thomas Frederikse ◽  
Theo Gerkema
Keyword(s):  
Sea Level ◽  
North Sea ◽  
Large Scale ◽  
Decadal Variability ◽  
Low Frequency ◽  
Sea Level Pressure ◽  
Mean Sea Level ◽  
Level Pressure ◽  
The North ◽  
The North Sea

Abstract. Seasonal deviations from annual-mean sea level in the North Sea region show a large low-frequency component with substantial variability at decadal and multi-decadal timescales. In this study, we quantify low-frequency variability in seasonal deviations from annual-mean sea level and look for drivers of this variability. The amplitude, as well as the temporal evolution of this multi-decadal variability shows substantial variations over the North Sea region, and this spatial pattern is similar to the well-known pattern of the influence of winds and pressure changes on sea level at higher frequencies. The largest low-frequency signals are found in the German Bight and along the Norwegian coast. We find that the variability is much stronger in winter and autumn than in other seasons and that this winter and autumn variability is predominantly driven by wind and sea-level pressure anomalies which are related to large-scale atmospheric patterns. For the spring and summer seasons, this atmospheric forcing explains a smaller fraction of the observed variability. Large-scale atmospheric patterns have been derived from a principal component analysis of sea-level pressure. The first principal component of sea-level pressure over the North Atlantic Ocean, which is linked to the North Atlantic Oscillation (NAO), explains the largest fraction of winter-mean variability for most stations, while for some stations, the variability consists of a combination of multiple principal components. The low-frequency variability in season-mean sea level can manifest itself as trends in short records of seasonal sea level. For multiple stations around the North Sea, running-mean 40-year trends for autumn and winter sea level often exceed the long-term trends in annual mean sea level, while for spring and summer, the seasonal trends have a similar order of magnitude as the annual-mean trends. Removing the variability explained by atmospheric variability vastly reduces the seasonal trends, especially in winter and autumn.

scholarly journals Reconstruction of high resolution atmospheric fields for Northern Europe using analog-upscaling

2012 ◽  
Vol 8 (2) ◽  
pp. 819-868 ◽  
Author(s):  
F. Schenk ◽  
E. Zorita
Keyword(s):  
High Resolution ◽  
Sea Level ◽  
Climate Model ◽  
Regional Climate ◽  
Low Frequency ◽  
Climate Simulation ◽  
Northern Europe ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Realistic Situation

Abstract. The analog method (AM) has found application to reconstruct gridded climate fields from the information provided by proxy data and climate model simulations. Here, we test the skill of different set-ups of the AM, in a controlled but realistic situation, by analysing several statistical properties of reconstructed daily high-resolution atmospheric fields for Northern Europe for a 50-year period. In this application, station observations of sea-level pressure and air temperature are combined with atmospheric fields from a 50-year high-resolution regional climate simulation. This reconstruction aims at providing homogeneous and physically consistent atmospheric fields with daily resolution suitable to drive high resolution ocean and ecosystem models. Different settings of the AM are evaluated in this study for the period 1958-2007 to estimate the robustness of the reconstruction and its ability to replicate high and low-frequent variability, realistic probability distributions and extremes of different meteorological variables. It is shown that the AM can realistically reconstruct variables with a strong physical link to daily sea-level pressure on daily and monthly scale. However, to reconstruct low-frequency decadal and longer temperature variations, additional monthly mean station temperature as predictor is required. Our results suggest that the AM is a suitable upscaling tool to predict daily fields taken from regional climate simulations based on sparse historical station data. After this testing and characterization of the different set-ups the method will be applied to reconstruct the high-resolution atmospheric fields for the last 160 years.

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