scholarly journals Atmospheric circulation patterns associated to the variability of River Ammer floods: evidence from observed and proxy data

2015 ◽  
Vol 11 (5) ◽  
pp. 4483-4504 ◽  
Author(s):  
N. Rimbu ◽  
M. Czymzik ◽  
M. Ionita ◽  
G. Lohmann ◽  
A. Brauer
Keyword(s):  
Time Series ◽  
Atmospheric Circulation ◽  
Time Scales ◽  
Western Europe ◽  
Wave Train ◽  
Circulation Pattern ◽  
Flood Frequency ◽  
Discharge Data ◽  
Western Asia ◽  
Instrumental Period

Abstract. The relationship between the frequency of River Ammer floods (southern Germany) and atmospheric circulation variability is investigated based on observational Ammer discharge data back to 1926 and a flood layer time series from varved sediments of the downstream Lake Ammersee for the pre-instrumental period back to 1766. A composite analysis reveals that, at synoptic time scales, observed River Ammer floods are associated with enhanced moisture transport from the Atlantic Ocean and the Mediterranean towards the Ammer region, a pronounced trough over Western Europe as well as enhanced potential vorticity at upper levels. We argue that this synoptic scale configuration can trigger heavy precipitation and floods in the Ammer region. Interannual to multidecadal increases in flood frequency as recorded in the instrumental discharge record are associated to a wave-train pattern extending from the North Atlantic to western Asia with a prominent negative center over western Europe. A similar atmospheric circulation pattern is associated to increases in flood layer frequency in the Lake Ammersee sediment record during the pre-instrumental period. We argue that the complete flood layer time-series from Lake Ammersee sediments covering the last 5500 years, contains information about atmospheric circulation variability on inter-annual to millennial time-scales.

scholarly journals Atmospheric circulation patterns associated with the variability of River Ammer floods: evidence from observed and proxy data

2016 ◽  
Vol 12 (2) ◽  
pp. 377-385 ◽  
Author(s):  
Norel Rimbu ◽  
Markus Czymzik ◽  
Monica Ionita ◽  
Gerrit Lohmann ◽  
Achim Brauer
Keyword(s):  
Time Series ◽  
Atmospheric Circulation ◽  
Western Europe ◽  
Wave Train ◽  
Heavy Precipitation ◽  
Circulation Pattern ◽  
Flood Frequency ◽  
Discharge Data ◽  
Western Asia ◽  
Instrumental Period

Abstract. The relationship between the frequency of River Ammer floods (southern Germany) and atmospheric circulation variability is investigated based on observational Ammer River discharge data back to 1926 and a flood layer time series from varved sediments of the downstream Lake Ammer for the pre-instrumental period back to 1766. A composite analysis reveals that, at synoptic timescales, observed River Ammer floods are associated with enhanced moisture transport from the Atlantic Ocean and the Mediterranean towards the Ammer region, a pronounced trough over western Europe as well as enhanced potential vorticity at upper levels. We argue that this synoptic-scale configuration can trigger heavy precipitation and floods in the Ammer region. Interannual to multidecadal increases in flood frequency, as detected in the instrumental discharge record, are associated with a wave train pattern extending from the North Atlantic to western Asia, with a prominent negative center over western Europe. A similar atmospheric circulation pattern is associated with increases in flood layer frequency in the Lake Ammer sediment record during the pre-instrumental period. We argue that the complete flood layer time series from Lake Ammer sediments covering the last 5500 years contains information about atmospheric circulation variability on interannual to millennial timescales.

scholarly journals Patterns of extreme weather associated with observed and proxy River Ammer flood records

2017 ◽  
Author(s):  
Norel Rimbu ◽  
Monica Ionita ◽  
Markus Czymzik ◽  
Achim Brauer ◽  
Gerrit Lohmann
Keyword(s):  
Solar Activity ◽  
Radiative Forcing ◽  
Large Scale ◽  
Western Europe ◽  
Extreme Temperature ◽  
Heavy Precipitation ◽  
Flood Frequency ◽  
Discharge Data ◽  
Blocking High ◽  
Northeastern Europe

Abstract. We investigate the relationship between the variability in the frequency of River Ammer floods (southern Germany) and temperature/precipitation extremes over Europe using observational River Ammer discharge data back to 1926 and the 5500-year-long flood layer record from varved Lake Ammersee sediments. We show that observed River Ammer flood frequency variability is not only related with local extreme precipitation, but also with large-scale temperature extreme anomalies. Less (more) extreme high temperatures over central and western (northeastern) Europe are recorded during periods of increased River Ammer flood frequency. We argue that changing radiative forcing due to cloudiness anomaly patterns associated with River Ammer floods induce these extreme temperature anomalies. Consistent patterns are obtained using observed discharge and proxy flood layer frequency data. Furthermore, a higher frequency of observed River Ammer floods and flood layers is associated with enhanced blocking activity over northeastern Europe. A blocking high over this region increases the probability of wave breaking and associated heavy precipitation over western Europe. A similar blocking pattern is associated with periods of reduced solar activity. Consequently, solar modulated changes in blocking frequency over northeastern Europe could explain the connection between River Ammer floods and solar activity, as also identified in previous studies. We argue that multi-decadal to millennial flood frequency variations in the Mid- to Late Holocene flood layer record from Lake Ammersee characterizes also the extreme temperatures in northeastern Europe.

scholarly journals Solar modulation of flood frequency in central Europe during spring and summer on interannual to multi-centennial timescales

2016 ◽  
Vol 12 (3) ◽  
pp. 799-805 ◽  
Author(s):  
Markus Czymzik ◽  
Raimund Muscheler ◽  
Achim Brauer
Keyword(s):  
Solar Activity ◽  
Atmospheric Circulation ◽  
Central Europe ◽  
Empirical Support ◽  
Total Solar Irradiance ◽  
Flood Frequency ◽  
Solar Modulation ◽  
Top Down ◽  
Discharge Data ◽  
Atmospheric Circulation Patterns

Abstract. Solar influences on climate variability are one of the most controversially discussed topics in climate research. We analyze solar forcing of flood frequency in central Europe during spring and summer on interannual to multi-centennial timescales, integrating daily discharge data of the River Ammer (southern Germany) back to AD 1926 (∼  solar cycles 16–23) and the 5500-year flood layer record from varved sediments of the downstream Ammersee. Flood frequency in the River Ammer discharge record is significantly correlated to changes in solar activity when the flood record lags the solar signal by 2–3 years (2-year lag: r = −0.375, p = 0.01; 3-year lag: r = −0.371, p = 0.03). Flood layer frequency in the Ammersee sediment record depicts distinct multi-decadal variations and significant correlations to a total solar irradiance reconstruction (r = −0.4, p <  0.0001) and 14C production rates (r = 0.37, p <  0.0001), reflecting changes in solar activity. On all timescales, flood frequency is higher when solar activity is reduced. In addition, the configuration of atmospheric circulation associated with periods of increased River Ammer flood frequency broadly resembles that during intervals of reduced solar activity, as expected to be induced by the so-called solar top-down mechanism by model studies. Both atmospheric patterns are characterized by an increase in meridional airflow associated with enhanced atmospheric blocking over central Europe. Therefore, the significant correlations as well as similar atmospheric circulation patterns might provide empirical support for a solar influence on hydroclimate extremes in central Europe during spring and summer by the so-called solar top-down mechanism.

scholarly journals A dynamical adjustment perspective on extreme event attribution

2021 ◽  
Author(s):  
Laurent Terray
Keyword(s):  
Atmospheric Circulation ◽  
Extreme Events ◽  
Western Europe ◽  
Climate Model ◽  
Extreme Event ◽  
Dynamic Component ◽  
Western Asia ◽  
Event Attribution ◽  
Climate Model Simulations

Abstract. Here we demonstrate that dynamical adjustment allows a straightforward approach to extreme event attribution within a conditional framework. We illustrate the potential of the approach with two iconic extreme events that occurred in 2010: the early winter European cold spell and the Russian summer heat wave. We use a dynamical adjustment approach based on constructed atmospheric circulation analogues to isolate the various contributions to these two extreme events using only observational and reanalysis datasets. Dynamical adjustment results confirm previous findings regarding the role of atmospheric circulation in the two extreme events and provide a quantitative estimate of the various dynamic and thermodynamic contributions to the event amplitude. Furthermore, the approach is also used to identify the drivers of the recent 1979–2018 trends in summer extreme maximum and minimum temperature changes over western Europe and western Asia. The results suggest a significant role of the dynamic component in explaining temperature extreme changes in different regions, including regions around the Black and Caspian Seas as well as central Europe and the coasts of western Europe. Finally, dynamical adjustment offers a simple and complementary storyline approach to extreme event attribution with the advantage that no climate model simulations are needed, making it a promising candidate for the fast-track component of any real-time extreme event attribution system.

scholarly journals Solar modulation of flood frequency in Central Europe during spring and summer on inter-annual to millennial time-scales

2015 ◽  
Vol 11 (5) ◽  
pp. 4833-4850 ◽  
Author(s):  
M. Czymzik ◽  
R. Muscheler ◽  
A. Brauer
Keyword(s):  
Solar Activity ◽  
Central Europe ◽  
Time Scales ◽  
Decadal Variability ◽  
Empirical Support ◽  
Flood Frequency ◽  
Solar Modulation ◽  
Solar Cycles ◽  
Discharge Data ◽  
Discharge Record

Abstract. Solar influences on climate variability are one of the most controversially discussed topics in climate research. We analyze solar forcing of flood frequency in Central Europe on inter-annual to millennial time-scales using daily discharge data of River Ammer (southern Germany) back to AD 1926 and revisiting the 5500 year flood layer time-series from varved sediments of the downstream Lake Ammersee. Flood frequency in the discharge record is significantly correlated to changes in solar activity during solar cycles 16–23 (r = −0.47, p < 0.0001, n = 73). Flood layer frequency (n = 1501) in the sediment record depicts distinct multi-decadal variability and significant correlations to 10Be fluxes from a Greenland ice core (r = 0.45, p < 0.0001) and 14C production rates (r =0.36, p < 0.0001), proxy records of solar activity. Flood frequency is higher when solar activity is reduced. These correlations between flood frequency and solar activity might provide empirical support for the solar top-down mechanism expected to modify the mid-latitude storm tracks over Europe by model studies. A lag of flood frequency responses in the Ammer discharge record to changes in solar activity of about one to three years could be explained by a modelled ocean–atmosphere feedback delaying the atmospheric reaction to solar activity variations up to a few years.

scholarly journals Locally and Remotely Forced Subtropical AMOC Variability: A Matter of Time Scales

2020 ◽  
Vol 33 (12) ◽  
pp. 5155-5172
Author(s):  
Quentin Jamet ◽  
William K. Dewar ◽  
Nicolas Wienders ◽  
Bruno Deremble ◽  
Sally Close ◽  
...  
Keyword(s):  
Time Series ◽  
Time Scales ◽  
North Atlantic ◽  
Time Scale ◽  
Low Frequency ◽  
Meridional Overturning Circulation ◽  
Open Boundary ◽  
Overturning Circulation ◽  
Decadal Scale ◽  
Meridional Overturning

AbstractMechanisms driving the North Atlantic meridional overturning circulation (AMOC) variability at low frequency are of central interest for accurate climate predictions. Although the subpolar gyre region has been identified as a preferred place for generating climate time-scale signals, their southward propagation remains under consideration, complicating the interpretation of the observed time series provided by the Rapid Climate Change–Meridional Overturning Circulation and Heatflux Array–Western Boundary Time Series (RAPID–MOCHA–WBTS) program. In this study, we aim at disentangling the respective contribution of the local atmospheric forcing from signals of remote origin for the subtropical low-frequency AMOC variability. We analyze for this a set of four ensembles of a regional (20°S–55°N), eddy-resolving (1/12°) North Atlantic oceanic configuration, where surface forcing and open boundary conditions are alternatively permuted from fully varying (realistic) to yearly repeating signals. Their analysis reveals the predominance of local, atmospherically forced signal at interannual time scales (2–10 years), whereas signals imposed by the boundaries are responsible for the decadal (10–30 years) part of the spectrum. Due to this marked time-scale separation, we show that, although the intergyre region exhibits peculiarities, most of the subtropical AMOC variability can be understood as a linear superposition of these two signals. Finally, we find that the decadal-scale, boundary-forced AMOC variability has both northern and southern origins, although the former dominates over the latter, including at the site of the RAPID array (26.5°N).

scholarly journals Scale-dependent intrinsic entropies of complex time series

2016 ◽  
Vol 374 (2065) ◽  
pp. 20150204 ◽  
Author(s):  
Jia-Rong Yeh ◽  
Chung-Kang Peng ◽  
Norden E. Huang
Keyword(s):  
Time Series ◽  
Time Scales ◽  
Spatial Scales ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Complex Time ◽  
Multi Scale ◽  
Mode Decomposition ◽  
Simulated Time ◽  
Simulated Time Series

Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal’s complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease.

scholarly journals Analysis Methods for Characterizing Salinity Variability from Multivariate Time Series Applied to the Apalachicola Bay Estuary

2012 ◽  
Vol 29 (4) ◽  
pp. 613-628 ◽  
Author(s):  
Steven L. Morey ◽  
Dmitry S. Dukhovskoy
Keyword(s):  
Time Series ◽  
Time Scales ◽  
River Discharge ◽  
River Flow ◽  
High Salinity ◽  
Multivariate Time Series ◽  
Salinity Range ◽  
Apalachicola Bay ◽  
Analysis Methods ◽  
Salinity Variability

Abstract Statistical analysis methods are developed to quantify the impacts of multiple forcing variables on the hydrographic variability within an estuary instrumented with an enduring observational system. The methods are applied to characterize the salinity variability within Apalachicola Bay, a shallow multiple-inlet estuary along the northeastern Gulf of Mexico coast. The 13-yr multivariate time series collected by the National Estuary Research Reserve at three locations within the bay are analyzed to determine how the estuary responds to variations in external forcing mechanisms, such as freshwater discharge, precipitation, tides, and local winds at multiple time scales. The analysis methods are used to characterize the estuarine variability under differing flow regimes of the Apalachicola River, a managed waterway, with particular focus on extreme events and scales of variability that are critical to local ecosystems. Multivariate statistical models are applied that describe the salinity response to winds from multiple directions, river flow, and precipitation at daily, weekly, and monthly time scales to understand the response of the estuary under different climate regimes. Results show that the salinity is particularly sensitive to river discharge and wind magnitude and direction, with local precipitation being largely unimportant. Applying statistical analyses with conditional sampling quantifies how the likelihoods of high-salinity and long-duration high-salinity events, conditions of critical importance to estuarine organisms, change given the state of the river flow. Intraday salinity range is shown to be negatively correlated with the salinity, and correlated with river discharge rate.

scholarly journals Methods of Constructing Time Series for Predicting Local Time Scales by Means of a GMDH-Type Neural Network

2021 ◽  
Vol 11 (12) ◽  
pp. 5615
Author(s):  
Łukasz Sobolewski ◽  
Wiesław Miczulski
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Local Time ◽  
Time Scales ◽  
Time Scale ◽  
Prediction Accuracy ◽  
Prediction Horizon

Ensuring the best possible stability of UTC(k) (local time scale) and its compliance with the UTC scale (Universal Coordinated Time) forces predicting the [UTC-UTC(k)] deviations, the article presents the results of work on two methods of constructing time series (TS) for a neural network (NN), increasing the accuracy of UTC(k) prediction. In the first method, two prepared TSs are based on the deviations determined according to the UTC scale with a 5-day interval. In order to improve the accuracy of predicting the deviations, the PCHIP interpolating function is used in subsequent TSs, obtaining TS elements with a 1-day interval. A limitation in the improvement of prediction accuracy for these TS has been a too large prediction horizon. The introduction in 2012 of the additional UTC Rapid scale by BIPM makes it possible to shorten the prediction horizon, and the building of two TSs has been proposed according to the second method. Each of them consists of two subsets. The first subset is based on deviations determined according to the UTC scale, the second on the UTC Rapid scale. The research of the proposed TS in the field of predicting deviations for the Polish Timescale by means of GMDH-type NN shows that the best accuracy of predicting the deviations has been achieved for TS built according to the second method.

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