| 1. |
- Carbone, Francesco, et al.
(author)
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Local dimensionality and inverse persistence analysis of atmospheric turbulence in the stable boundary layer
- 2022
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In: Physical review. E. - : American Physical Society. - 2470-0045 .- 2470-0053. ; 106:6
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Journal article (peer-reviewed)abstract
- The dynamics across different scales in the stable atmospheric boundary layer has been investigated by means of two metrics, based on instantaneous fractal dimensions and grounded in dynamical systems theory. The wind velocity fluctuations obtained from data collected during the Cooperative Atmosphere-Surface Exchange Study- 1999 experiment were analyzed to provide a local (in terms of scales) and an instantaneous (in terms of time) description of the fractal properties and predictability of the system. By analyzing the phase-space projections of the continuous turbulent, intermittent, and radiative regimes, a progressive transformation, characterized by the emergence of multiple low-dimensional clusters embedded in a high-dimensional shell and a two-lobe mirror symmetrical structure of the inverse persistence, have been found. The phase space becomes increasingly complex and anisotropic as the turbulent fluctuations become uncorrelated. The phase space is characterized by a three-dimensional structure for the continuous turbulent samples in a range of scales compatible with the inertial subrange, where the phase-space-filling turbulent fluctuations dominate the dynamics, and is low dimensional in the other regimes. Moreover, lower-dimensional structures present a stronger persistence than the higher-dimensional structures. Eventually, all samples recover a three-dimensional structure and higher persistence level at large scales, far from the inertial subrange. The two metrics obtained in the analysis can be considered as proxies for the decorrelation time and the local anisotropy in the turbulent flow.
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| 2. |
- De Luca, Paolo, et al.
(author)
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Compound warm-dry arid cold-wet events over the Mediterranean
- 2020
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In: Earth System Dynamics. - : Copernicus GmbH. - 2190-4979 .- 2190-4987. ; 11:3, s. 793-805
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Journal article (peer-reviewed)abstract
- The Mediterranean (MED) Basin is a climate change hotspot that has seen drying and a pronounced increase in heatwaves over the last century. At the same time, it is experiencing increased heavy precipitation during wintertime cold spells. Understanding and quantifying the risks from compound events over the MED is paramount for present and future disaster risk reduction measures. Here, we apply a novel method to study compound events based on dynamical systems theory and analyse compound temperature and precipitation events over the MED from 1979 to 2018. The dynamical systems analysis quantifies the strength of the coupling between different atmospheric variables over the MED. Further, we consider compound warm-dry anomalies in summer and cold-wet anomalies in winter. Our results show that these warm-dry and cold-wet compound days are associated with large values of the temperature-precipitation coupling parameter of the dynamical systems analysis. This indicates that there is a strong interaction between temperature and precipitation during compound events. In winter, we find no significant trend in the coupling between temperature and precipitation. However in summer, we find a significant upward trend which is likely driven by a stronger coupling during warm and dry days. Thermodynamic processes associated with long-term MED warming can best explain the trend, which intensifies compound warm-dry events.
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| 3. |
- Faranda, Davide, et al.
(author)
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A climate-change attribution retrospective of some impactful weather extremes of 2021
- 2022
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In: Weather and Climate Dynamics. - : European Geosciences Union (EGU). - 2698-4024 .- 2698-4016. ; 3:4, s. 1311-1340
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Journal article (peer-reviewed)abstract
- The IPCC AR6 report outlines a general consensus that anthropogenic climate change is modifying the frequency and intensity of extreme events such as cold spells, heat waves, storms or floods. A pertinent question is then whether climate change may have affected the characteristics of a specific extreme event or whether such event would have even been possible in the absence of climate change. Here, we address this question by performing an attribution of some major extreme events that occurred in 2021 over Europe and North America: the Winter Storm Filomena, the French spring cold spell, the Westphalia floods, the Mediterranean summer heat wave, Hurricane Ida, the Po Valley tornado outbreak, Medicane Apollo and the late-autumn Scandinavian cold spell. We focus on the role of the atmospheric circulation associated with the events and its typicality in present (factual world) and past climate conditions (counterfactual world) – defined using the ERA5 dataset 1950 to present. We first identify the most similar sea-level pressure patterns to the extreme events of interest in the factual and counterfactual worlds – so-called analogues. We then compute significant shifts in the spatial characteristics, persistence, predictability, seasonality and other characteristics of these analogues. We also diagnose whether in the present climate the analogues of the studied events lead to warmer/cooler or dryer/wetter conditions than in the past. Finally we verify whether the El Niño–Southern Oscillation and the Atlantic Multidecadal Oscillation may explain interdecadal changes in the analogues' characteristics. We find that most of the extreme events we investigate are significantly modified in the present climate with respect to the past, because of changes in the location, persistence and/or seasonality of cyclonic/anticyclonic patterns in the sea-level pressure analogues. One of the events, Medicane Apollo, appears to be a black swan of the atmospheric circulation, with poor-quality analogues. Our approach, complementary to the statistical extreme-event attribution methods in the literature, points to the potentially important role of the atmospheric circulation in attribution studies.
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| 4. |
- Faranda, Davide, et al.
(author)
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Atmospheric circulation compounds anthropogenic warming and impacts of climate extremes in Europe
- 2023
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In: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 120:13
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Journal article (peer-reviewed)abstract
- Diagnosing dynamical changes in the climate system, such as those in atmospheric circulation patterns, remains challenging. Here, we study 1950 to 2021 trends in the frequency of occurrence of atmospheric circulation patterns over the North Atlantic. Roughly 7% of atmospheric circulation patterns display significant occurrence trends, yet they have major impacts on surface climate. Increasingly frequent patterns drive heatwaves across Europe and enhanced wintertime storminess in the northern part of the continent. Over 91% of recent heatwave-related deaths and 33% of high-impact windstorms in Europe were concurrent with increasingly frequent atmospheric circulation patterns. While the trends identified are statistically significant, they are not necessarily anthropogenic. Atmospheric patterns which are becoming rarer correspond instead to wet, cool summer conditions over northern Europe and wet winter conditions over continental Europe. The combined effect of these circulation changes is that of a strong, dynamically driven year-round warming over most of the continent and large regional and seasonal changes in precipitation and surface wind.
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| 5. |
- Faranda, Davide, et al.
(author)
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Attractor dimension of time-averaged climate observables : insights from a low-order ocean-atmosphere model
- 2019
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In: Tellus. Series A, Dynamic meteorology and oceanography. - : Stockholm University Press. - 0280-6495 .- 1600-0870. ; 71:1
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Journal article (peer-reviewed)abstract
- The ocean and atmosphere have very different characteristic timescales and display a rich range of interactions. Here, we investigate the sensitivity of the dynamical properties of the coupled atmosphere-ocean system when time-averaging of the trajectories of the original system is performed. We base our analysis on a conceptual model of the atmosphere-ocean dynamics which allows us to compute the attractor properties for different coupling coefficients and averaging periods. When the averaging period is increased, the attractor dimension initially shows a non-monotonic behaviour, but ultimately decreases for windows longer than 1year. The analysis of daily, monthly and annual instrumental and reconstructed indices of oceanic and atmospheric circulation supports our results. This has important implications for the analysis and interpretation of long climate timeseries with a low temporal resolution, but also for the possible convergence of climate observables subjected to long time-averages towards attractors close to hyperbolicity.
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| 6. |
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| 7. |
- Faranda, Davide, et al.
(author)
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Correcting biases in tropical cyclone intensities in low-resolution datasets using dynamical systems metrics
- 2023
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In: Climate Dynamics. - : Springer Nature. - 0930-7575 .- 1432-0894. ; 61, s. 4393-4409
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Journal article (peer-reviewed)abstract
- Although the life-cycle of tropical cyclones is relatively well understood, many of the underlying physical processes occur at scales below those resolved by global climate models (GCMs). Projecting future changes in tropical cyclone characteristics thus remains challenging. We propose a methodology, based on dynamical system metrics, to reconstruct the statistics of cyclone intensities in coarse-resolution datasets, where maximum wind speed and minimum sea-level pressure may not be accurately represented. We base our analysis on 411 tropical cyclones occurring between 2010 and 2020, using both ERA5 reanalysis data and observations from the HURDAT2 database, as well as a control simulation of the IPSL-CM6A-ATM-ICO-HR model. For both ERA5 and model data, we compute two dynamical system metrics related to the number of degrees of freedom of the atmospheric flow and to the coupling between different atmospheric variables, namely the local dimension and the co-recurrence ratio. We then use HURDAT2 data to develop three bias-correction approaches for SLP minima: a univariate, unconditional quantile–quantile bias correction, a quantile–quantile bias correction conditioned on the two dynamical systems metrics, and a multivariate correction method. The conditional approach generally outperforms the unconditional approach for ERA5, pointing to the usefulness of the dynamical systems metrics in this context. We then show that the multivariate approach can be used to recover a realistic distribution of cyclone intensities from comparatively coarse-resolution model data.
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| 8. |
- Faranda, Davide, et al.
(author)
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Diagnosing concurrent drivers of weather extremes : application to warm and cold days in North America
- 2020
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In: Climate Dynamics. - : Springer Science and Business Media LLC. - 0930-7575 .- 1432-0894. ; 54:3-4, s. 2187-2201
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Journal article (peer-reviewed)abstract
- A fundamental challenge in climate science is decomposing the concurrent drivers of weather extremes in observations. Achieving this can provide insights into the drivers of individual extreme events as well as into possible future changes in extreme event frequencies under greenhouse forcing. In the present work, we exploit recent results from dynamical systems theory to study the co-variation and recurrence statistics of different atmospheric variables. Specifically, we present a methodology to quantify the recurrences of bivariate variables and the coupling between distinct univariate variables in terms of their joint recurrences. The coupling is defined by a parameter which varies according to the chosen variables, season, and domain and can be understood in terms of the underlying physics of the atmosphere. For suitably chosen variables, this approach enables to decompose the different drivers of weather extremes. Here, we compute the above metrics for near-surface temperature and sea level pressure, and use them to study warm or cold days over North America. We first identify states where temperature is strongly or weakly coupled to the large-scale atmospheric circulation, and then elucidate the interplay between coupling and the occurrence of temperature extremes.
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| 9. |
- Faranda, Davide, et al.
(author)
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Dynamical properties and extremes of Northern Hemisphere climate fields over the past 60 years
- 2017
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In: Nonlinear processes in geophysics. - : Copernicus GmbH. - 1023-5809 .- 1607-7946. ; 24:4, s. 713-725
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Journal article (peer-reviewed)abstract
- Atmospheric dynamics are described by a set of partial differential equations yielding an infinite-dimensional phase space. However, the actual trajectories followed by the system appear to be constrained to a finite-dimensional phase space, i.e. a strange attractor. The dynamical properties of this attractor are difficult to determine due to the complex nature of atmospheric motions. A first step to simplify the problem is to focus on observables which affect - or are linked to phenomena which affect - human welfare and activities, such as sea-level pressure, 2m temperature, and precipitation frequency. We make use of recent advances in dynamical systems theory to estimate two instantaneous dynamical properties of the above fields for the Northern Hemisphere: local dimension and persistence. We then use these metrics to characterize the seasonality of the different fields and their interplay. We further analyse the large-scale anomaly patterns corresponding to phase-space extremes - namely time steps at which the fields display extremes in their instantaneous dynamical properties. The analysis is based on the NCEP/NCAR reanalysis data, over the period 1948-2013. The results show that (i) despite the high dimensionality of atmospheric dynamics, the Northern Hemisphere sea-level pressure and temperature fields can on average be described by roughly 20 degrees of freedom; (ii) the precipitation field has a higher dimensionality; and (iii) the seasonal forcing modulates the variability of the dynamical indicators and affects the occurrence of phase-space extremes. We further identify a number of robust correlations between the dynamical properties of the different variables.
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| 10. |
- Faranda, Davide, et al.
(author)
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Dynamical proxies of North Atlantic predictability and extremes
- 2017
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In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 7
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Journal article (peer-reviewed)abstract
- Atmospheric flows are characterized by chaotic dynamics and recurring large-scale patterns. These two characteristics point to the existence of an atmospheric attractor defined by Lorenz as: the collection of all states that the system can assume or approach again and again, as opposed to those that it will ultimately avoid. The average dimension D of the attractor corresponds to the number of degrees of freedom sufficient to describe the atmospheric circulation. However, obtaining reliable estimates of D has proved challenging. Moreover, D does not provide information on transient atmospheric motions, such as those leading to weather extremes. Using recent developments in dynamical systems theory, we show that such motions can be classified through instantaneous rather than average properties of the attractor. The instantaneous properties are uniquely determined by instantaneous dimension and stability. Their extreme values correspond to specific atmospheric patterns, and match extreme weather occurrences. We further show the existence of a significant correlation between the time series of instantaneous stability and dimension and the mean spread of sea-level pressure fields in an operational ensemble weather forecast at lead times of over two weeks. Instantaneous properties of the attractor therefore provide an efficient way of evaluating and informing operational weather forecasts.
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