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Statistics and Dynamics of Climate Extreme Events
ESTIMR team

Figure: Seine river reaching 6 m height in Paris on Jan 27th 2018 after an excess in precipitation due to a cluster of extratropical storms.

Atmospheric extreme events such as windstorms, heat-waves, cold-spells and intense precipitations have serious effects on human activities and natural ecosystems. These events are difficult to study because they are rare or may have never occurred before, and because their effect can be extremely localized in space & time. The understanding of extreme events therefore requires special tools to overcome sample size and resolution issues.

In this framework, our efforts have been directed in three main axes: i) studying the relation between the occurrence of extreme events and their large-scale dynamical or thermodynamic drivers, ii) providing robust estimates of their return times in a changing climate iii) improving the representation of observed extreme events in climate simulations via statistical downscaling.

Extreme Events and large-scale circulation drivers

By adapting the theory of recurrences in dynamical systems to atmospheric fields, we have derived metrics that capture the predictability and the persistence of daily atmospheric fields. We have found that blocking patterns (associated to cold spells and heat-waves) afford low predictability and persistence, whereas extratropical storms are associated to patterns with higher predictability [9,10,11]. 

The ESTIMR team has also developed a strong expertise on European heatwaves. Analogues of circulation have been used to investigate the properties of observation datasets during recent events [5,7]. We have investigated the atmospheric dynamics during European heatwaves and shown how this dynamics has evolved since the beginning of the 20th century [1]. Other case studies were investigated in an attribution context [16].

We have developed tools to analyse extra-tropical storms [6]. This methodology was combined with a weather generator based on analogues to create an efficient storm generator.

Statistical Extreme Value Analysis

A wide range of statistical advances were made to take into account issues linked to the specific extremal features in geophysical time series: change point detection in extremes [12], spatial clustering of extremes [4], climate records detection, rainfall extreme modelling [14], extreme weather generators [13], snow avalanches modelling [8] and post processing of forecasts [15]

Downscaling techniques for Extreme Events

Many impact studies or climate investigations require simulations at a much higher spatial resolution than that provided by GCMs, especially for some extremes (e.g., wind, precipitation). Downscaling of GCM simulations by dynamical (RCMs) or statistical models (SDMs) is thus often required. ESTIMR contributes to both approaches with a focus on statistical modelling of extremes and their spatial dependencies in SDMs [2,3,17].

 

References

[1] Alvarez-Castro, Faranda, Yiou, Atmospheric Dynamics Leading to West European Summer Hot Temperatures Since 1851, Complexity, 2018

[2] Bechler, Vrac, Bel. A spatial hybrid approach for downscaling of extreme precipitation fields. J. Geophys. Res. Atmos., 120, 4534-4550, 2015.

[3] Bevacqua, Maraun, Hobaek Haff, Widmann,  Vrac. Multivariate Statistical Modelling of Compound Events via Pair-Copula Constructions: Analysis of Floods in Ravenna (Italy). Hydrol. Earth Syst. Sci., 21, 2701–2723, 2017.

[4] Carreau, Naveau, Neppel. Partitioning into hazard subregions for regional peaks‐over‐threshold modeling of heavy precipitation. Water Resources Research, 2017.

[5] Chiriaco, Bastin, Yiou, Haeffelin, Dupont, Stéfanon, European heatwave in July 2006: Observations and modeling showing how local processes amplify conducive large-scale conditions, Geophys. Res. Lett., 41, 5644–5652, 2014.

[6] Deroche, Choux, Codron, Yiou. Three variables are better than one: detection of European winter windstorms causing important damages, Nat. Hazards Earth Syst. Sci., 14, 981-993, 2014.  

[7] Dione, Lohou, Chiriaco, Lothon, Bastin,  Baray, Yiou, Colomb. The influence of synoptic circulations and local processes on temperature. Journal of Applied Meteorology and Climatology. 56, (1), 2017.

[8] Dkengne, Eckert, & Naveau. A limiting distribution for maxima of discrete stationary triangular arrays with an application to risk due to avalanches. Extremes, 19(1), 25-40, 2016.

[9] Faranda, Alvarez-Castro, Yiou, Return times of hot and cold days via recurrences and extreme value theory, Climate Dynamics, 1-13, 2016.

[10] Faranda, Messori, Alvarez-Castro, Yiou. Dynamical properties and extremes of Northern Hemisphere climate fields over the past 60 years, Nonlin. Proc. Geophys. 2017.

[11] Faranda, Messori, Yiou. Dynamical Proxies of North Atlantic predictability and extremes, Scientific Reports, 2017

[12] Kojadinovic, Naveau. "Detecting distributional changes in samples of independent block maxima using probability weighted moments." Extremes 20.2: 417-450, 2017.

[13] Marcon, G., Padoan, S. A., Naveau, P., Muliere, P., & Segers, J. (2017). Multivariate nonparametric estimation of the Pickands dependence function using Bernstein polynomials. Journal of Statistical Planning and Inference, 183, 1-17.

[14] Naveau, Huser, Ribereau, Hannart. Modeling jointly low, moderate, and heavy rainfall intensities without a threshold selection. Water Resources Research, 52(4), 2753-2769, 2016.

[15] Taillardat, Mestre, Zamo, Naveau. Calibrated ensemble forecasts using quantile regression forests and ensemble model output statistics. Monthly Weather Review, 144(6), 2375-2393, 2016.

[16] Van Oldenborgh, Stephenson, Sterl, Vautard, Yiou, Drijfhout,  Von Storch, Van Den Dool. Drivers of the 2013/14 winter floods in the UK, Nature Climate Change, 5 (6), pp. 490-491, 2015

[17] Wong, G., Maraun, D., Vrac, M., Widmann, M., Eden, J., Kent, T. Stochastic model output statistics for bias correcting and downscaling precipitation including extremes. J. Climate, 27, 6940–6959, 2014.

Projects

-A2C2 (ERC: 2014-2019). The goal is to investigate the statistical and mathematical properties of atmospheric circulation analogues, in particular during rare climate events.

-MILEX (Swedish Research Council: 2013-2016). The goal is to investigate the properties of extreme events of the last millennium, from observational datasets and model simulations.

-SEEN (ANR: 2014-2017). The goal is to investigate extreme heatwaves that hit France and can affect the nuclear energy sector.

-DAMA (CEA BOTTOM UP 2018). The goal is to use dynamical indicators to perform detection & attribution studies of southern European cold spells.

 

Maj : 26/03/2018 (160)

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