EXTREME EVENTS: ARTIFICIAL INTELLIGENCE FOR DETECTION AND ATTRIBUTION

Livrables

Report and delivery of a draft framework for event definition developed in collaboration with stakeholders

(Task 2.1) This report will provide clear guidance and principles on how to define an event to be considered in an attribution study that is on one hand closely related to what actually caused the damages and thus societies are vulnerable to and on the other hand can in principle be simulated using state-of-the-art climate models. Given the diverse nature of damages, societies and stakeholders as well as hazards there will be no strict framework, but instead a set of principles that allows flexibility with respect to divers vulnerabilities and stakeholder needs.

Report on joint activities with other EU projects

[Task 1.3] This report will describe the common activities that have took place at M18 with other EU. We envisage in particular a strong link with the C3S, and the H2020 EUCP project. We will report also on common activities with parallel projects of the same call.

List of high precipitation and flood events for the present and future periods

"By using the available observations and survey a list of high precipitation and flood events will be compiled. For hurricanes we will largely rely on the HURDAT database available at https://www.nhc.noaa.gov/data/#hurdat. A similar list will be done for the events detected and not by the CP models in present and future scenario simulations. (from Task 8.1)"

Report on the Summer training school

Report on the Summer training school. The report will include in particular the programme, the training exercises, the number of participant, an evaluation from participating students and young researchers. [Task 1.2]

Report detailing and collating databases of impacts, vulnerability and exposure relevant to extreme weather events

(Task 2.2) This report will provide an overview of currently available data and crucially highlight gaps in the data available to truly learn from past extreme events. This will consist of hazard data as well as data on damages, economic and non-economic but also other determinants of vulnerability, like population structure and changes. Ultimately allowing stakeholders to assess physical, transition and liability risks.

Value promotion plan

A plan for promoting various values from the promotion committee (recruitment, climate and environment fairness, communication, ethics)

Project website

The website will target both the scientific community and the large public and updated on a regular basis.

Open source code for detection and characterization of spatio-temporal extreme events

(Task 3.2) An open source toolbox based on spatio-temporal deep learning architectures will be deployed with tunable parameterizations and training modules. Several examples of use will be included to deal with (i) detection and (ii) characterization of extremes. A Jupyter notebook will exemplify tools, tuning and applications in control scenarios, aimed to serve adoption by other members of the consortium (inside WP3 and in collaborations with WP4 and WP7). This deliverable will be also accompanied by a report on the theoretical underpinnings and limitations of the proposed methods in terms of computational efficiency, automatism and robustness (to noise and dimensionality).

Publications

Guidelines for Studying Diverse Types of Compound Weather and Climate Events

Auteurs: Bevacqua, E., De Michele, C., Manning, C., Couasnon, A., Ribeiro, A. F. S., Ramos, A. M., Vignotto, E., Bastos, A., Blesić, S., Durante, F., Hillier, J., Oliveira, S. C., Pinto, J. G., Ragno, E., Rivoire, P., Saunders, K., van der Wiel, K., Wu, W., Zhang, T., Zscheischler, J.
Publié dans: Earth's Future, 2022, ISSN 2328-4277
Éditeur: John Wiley & Sons, Ltd
DOI: 10.1029/2021ef002340

Record events attribution in climate studies

Auteurs: Julien Worms, Philippe Naveau
Publié dans: Environmetrics, Numéro Volume 33, Numéro 8, 2022, ISSN 1180-4009
Éditeur: John Wiley & Sons Inc.
DOI: 10.1002/env.2777

Classification of tropical cyclone containing images using a convolutional neural network: performance and sensitivity to the learning dataset

Auteurs: Olivier Boucher; Sébastien Gardoll
Publié dans: Geoscientific Model Development, Numéro 15, 2022, Page(s) 7051-7073, ISSN 1991-9603
Éditeur: Copernicus Publications
DOI: 10.5194/gmd-15-7051-2022

Early snowmelt and polar jet dynamics co–influence recent extreme Siberian fire seasons

Auteurs: Rebecca C. Scholten, Dim Coumou, Fei Luo, and Sander Veraverbeke
Publié dans: Science, Numéro Vol 378, Numéro 6623, 2022, Page(s) 1005-1009, ISSN 0036-8075
Éditeur: American Association for the Advancement of Science
DOI: 10.1126/science.abn4419

Robust global detection of forced changes in mean and extreme precipitation despite observational disagreement on the magnitude of change

Auteurs: Iris Elisabeth de Vries; Sebastian Sippel; Angeline Greene Pendergrass; Reto Knutti
Publié dans: Earth System Dynamics, Numéro 14, 2023, Page(s) 81-100, ISSN 2190-4987
Éditeur: Copernicus Publications
DOI: 10.5194/esd-14-81-2023

Dynamical footprints of Hurricanes in the Tropical Dynamics

Auteurs: Davide Faranda, Gabriele Messori, Pascal Yiou, Soulivanh Thao, Flavio Pons, Berengere Dubrulle
Publié dans: Chaos: An Interdisciplinary Journal of Nonlinear Science, 2022, ISSN 1054-1500
Éditeur: American Institute of Physics
DOI: 10.1063/5.0093732

Precipitation trends determine future occurrences of compound hot–dry events

Auteurs: Bevacqua, E., Zappa, G., Lehner, F., Zscheischler, J.
Publié dans: Nature Climate Change, 2022, ISSN 1758-6798
Éditeur: Springer Nature
DOI: 10.1038/s41558-022-01309-5

Attributing Compound Events to Anthropogenic Climate Change

Auteurs: Jakob Zscheischler, Flavio Lehner
Publié dans: Bulletin of the American Meteorological Society, Numéro Volume 103, Numéro 3, 2022, Page(s) E936–E953, ISSN 0003-0007
Éditeur: American Meteorological Society
DOI: 10.1175/bams-d-21-0116.1

Causality and the fate of climate litigation: The Role of the social Superstructure Narrative

Auteurs: Friederike E. L. Otto; Petra Minnerop; Emmanuel Raju; Luke J. Harrington; Rupert F. Stuart‐Smith; Emily Boyd; Rachel James; Richard Jones; Kristian C. Lauta
Publié dans: Global Policies, Numéro Volume 13, Numéro 5, 2022, Page(s) 623-833, ISSN 1758-5880
Éditeur: John Wiley and Sons Ltd
DOI: 10.1111/1758-5899.13113

Reconstruction of zonal precipitation from sparse historical observations using climate model information and statistical learning

Auteurs: Egli, M., Sippel, S., Pendergrass, A. G., de Vries, I., & Knutti, R.
Publié dans: Geophysical Research Letters, Numéro 49, 2022, ISSN 0094-8276
Éditeur: American Geophysical Union
DOI: 10.1029/2022gl099826

Regional asymmetry in the response of global vegetation growth to springtime compound climate events

Auteurs: Jun Li; Emanuele Bevacqua; Chi Chen; Zhaoli Wang; Xiaohong Chen; Ranga B. Myneni; Xushu Wu; Chong-Yu Xu; Zhenxing Zhang; Jakob Zscheischler
Publié dans: Communications Earth & Environment, Numéro 3;123, 2022, ISSN 2662-4435
Éditeur: Communications Earth & Environment
DOI: 10.1038/s43247-022-00455-0

High return level estimates of daily ERA-5 precipitation in Europe estimated using regionalized extreme value distributions

Auteurs: Pauline Rivoire, Philomène Le Gall, Anne-Catherine Favre, Philippe Naveau, Olivia Martius
Publié dans: Weather and Climate Extremes, Numéro Volume 38, 2022, ISSN 2212-0947
Éditeur: Elsevier BV
DOI: 10.1016/j.wace.2022.100500

A climate-change attribution retrospective of some impactful weather extremes of 2021

Auteurs: Faranda, D., Bourdin, S., Ginesta, M., Krouma, M., Messori, G., Noyelle, R., Pons, F., and Yiou, P.
Publié dans: Weather and Climate Dynamics, Numéro 3, 1311–1340, 2022, 2022, ISSN 2698-4016
Éditeur: Copernicus Publications
DOI: 10.5194/wcd-3-1311-2022

Challenges in Attributing the 2022 Australian Rain Bomb to Climate Change

Auteurs: Cadiou, C., Noyelle, R., Malhomme, N., Faranda, D.
Publié dans: Asia-Pacific Journal of Atmospheric Sciences, 2022, ISSN 1976-7951
Éditeur: Springer Nature
DOI: 10.1007/s13143-022-00305-1

Multimodel Errors and Emergence of Times in Climate Attribution Studies

Auteurs: Naveau, P., Thao, S.
Publié dans: Journal of Climate, Numéro Volume 35, Numéro 14, 2022, Page(s) 4791–4804, ISSN 0894-8755
Éditeur: American Meteorological Society
DOI: 10.1175/jcli-d-21-0332.1

Drivers and Mechanisms of the 2021 Pacific Northwest Heatwave

Auteurs: D. L. Schumacher, M. Hauser, S. I. Seneviratne
Publié dans: Earth's Future, Numéro Volume 10, Numéro 12, 2022, ISSN 2328-4277
Éditeur: American Geophysical Union
DOI: 10.1029/2022ef002967

Extreme weather impacts of climate change: an attribution perspective

Auteurs: Ben Clarke; Friederike Otto; Rupert Stuart-Smith; Luke Harrington
Publié dans: Environmental Research Climate, Numéro 1, 2022, ISSN 2752-5295
Éditeur: IOP Publishing
DOI: 10.1088/2752-5295/ac6e7d

Robust detection of forced warming in the presence of potentially large climate variability

Auteurs: Sebastian Sippel, Nicolai Meinshausen, Enikő Székely, Erich Fischer, Angeline G. Pendergrass, Flavio Lehner, Reto Knutti
Publié dans: Science Advances, Numéro Vol. 7, No. 43, 2021, ISSN 2375-2548
Éditeur: American Association for the Advancement of Science
DOI: 10.1126/sciadv.abh4429

Time of Emergence of compound events: contribution of univariate and dependence properties

Auteurs: Bastien François; Mathieu Vrac
Publié dans: Natural Hazards and Earth System Sciences, Numéro 23, 2023, Page(s) 21-44, ISSN 1684-9981
Éditeur: Copernicus Publications
DOI: 10.5194/nhess-2022-127

Stable sums to infer high return levels of multivariate rainfall time series

Auteurs: Gloria Buriticá, Philippe Naveau
Publié dans: Environmetrics, 2022, ISSN 1180-4009
Éditeur: John Wiley & Sons Inc.
DOI: 10.1002/env.2782

Compound wind and precipitation extremes across the Indo-Pacific: climatology, variability and drivers

Auteurs: Delei Li, Yang Chen, Martina Messmer, Yuchao Zhu, Jianlong Feng, Baoshu Yin, Emanuele Bevacqua
Publié dans: Geophysical Research Letters, Numéro 49, 14, 2022, ISSN 0094-8276
Éditeur: American Geophysical Union
DOI: 10.1029/2022gl098594

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