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CLImate INTelligence: Extreme events detection, attribution and adaptation design using machine learning

Deliverables

Local Climate Services

Report from T7.1 integrating milestone MS2 and reporting the needs, as suggested by the stakeholders in dedicated meeting, for local CS in the different Climate Change Hotspots and the specifications of existing services, formulating any user-inspired EE variables and indices as input to WP3-5, and formulating the impact indicators for quantifying the value of AI-enhanced CS.

Project Management Plan

Report from T1.1 describing the decision-making structures and procedures adopted in the process; the review quality procedures; the management processes to be implemented in steering each WP and task; the financial and resource use reporting guidelines.

Communication and Dissemination plan - first update

The report from T9.3 will include an update of deliverable D9.2 with the activities carried out in the first reporting period.

Extreme Events detection

Report from T3.1-3.4 integrating milestones MS5-11 and reviewing existing knowledge, data and models for EE detection, and, for each category of EEs, identifying indices, datasets, and candidate drivers for ML based detection.

Extreme Events attribution

The report from T5.1 expands milestone MS16 and reviews existing knowledge, data and models for attribution analysis of different EE.

Review of ML algorithms for Climate Science

Report describing state-of-the-art algorithms developed in the Machine Learning and Artificial Intelligence domain to support climate science in the detection, causation, and attribution of extreme events addressed in T2.1-3.

EU Climate Services on the impacts of Extreme Events

The report from T6.1-6.3 integrates milestones MS3-4 and reviews existing EU CS with a focus on EE impacts for the water, energy and food sectors. It will also report suggestions and requirements gathered from the stakeholders in dedicated meetings.

Communication and Dissemination plan

Report from T9.1-9.2 describing the strategies that will be used to obtain the objectives of this WP. The plan will include a communication requirements analysis, identification of stakeholders and target audiences, and will outline dissemination activities and channels to be used and will display time management features for their implementation.

CLINT website, visual identity and logo

Initial package of the communication material, including the project logo, website, social media. This dissemination material from T9.2 will be continuously updated throughout the project.

Data Management Plan

Report from T8.1 describing the policy concerning the acquisition, storage and classification and management and distribution of project data. The report will include procedures for data collection, storage, protection, retention and destruction.

Publications

Tropical Cyclone Genesis Potential Indices in a New High‐Resolution Climate Models Ensemble: Limitations and Way Forward

Author(s): L. Cavicchia, E. Scoccimarro, G. Ascenso, A. Castelletti, M. Giuliani, S. Gualdi
Published in: Geophysical Research Letters, Issue 50, 2024, ISSN 0094-8276
Publisher: American Geophysical Union
DOI: 10.1029/2023gl103001

Nighttime heat waves in the Euro-Mediterranean region: definition, characterisation, and seasonal prediction

Author(s): Verónica Torralba, Stefano Materia, Leone Cavicchia, M Carmen Álvarez-Castro, Chloé Prodhomme, Ronan McAdam, Enrico Scoccimarro, Silvio Gualdi
Published in: Environmental Research Letters, Issue 19, 2024, Page(s) 034001, ISSN 1748-9326
Publisher: Institute of Physics Publishing
DOI: 10.1088/1748-9326/ad24cf

Robustness of hydrometeorological extremes in surrogated seasonal forecasts

Author(s): Katharina Klehmet, Peter Berg, Denica Bozhinova, Louise Crochemore, Yiheng Du, Ilias Pechlivanidis, Christiana Photiadou, Wei Yang
Published in: International Journal of Climatology, Issue 44, 2024, Page(s) 1725-1738, ISSN 0899-8418
Publisher: John Wiley & Sons Inc.
DOI: 10.1002/joc.8407

The New Max Planck Institute Grand Ensemble With CMIP6 Forcing and High‐Frequency Model Output

Author(s): Dirk Olonscheck, Laura Suarez‐Gutierrez, Sebastian Milinski, Goratz Beobide‐Arsuaga, Johanna Baehr, Friederike Fröb, Tatiana Ilyina, Christopher Kadow, Daniel Krieger, Hongmei Li, Jochem Marotzke, Étienne Plésiat, Martin Schupfner, Fabian Wachsmann, Lara Wallberg, Karl‐Hermann Wieners, Sebastian Brune
Published in: Journal of Advances in Modeling Earth Systems, Issue 15, 2023, ISSN 1942-2466
Publisher: American Geophysical Union
DOI: 10.1029/2023ms003790

Analysis, characterization, prediction, and attribution of extreme atmospheric events with machine learning and deep learning techniques: a review

Author(s): Sancho Salcedo-Sanz, Jorge Pérez-Aracil, Guido Ascenso, Javier Del Ser, David Casillas-Pérez, Christopher Kadow, Dušan Fister, David Barriopedro, Ricardo García-Herrera, Matteo Giuliani, Andrea Castelletti
Published in: Theoretical and Applied Climatology, Issue 155, 2024, Page(s) 1-44, ISSN 0177-798X
Publisher: Springer Verlag
DOI: 10.1007/s00704-023-04571-5

When it comes to Earth observations in AI for disaster risk reduction, is it feast or famine? A topical review

Author(s): Monique M Kuglitsch, Arif Albayrak, Jürg Luterbacher, Allison Craddock, Andrea Toreti, Jackie Ma, Paula Padrino Vilela, Elena Xoplaki, Rui Kotani, Dominique Berod, Jon Cox, Ivanka Pelivan
Published in: Environmental Research Letters, Issue 18, 2023, Page(s) 093004, ISSN 1748-9326
Publisher: Institute of Physics Publishing
DOI: 10.1088/1748-9326/acf601

Long-term temperature prediction with hybrid autoencoder algorithms

Author(s): J. Pérez-Aracil, D. Fister, C.M. Marina, C. Peláez-Rodríguez, L. Cornejo-Bueno, P.A. Gutiérrez, M. Giuliani, A. Castelleti, S. Salcedo-Sanz
Published in: Applied Computing and Geosciences, Issue 23, 2024, Page(s) 100185, ISSN 2590-1974
Publisher: elsevier
DOI: 10.1016/j.acags.2024.100185

Interpretable linear dimensionality reduction based on bias-variance analysis

Author(s): Paolo Bonetti, Alberto Maria Metelli, Marcello Restelli
Published in: Data Mining and Knowledge Discovery, Issue 38, 2024, Page(s) 1713-1781, ISSN 1384-5810
Publisher: Kluwer Academic Publishers
DOI: 10.1007/s10618-024-01015-0

Optimisation-based refinement of genesis indices for tropical cyclones

Author(s): Ascenso, Guido Cavicchia, Leone Scoccimarro, Enrico Castelletti, Andrea
Published in: Environmental Research Communications, 2023, ISSN 2515-7620
Publisher: IOP Publishing
DOI: 10.1088/2515-7620/acb52a

Country-level energy demand for cooling has increased over the past two decades

Author(s): Enrico Scoccimarro, Oreste Cattaneo, Silvio Gualdi, Francesco Mattion, Alexandre Bizeul, Arnau Martin Risquez, Roberta Quadrelli
Published in: Communications Earth & Environment, Issue 4, 2023, ISSN 2662-4435
Publisher: nature
DOI: 10.1038/s43247-023-00878-3

The extremely hot and dry 2018 summer in central and northern Europe from a multi-faceted weather and climate perspective

Author(s): Efi Rousi, Andreas H. Fink, Lauren S. Andersen, Florian N. Becker, Goratz Beobide-Arsuaga, Marcus Breil, Giacomo Cozzi, Jens Heinke, Lisa Jach, Deborah Niermann, Dragan Petrovic, Andy Richling, Johannes Riebold, Stella Steidl, Laura Suarez-Gutierrez, Jordis S. Tradowsky, Dim Coumou, André Düsterhus, Florian Ellsäßer, Georgios Fragkoulidis, Daniel Gliksman, Dörthe Handorf, Karsten Haustein, Ka
Published in: Natural Hazards and Earth System Sciences, Issue 23, 2023, Page(s) 1699-1718, ISSN 1684-9981
Publisher: EGU Journal
DOI: 10.5194/nhess-23-1699-2023

Significant relationships between drought indicators and impacts for the 2018–2019 drought in Germany

Author(s): Anastasiya Shyrokaya, Gabriele Messori, Ilias Pechlivanidis, Florian Pappenberger, Hannah L Cloke, Giuliano Di Baldassarre
Published in: Environmental Research Letters, Issue 19, 2023, Page(s) 014037, ISSN 1748-9326
Publisher: Institute of Physics Publishing
DOI: 10.1088/1748-9326/ad10d9

New Probabilistic, Dynamic Multi-Method Ensembles for Optimization Based on the CRO-SL

Author(s): Jorge Pérez-Aracil, Carlos Camacho-Gómez, Eugenio Lorente-Ramos, Cosmin M. Marina, Laura M. Cornejo-Bueno, Sancho Salcedo-Sanz
Published in: Mathematics, Issue 11, 2023, Page(s) 1666, ISSN 2227-7390
Publisher: mdpi
DOI: 10.3390/math11071666

One month in advance prediction of air temperature from Reanalysis data with eXplainable Artificial Intelligence techniques

Author(s): Gómez-Orellana, Antonio Manuel Guijo-Rubio, David Pérez-Aracil, Jorge Gutiérrez, Pedro Antonio Salcedo-Sanz, Sancho Hervás-Martínez, César
Published in: Atmospheric Research, 2023, ISSN 0169-8095
Publisher: Elsevier BV
DOI: 10.1016/j.atmosres.2023.106608

Advances and gaps in the science and practice of impact‐based forecasting of droughts

Author(s): Anastasiya Shyrokaya, Florian Pappenberger, Ilias Pechlivanidis, Gabriele Messori, Sina Khatami, Maurizio Mazzoleni, Giuliano Di Baldassarre
Published in: WIREs Water, Issue 11, 2024, ISSN 2049-1948
Publisher: WIREs
DOI: 10.1002/wat2.1698

Accurate Long-term Air Temperature Prediction with a Fusion of Artificial Intelligence and Data Reduction Techniques

Author(s): Fister, Dušan; Pérez-Aracil, Jorge; Peláez-Rodríguez, César; Del Ser, Javier; Salcedo-Sanz, Sancho
Published in: arXiv preprint arXiv:2209.15424, Issue 2, 2022, ISSN 2331-8422
Publisher: Arxiv
DOI: 10.48550/arxiv.2209.15424

Increasing heat and rainfall extremes now far outside the historical climate

Author(s): Alexander Robinson, Jascha Lehmann, David Barriopedro, Stefan Rahmstorf, Dim Coumou
Published in: npj Climate and Atmospheric Science, Issue 4, 2022, ISSN 2397-3722
Publisher: nature
DOI: 10.1038/s41612-021-00202-w

Model Predictive Control of water resources systems: A review and research agenda

Author(s): Andrea Castelletti, Andrea Ficchì, Andrea Cominola, Pablo Segovia, Matteo Giuliani, Wenyan Wu, Sergio Lucia, Carlos Ocampo-Martinez, Bart De Schutter, José María Maestre
Published in: Annual Reviews in Control, Issue 55, 2024, Page(s) 442-465, ISSN 1367-5788
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.arcontrol.2023.03.013

An Action‐Oriented Approach to Make the Most of the Wind and Solar Power Complementarity

Author(s): Sonia Jerez, David Barriopedro, Alejandro García‐López, Raquel Lorente‐Plazas, Andrés M. Somoza, Marco Turco, Judit Carrillo, Ricardo M. Trigo
Published in: Earth's Future, Issue 11, 2024, ISSN 2328-4277
Publisher: Earth's Future
DOI: 10.1029/2022ef003332

A hierarchical classification/regression algorithm for improving extreme wind speed events prediction

Author(s): Peláez-Rodríguez, C., Pérez-Aracil, J., Fister, D., Prieto-Godino, L., Deo, R.C., Salcedo-Sanz, S.
Published in: Renewable Energy, 2022, ISSN 0960-1481
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.renene.2022.11.042

A general explicable forecasting framework for weather events based on ordinal classification and inductive rules combined with fuzzy logic

Author(s): C. Peláez-Rodríguez, J. Pérez-Aracil, C.M. Marina, L. Prieto-Godino, C. Casanova-Mateo, P.A. Gutiérrez, S. Salcedo-Sanz
Published in: Knowledge-Based Systems, Issue 291, 2024, Page(s) 111556, ISSN 0950-7051
Publisher: Elsevier BV
DOI: 10.1016/j.knosys.2024.111556

Connecting hydrological modelling and forecasting from global to local scales: Perspectives from an international joint virtual workshop

Author(s): Antara Dasgupta, Louise Arnal, Rebecca Emerton, Shaun Harrigan, Gwyneth Matthews, Ameer Muhammad, Karen O'Regan, Teresa Pérez-Ciria, Emixi Valdez, Bart van Osnabrugge, Micha Werner, Carlo Buontempo, Hannah Cloke, Florian Pappenberger, Ilias G. Pechlivanidis, Christel Prudhomme, Maria-Helena Ramos, Peter Salamon
Published in: Journal of Flood and Risk Management, 2022, ISSN 1753-318X
Publisher: Blackwell Publishing
DOI: 10.1111/jfr3.12880

Hydrological regimes explain the seasonal predictability of streamflow extremes

Author(s): Yiheng Du, Ilaria Clemenzi, Ilias G Pechlivanidis
Published in: Environmental Research Letters, Issue 18, 2024, Page(s) 094060, ISSN 1748-9326
Publisher: Institute of Physics Publishing
DOI: 10.1088/1748-9326/acf678

Heat Waves: Physical Understanding and Scientific Challenges

Author(s): D. Barriopedro, R. García‐Herrera, C. Ordóñez, D. G. Miralles, S. Salcedo‐Sanz
Published in: Reviews of Geophysics, Issue 61, 2023, ISSN 8755-1209
Publisher: American Geophysical Union
DOI: 10.1029/2022rg000780

DEPLOYMENT OF AI-ENHANCED SERVICES IN CLIMATE RESILIENCE INFORMATION SYSTEMS

Author(s): N. Hempelmann, C. Ehbrecht, E. Plesiat, G. Hobona, J. Simoes, D. Huard, T. J. Smith, U. S. McKnight, I. G. Pechlivanidis, and C. Alvarez-Castro
Published in: 2022
Publisher: Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.,
DOI: 10.5194/isprs-archives-xlviii-4-w1-2022-187-2022

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