Articles | Volume 21, issue 8
https://doi.org/10.5194/nhess-21-2379-2021
https://doi.org/10.5194/nhess-21-2379-2021
Research article
 | 
11 Aug 2021
Research article |  | 11 Aug 2021

The potential of machine learning for weather index insurance

Luigi Cesarini, Rui Figueiredo, Beatrice Monteleone, and Mario L. V. Martina

Related authors

Large-scale flood risk assessment in data-scarce areas: an application to Central Asia
Paola Ceresa, Gianbattista Bussi, Simona Denaro, Gabriele Coccia, Paolo Bazzurro, Mario Martina, Ettore Fagà, Carlos Avelar, Mario Ordaz, Benjamin Huerta, Osvaldo Garay, Zhanar Raimbekova, Kanatbek Abdrakhmatov, Sitora Mirzokhonova, Vakhitkhan Ismailov, and Vladimir Belikov
Nat. Hazards Earth Syst. Sci., 25, 403–428, https://doi.org/10.5194/nhess-25-403-2025,https://doi.org/10.5194/nhess-25-403-2025, 2025
Short summary
Advancing nearshore and onshore tsunami hazard approximation with machine learning surrogates
Naveen Ragu Ramalingam, Kendra Johnson, Marco Pagani, and Mario Martina
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-72,https://doi.org/10.5194/nhess-2024-72, 2024
Revised manuscript accepted for NHESS
Short summary
The whole is greater than the sum of its parts: a holistic graph-based assessment approach for natural hazard risk of complex systems
Marcello Arosio, Mario L. V. Martina, and Rui Figueiredo
Nat. Hazards Earth Syst. Sci., 20, 521–547, https://doi.org/10.5194/nhess-20-521-2020,https://doi.org/10.5194/nhess-20-521-2020, 2020
Short summary
A joint probabilistic index for objective drought identification: the case study of Haiti
Beatrice Monteleone, Brunella Bonaccorso, and Mario Martina
Nat. Hazards Earth Syst. Sci., 20, 471–487, https://doi.org/10.5194/nhess-20-471-2020,https://doi.org/10.5194/nhess-20-471-2020, 2020
Short summary
Natural hazard risk of complex systems – the whole is more than the sum of its parts: II. A pilot study in Mexico City
Marcello Arosio, Mario L. V. Martina, and Rui Figueiredo
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2018-278,https://doi.org/10.5194/nhess-2018-278, 2018
Revised manuscript has not been submitted
Short summary

Related subject area

Risk Assessment, Mitigation and Adaptation Strategies, Socioeconomic and Management Aspects
Enhancement of state response capability and famine mitigation: a comparative analysis of two drought events in northern China during the Ming dynasty
Fangyu Tian, Yun Su, Xudong Chen, and Le Tao
Nat. Hazards Earth Syst. Sci., 25, 591–607, https://doi.org/10.5194/nhess-25-591-2025,https://doi.org/10.5194/nhess-25-591-2025, 2025
Short summary
Flood exposure of environmental assets
Gabriele Bertoli, Chiara Arrighi, and Enrica Caporali
Nat. Hazards Earth Syst. Sci., 25, 565–580, https://doi.org/10.5194/nhess-25-565-2025,https://doi.org/10.5194/nhess-25-565-2025, 2025
Short summary
A new method for calculating highway blocking due to high-impact weather conditions
Duanyang Liu, Tian Jing, Mingyue Yan, Ismail Gultepe, Yunxuan Bao, Hongbin Wang, and Fan Zu
Nat. Hazards Earth Syst. Sci., 25, 493–513, https://doi.org/10.5194/nhess-25-493-2025,https://doi.org/10.5194/nhess-25-493-2025, 2025
Short summary
Impacts from cascading multi-hazards using hypergraphs: a case study from the 2015 Gorkha earthquake in Nepal
Alexandre Dunant, Tom R. Robinson, Alexander L. Densmore, Nick J. Rosser, Ragindra Man Rajbhandari, Mark Kincey, Sihan Li, Prem Raj Awasthi, Max Van Wyk de Vries, Ramesh Guragain, Erin Harvey, and Simon Dadson
Nat. Hazards Earth Syst. Sci., 25, 267–285, https://doi.org/10.5194/nhess-25-267-2025,https://doi.org/10.5194/nhess-25-267-2025, 2025
Short summary
Review article: Insuring the green economy against natural hazards – charting research frontiers in vulnerability assessment
Harikesan Baskaran, Ioanna Ioannou, Tiziana Rossetto, Jonas Cels, Mathis Joffrain, Nicolas Mortegoutte, Aurelie Fallon Saint-Lo, and Catalina Spataru
Nat. Hazards Earth Syst. Sci., 25, 49–76, https://doi.org/10.5194/nhess-25-49-2025,https://doi.org/10.5194/nhess-25-49-2025, 2025
Short summary

Cited articles

Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G. S., Davis, A., Dean, J., Devin, M., Ghemawat, S., Goodfellow, I., Harp, A., Irving, G., Isard, M., Jia, Y., Jozefowicz, R., Kaiser, L., Kudlur, M., Levenberg, J., Mane, D., Monga, R., Moore, S., Murray, D., Olah, C., Schuster, M., Shlens, J., Steiner, B., Sutskever, I., Talwar, K., Tucker, P., Vanhoucke, V., Vasudevan, V., Viegas, F., Vinyals, O., Warden, P., Wattenberg, M., Wicke, M., Yu, Y., and Zheng, X.: TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems, arXiv [preprint], arXiv:1603.04467, 2016. a
ADRC and UNDRR: GLIDE number, available at: https://glidenumber.net/glide/public/search/search.jsp (last access: 21 June 2020), Asian Disaster Reduction Centre (ADRC), Kobe, Japan, 2020. a, b, c, d, e, f, g, h, i, j, k, l, m
African Union: African Risk Capacity: Transforming disaster risk management & financing in Africa, available at: https://www.africanriskcapacity.org/ (last access: 21 June 2020), 2021. a
Aksoy, S. and Haralick, R. M.: Feature normalization and likelihood-based similarity measures for image retrieval, Pattern Recogn. Lett., 22, 563–582, https://doi.org/10.1016/S0167-8655(00)00112-4, 2001. a
Alipour, A., Ahmadalipour, A., Abbaszadeh, P., and Moradkhani, H.: Leveraging machine learning for predicting flash flood damage in the Southeast US, Environ. Res. Lett., 15, 024011, https://doi.org/10.1088/1748-9326/ab6edd, 2020. a
Download
Short summary
Weather index insurance is an innovative program used to manage the risk associated with natural disasters, providing instantaneous financial support to the insured party. This paper proposes a methodology that exploits the power of machine learning to identify extreme events for which a payout from the insurance could be delivered. The improvements achieved using these algorithms are an encouraging step forward in the promotion and implementation of this insurance instrument.
Share
Altmetrics
Final-revised paper
Preprint