Articles | Volume 23, issue 3
https://doi.org/10.5194/nhess-23-1157-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-23-1157-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Mar 2023
Research article |
| 21 Mar 2023
| 21 Mar 2023
Deadly disasters in southeastern South America: flash floods and landslides of February 2022 in Petrópolis, Rio de Janeiro
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
José A. Marengo
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil
José Mantovani
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
Luciana R. Londe
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil
Rachel Lau Yu San
National Institute of Education, Earth Observatory of Singapore and Asian School of the Environment, Nanyang Technological University (NTU), Singapore
Edward Park
National Institute of Education, Earth Observatory of Singapore and Asian School of the Environment, Nanyang Technological University (NTU), Singapore
Yunung Nina Lin
Institute of Earth Sciences, Academia Sinica, Taipei, Taiwan
Jingyu Wang
National Institute of Education, Earth Observatory of Singapore and Asian School of the Environment, Nanyang Technological University (NTU), Singapore
Tatiana Mendes
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
Department of Environmental Engineering, Institute of Science and Technology, São Paulo State University (Unesp), São José dos Campos, Brazil
Ana Paula Cunha
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil
Luana Pampuch
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
Department of Environmental Engineering, Institute of Science and Technology, São Paulo State University (Unesp), São José dos Campos, Brazil
Marcelo Seluchi
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil
Silvio Simões
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
Luz Adriana Cuartas
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil
Demerval Goncalves
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil
Klécia Massi
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
Department of Environmental Engineering, Institute of Science and Technology, São Paulo State University (Unesp), São José dos Campos, Brazil
Regina Alvalá
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil
Osvaldo Moraes
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil
Carlos Souza Filho
Institute of Geosciences (IG/Unicamp), University of Campinas, Campinas, Brazil
Rodolfo Mendes
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, Brazil
Carlos Nobre
Graduate Program in Natural Disasters, Unesp/CEMADEN, São José dos Campos, Brazil
Institute of Advanced Studies, University of São Paulo (IEA/USP), São Paulo, Brazil
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Nat. Hazards Earth Syst. Sci., 25, 1387–1404, https://doi.org/10.5194/nhess-25-1387-2025, https://doi.org/10.5194/nhess-25-1387-2025, 2025
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This study applies climate extreme indices to assess climate risks to food security. Using an explainable machine learning analysis, key climate indices affecting maize and soybean yields in Brazil were identified. Results reveal the temporal sensitivity of these indices and critical yield loss thresholds, informing policy and adaptation strategies.
Jennifer Fortes Cavalcante Renk, Tatiana Sussel Gonçalves Mendes, Silvio Jorge Coelho Simões, Marcio Roberto Magalhães de Andrade, Luana Albertani Pampuch Bortolozo, Adriano Martins Junqueira, and Melina Almeida Silva
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-3-2024, 463–470, https://doi.org/10.5194/isprs-annals-X-3-2024-463-2024, https://doi.org/10.5194/isprs-annals-X-3-2024-463-2024, 2024
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Wei Jing Ang, Edward Park, Yadu Pokhrel, Dung Duc Tran, and Ho Huu Loc
Earth Syst. Sci. Data, 16, 1209–1228, https://doi.org/10.5194/essd-16-1209-2024, https://doi.org/10.5194/essd-16-1209-2024, 2024
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Dams have burgeoned in the Mekong, but information on dams is scattered and inconsistent. Up-to-date evaluation of dams is unavailable, and basin-wide hydropower potential has yet to be systematically assessed. We present a comprehensive database of 1055 dams, a spatiotemporal analysis of the dams, and a total hydropower potential of 1 334 683 MW. Considering projected dam development and hydropower potential, the vulnerability and the need for better dam management may be highest in Laos.
Jingyu Wang, Jiwen Fan, and Zhe Feng
Nat. Hazards Earth Syst. Sci., 23, 3823–3838, https://doi.org/10.5194/nhess-23-3823-2023, https://doi.org/10.5194/nhess-23-3823-2023, 2023
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Hail and tornadoes are devastating hazards responsible for significant property damage and economic losses in the United States. Quantifying the connection between hazard events and mesoscale convective systems (MCSs) is of great significance for improving predictability, as well as for better understanding the influence of the climate-scale perturbations. A 14-year statistical dataset of MCS-related hazard production is presented.
Jingyu Wang, Xianfeng Wang, Edward Park, and Yun Lin
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-100, https://doi.org/10.5194/nhess-2023-100, 2023
Manuscript not accepted for further review
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Building upon the findings in a preceding study by the authors (Wang et al., 2023), this brief communication successfully applied the soil moisture-based tornado damage track detection method to the 24–25 March 2023 Mississippi outbreak. This study also found that the notable discrepancies between spotter reports and ground survey assessments at the tornado early stage can be reconciled using the new method.
Marcos Roberto Benso, Gabriela Chiquito Gesualdo, Roberto Fray Silva, Greicelene Jesus Silva, Luis Miguel Castillo Rápalo, Fabricio Alonso Richmond Navarro, Patricia Angélica Alves Marques, José Antônio Marengo, and Eduardo Mario Mendiondo
Nat. Hazards Earth Syst. Sci., 23, 1335–1354, https://doi.org/10.5194/nhess-23-1335-2023, https://doi.org/10.5194/nhess-23-1335-2023, 2023
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This article is about how farmers can better protect themselves from disasters like droughts, extreme temperatures, and floods. The authors suggest that one way to do this is by offering insurance contracts that cover these different types of disasters. By having this insurance, farmers can receive financial support and recover more quickly. The article elicits different ideas about how to design this type of insurance and suggests ways to make it better.
M. L. L. Reiss, T. S. G. Mendes, F. F. Pereira, M. R. M. de Andrade, R. M. Mendes, S. J. C. Simões, R. de Lara, and S. F. de Souza
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 1077–1083, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1077-2022, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1077-2022, 2022
Po-Lun Ma, Bryce E. Harrop, Vincent E. Larson, Richard B. Neale, Andrew Gettelman, Hugh Morrison, Hailong Wang, Kai Zhang, Stephen A. Klein, Mark D. Zelinka, Yuying Zhang, Yun Qian, Jin-Ho Yoon, Christopher R. Jones, Meng Huang, Sheng-Lun Tai, Balwinder Singh, Peter A. Bogenschutz, Xue Zheng, Wuyin Lin, Johannes Quaas, Hélène Chepfer, Michael A. Brunke, Xubin Zeng, Johannes Mülmenstädt, Samson Hagos, Zhibo Zhang, Hua Song, Xiaohong Liu, Michael S. Pritchard, Hui Wan, Jingyu Wang, Qi Tang, Peter M. Caldwell, Jiwen Fan, Larry K. Berg, Jerome D. Fast, Mark A. Taylor, Jean-Christophe Golaz, Shaocheng Xie, Philip J. Rasch, and L. Ruby Leung
Geosci. Model Dev., 15, 2881–2916, https://doi.org/10.5194/gmd-15-2881-2022, https://doi.org/10.5194/gmd-15-2881-2022, 2022
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An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based on a tuning strategy that focuses on clouds. When clouds in every regime are improved, other aspects of the model are also improved, even though they are not the direct targets for calibration. The recalibrated model shows a lower sensitivity to anthropogenic aerosols and surface warming, suggesting potential improvements to the simulated climate in the past and future.
Flavio Lopes Ribeiro, Mario Guevara, Alma Vázquez-Lule, Ana Paula Cunha, Marcelo Zeri, and Rodrigo Vargas
Nat. Hazards Earth Syst. Sci., 21, 879–892, https://doi.org/10.5194/nhess-21-879-2021, https://doi.org/10.5194/nhess-21-879-2021, 2021
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The main objective of this paper was to analyze differences in soil moisture responses to drought for each biome of Brazil. For that we used satellite data from the European Space Agency from 2009 to 2015. We found an overall soil moisture decline of −0.5 % yr−1 at the country level and identified the most vulnerable biomes of Brazil. This information is crucial to enhance the national drought early warning system and develop strategies for drought risk reduction and soil moisture conservation.
Jingyu Wang, Jiwen Fan, Robert A. Houze Jr., Stella R. Brodzik, Kai Zhang, Guang J. Zhang, and Po-Lun Ma
Geosci. Model Dev., 14, 719–734, https://doi.org/10.5194/gmd-14-719-2021, https://doi.org/10.5194/gmd-14-719-2021, 2021
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This paper presents an evaluation of the E3SM model against NEXRAD radar observations for the warm seasons during 2014–2016. The COSP forward simulator package is implemented in the model to generate radar reflectivity, and the NEXRAD observations are coarsened to the model resolution for comparison. The model severely underestimates the reflectivity above 4 km. Sensitivity tests on the parameters from cumulus parameterization and cloud microphysics do not improve this model bias.
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Short summary
The municipality of Petrópolis (approximately 305 687 inhabitants) is nestled in the mountains 68 km outside the city of Rio de Janeiro. On 15 February 2022, the city of Petrópolis in Rio de Janeiro, Brazil, received an unusually high volume of rain within 3 h (258 mm). This resulted in flash floods and subsequent landslides that caused 231 fatalities, the deadliest landslide disaster recorded in Petrópolis. This work shows how the disaster was triggered.
The municipality of Petrópolis (approximately 305 687 inhabitants) is nestled in the mountains...
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