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Record W4408252400 · doi:10.1016/j.gespch.2025.100004

Hurricane Otis: Category 5 storm effects and cascading hazards in Acapulco Bay, Mexico

2025· article· en· W4408252400 on OpenAlexfundno aff
María Teresa Ramírez‐Herrera, Oswaldo Coca, Krzysztof Gaidzik, Víctor H. Vargas Espinoza

Bibliographic record

VenueGlobal and earth surface processes change. · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsnot available
FundersCoordinación de la Investigación CientíficaDirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de MéxicoInformation and Communications Technology CouncilConsejo Nacional de Ciencia y Tecnología
KeywordsStormBayEnvironmental scienceMeteorologyGeographyGeologyOceanography

Abstract

fetched live from OpenAlex

Hurricane Otis, a Category 5 storm, made landfall in Acapulco, Mexico, on October 25, 2023, with sustained winds of 270 km/h and wind gusts up to 330 km/h. Its unprecedented rapid intensification, attributed to record-high sea surface temperatures, marked it as the strongest storm to hit the region in the satellite era. This study documents the geomorphic, infrastructural, and socio-political impacts of the event, highlighting extensive coastal erosion, sediment deposition, and cascading hazards such as landslides and flooding. Coastal changes included severe beach erosion, overwash effects, and delta formation. Notably, beaches like Revolcadero experienced erosion exceeding 76 meters, while scoured channels and widened tidal inlets transformed coastal geomorphology. Beyond physical alterations, the hurricane caused widespread infrastructure damage, displacing over 34,500 families and affecting more than 560,000 residents. Economic losses are estimated at over $15 billion USD, with significant impacts on hotels, residential buildings, transportation networks, and commercial establishments. The event revealed substantial gaps in disaster preparedness, as limited warnings and delayed responses worsened the socio-economic impact. Stagnant water and poor sanitation caused disease outbreaks, while inadequate aid distribution highlighted systemic inequities. The findings stress the urgent need for better disaster management, including early warning systems, equitable aid, and climate adaptation to address escalating risks from extreme weather intensified by climate change. By examining the geomorphic, infrastructural, and socio-political consequences of Hurricane Otis, this study emphasizes the necessity of proactive resilience measures to mitigate the long-term risks posed by such unprecedented cascading hazards. • Hurricane Otis was the strongest storm to hit Acapulco, with 270 km/h winds. • The storm caused >76 m beach erosion, scoured channels, and coastal reshaping. • Otis triggered cascading hazards, including flooding, landslides, and vegetation loss. • Economic losses topped $15 billion USD, displacing 34,500 families and affecting many. • Findings stress urgent need for climate adaptation, prevention, and disaster resilience strategies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.453

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.222
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2025
Admission routes1
Has abstractyes

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