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Notes from the Front Lines of the Climate Crisis - The Threat of Cyclonic Storms and Sea Level Rise in a Warming World

2020· article· en· W3083974963 on OpenAlexaff
John J. Clague

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsStormClimate changeWinter stormNatural (archaeology)Natural hazardNatural disasterFlooding (psychology)Heat waveCoastal floodGlobal warmingEnvironmental scienceClimatologyMeteorologyGeographyOceanographySea level riseGeology

Abstract

fetched live from OpenAlex

The loss of life from natural hazards has decreased over the past century, due partly to much improved understanding and monitoring of hazards and partly to improvements in preparedness, communication, engineered infrastructure. This has happened at a time when human numbers have more than quadrupled and now approach 8 billion, and when populations in areas vulnerable to earthquakes and cyclones have greatly increased. Now, however, we may be on the doorstep of a ‘tipping point’ in human suffering and life loss due to the rapid changes in Earth’s climate that we are experiencing. Human-induced climate change is increasingly amplifying dangerous meteorological processes, including severe storms, drought, wildfires, heat waves, and flooding. These changes have no precedent in the past 10,000 years and are blurring the distinction between ‘natural hazards’ and human-induced hazards. The threats posed by climate change are legion; in this presentation, I discuss a set of linked phenomena that represent an emerging threat to people and society over the remainder of this century and beyond – specifically sea-level rise and coincident stronger cyclonic storms, which, on occasion, inundate low-lying coastal areas. Hurricanes and typhoons are likely to become more intense in a warmer climate and will produce higher storm surges that move ashore on an elevated sea surface. The average level of Earth’s oceans is currently rising at a rate of over 3 mm per year, which is nearly 50 percent higher than a century ago. The rate of sea-level rise is increasing due, in part, to increasing transfers of water into oceans from glaciers and ice sheets and, in part, to the warming and expansion of seawater. Scientists forecast that average global sea level will be about 1 m higher by the end of this century than today. Over 600 million people, nearly 10% of the human population, currently live less than 10 m above sea level, many in growing coastal megacities. That number will increase dramatically over the next 50 years, increasing the overall risk that people face from extreme storms. The number of people living at low elevations along coasts, and thus exposed to flooding from storm surges, is highest in Asia, particularly in China, India, Bangladesh, Indonesia, and Viet Nam, which are ill-equipped to deal with the emerging crisis. Within limits, humans can adapt to severe storms and higher sea levels, but few countries have the resources to adequately protect people and property from this threat. Thus, without urgent action on a global scale to limit the damage we are causing to Earth’s climate and without a stabilization of human numbers, many populated low-lying coastal areas could become uninhabitable by the end of this century. The forced relocation of large numbers of people is likely to cause suffering and conflict that we do not appreciate and have not planned for. More generally, human suffering stemming from human-induced climate change will outstrip the progress we have made over the past century in reducing life loss from ‘natural hazards’.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.028
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0060.005
Open science0.0010.003
Research integrity0.0050.011
Insufficient payload (model declined to judge)0.0280.010

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 head0.055
GPT teacher head0.253
Teacher spread0.198 · 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 designNot applicable
Domainnot available
GenreCommentary

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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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