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Record W3173050191 · doi:10.34237/1008921

Coastal windstorms create unsteady, unpredictable storm surges in a fluvial Maine estuary

2021· article· en· W3173050191 on OpenAlexaff
Preston Spicer, Pascal Matte, Kimberly Huguenard, Laura N. Rickard

Bibliographic record

VenueShore & Beach · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsStorm surgeEstuarySurgeFluvialTidal irrigationStormEnvironmental scienceForcing (mathematics)OceanographyHydrology (agriculture)GeologyDischargeClimatologyGeomorphologyGeographyDrainage basin

Abstract

fetched live from OpenAlex

Storm surges create coastal flooding that can be damaging to life and property. In estuaries with significant river influence (fluvial), it is possible for tides, storm surge, and river discharge to interact and enhance surges relative to the immediate coast. These tide-surge-river interactions were previously identified in a fluvial Maine estuary as higher frequency (>four cycles per day) oscillations to storm surge which were proposed to be incited by enhanced friction and resonance during certain windstorm events (Spicer et al. 2019). The relative contributions to tide-surge-river interaction from atmospheric forcing variables (wind, barometric pressure, and externally generated surge) remains unclear. This work seeks to decompose and analyze a recent windstorm surge event to better isolate the effects of atmospheric forcing on tidesurge- river interaction. Results show total storm surges in the fluvial estuary to be two times larger than at the estuary mouth because of tide-surge-river interaction. Analysis indicated at least 50% of the magnitude of tide-surge-river interactions are created by non-tidal forcing, in the form of wind, enhancing frictional energy in the estuary. The remaining tide-surge-river interaction is likely a result of changes in tidal wave propagation speed due to surge deepening the mean estuary water level.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.016
GPT teacher head0.233
Teacher spread0.217 · 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 teacher head, not a consensus.

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

Citations7
Published2021
Admission routes1
Has abstractyes

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