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Record W3139355006 · doi:10.5194/bg-18-1803-2021

An observation-based evaluation and ranking of historical Earth system model simulations in the northwest North Atlantic Ocean

2021· article· en· W3139355006 on OpenAlexafffundabout
Arnaud Laurent, Katja Fennel, Angela M. Kuhn

Bibliographic record

VenueBiogeosciences · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsDalhousie University
FundersCompute CanadaU.S. Department of Energy
KeywordsBiogeochemical cycleBiogeochemistryEnvironmental scienceEarth system scienceOceanographyContinental shelfSalinityClimatologyClimate changeOcean currentRepresentative Concentration PathwaysSea surface temperatureNitrateClimate modelSpatial ecologyGeologyEcologyBiology

Abstract

fetched live from OpenAlex

Continental shelf regions in the ocean play an important role in the global cycling of carbon and nutrients, but their responses to global change are understudied. Global Earth system models (ESMs), as essential tools for building understanding of ocean biogeochemistry, are used extensively and routinely for projections of future climate states; however, their relatively coarse spatial resolution is likely not appropriate for accurately representing the complex patterns of circulation and elemental fluxes on the shelves along ocean margins. Here, we compared 29 ESMs used in the Intergovernmental Panel on Climate Change (IPCC)'s Assessment Reports (ARs) 5 and 6 and a regional biogeochemical model for the northwest North Atlantic (NWA) shelf to assess their ability to reproduce surface observations of temperature, salinity, nitrate and chlorophyll. The NWA region is biologically productive, influenced by the large-scale Gulf Stream and Labrador Current systems and particularly sensitive to climatically induced changes in large-scale circulation. Most ESMs compare relatively poorly to observed surface nitrate and chlorophyll and show differences with observed surface temperature and salinity that suggest spatial mismatches in their large-scale current systems. Model-simulated nitrate and chlorophyll compare better with available observations in AR6 than in AR5, but none of the models perform equally well for all four parameters. The ensemble means of all ESMs, and of the five best-performing ESMs, strongly underestimate observed chlorophyll and nitrate. The regional model has a much higher spatial resolution and reproduces the observations significantly better than any of the ESMs. It also simulates reasonably well vertically resolved observations from gliders and bi-monthly ship-based monitoring observations. A ranking of the ESMs indicates that only one ESM has good and consistent performance for all variables. An additional evaluation of the ESMs along the regional model boundaries shows larger variability but is generally consistent with the ranking on the shelf. Overall, 11 ESMs were deemed satisfactory for use in the NWA, either directly or for regional downscaling.

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)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.276
Teacher spread0.223 · 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 designSimulation or modeling
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

Citations51
Published2021
Admission routes3
Has abstractyes

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