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Record W3142714348 · doi:10.1088/1748-9326/abf28a

Can we trust CMIP5/6 future projections of European winter precipitation?

2021· article· en· W3142714348 on OpenAlexaff
Eduardo Moreno‐Chamarro, L-P Caron, Pablo Ortega, Saskia Loosveldt Tomas, Malcolm Roberts

Bibliographic record

VenueEnvironmental Research Letters · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsOuranos
FundersHorizon 2020 Framework ProgrammeMinisterio de Asuntos Económicos y Transformación Digital, Gobierno de EspañaMet OfficeDepartment for Environment, Food and Rural Affairs, UK Government
KeywordsExtratropical cycloneClimatologyEnvironmental sciencePrecipitationAtmosphere (unit)Climate modelBaroclinityEddyClimate changeAtmospheric sciencesGeologyMeteorologyOceanographyGeographyTurbulence

Abstract

fetched live from OpenAlex

Abstract IPCC models project a likely increase in winter precipitation over northern Europe under a high-emission scenario. These projections, however, typically rely on relatively coarse ∼100 km resolution models that can misrepresent important processes driving precipitation, such as extratropical cyclone activity, and ocean eddies. Here, we show that a pioneering 50 km atmosphere–1/12° ocean global coupled model projects a substantially larger increase in winter precipitation over northwestern Europe by mid-century than lower-resolution configurations. For this increase, both the highest ocean and atmosphere model resolutions are essential: only the eddy-rich (1/12°) ocean projects a progressive northward shift of the Gulf Stream. This leads to a strong regional ocean surface warming that intensifies air–sea heat fluxes and baroclinicity. For this then to translate into a strengthening of North Atlantic extratropical cyclone activity, the 50 km atmosphere is essential, as it enables enhanced diabatic heating from water vapor condensation and an acceleration of the upper-level mean flow, which weaken vertical stability. Our results suggest that all recent IPCC climate projections using traditional ∼100 km resolution models could be underestimating the precipitation increase over Europe in winter and, consequently, the related potential risks.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.033
GPT teacher head0.292
Teacher spread0.259 · 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 designBench or experimental
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

Citations45
Published2021
Admission routes1
Has abstractyes

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