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Record W3169515086 · doi:10.1088/1748-9326/ac0849

Internal variability and temperature scaling of future sub-daily rainfall return levels over Europe

2021· article· en· W3169515086 on OpenAlexaboutno aff
Benjamin Poschlod, Ralf Ludwig

Bibliographic record

VenueEnvironmental Research Letters · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
FundersBayerisches Landesamt für Umwelt
KeywordsPrecipitationEnvironmental scienceQuantileMediterranean climateClimatologyScalingReturn periodClimate changeAtmospheric sciencesRange (aeronautics)MeteorologyGeographyMathematicsStatisticsGeology

Abstract

fetched live from OpenAlex

Abstract The range of sub-daily extreme precipitation due to internal variability is quantified within the single model initial-condition large ensemble featuring 50 members of the Canadian regional climate model, version 5 (CRCM5) under the high-emission scenario representative concentration pathway 8.5. Ten-year return levels of sub-daily precipitation are calculated for three future periods (2010–2039, 2040–2069, 2070–2099) and hourly to 24-hourly aggregations over a European domain. The return levels are found to increase by 4%–8% for every future 30 year period averaged for the study area, where short-duration rainfall intensities increase to a greater extent than longer-duration rainfall intensities. The ranges between the median of the 50 members and the 5th and 95th quantile amount to −15.6%–19.3%, −16.0%–20.1%, and −16.5%–20.9% for the near, mid and far future, respectively. It is also shown that the scaling of the precipitation increase with temperature (Clausius–Clapeyron scaling) exhibits substantial variations between the 50 CRCM5 members at regional aggregations. These findings illustrate the large impact of internal variability on the uncertainty of extreme precipitation return level estimates. Here, regions of significant changes are identified, where future median extreme precipitation exceeds the 95th quantile of the reference period (1980–2009). These regions are located in northern Europe, central Europe and the eastern part of the Mediterranean.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.023
GPT teacher head0.275
Teacher spread0.252 · 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

Citations24
Published2021
Admission routes1
Has abstractyes

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