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Record W2772029939 · doi:10.1175/jhm-d-17-0117.1

Surface Moistening Trends in the Northern North American Great Plains Increase the Likelihood of Convective Initiation

2017· article· en· W2772029939 on OpenAlexaboutno aff
Tobias Gerken, Gabriel Bromley, Paul C. Stoy

Bibliographic record

VenueJournal of Hydrometeorology · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
FundersNational Institute of Food and AgricultureDirectorate for Biological SciencesMontana Wheat and Barley Committee
KeywordsHydrometeorologyConvective Boundary LayerEnvironmental sciencePrecipitationLatent heatConvectionSensible heatAtmospheric sciencesClimatologyBoundary layerPlanetary boundary layerEddy covarianceMeteorologyGeographyGeologyEcosystemTurbulence

Abstract

fetched live from OpenAlex

Abstract Land management impacts atmospheric boundary layer processes, and recent trends reducing the practice of summer fallow have led to increases in precipitation and decreases in temperature in the Canadian Prairie provinces during summer. It is unclear if such trends also impact the hydrometeorology of the adjacent U.S. northern Great Plains, parts of which have seen similar changes in land management. Here, MERRA-2 reanalysis data, eddy covariance observations, and a mixed-layer (ML) atmospheric modeling framework are combined to demonstrate that the likelihood of convectively preconditioned conditions has increased by approximately 10% since the mid-1980s and is now more sensitive to further decreases in the Bowen ratio (Bo) and maximum daily net radiation in northeastern Montana. Convective season Bo in the study area has decreased from approximately 2 to 1 from the 1980s until the present, largely due to simultaneous increases in latent heat flux and decreases in sensible heat flux, consistent with observed decreases of summer fallow and increases in cropping. Daily net radiation has not changed despite a significant decrease in May and June humidity lapse rates from the 1980s to present. Future research should determine the area of the U.S. Great Plains that has seen changes in the dynamics of the atmospheric boundary layer height and lifted condensation level and their crossings as a necessary condition for convective precipitation to occur and ascertain if ongoing changes in land management will lead to future changes in convective outcomes.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.985

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.265
Teacher spread0.245 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations39
Published2017
Admission routes1
Has abstractyes

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