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Record W1996605018 · doi:10.1175/2010ei381.1

On the Surface-Convection Feedback during Drought Periods on the Canadian Prairies

2011· article· en· W1996605018 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEarth Interactions · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsEnvironment and Climate Change CanadaUniversity of Manitoba
FundersCanadian Foundation for Climate and Atmospheric SciencesU.S. Department of Energy
KeywordsThunderstormNormalized Difference Vegetation IndexPrecipitationGrowing seasonEnvironmental scienceAnomaly (physics)Lightning (connector)ClimatologyVegetation (pathology)Magnitude (astronomy)GeographyPhysical geographyMeteorologyClimate changeGeologyEcologyPhysics

Abstract

fetched live from OpenAlex

Abstract Linkages between the terrestrial ecosystem and precipitation play a critical role in regulating regional weather and climate. These linkages can manifest themselves as positive or negative feedback loops, which may either favor or inhibit the triggering and intensity of thunderstorms. Although the Canadian Prairies terrestrial system has been identified as having the potential to exert a detectable influence on convective precipitation during the warm season, little work has been done in this area using in situ observations. The authors present findings from a novel study designed to explore linkages between the normalized difference vegetation index (NDVI) and lightning duration (DUR) from the Canadian Lightning Detection Network for 38 census agricultural regions (CARs) on the Canadian Prairies. Statistics Canada divides the prairie agricultural zone into CARs (polygons of varying size and shape) for the purpose of calculating agricultural statistics. Here, DUR is used as a proxy for thunderstorm activity. Statistical analyses were undertaken for 38 CARs for summers [June–August (JJA)] between 1999 and 2008. Specifically, coefficients of determination were calculated between pairs of standardized anomalies of DUR and NDVI by season and by month. Correlations were also calculated for CARs grouped by size and/or magnitude of the NDVI anomalies. The main findings are as follows: 1) JJA lightning activity is overwhelmingly below average within larger dry areas (i.e., areas with below-average NDVI); that is, the linkages between NDVI and DUR increased significantly as both the area and magnitude of the dry anomaly increased. 2) In contrast, CARs with above-average NDVI did not consistently experience above-average lightning activity, regardless of the CAR size. 3) The lower threshold for the length scale of the dry anomalies required to affect the boundary layer sufficiently to reduce lightning activity was found to be approximately 150 km (~18 000 km2). 4) The authors’ analysis suggests that the surface-convection feedback appears to be a real phenomenon, in which drought tends to perpetuate drought with respect to convective storms and associated rainfall, within the limits found in 1) and 3).

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.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.501
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.003

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 head0.018
GPT teacher head0.198
Teacher spread0.180 · 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