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Record W2811155238 · doi:10.1002/lno.10950

Geographic and temporal variations in turbulent heat loss from lakes: A global analysis across 45 lakes

2018· article· en· W2811155238 on OpenAlexafffund
R. Iestyn Woolway, Piet Verburg, John D. Lenters, Christopher J. Merchant, David P. Hamilton, Justin D. Brookes, Elvira de Eyto, Sean D. Kelly, Nathan C. Healey, Simon J. Hook, Alo Laas, Donald C. Pierson, James A. Rusak, Jonna Kuha, Juha Karjalainen, Kari Kallio, Ahti Lepistö, Ian D. Jones

Bibliographic record

VenueLimnology and Oceanography · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsMinistry of the Environment, Conservation and Parks
FundersNatural Environment Research CouncilEuropean CommissionSight Research UKCentre for Ecology and HydrologyGlobal Lake Ecological Observatory NetworkInter-American Institute for Global Change ResearchNational Science Foundation
KeywordsLatent heatLatitudeEnvironmental scienceTurbulenceBowen ratioSensible heatAtmospheric sciencesClimatologyEnergy budgetMeteorologyGeologyEcologyGeographyBiology

Abstract

fetched live from OpenAlex

Abstract Heat fluxes at the lake surface play an integral part in determining the energy budget and thermal structure in lakes, including regulating how lakes respond to climate change. We explore patterns in turbulent heat fluxes, which vary across temporal and spatial scales, using in situ high‐frequency monitoring data from 45 globally distributed lakes. Our analysis demonstrates that some of the lakes studied follow a marked seasonal cycle in their turbulent surface fluxes and that turbulent heat loss is highest in larger lakes and those situated at low latitude. The Bowen ratio, which is the ratio of mean sensible to mean latent heat fluxes, is smaller at low latitudes and, in turn, the relative contribution of evaporative to total turbulent heat loss increases toward the tropics. Latent heat transfer ranged from ~ 60% to > 90% of total turbulent heat loss in the examined lakes. The Bowen ratio ranged from 0.04 to 0.69 and correlated significantly with latitude. The relative contributions to total turbulent heat loss therefore differ among lakes, and these contributions are influenced greatly by lake location. Our findings have implications for understanding the role of lakes in the climate system, effects on the lake water balance, and temperature‐dependent processes in lakes.

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)0.000
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 score0.323
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.007
GPT teacher head0.215
Teacher spread0.208 · 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

Citations66
Published2018
Admission routes2
Has abstractyes

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