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A comparison between direct and pan-derived measurements of the isotopic composition of atmospheric waters

2011· article· en· W2189066111 on OpenAlexaff
Cecilia Azcurra, Catherine E. Hughes, Stephen Parkes, S.E. Hollins, J. J. Gibson, Matthew F. McCabe, Jason P. Evans

Bibliographic record

VenueChan, F., Marinova, D. and Anderssen, R.S. (eds) MODSIM2011, 19th International Congress on Modelling and Simulation. · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsUniversity of VictoriaAlberta Innovates
FundersUniversity of New South WalesNational Centre for Groundwater Research and TrainingAustralian Nuclear Science and Technology Organisation
KeywordsComposition (language)Atmospheric compositionEnvironmental scienceAtmospheric sciencesRemote sensingEnvironmental chemistryChemistryGeologyMeteorologyAtmosphere (unit)Physics

Abstract

fetched live from OpenAlex

The stable isotopes of water can be used to examine and quantify the contribution to atmospheric moisture from evaporation, transpiration and surface-waters.However, obtaining extensive and ongoing time series data of the isotopic composition of atmospheric moisture has been difficult.Presented here is an alternate method using an isotope mass balance approach to estimate the isotopic composition of atmospheric moisture using water samples collected from class A evaporation pans.While this evaporation pan method does not provide the high-resolution time series data that can be obtained from an isotope analyser taking in-situ measurements of atmospheric moisture, the method is relatively simple and inexpensive to set-up and maintain.In this preliminary investigation, a comparison between the isotopic composition of atmospheric moisture estimated from the evaporation pan method and in-situ measurements of the isotopic composition of water vapour using a Fourier Transform Infrared (FTIR) spectrometer deployed at the Lucas Heights weather station in New South Wales is undertaken.Through comparison of the two series of hydrogen isotope data, an assessment of the evaporation pan method can be made.Although there was some agreement between the isotopic composition of vapour measured by the FTIR spectrometer and the estimation for the atmospheric moisture (R 2 = 0.49), the comparison is sensitive to climatic parameters that vary significantly within a 24hour period such as the relative humidity of air and the air and pan temperatures.Inverting the model to use the FTIR spectrometer measurements at an hourly resolution improved the performance of the model (R 2 = 0.57).However, this also revealed that the model produced more depleted values of the evaporation pan water isotopes than those observed.In contrast, there was a variable relationship between the modelled and observed isotope values of atmospheric moisture.These conflicting results will need to be resolved before the evaporation pan method is broadly applied in isotope hydrology.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.085
GPT teacher head0.270
Teacher spread0.185 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations2
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueChan, F., Marinova, D. and Anderssen, R.S. (eds) MODSIM2011, 19th International Congress on Modelling and Simulation.Same topicGroundwater and Isotope GeochemistryFrench-language works237,207