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Pan Evaporation Trends and the Terrestrial Water Balance. II. Energy Balance and Interpretation

2009· article· en· W2113455199 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGeography Compass · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
FundersCurtin University of TechnologyAustralian National UniversityUniversity of LeedsColorado State University
KeywordsEnergy balanceEvaporationBalance (ability)Forcing (mathematics)Pan evaporationWater balanceAtmosphere (unit)ClimatologyEnvironmental scienceConfusionWater cycleMeteorologyGeographyGeology

Abstract

fetched live from OpenAlex

Abstract Declines in pan evaporation have been reported across the USA, former Soviet Union, India, China, Australia, New Zealand and Canada, among other places. The trend is large – approximately an order of magnitude larger than model‐based estimates of top of the atmosphere radiative forcing. The pan evaporation trend also has a different sign (i.e. decline) from commonly held conceptions. These are a remarkably interesting set of observations. In the first article of this two‐part series, we discussed the measurements themselves and then presented summaries of the worldwide observations. In this, the second article, we outline the use of energy balance methods to attribute the observed changes in pan evaporation to changes in the underlying physical variables, namely, radiation, temperature, vapour pressure deficit and wind speed. We find that much of the decline in pan evaporation can be attributed to declines in radiation (i.e. dimming) and/or wind speed (i.e. stilling). We then discuss the interpretation of changes in the terrestrial water balance. This has been an area of much misunderstanding and confusion, most of which can be rectified through use of the familiar and longstanding supply/demand framework. The key in using the pan evaporation data to make inferences about changes in the terrestrial water balance is to distinguish between water‐ and energy‐limited conditions where different interpretations apply.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.245

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 studies0.0000.000
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 head0.006
GPT teacher head0.210
Teacher spread0.203 · 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