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Record W7090439862 · doi:10.18150/xgcono

Subdaily records of atmospheric pressure, wind speed and direction, and air temperature in southwest Greenland during the latter half of the 18th century.

2025· dataset· en· W7090439862 on OpenAlexaboutno aff

Bibliographic record

VenueRepOD · 2025
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
Fundersnot available
KeywordsAtmospheric pressureWind speedWind directionAtmospheric temperatureAir temperatureAltitude (triangle)BarometerTable (database)

Abstract

fetched live from OpenAlex

The oldest meteorological data for the southwest coast of Greenland date from the second half of the 18th century. Weather observations were conducted by the Moravian Brothers, who established the first Christian mission in a settlement called Nuuk (formerly: Neu-Herrnhut, Godthaab, Godthab or Godthåb).During their mission, the Moravian Brothers compiled two series of meteorological data: 1) Sep 1767 – Jul 1768 and 2) Sep 1784 – Jun 1792. For the first series (Neu-Herrnhut), observations were made twice a day (8:00 AM and 2:00 PM LT). Parameters such as air temperature (°F), atmospheric pressure (Paris inch and Paris line), and wind direction and force (1-6) were measured. The second series (Godthaab) consists of measurements taken three times a day (7:00 AM, 2:00 PM, and 9:00 PM LT). Air temperature (°R), atmospheric pressure (Paris inch), and wind direction and force (0-4) were measured.Historical data were quality-checked and corrected. Air temperature was converted to degrees Celsius. Atmospheric pressure to mmHg and them to hPa. The gravity correction "Pφcorr" was then applied, and the pressure was reduced to sea level altitude "SLP" using the formulas provided in Cappelan (2009). Atmospheric pressure was also corrected to the value at 0°C. For this purpose, the Kämtz formula from Können et al. (2003). For more details, see Przybylek et al. (2013). Wind speed was converted to m∙s-1 using the Beaufort scale. For more details on the conversion, see Chmist et al. (2025). New wind speed classes were defined for each series and assigned appropriate values, see Table in wind_conversion.pdf file.References: Cappelen J (ed.) (2009) DMI monthly climate data collection 1768–2008, Denmark, The Faroe Islands and Greenland, Technical Report 09-05. Dan. Meteorol. Inst.Chmist K, Araźny A, Przybylak R, Wyszyński P, Singh G (2025) Changes in bioclimatic conditions on the coast of the Labrador Peninsula in the second half of the 18th century. Climatic Change 178:46. https://doi.org/10.1007/s10584-025-03883-xKönnen GP, Zaiki M, Baede APM, Mikami T, Jones PD, Tsukahara T (2003) Pre-1872 extension of the Japanese instrumental meteorological observation series back to 1819. Journal of Climate 16:118–131. https://doi.org/10.1175/1520-0442(2003)016<0118:PEOTJI>2.0.CO;2Przybylak R, Wyszyński P, Vizi Z, Jankowska J (2013) Atmospheric pressure changes in the Arctic, from 1801 to 1920. Int. J. Climatol. 33:1730–1760. https://doi.org/10.1002/joc.3546

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.156
Threshold uncertainty score0.310

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.198
Teacher spread0.193 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2025
Admission routes1
Has abstractyes

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