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Record W4400345486 · doi:10.5194/ems2024-891

A gridded data set to study historical climate impacts in Switzerland since 1763

2024· preprint· en· W4400345486 on OpenAlexaboutno aff
Noemi Imfeld, Brönnimann Stefan

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
Fundersnot available
KeywordsClimatologyData setEnvironmental scienceClimate changeSet (abstract data type)MeteorologyGeographyPhysical geographyGeologyComputer scienceMathematicsStatisticsOceanography

Abstract

fetched live from OpenAlex

For Switzerland, high-resolution gridded data of daily mean temperature and daily precipitation sums have recently been developed based on a large amount of early instrumental data for a period from 1763 to 1960. These temperature and precipitation fields were reconstructed with the analogue resampling method and subsequently improved using data assimilation for the temperature fields and bias correction for the precipitation fields. This new data set together with present-day meteorological fields since 1961 allows us to study a wide range of historical extreme weather events in Switzerland and their impacts on past societies. However, to study the impact of historical weather events in more detail, other variables are often needed, such as sunshine duration, wind speed, and humidity, but also minimum and maximum temperature.Here, we present the daily gridded Swiss reconstruction of daily temperature and precipitation, as well as the extension of the Swiss reconstruction to more variables, focusing mainly on sunshine duration, relative humidity, and wind speed. These additional reconstructions are based as well on the analogue resampling method, however, with a partly different reference period for the analogue pool compared to the temperature and precipitation reconstructions, and with a different data source for the resampled field. The extended Swiss gridded reconstructions make it possible to perform impact studies of historical weather and climate events, for example through agricultural modelling and calculating impact-based indices.Furthermore, we explore the potential of the extended reconstructions by evaluating historical and contemporary wildfire events in Switzerland. Wildfires are analysed using commonly used fire weather indices, such as the Canadian Fire Weather Index. We compare these indices with historical documents reporting on the fire events in Switzerland and, where possible, with the synoptic conditions over Switzerland and Europe leading up to the event.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.059
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.002

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 head0.082
GPT teacher head0.320
Teacher spread0.238 · 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 designSimulation or modeling
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
Published2024
Admission routes1
Has abstractyes

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