Evidence map›Paper›PMID 39191780›Full record

ArticleScientific data2024

WorldSeasons: a seasonal classification system interpolating biome classifications within the year for better temporal aggregation in climate science.

Chris Littleboy, Jens-Arne Subke, Nils Bunnefeld, Isabel L Jones

Abstract read
In one paragraph

Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Chris LittleboyBiological & Environmental Sciences, Faculty of Natural Sciences, University of Stirling, Stirling, United Kingdom. chris.littleboy@stir.ac.uk.ORCID http://orcid.org/0000-0002-3293-7987
Jens-Arne SubkeBiological & Environmental Sciences, Faculty of Natural Sciences, University of Stirling, Stirling, United Kingdom.
Nils BunnefeldBiological & Environmental Sciences, Faculty of Natural Sciences, University of Stirling, Stirling, United Kingdom.
Isabel L JonesBiological & Environmental Sciences, Faculty of Natural Sciences, University of Stirling, Stirling, United Kingdom.ORCID http://orcid.org/0000-0002-8361-1370

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present a seasonal classification system to improve the temporal framing of comparative scientific analysis. Research often uses yearly aggregates to understand inherently seasonal phenomena like harvests, monsoons, and droughts. This obscures important trends across time and differences through space by including redundant data. Our classification system allows for a more targeted approach. We split global land into four principal climate zones: desert, arctic and high montane, tropical, and temperate. A cluster analysis with zone-specific variables and weighting splits each month of the year into discrete seasons based on the monthly climate. We expect the data will be able to answer global comparative analysis questions like: are global winters less icy than before? Are wildfires more frequent now in the dry season? How severe are monsoon season flooding events? This is a natural extension of the historical concept of biomes, made possible by recent advances in climate data availability and artificial intelligence.

Identifiers

PMID39191780
PMCPMC11350142

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.