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Appears in Collections:University of Stirling Research Data
Title: A seasonal classification system interpolating biomes within the year for improved temporal aggregation
Creator(s): Littleboy, Chris
Bunnefeld, Nils
Subke, Jens-Arne
Jones, Isabel
Contact Email:
Keywords: Seasons
Date Available: 22-Jan-2024
Citation: Littleboy, C; Bunnefeld, N; Subke, JA; Jones, I (2024): A seasonal classification system interpolating biomes within the year for improved temporal aggregation. Version 1.0. University of Stirling. Dataset.
Publisher: University of Stirling. School of Natural Sciences.
Dataset Description (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.
Dataset Description (TOC): Every 8km x 8km grid cell on land (projected using Equal Earth) is assigned a climate zone and twelve seasons for each month of the year. The seasons .tif is coded: 1 - Winter; 2 - Spring; 3 - Summer; 4 Autumn; 5 - Hotter; 6 - Cooler; 7 - Dry; 8 - Wet. The climate zone .tif is coded: 1 - Arctic and high montane; 2 - Desert; 3 - Tropical; 4 - Temperate. Alternatively, you can download a .txt with all data in comma separated format.
Type: dataset
Contract/Grant Title: The Beacon Project: Using Biodiversity and Energy justice to resolve Conflicts between Sustainable Development Goals
Funder(s): UKRI Future Leader Fellowship
MRC – Medical Research Council
Contract/Grant Number: MR/T019018/1
Worktribe Project ID: 1244952
Geographic Location(s): Global
Rights: Rights covered by the standard CC-BY 4.0 licence:
Affiliation(s) of Dataset Creator(s): University of Stirling (BES)

Files in This Item:
File Description SizeFormat 
season.tif13.54 MBTIFFView/Open
type.tif1.4 MBTIFFView/Open
seasons_data.txt161.52 MBTextView/Open

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