Aller au contenu principal
Accès ouvert déclaré 2026 dataset

RIME-X mask collection

0Citations signalées, ce qui n’est pas une note de qualité
5Institutions déclarées
3Pays d’affiliation déclarés

Rattachement africain : at, de, be. Niveau de preuve : code pays fourni par la source.

Le résumé fourni par la source

This dataset contains regional aggregation mask files (NetCDF4, .nc4) for use as inputs to the Rapid Impact Model Emulator eXtended (RIME-X) (Schwind et al., 2026). Version 1 contains the masks also used to process the ISIMIP variables shown in the Climate Impact Explorer (CIE); we expect to add further masks in future versions. For each region (scientific regions, countries, provinces), three mask variables are provided: a latitude-weighting mask (latWeight) a GDP-2020 mask (gdp2020) a population-2020 mask (pop2020) latWeight is derived from the cosine of latitude, a standard proxy for grid-cell area on a regular lat-lon grid. The population mask uses year-2020 gridded population data from WorldPop, described in Lloyd et al.(2019). The GDP mask uses year-2020 gridded GDP data from Kummu et al.(2025).Regional boundaries come from GADM version 3.6 shapefiles for countries and provinces, and from the regionmask package API for scientific regions. A few notes on how the masks were built: A small number of manual edits were applied, e.g., separating France from its overseas regions. The country masks are based on a dataset published in 2018, so some administrative boundaries may be outdated (e.g., the provinces of Pakistan). The masks are fractional: at border grid cells, GDP or population is weighted by the fraction of the grid cell’s area that falls within the region. For disputed borders, the masks generally follow the German government’s position from 2021. Version 2 contains ssp_population_masks.zip, including masks for the same regions as in Version 1, but with population weightings and total population counts per grid cell (the popWeight and populationFull files) for each SSP scenario and decade from 2020 to 2100. These are derived from Werning, 2024 by distributing each grid cell's population across the regions that contain it. Population is assumed to exist only on land, so each region's share of a grid cell's population is set in proportion to that region's share of the cell's land area, not the cell's total area: a region covering half a grid cell that is otherwise entirely sea still receives 100% of that cell's population, while a grid cell split among several regions has its population divided in proportion to each region's share of the cell's land area. Files are currently under restricted access pending internal review. Please contact the depositor to request access. Use at your own risk!

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.

Le contrôle bibliographique ouvert

La source scientifique ouverte est momentanément indisponible.

Où se fait cette recherche

  • International Institute for Applied Systems Analysis pays non établi dans la notice
    Organisation à but non lucratif
  • Humboldt-Universität zu Berlin pays non établi dans la notice
    Université ou école supérieure
  • Leipzig University pays non établi dans la notice
    Université ou école supérieure
  • Vrije Universiteit Brussel pays non établi dans la notice
    Université ou école supérieure
  • Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung pays non établi dans la notice
    Structure de recherche
  • Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research pays non établi dans la notice
    Structure de recherche

International Institute for Applied Systems Analysis, Humboldt-Universität zu Berlin et Leipzig University, avec 3 autres affiliations.

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

BNTIC News n’est pas le producteur de ces données. Les publications sont interrogées à la demande dans Crossref, OpenAIRE, DOAJ, Europe PMC, HAL, DataCite, AfricArXiv, ROR et la Banque mondiale, sans clé d’accès. OpenAlex reste optionnel. Aucun service payant n’est nécessaire et aucune donnée externe n’est enregistrée en base. Consulter les sources et leurs limites.