Climate Solutions Explorer - hazard, impacts and exposure data
Notice bibliographique
Résumé
This is a pre-release dataset and is subject to change. The Climate Solutions Explorer website maps and presents information about mitigation pathways, avoided climate impacts, vulnerabilities and risks arising from development and climate change. www.climate-solutions-explorer.eu Using the latest data, state-of-the-art models were used to assess the future trends of indicators of development- and climate-induced challenges. Updated gridded global climate and impact model data are based on CMIP6 and CMIP5 projections, using a subset of models from the ISIMIP project that have been consistently downscaled and bias-corrected. The data includes various indicators (~30) relating to extremes of precipitation and temperature (e.g. from Expert Team on Climate Change Detection and Indices), hydrological variables including runoff and discharge, heat stress (from wet bulb temperature) events (multiple statistics and durations), and cooling degree days, as well as further indicators relating to air pollution (PM2.5 from the GAINs model), and crop yields and natural habitat land-use change (biodiversity pressure) from the GLOBIOM model. Indicators were calculated at a spatial resolution of 0.5° (approximately 50km at the equator), and subsequently spatially aggregated to the country level – from which population and land area exposure to the impacts were calculated. This has enabled the country-by-country comparison of national climate impacts and avoided exposure. Impacts were calculated at global mean temperature intervals, i.e. 1.2, 1.5, 2, 2.5, 3, and 3.5 °C, compared to a pre-industrial climate. The dataset includes: Global gridded projections (in netcdf format) of all the climate impact indicators at 0.5° spatial resolution, at global mean temperature intervals of 1.2, 1.5, 2, 2.5, 3, and 3.5 °C Tabular data (Excel .csv) is also provided, aggregating the impact indicators to the country level, for both hazards and exposure (both population and land) Further details on the methodology and indicator definitions are available on the Data Story page – www.climate-solutions-explorer.eu/story/data. Release Notes (v0.3) Changes in this version: Heatwave data calculated on an annual basis instead for the entire 31-year period Tropical nights and consecutive dry days data calculated using a 2-year window to avoid cutting consecutive periods in half when calculating from January to December only Indicator scores calculated using new bivariate scoring methodology (range 0-6 instead of 0-3) R10 associations for North Macedonia and Ukraine fixed in line with R10 definitions of the IPCC Exposure and avoided impacts data based on new scoring methodology Population exposure calculated using scaled spatial population maps to match data from IIASAPOP2.0 Exposure and avoided impact csv files for R10 regions and EU merged into one file (*_R10_EU)
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».