Climate Change Scenarios in the Southern Caribbean region of Central America
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Notice bibliographique
Résumé
Introduction: Warming is already significant in Central America and the Caribbean and may be magnified even further in the future. A decrease in the precipitation is projected, increasing also regional aridity. Objective: To study observed and projected latitudinal gradients for precipitation and temperature in three Southern Caribbean locations of Central America: Bluefields (Nicaragua), Limón (Costa Rica) and Bocas del Toro (Panamá) and to characterize their future changes and determine if there are differences or similarities in a north-south direction. Methods: Monthly precipitation (P) and temperature (T) data from General Circulation Models from 1979 to 2099, were downloaded from the WRF repository. Data from the selected models from the repository were subjected to a delta-type statistical downscaling to bring them to a resolution of 1 x 1 km. These models are part of the latest generation of the Coupled Model Intercomparison Project-Phase 6 used by the Intergovernmental Panel on Climate Change. The ground-truth data necessary for bias correction were obtained from the ERA5 reanalysis. Monthly P and T data were downloaded from 1979 to 2014 at different native spatial resolutions and climatologies at 1 x 1 km spatial resolution at global scales were obtained from WorldClim data. Results: Scenarios show that some regions would go from very humid to humid, based on strong reductions in precipitation and warming at the end of the 21st century. This expected increase in the aridity is going to have impacts on ecology and ecosystem services, agriculture, human consumption due to a water availability reduction per capita and hydroelectric generation. Conclusions: Generation of high spatial Climate Change scenarios is necessary because Central America is a region characterized by significant topographic complexity, land use variety and spatial occurrence of hydrometeorological disasters. This intrinsic variability suggests that local risk management and planning strategies must be designed with a highly specific approach to each locality or region. This implies that, even in areas geographically near to each other, the measures taken may not necessarily be transferable due to differences in climate projections, as it was found for the three nearby communities in the Southern Central American Caribbean coastal region.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 découle