نبذة مختصرة : Drought and climate change pose a threat to southern African vegetation. This study examines the response of southern African vegetation to drought in both past and future climates. Multiyear and multi-simulation datasets from three dynamic global vegetation models (DGVMs), namely, Community Land Model version 4 (CLM4), Community Land Model version 4 with Variable Infiltration Capacity hydrology (CLM4VIC), and Organising Carbon and Hydrology in Dynamic Ecosystems designed by Laboratoire des Sciences du Climat et de l’Environnement (ORCHIDEE-LSCE). These three DGVMs and the Community Earth System Model (CESM) were analyzed for the study. The DGVM simulations were forced with the reanalysis climate dataset from the National Centers for Environmental Prediction (NCEP) and the Climatic Research Unit - NCEP (CRUNCEP). The simulated climate results were evaluated with observation datasets from the Climatic Research Unit (CRU), while the simulated vegetation index (i.e. Normalized Difference Vegetation Index, NDVI) were evaluated with NDVI data from the Global Inventory Modelling and Mapping Studies (GIMMS). Meteorological droughts were analyzed at different timescales (1- to 18-month timescales), using two drought indexes: the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Precipitation Index (SPI). The responses of vegetation to drought were quantified by means of Pearson Correlation Analysis. The DGVMs were applied to study the sensitivity of vegetation to fire, while the CESM was used to project impact of climate change on the characteristics of southern African vegetation in the future (up to the year 2100) under the 8.5 Representative Concentration Pathway (RCP8.5) scenario, focusing on impacts at 1.5oC and 2.0oC global warming levels (GWLs). Analysis of the observed data shows that the spatial distribution of vegetation across southern Africa is more influenced by the rainfall distribution than by the temperature distribution. The observed correlation between drought index and ...
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