The response of southern African vegetation to droughts in past and future climates

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 vegetation index is higher than 0.8 over southeastern part of the region at 3-month drought timescale, and there is no difference between the spatial distribution of the correlation between the SPEI and the vegetation index, and between the SPI and the vegetation index. The three DGVMs failed to capture the response of vegetation to drought; however, the CLM4 shows the best performance while ORCHIDEELSCE fared the worst of the three. The CLM4 simulation show that fire strongly influences growth of vegetation over the summer rainfall region but it has weak influence over vegetation in the western arid zone. The CESM strongly captures the spatial patterns of precipitation and the vegetation index across southern Africa, but it overestimates the magnitudes of the vegetation index across the region, except in Namibia and Angola. The CESM also underestimates the correlation between drought indexes with vegetation, and the timescales at which the vegetation respond to droughts. The CESM projects an increase in the drought intensity as a result of an increased temperature across southern African biomes. However the increase in drought intensity is more pronounced with the SPEI than with the SPI. CESM also projects a future decrease in the vegetation index (i.e. NDVI) in the region except in the dry savanna biome. The impacts of 1.5oC GWLs on the vegetation fluxes vary throughout southern Africa, and the magnitudes of changes in the vegetation fluxes are affected by a further increase in global warming over the region. While there is a good agreement among the CESM simulations on the projected changes in vegetation fluxes across the biomes, the uncertainty in the projections is higher with 1.5oC than with 2.0oC GWL. The results of the study can be applied to mitigate the impacts of climate variability and change on southern African vegetation. Specific mitigation efforts that could be applied to reduce the impacts of droughts and climate change are watershed management, improved vegetation management, impact monitoring, environmental awareness, and remote sensing tools

The terrestrial biosphere model farm

Model Intercomparison Projects (MIPs) are fundamental to our understanding of how the land surface responds to changes in climate. However, MIPs are challenging to conduct, requiring the organization of multiple, decentralized modeling teams throughout the world running common protocols. We explored centralizing these models on a single supercomputing system. We ran nine offline terrestrial biosphere models through the Terrestrial Biosphere Model Farm: CABLE, CENTURY, HyLand, ISAM, JULES, LPJ-GUESS, ORCHIDEE, SiB-3, and SiB-CASA. All models were wrapped in a software framework driven with common forcing data, spin-up, and run protocols specified by the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) for years 1901–2100. We ran more than a dozen model experiments. We identify three major benefits and three major challenges. The benefits include: (a) processing multiple models through a MIP is relatively straightforward, (b) MIP protocols are run consistently across models, which may reduce some model output variability, and (c) unique multimodel experiments can provide novel output for analysis. The challenges are: (a) technological demand is large, particularly for data and output storage and transfer; (b) model versions lag those from the core model development teams; and (c) there is still a need for intellectual input from the core model development teams for insight into model results. A merger with the open-source, cloud-based Predictive Ecosystem Analyzer (PEcAn) ecoinformatics system may be a path forward to overcoming these challenges

Assessing Future Spatio-Temporal Changes in Crop Suitability and Planting Season over West Africa: Using the Concept of Crop-Climate Departure

The changing climate is posing significant threats to agriculture, the most vulnerable sector, and the main source of livelihood in West Africa. This study assesses the impact of the climate-departure on the crop suitability and planting month over West Africa. We used 10 CMIP5 Global climate models bias-corrected simulations downscaled by the CORDEX regional climate model, RCA4 to drive the crop suitability model, Ecocrop. We applied the concept of the crop-climate departure (CCD) to evaluate future changes in the crop suitability and planting month for five crop types, cereals, legumes, fruits, root and tuber and horticulture over the historical and future months. Our result shows a reduction (negative linear correlation) and an expansion (positive linear correlation) in the suitable area and crop suitability index value in the Guinea-Savanna and Sahel (southern Sahel) zone, respectively. The horticulture crop was the most negatively affected with a decrease in the suitable area while cereals and legumes benefited from the expansion in suitable areas into the Sahel zone. In general, CCD would likely lead to a delay in the planting season by 2–4 months except for the orange and early planting dates by about 2–3 months for cassava. No projected changes in the planting month are observed for the plantain and pineapple which are annual crops. The study is relevant for a short and long-term adaptation option and planning for future changes in the crop suitability and planting month to improve food security in the region

The African Regional Greenhouse Gases Budget (2010–2019)

International audienceAbstract As part of the REgional Carbon Cycle Assessment and Processes Phase 2 (RECCAP2) project, we developed a comprehensive African Greenhouse gases (GHG) budget covering 2000 to 2019 (RECCAP1 and RECCAP2 time periods), and assessed uncertainties and trends over time. We compared bottom‐up process‐based models, data‐driven remotely sensed products, and national GHG inventories with top‐down atmospheric inversions, accounting also for lateral fluxes. We incorporated emission estimates derived from novel methodologies for termites, herbivores, and fire, which are particularly important in Africa. We further constrained global woody biomass change products with high‐quality regional observations. During the RECCAP2 period, Africa's carbon sink capacity is decreasing, with net ecosystem exchange switching from a small sink of −0.61 ± 0.58 PgC yr −1 in RECCAP1 to a small source in RECCAP2 at 0.16 (−0.52/1.36) PgC yr −1 . Net CO 2 emissions estimated from bottom‐up approaches were 1.6 (−0.9/5.8) PgCO 2 yr −1 , net CH 4 were 77 (56.4/93.9) TgCH 4 yr −1 and net N 2 O were 2.9 (1.4/4.9) TgN 2 O yr −1 . Top‐down atmospheric inversions showed similar trends. Land Use Change emissions increased, representing one of the largest contributions at 1.7 (0.8/2.7) PgCO 2 eq yr −1 to the African GHG budget and almost similar to emissions from fossil fuels at 1.74 (1.53/1.96) PgCO 2 eq yr −1 , which also increased from RECCAP1. Additionally, wildfire emissions decreased, while fuelwood burning increased. For most component fluxes, uncertainty is large, highlighting the need for increased efforts to address Africa‐specific data gaps. However, for RECCAP2, we improved our overall understanding of many of the important components of the African GHG budget that will assist to inform climate policy and action

The African Regional Greenhouse Gases Budget (2010–2019)

As part of the REgional Carbon Cycle Assessment and Processes Phase 2 (RECCAP2) project, we developed a comprehensive African Greenhouse gases (GHG) budget covering 2000 to 2019 (RECCAP1 and RECCAP2 time periods), and assessed uncertainties and trends over time. We compared bottom‐up process‐based models, data‐driven remotely sensed products, and national GHG inventories with top‐down atmospheric inversions, accounting also for lateral fluxes. We incorporated emission estimates derived from novel methodologies for termites, herbivores, and fire, which are particularly important in Africa. We further constrained global woody biomass change products with high‐quality regional observations. During the RECCAP2 period, Africa's carbon sink capacity is decreasing, with net ecosystem exchange switching from a small sink of −0.61 ± 0.58 PgC yr−1 in RECCAP1 to a small source in RECCAP2 at 0.16 (−0.52/1.36) PgC yr−1. Net CO2 emissions estimated from bottom‐up approaches were 1.6 (−0.9/5.8) PgCO2 yr−1, net CH4 were 77 (56.4/93.9) TgCH4 yr−1 and net N2O were 2.9 (1.4/4.9) TgN2O yr−1. Top‐down atmospheric inversions showed similar trends. Land Use Change emissions increased, representing one of the largest contributions at 1.7 (0.8/2.7) PgCO2eq yr−1 to the African GHG budget and almost similar to emissions from fossil fuels at 1.74 (1.53/1.96) PgCO2eq yr−1, which also increased from RECCAP1. Additionally, wildfire emissions decreased, while fuelwood burning increased. For most component fluxes, uncertainty is large, highlighting the need for increased efforts to address Africa‐specific data gaps. However, for RECCAP2, we improved our overall understanding of many of the important components of the African GHG budget that will assist to inform climate policy and action.</p