Uncertainties of climate and CO2 impacts on carbon stocks and biome distribution in Africa

2020 ◽  
Author(s):  
Carola Martens ◽  
Thomas Hickler ◽  
Claire Davis-Reddy ◽  
Francois Engelbrecht ◽  
Steven I. Higgins ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
General Circulation Models ◽  
Woody Encroachment ◽  
Strong Increase ◽  
Climate Mitigation ◽  
Climate Modelling ◽  
Dynamic Global Vegetation Model ◽  
Mitigation And Adaptation ◽  
Rcp 8.5

<p>Climate change is expected to cause vegetation change in Africa, with profound impacts on ecosystems and biodiversity. Projections of future ecosystem states are constrained by uncertainties regarding relative impacts of climate change and CO<sub>2</sub> fertilisation effects. Rising atmospheric CO<sub>2</sub> drives climate change, but also directly affects plant physiological functions via carbon uptake, carbon allocation, water use efficiency, and growth. We use the adaptive Dynamic Global Vegetation Model (aDGVM) to quantify uncertainties in projected African vegetation until 2099. High-resolution climate forcing for the aDGVM, was generated by regional climate modelling. An ensemble of 24 aDGVM simulations based on six downscaled General Circulation Models (GCMs) under two Representative Concentration Pathways (RCPs 4.5 and 8.5) with plant-physiological CO<sub>2</sub> effects enabled and disabled was implemented.</p><p>Under strong climatic change with high CO<sub>2</sub> increases (RCP 8.5), almost a third of terrestrial Africa is projected to experience biome changes with woody encroachment into grassy biomes dominating biome changes. Projections under medium-impact scenarios (RCP 4.5) still predict biome changes for around a quarter of Africa. With climate change only and elevated-CO<sub>2</sub> effects disabled, woody encroachment is weak and reduction of forest cover in favour of savannas prevails. Change in aboveground vegetation carbon until 2099 varied from a strong increase under elevated CO<sub>2 </sub>(61.5%, RCP 8.5; 33.9%, RCP 4.5) to a small increase of 5.4% (RCP 4.5) and a decrease of -13.6% (RCP 8.5) without CO<sub>2</sub> effects.</p><p>CO<sub>2</sub> effects in combination with RCP scenarios caused the greatest uncertainty in projected ecosystem changes. Downscaled GCM projections caused weaker uncertainties in the simulations. Future biome changes due to climate and CO<sub>2</sub> change are therefore likely in large parts of Africa. Their magnitude and location often remain uncertain. Climate mitigation and adaptation response measures that rely upon vegetation-derived ecosystem services will need to account for alternative climate futures.</p>

scholarly journals Climatic suitability predictions for the cultivation of macadamia in Malawi using climate change scenarios.

2021 ◽  
Author(s):  
Emmanuel Junior Zuza ◽  
Yoseph Negusse Araya ◽  
Kadmiel Maseyk ◽  
Shonil A Bhagwat ◽  
Kaue de Sousa ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
General Circulation Models ◽  
Food Sources ◽  
Climate Change Scenarios ◽  
Crop Species ◽  
Cascading Effects ◽  
Northern Regions ◽  
Rcp 8.5 ◽  
Model Approach

Climate change is altering suitable areas of crop species worldwide, with cascading effects on people and animals reliant upon those crop species as food sources. Macadamia is one of Malawi's most important and profitable crop species. Here, we used an ensemble model approach to determine the current distribution of macadamia producing areas across Malawi in relation to climate. For future distribution of suitable areas, we used the climate outputs of 17 general circulation models (GCM's) based on two climate change scenarios (RCP 4.5 and RCP 8.5). We found that the precipitation of the driest month and isothermality were the climatic variables that strongly influenced macadamia's suitability in Malawi. These climatic requirements were fulfilled across many areas in Malawi under the current conditions. Future projections indicated that large parts of Malawi's macadamia growing regions will remain suitable for macadamia, amounting to 36,910 km2 (39.1%) and 33,511 km2 (35.5%) of land based on RCP 4.5 and RCP 8.5, respectively. Of concern, suitable areas for macadamia production are predicted to shrink by −18% (17,015 km2) and −22% (20,414 km2) based on RCP 4.5 and RCP 8.5, respectively, with much of the suitability shifting northwards. Although a net loss of area suitable for macadamia is predicted, some currently unsuitable areas will become suitable in the future. Notably, suitable areas will increase in Malawi's central and northern regions, while the southern region will lose most of its suitable areas. In conclusion, our study provides critical evidence that climate change will significantly affect the macadamia sub-sector in Malawi. Therefore area-specific adaptation strategies are required to build resilience.

scholarly journals Evaluation of a Unique Approach to High-Resolution Climate Modelling using the Model for Prediction Across Scales (MPAS) version 5.1

2019 ◽  
Author(s):  
Allison C. Michaelis ◽  
Gary M. Lackmann ◽  
Walter A. Robinson
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Sea Ice ◽  
Northern Hemisphere ◽  
General Circulation ◽  
Southern Oscillation ◽  
Spatial Scales ◽  
General Circulation Models ◽  
Climate Modelling ◽  
Northern Hemispheric

Abstract. We present multi-seasonal simulations representative of present-day and future thermodynamic environments using the global Model for Prediction Across Scales-Atmosphere (MPAS) version 5.1 with high resolution (15 km) throughout the Northern Hemisphere. We select ten simulation years with varying phases of El Niño-Southern Oscillation (ENSO) and integrate each for 14.5 months. We use analysed sea surface temperature (SST) patterns for present-day simulations. For the future climate simulations, we alter present-day SSTs by applying monthly-averaged temperature changes derived from a 20-member ensemble of Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs) following the Representative Concentration Pathway (RCP) 8.5 emissions scenario. Daily sea ice fields, obtained from the monthly-averaged CMIP5 ensemble mean sea ice, are used for present-day and future simulations. The present-day simulations provide a reasonable reproduction of large-scale atmospheric features in the Northern Hemisphere such as the wintertime midlatitude storm tracks, upper-tropospheric jets, and maritime sea-level pressure features as well as annual precipitation patterns across the tropics. The simulations also adequately represent tropical cyclone (TC) characteristics such as strength, spatial distribution, and seasonal cycles for most of Northern Hemispheric basins. These results demonstrate the applicability of these model simulations for future studies examining climate change effects on various Northern Hemispheric phenomena, and, more generally, the utility of MPAS for studying climate change at spatial scales generally unachievable in GCMs.

scholarly journals Climate versus carbon dioxide controls on biomass burning: a model analysis of the glacial–interglacial contrast

2014 ◽  
Vol 11 (21) ◽  
pp. 6017-6027 ◽  
Author(s):  
M. Martin Calvo ◽  
I. C. Prentice ◽  
S. P. Harrison
Keyword(s):  
Climate Change ◽  
Primary Production ◽  
Biomass Burning ◽  
Land Surface ◽  
General Circulation ◽  
Co2 Concentration ◽  
General Circulation Models ◽  
Fuel Load ◽  
Substantial Part ◽  
Dynamic Global Vegetation Model

Abstract. Climate controls fire regimes through its influence on the amount and types of fuel present and their dryness. CO2 concentration constrains primary production by limiting photosynthetic activity in plants. However, although fuel accumulation depends on biomass production, and hence on CO2 concentration, the quantitative relationship between atmospheric CO2 concentration and biomass burning is not well understood. Here a fire-enabled dynamic global vegetation model (the Land surface Processes and eXchanges model, LPX) is used to attribute glacial–interglacial changes in biomass burning to an increase in CO2, which would be expected to increase primary production and therefore fuel loads even in the absence of climate change, vs. climate change effects. Four general circulation models provided last glacial maximum (LGM) climate anomalies – that is, differences from the pre-industrial (PI) control climate – from the Palaeoclimate Modelling Intercomparison Project Phase~2, allowing the construction of four scenarios for LGM climate. Modelled carbon fluxes from biomass burning were corrected for the model's observed prediction biases in contemporary regional average values for biomes. With LGM climate and low CO2 (185 ppm) effects included, the modelled global flux at the LGM was in the range of 1.0–1.4 Pg C year-1, about a third less than that modelled for PI time. LGM climate with pre-industrial CO2 (280 ppm) yielded unrealistic results, with global biomass burning fluxes similar to or even greater than in the pre-industrial climate. It is inferred that a substantial part of the increase in biomass burning after the LGM must be attributed to the effect of increasing CO2 concentration on primary production and fuel load. Today, by analogy, both rising CO2 and global warming must be considered as risk factors for increasing biomass burning. Both effects need to be included in models to project future fire risks.

scholarly journals Assessing the Spatial Pattern of Irrigation Demand under Climate Change in Arid Area

2020 ◽  
Vol 9 (9) ◽  
pp. 506
Author(s):  
Liping Wang ◽  
Shufang Wang ◽  
Liudong Zhang ◽  
Mohamed Khaled Salahou ◽  
Xiyun Jiao ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Spatial Pattern ◽  
General Circulation ◽  
General Circulation Models ◽  
Northwest China ◽  
Arid Areas ◽  
Irrigation Demand ◽  
Balance System ◽  
Rcp 8.5

Studying the pattern of agricultural water demand under climate change has great significance for the regional water resources management, especially in arid areas. In this study, the future pattern of the irrigation demand in Hotan Oasis in Xinjiang Uygur Autonomous Region in Northwest China, including Hotan City, Hotan County, Moyu County and Luopu County, was assessed based on the general circulation models (GCMs) and the Surface Energy Balance System model (SEBS). Six different scenarios were used based on the GCMs of BCC_CSM1.1, HadGEM2-ES and MIROC-ESM-CHEM under the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5. The results showed that the method integrating the GCMs and SEBS to predict the spatial pattern was useful. The irrigation demand of Hotan Oasis will increase in 2021–2040. The annual irrigation demand of Hotan City is higher, with 923.2 and 936.2 mm/a in 2021–2030 and 2031–2040, respectively. The other three regions (Hotan County, Moyu County and Luopu County) are lower in the six scenarios. The annual irrigation demand showed a spatial pattern of high in the middle, low in the northwest and southeast under the six scenarios in 2021–2040. The study can provide useful suggestions on the water resources allocation in different regions to protect water resources security in arid areas.

Future climate change risk to forests in China responding to intensified dryness

2020 ◽  
Author(s):  
Yunhe Yin ◽  
Danyang Ma ◽  
Shaohong Wu
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Net Primary Productivity ◽  
Emission Scenario ◽  
General Circulation Models ◽  
Future Climate Change ◽  
Ecosystem Structure ◽  
Dynamic Global Vegetation Model ◽  
Climate Change Risk ◽  
The Impact

<p>Variations in forest net primary productivity (NPP) reflects the combined effects of key climate variables on ecosystem structure and function, especially on the carbon cycle. We performed risk analysis indicated by the magnitude of future negative anomalies in NPP in comparison with the natural interannual variability to investigate the impact of future climatic projections on forests in China. The analysis was conducted mainly based on modifying the Lund–Potsdam–Jena Dynamic Global Vegetation Model, which was driven by five general circulation models (GCMs) simulations. Results from the multi-model ensemble showed that climate change risk of decreases in forest NPP would be more significant in higher emission scenario in China. Under relatively low emission scenarios, the total area of risk was predicted to decline, while for RCP8.5, it was predicted to first decrease and then increase after the middle of 21st century. The rapid temperature increases predicted under the RCP8.5 scenario would be probably unfavorable for forest vegetation growth in the long term. High-level risk area was likely to increase except RCP2.6. The percentage area at high risk was predicted to increase from 5.39% (2021–2050) to 27.62% (2071–2099) under RCP8.5. Climate change risk to forests was mostly concentrated in southern subtropical and tropical regions, generally significant under high emission scenario of RCP8.5, which was mainly attributed to the intensified dryness in south China.</p>

scholarly journals Climate Change Projections of Temperature Over the Coastal Area of China Using SimCLIM

2021 ◽  
Vol 9 ◽  
Author(s):  
Xiaoli Wang ◽  
Xiyong Hou ◽  
Yingchao Piao ◽  
Aiqing Feng ◽  
Yinpeng Li
Keyword(s):  
Climate Change ◽  
Coastal Area ◽  
General Circulation ◽  
Large Population ◽  
General Circulation Models ◽  
Maximum Temperature ◽  
Adaptation Measures ◽  
Temperature Changes ◽  
Mitigation And Adaptation ◽  
The Future

Facing the western Pacific Ocean and backed by the Eurasian continent, the coastal area of China (hereafter as CAC) is sensitive and vulnerable to climate change due to the compound effects of land-ocean-atmosphere, and thus is prone to suffer huge climate-related disaster losses because of its large population density and fast developed economy in the context of global warming. Here in this study the near- (2040), mid- (2070), and long-future (2100) mean, minimum, and maximum temperature (Tmean, Tmin, and Tmax) projections based on the statistic downscaling climate prediction model (SimCLIM) integrated with 44 General Circulation Models (GCMs) of CMIP5 under three representative concentration pathway (RCP4.5, RCP6.0, and RCP8.5) scenarios are evaluated over CAC and its sub-regions. Multi-model ensemble of the selected GCMs demonstrated that there was a dominating and consistent warming trend of Tmean, Tmin, and Tmax in the Chinese coastal area in the future. Under RCP4.5, RCP6.0, and RCP8.5 scenarios, the annual temperature increase was respectively projected to be in the range of 0.8–1.2°C for 2040, 1.5–2.7°C for 2070, and 1.6–4.4°C for 2100 over the entire CAC. Moreover, a spatial differentiation of temperature changes both on the sub-regional and meteorological station scales was also revealed, generally showing an increment with “high south and low north” for annual average Tmean but “high north and low south” for Tmin and Tmax. An obvious lower increase of Tmean in the hotter months like July and August in the south and a significant sharper increment of Tmin and Tmax in the colder months such as January, February, and December in the north were expected in the future. Results derived from this study are anticipated to provide insights into future temperature changes and also assist in the development of target climate change mitigation and adaptation measures in the coastal area of China.

scholarly journals Climate vs. carbon dioxide controls on biomass burning: a model analysis of the glacial-interglacial contrast

2014 ◽  
Vol 11 (2) ◽  
pp. 2569-2593 ◽  
Author(s):  
M. Martin Calvo ◽  
I. C. Prentice ◽  
S. P. Harrison
Keyword(s):  
Climate Change ◽  
Primary Production ◽  
Biomass Burning ◽  
Land Surface ◽  
General Circulation ◽  
Co2 Concentration ◽  
General Circulation Models ◽  
Fuel Load ◽  
Substantial Part ◽  
Dynamic Global Vegetation Model

Abstract. Climate controls fire regimes through its influence on the amount and types of fuel present and their dryness; CO2 availability, in turn, constrains primary production by limiting photosynthetic activity in plants. However, although fuel accumulation depends on biomass production, and hence CO2 availability, the links between atmospheric CO2 and biomass burning are not well known. Here a fire-enabled dynamic global vegetation model (the Land surface Processes and eXchanges model, LPX) is used to attribute glacial-interglacial changes in biomass burning to CO2 increase, which would be expected to increase primary production and therefore fuel loads even in the absence of climate change, vs. climate change effects. Four general circulation models provided Last Glacial Maximum (LGM) climate anomalies – that is, differences from the pre-industrial (PI) control climate – from the Palaeoclimate Modelling Intercomparison Project Phase 2, allowing the construction of four scenarios for LGM climate. Modelled carbon fluxes in biomass burning were corrected for the model's observed biases in contemporary biome-average values. With LGM climate and low CO2 (185 ppm) effects included, the modelled global flux was 70 to 80% lower at the LGM than in PI time. LGM climate with pre-industrial CO2 (280 ppm) however yielded unrealistic results, with global and Northern Hemisphere biomass burning fluxes greater than in the pre-industrial climate. Using the PI CO2 concentration increased the modelled LGM biomass burning fluxes for all climate models and latitudinal bands to between four and ten times their values under LGM CO2 concentration. It is inferred that a substantial part of the increase in biomass burning after the LGM must be attributed to the effect of increasing CO2 concentration on productivity and fuel load. Today, by analogy, both rising CO2 and global warming must be considered as risk factors for increasing biomass burning. Both effects need to be included in models to project future fire risks.

scholarly journals Emerging role of wetland methane emissions in driving 21st century climate change

2017 ◽  
Vol 114 (36) ◽  
pp. 9647-9652 ◽  
Author(s):  
Zhen Zhang ◽  
Niklaus E. Zimmermann ◽  
Andrea Stenke ◽  
Xin Li ◽  
Elke L. Hodson ◽  
...  
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Radiative Forcing ◽  
General Circulation ◽  
General Circulation Models ◽  
Cold Season ◽  
Climate Mitigation ◽  
Climate Feedbacks ◽  
Intergovernmental Panel ◽  
Worst Case

Wetland methane (CH4) emissions are the largest natural source in the global CH4 budget, contributing to roughly one third of total natural and anthropogenic emissions. As the second most important anthropogenic greenhouse gas in the atmosphere after CO2, CH4 is strongly associated with climate feedbacks. However, due to the paucity of data, wetland CH4 feedbacks were not fully assessed in the Intergovernmental Panel on Climate Change Fifth Assessment Report. The degree to which future expansion of wetlands and CH4 emissions will evolve and consequently drive climate feedbacks is thus a question of major concern. Here we present an ensemble estimate of wetland CH4 emissions driven by 38 general circulation models for the 21st century. We find that climate change-induced increases in boreal wetland extent and temperature-driven increases in tropical CH4 emissions will dominate anthropogenic CH4 emissions by 38 to 56% toward the end of the 21st century under the Representative Concentration Pathway (RCP2.6). Depending on scenarios, wetland CH4 feedbacks translate to an increase in additional global mean radiative forcing of 0.04 W·m−2 to 0.19 W·m−2 by the end of the 21st century. Under the “worst-case” RCP8.5 scenario, with no climate mitigation, boreal CH4 emissions are enhanced by 18.05 Tg to 41.69 Tg, due to thawing of inundated areas during the cold season (December to May) and rising temperature, while tropical CH4 emissions accelerate with a total increment of 48.36 Tg to 87.37 Tg by 2099. Our results suggest that climate mitigation policies must consider mitigation of wetland CH4 feedbacks to maintain average global warming below 2 °C.

scholarly journals Mid-Holocene climate change in Europe: a data-model comparison

2007 ◽  
Vol 3 (3) ◽  
pp. 499-512 ◽  
Author(s):  
S. Brewer ◽  
J. Guiot ◽  
F. Torre
Keyword(s):  
Climate Change ◽  
Data Model ◽  
General Circulation ◽  
Model Comparison ◽  
General Circulation Models ◽  
Growing Degree Days ◽  
Degree Days ◽  
European Continent ◽  
Holocene Climate Change ◽  
Correct Location

Abstract. We present here a comparison between the outputs of 25 General Circulation Models run for the mid-Holocene period (6 ka BP) with a set of palaeoclimate reconstructions based on over 400 fossil pollen sequences distributed across the European continent. Three climate parameters were available (moisture availability, temperature of the coldest month and growing degree days), which were grouped together using cluster analysis to provide regions of homogenous climate change. Each model was then investigated to see if it reproduced 1) similar patterns of change and 2) the correct location of these regions. A fuzzy logic distance was used to compare the output of the model with the data, which allowed uncertainties from both the model and data to be taken into account. The models were compared by the magnitude and direction of climate change within the region as well as the spatial pattern of these changes. The majority of the models are grouped together, suggesting that they are becoming more consistent. A test against a set of zero anomalies (no climate change) shows that, although the models are unable to reproduce the exact patterns of change, they all produce the correct signs of change observed for the mid-Holocene.

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