scholarly journals Reaching 1.5 °C and 2.0 °C global surface temperature targets using stratospheric aerosol geoengineering

2019 ◽  
Author(s):  
Simone Tilmes ◽  
Douglas E. MacMartin ◽  
Jan T. M. Lenaerts ◽  
Leo van Kampenhout ◽  
Laura Muntjewerf ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Surface Air Temperature ◽  
Co2 Concentration ◽  
Stratospheric Aerosol ◽  
Meridional Overturning Circulation ◽  
Baseline Scenario ◽  
Surface Mass ◽  
Ecosystem Impacts

Abstract. We propose new testbed model experiments for the Geoengineering Model Intercomparison Project (GeoMIP) that are designed to limit global warming to 1.5 °C or 2.0 °C above 1850–1900 conditions using stratospheric aerosol geoengineering (SAG). The new modeling experiments use the overshoot scenario defined in CMIP6 (SSP5-34-OS) as a baseline scenario and are designed to reduce side effects of SAG in reaching three temperature targets: global mean surface temperature, and inter-hemispheric and pole-to-equator surface temperature gradients. We further compare results to another SAG simulation using a high emission scenario (SSP5-85) as a baseline scenario in order to investigate the dependency of impacts using different injection amounts to offset different amounts of warming by SAG. The new testbed simulations are performed with the CESM2(WACCM6). We use a feedback algorithm that identifies the needed amount of sulfur dioxide injections in the stratosphere at four predefined latitudes, 30° N, 15° N, 15° S, and 30° S, to reach the three temperature targets. Here we analyze climate variables and quantities that matter for societal and ecosystem impacts. We find that changes from present day conditions (2015–2025) in some variables depend strongly on the defined temperature target (1.5 °C vs 2.0 °C). These include surface air temperature and related impacts, the Atlantic Meridional Overturning Circulation (AMOC), which impacts ocean net primary productivity, and changes in ice sheet surface mass balance, which impacts sea-level rise. Others, including global precipitation changes and the recovery of the Antarctic ozone hole, depend strongly on the amount of SAG application. Furthermore, land net primary productivity as well as ocean acidification depend mostly on the global atmospheric CO2 concentration and therefore the baseline scenario. Multi-model comparisons of the experiments proposed here would help identify consequences of scenarios that include strong mitigation, carbon dioxide removal with some SAG application, on societal impacts and ecosystems.

scholarly journals Reaching 1.5 and 2.0 °C global surface temperature targets using stratospheric aerosol geoengineering

2020 ◽  
Vol 11 (3) ◽  
pp. 579-601 ◽  
Author(s):  
Simone Tilmes ◽  
Douglas G. MacMartin ◽  
Jan T. M. Lenaerts ◽  
Leo van Kampenhout ◽  
Laura Muntjewerf ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Stratospheric Aerosol ◽  
Meridional Overturning Circulation ◽  
Baseline Scenario ◽  
Surface Mass ◽  
Emission Pathway

Abstract. A new set of stratospheric aerosol geoengineering (SAG) model experiments has been performed with Community Earth System Model version 2 (CESM2) with the Whole Atmosphere Community Climate Model (WACCM6) that are based on the Coupled Model Intercomparison Project phase 6 (CMIP6) overshoot scenario (SSP5-34-OS) as a baseline scenario to limit global warming to 1.5 or 2.0 ∘C above 1850–1900 conditions. The overshoot scenario allows us to applying a peak-shaving scenario that reduces the needed duration and amount of SAG application compared to a high forcing scenario. In addition, a feedback algorithm identifies the needed amount of sulfur dioxide injections in the stratosphere at four pre-defined latitudes, 30∘ N, 15∘ N, 15∘ S, and 30∘ S, to reach three surface temperature targets: global mean temperature, and interhemispheric and pole-to-Equator temperature gradients. These targets further help to reduce side effects, including overcooling in the tropics, warming of high latitudes, and large shifts in precipitation patterns. These experiments are therefore relevant for investigating the impacts on society and ecosystems. Comparisons to SAG simulations based on a high emission pathway baseline scenario (SSP5-85) are also performed to investigate the dependency of impacts using different injection amounts to offset surface warming by SAG. We find that changes from present-day conditions around 2020 in some variables depend strongly on the defined temperature target (1.5 ∘C vs. 2.0 ∘C). These include surface air temperature and related impacts, the Atlantic Meridional Overturning Circulation, which impacts ocean net primary productivity, and changes in ice sheet surface mass balance, which impacts sea level rise. Others, including global precipitation changes and the recovery of the Antarctic ozone hole, depend strongly on the amount of SAG application. Furthermore, land net primary productivity as well as ocean acidification depend mostly on the global atmospheric CO2 concentration and therefore the baseline scenario. Multi-model comparisons of experiments that include strong mitigation and carbon dioxide removal with some SAG application are proposed to assess the robustness of impacts on societies and ecosystems.

scholarly journals Modelling the response of net primary productivity of the Zambezi teak forests to climate change along a rainfall gradient in Zambia

2019 ◽  
Vol 16 (19) ◽  
pp. 3853-3867
Author(s):  
Justine Ngoma ◽  
Maarten C. Braakhekke ◽  
Bart Kruijt ◽  
Eddy Moors ◽  
Iwan Supit ◽  
...  
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Primary Productivity ◽  
General Circulation ◽  
Net Primary Productivity ◽  
Co2 Concentration ◽  
Annual Rainfall ◽  
Rainfall Gradient ◽  
Local Soil ◽  
Parameter Values

Abstract. Understanding climate change effects on forests is important considering the role forests play in mitigating climate change. We studied the effects of changes in temperature, rainfall, atmospheric carbon dioxide (CO2) concentration, solar radiation, and number of wet days (as a measure of rainfall intensity) on net primary productivity (NPP) of the Zambian Zambezi teak forests along a rainfall gradient. Using 1960–1989 as a baseline, we projected changes in NPP for the end of the 21st century (2070–2099). We adapted the parameters of the dynamic vegetation model, LPJ-GUESS, to simulate the growth of Zambian forests at three sites along a moisture gradient receiving annual rainfall of between 700 and more than 1000 mm. The adjusted plant functional type was tested against measured data. We forced the model with contemporary climate data (1960–2005) and with climatic forecasts of an ensemble of five general circulation models (GCMs) following Representative Concentration Pathways (RCPs) RCP4.5 and RCP8.5. We used local soil parameter values to characterize texture and measured local tree parameter values for maximum crown area, wood density, leaf longevity, and allometry. The results simulated with the LPJ-GUESS model improved when we used these newly generated local parameters, indicating that using local parameter values is essential to obtaining reliable simulations at site level. The adapted model setup provided a baseline for assessing the potential effects of climate change on NPP in the studied Zambezi teak forests. Using this adapted model version, NPP was projected to increase by 1.77 % and 0.69 % at the wetter Kabompo and by 0.44 % and 0.10 % at the intermediate Namwala sites under RCP8.5 and RCP4.5 respectively, especially caused by the increased CO2 concentration by the end of the 21st century. However, at the drier Sesheke site, NPP would respectively decrease by 0.01 % and 0.04 % by the end of the 21st century under RCP8.5 and RCP4.5. The projected decreased NPP under RCP8.5 at the Sesheke site results from the reduced rainfall coupled with increasing temperature. We thus demonstrated that differences in the amount of rainfall received in a site per year influence the way in which climate change will affect forest resources. The projected increase in CO2 concentration would thus have more effects on NPP in high rainfall receiving areas, while in arid regions, NPP would be affected more by the changes in rainfall and temperature. CO2 concentrations would therefore be more important in forests that are generally not temperature- or precipitation-limited; however, precipitation will continue to be the limiting factor in the drier sites.

scholarly journals Modelling a Modern-like-<i>p</i>CO<sub>2</sub> Warm Period (MIS KM5c) with Two Versions of IPSL AOGCM

2019 ◽  
Author(s):  
Ning Tan ◽  
Camille Contoux ◽  
Gilles Ramstein ◽  
Yong Sun ◽  
Christophe Dumas ◽  
...  
Keyword(s):  
General Circulation ◽  
Surface Air Temperature ◽  
Greenland Ice Sheet ◽  
Circulation Model ◽  
Warm Period ◽  
Meridional Overturning Circulation ◽  
High Latitudes ◽  
Sea Ice Extent ◽  
Surface Mass ◽  
Model Response

Abstract. The mid-Piacenzian warm period (3.264 to 3.025 Ma) is the most recent geological period with a present-like atmospheric pCO2 exhibiting significant warming relative to present conditions. With the advanced understanding of the climate variability of this interval, a specific interglacial (marine isotope stage KM5c, MIS KM5c, 3.205 Ma) is selected for Pliocene Model Intercomparison Project phase 2 (PlioMIP 2) and updated boundary conditions are provided. In this study, we carried out series of experiments according to the design of PlioMIP2 with two versions of the IPSL Atmosphere-Ocean Coupled General Circulation Model (AOGCM) (IPSL-CM5A and IPSL-CM5A2). By comparing with PlioMIP 1 experiment, run with IPSL-CM5A, our results show that the simulated MIS KM5c climate presents enhanced warming in mid-to-high latitudes, especially in ocean regions. This warming can be attributed to the largely enhanced Atlantic Meridional Overturning Circulation caused by the high latitude seaway changes. The tier experiments, conducted with IPSL-CM5A2 (with faster computation scheme), show that besides the increased pCO2, both modified orography and reduced ice sheets contribute substantially in mid-to-high latitudes warming of MIS KM5c. When considering the pCO2 uncertainties, the warming pattern changes, our model response to the variation of pCO2 by &amp;pm;50 ppmv is not symmetric in the surface air temperature, due to the non-linear response of the cryosphere (snow cover and sea ice extent). By analysing the Greenland Ice Sheet surface mass balance, we also demonstrate its vulnerability under both MIS KM5c and modern warm climate.

scholarly journals Response of Net Primary Productivity of Zambezi teak forests to climate change along a rainfall gradient in Zambia

2018 ◽  
Author(s):  
Justine Ngoma ◽  
Maarten C. Braakhekke ◽  
Bart Kruijt ◽  
Eddy Moors ◽  
Iwan Supit ◽  
...  
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Co2 Concentration ◽  
Annual Rainfall ◽  
Base Line ◽  
Rainfall Gradient ◽  
Local Soil ◽  
Parameter Values

Abstract. Understanding climate change effects on forests is important considering the role forests play in mitigating climate change. We studied the effects of changes in temperature, rainfall, atmospheric carbon dioxide (CO2) concentration, solar radiation, and number of wet days (as a measure of rainfall intensity) on net primary productivity (NPP) of the Zambian Zambezi teak forests along a rainfall gradient. Using 1960–1989 as base-line, we projected changes in NPP for the end of the 21st century (2070–2099). We adapted the parameters of the dynamic vegetation model, LPJ-GUESS, to simulate the growth of Zambian forests at three sites along a moisture gradient receiving annual rainfall of between 700 mm to more than 1000 mm. The thus adjusted plant functional type was tested against measured data. We forced the model with contemporary climate data (1960–2005) and with climatic forecasts of an ensemble of five General Circulation Models (GCMs) following RCP4.5 and RCP8.5. We used local soil parameter values to characterize texture and measured local tree parameter values for maximum crown area, wood density, leaf longevity, and allometry. While increased CO2 concentration enhances NPP at the wetter Kabompo and the intermediate Namwala sites, NPP decreases at the drier Sesheke site under both scenarios by the end of 21st century. The projected decreased NPP under RCP8.5 at the Sesheke site results from the reduced rainfall. We thus demonstrated that differences in rainfall pattern influence the way in which climate change will affect forests resources. We also showed that using local parameter values is essential to obtaining reasonably reliable simulations.

scholarly journals Roles of Climate Change and Increasing CO2 in Driving Changes of Net Primary Productivity in China Simulated Using a Dynamic Global Vegetation Model

2019 ◽  
Vol 11 (15) ◽  
pp. 4176 ◽  
Author(s):  
Qing Huang ◽  
Weimin Ju ◽  
Fangyi Zhang ◽  
Qian Zhang
Keyword(s):  
Climate Change ◽  
Interannual Variability ◽  
Primary Productivity ◽  
Southwest China ◽  
Net Primary Productivity ◽  
Terrestrial Ecosystem ◽  
Co2 Concentration ◽  
Series Data ◽  
Geographical Regions ◽  
The Future

Net primary productivity (NPP) is the key component of the terrestrial carbon cycle, and terrestrial NPP trends under increasing CO2 and climate change in the past and future are of great significance in the study of the global carbon budget. Here, the LPJ-DGVM was employed to simulate the magnitude and pattern of China’s terrestrial NPP using long-term series data to understand the response of terrestrial NPP to increasing CO2 concentration and climate change. The results showed that total NPP of China’s terrestrial ecosystem increased from 2.8 to 3.6 Pg C yr−1 over the period of 1961–2016, with an annual average of 3.1 Pg C yr−1. The average NPP showed a gradient decrease from the southeast to northwest. Southwest China and Northwest China, comprising mostly arid and semi-arid regions, exhibited the largest increase rate in total NPP among the six geographical regions of China. Additionally, large interannual variability around the NPP trends was presented, and NPP anomalies in China’s terrestrial ecosystem are strongly associated with the El Niño-Southern Oscillation (ENSO). Southwest China made the largest contribution to the interannual variability of national total NPP. The total NPP of China’s terrestrial ecosystem continuously increased with the concurrent increase in the CO2 concentration and climate change under different scenarios in the future. During the period from 2091 to 2100, the average total NPP under the A2 and RCP85 scenarios would reach 4.9 and 5.1 Pg C yr−1 respectively, higher than 4.2 and 3.9 Pg C yr−1 under the B1 and RCP45 scenarios. Forests, especially temperate forests, make the largest contribution to the future increase in NPP. The increase in CO2 concentration would play a dominant role in driving further NPP increase in China’s terrestrial ecosystems, and climate change may slightly attenuate the fertilization effect of CO2 on NPP.

scholarly journals Assessing the impact of land surface temperature on urban net primary productivity increment based on geographically weighted regression model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xue-Yuan Lu ◽  
Xu Chen ◽  
Xue-Li Zhao ◽  
Dan-Jv Lv ◽  
Yan Zhang
Keyword(s):  
Surface Temperature ◽  
Spatial Heterogeneity ◽  
Land Surface Temperature ◽  
Primary Productivity ◽  
Geographically Weighted Regression ◽  
Land Surface ◽  
Net Primary Productivity ◽  
Weighted Regression ◽  
The Impact ◽  
Gwr Model

AbstractUrbanization had a huge impact on the regional ecosystem net primary productivity (NPP). Although the urban heat island (UHI) caused by urbanization has been found to have a certain promoting effect on urban vegetation NPP, the factors on the impact still are not identified. In this study, the impact of urbanization on NPP was divided into direct impact (NPPdir) and indirect impact (NPPind), taking Kunming city as a case study area. Then, the spatial heterogeneity impact of land surface temperature (LST) on NPPind was analyzed based on the geographically weighted regression (GWR) model. The results indicated that NPP, LST, NPPdir and NPPind in 2001, 2009 and 2018 had significant spatial autocorrelation in Kunming based on spatial analytical model. LST had a positive impact on NPPind in the central area of Kunming. The positively correlation areas of LST on NPPind increased by 4.56%, and the NPPind caused by the UHI effect increased by an average of 4.423 gC m−2 from 2009 to 2018. GWR model can reveal significant spatial heterogeneity in the impacts of LST on NPPind. Overall, our findings indicated that LST has a certain role in promoting urban NPP.

scholarly journals A simple parameterization of nitrogen limitation on primary productivity for global vegetation models

2005 ◽  
Vol 2 (4) ◽  
pp. 1243-1282 ◽  
Author(s):  
G. Krinner ◽  
P. Ciais ◽  
N. Viovy ◽  
P. Friedlingstein
Keyword(s):  
Primary Productivity ◽  
Nitrogen Limitation ◽  
Net Primary Productivity ◽  
Co2 Concentration ◽  
C Sequestration ◽  
Ecosystem Productivity ◽  
Soil Warming ◽  
Co2 Fertilization ◽  
Vegetation Models ◽  
Global Vegetation

Abstract. Nitrogen limitation of ecosystem productivity is ubiquitous, and it is thought that it has and will have a significant impact on net ecosystem productivity, and thus carbon sequestration, in the context of ongoing future increase of atmospheric CO2 concentration and climate change. However, many vegetation models do not represent nitrogen limitation, and might thus overestimate future terrestrial C sequestration. This work presents a simple parameterization of nitrogen limitation that can be easily implemented in vegetation models which do not yet include a complete nitrogen cycle. This parameterization is based on the ratio between heterotrophic respiration (considered a "proxy" of net mineralization rate) and net primary productivity of the ecosystem (considered a "proxy" of nitrogen demand). It is implemented in a global vegetation model and tested against site experiments of CO2 fertilization and soil warming. Furthermore, global simulations of past and future CO2 fertilization are carried out and compared to other model results and available estimates of global C sequestration. It is shown that when N limitation is taken into account using the simple parameterization presented here, the model reproduces fairly realistically the carbon dynamics observed under CO2 fertilization and soil warming.

scholarly journals Combining livestock production information in a process based vegetation model to reconstruct the history of grassland management

2016 ◽  
Author(s):  
Jinfeng Chang ◽  
Philippe Ciais ◽  
Mario Herrero ◽  
Petr Havlik ◽  
Matteo Campioli ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Biomass Productivity ◽  
Co2 Concentration ◽  
Grassland Management ◽  
Surface Energy Budget ◽  
Large Spatial Scale ◽  
Spatial And Temporal Scales ◽  
Management Intensity ◽  
Grass Biomass

Abstract. Grassland management type (grazed or mown) and intensity (intensive or extensive) play a crucial role in the GHG balance and surface energy budget of this biome, both at field scale and at large spatial scale. Yet, global gridded historical information on grassland management intensity is not available. Combining modelled grass biomass productivity with statistics of the grass-biomass demand by livestock, we reconstruct gridded maps of grassland management intensity from 1901 to 2012. These maps include the minimum area of managed vs. maximum area of un-managed grasslands, and the fraction of mown versus grazed area at a resolution of 0.5° by 0.5°. The grass-biomass demand is derived from a livestock dataset for 2000, extended to cover the period 1901–2012. The nature of grass-biomass supply (i.e., forage grass from mown grassland and biomass grazed) is simulated by the process based model ORCHIDEE-GM driven by historical climate change, rising CO2 concentration, and changes in nitrogen fertilization. The global area of managed grassland obtained in this study is simulated to increase from 5.1 × 106 km2 in 1901 to 11 × 106 km2 in 2000, although the expansion pathway varies between different regions. The gridded grassland management intensity maps are model-dependent because they depend on Net Primary Productivity (NPP), which is the reason why specific attention is given to the evaluation of NPP. Namely, ORCHIDEE-GM is calibrated for C3 and C4 grass functional traits, and then evaluated against a series of observations from site-level NPP measurements to two global satellite products of Gross Primary Productivity (GPP) (MODIS-GPP and SIF data). The distribution of GPP and NPP with and without management, are evaluated against observations at different spatial and temporal scales. Generally, ORCHIDEE-GM captures the spatial pattern, seasonal cycle and interannual variability of grassland productivity at global scale well, and thus appears to be appropriate for global applications.

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