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  • 1
    ISSN: 1365-2486
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Biology , Energy, Environment Protection, Nuclear Power Engineering , Geography
    Notes: Changes in vegetation structure and biogeography due to climate change feedback to alter climate by changing fluxes of energy, moisture, and momentum between land and atmosphere. While the current class of land process models used with climate models parameterizes these fluxes in detail, these models prescribe surface vegetation and leaf area from data sets. In this paper, we describe an approach in which ecological concepts from a global vegetation dynamics model are added to the land component of a climate model to grow plants interactively. The vegetation dynamics model is the Lund–Potsdam–Jena (LPJ) dynamic global vegetation model. The land model is the National Center for Atmospheric Research (NCAR) Land Surface Model (LSM). Vegetation is defined in terms of plant functional types. Each plant functional type is represented by an individual plant with the average biomass, crown area, height, and stem diameter (trees only) of its population, by the number of individuals in the population, and by the fractional cover in the grid cell. Three time-scales (minutes, days, and years) govern the processes. Energy fluxes, the hydrologic cycle, and carbon assimilation, core processes in LSM, occur at a 20 min time step. Instantaneous net assimilated carbon is accumulated annually to update vegetation once a year. This is carried out with the addition of establishment, resource competition, growth, mortality, and fire parameterizations from LPJ. The leaf area index is updated daily based on prevailing environmental conditions, but the maximum value depends on the annual vegetation dynamics. The coupling approach is successful. The model simulates global biogeography, net primary production, and dynamics of tundra, boreal forest, northern hardwood forest, tropical rainforest, and savanna ecosystems, which are consistent with observations. This suggests that the model can be used with a climate model to study biogeophysical feedbacks in the climate system related to vegetation dynamics.
    Type of Medium: Electronic Resource
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  • 2
    ISSN: 1365-2486
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Biology , Energy, Environment Protection, Nuclear Power Engineering , Geography
    Notes: Process-based models can be classified into: (a) terrestrial biogeochemical models (TBMs), which simulate fluxes of carbon, water and nitrogen coupled within terrestrial ecosystems, and (b) dynamic global vegetation models (DGVMs), which further couple these processes interactively with changes in slow ecosystem processes depending on resource competition, establishment, growth and mortality of different vegetation types. In this study, four models – RHESSys, GOTILWA+, LPJ-GUESS and ORCHIDEE – representing both modelling approaches were compared and evaluated against benchmarks provided by eddy-covariance measurements of carbon and water fluxes at 15 forest sites within the EUROFLUX project. Overall, model-measurement agreement varied greatly among sites. Both modelling approaches have somewhat different strengths, but there was no model among those tested that universally performed well on the two variables evaluated. Small biases and errors suggest that ORCHIDEE and GOTILWA+ performed better in simulating carbon fluxes while LPJ-GUESS and RHESSys did a better job in simulating water fluxes. In general, the models can be considered as useful tools for studies of climate change impacts on carbon and water cycling in forests. However, the various sources of variation among models simulations and between models simulations and observed data described in this study place some constraints on the results and to some extent reduce their reliability. For example, at most sites in the Mediterranean region all models generally performed poorly most likely because of problems in the representation of water stress effects on both carbon uptake by photosynthesis and carbon release by heterotrophic respiration (Rh).The use of flux data as a means of assessing key processes in models of this type is an important approach to improving model performance. Our results show that the models have value but that further model development is necessary with regard to the representation of the some of the key ecosystem processes.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Science Ltd
    Global change biology 8 (2002), S. 0 
    ISSN: 1365-2486
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Biology , Energy, Environment Protection, Nuclear Power Engineering , Geography
    Notes: A new fire model is proposed which estimates areas burnt on a macro-scale (10–100 km). It consists of three parts: evaluation of fire danger due to climatic conditions, estimation of the number of fires and the extent of the area burnt. The model can operate on three time steps, daily, monthly and yearly, and interacts with a Dynamic Global Vegetation Model (DGVM), thereby providing an important forcing for natural competition. Fire danger is related to number of dry days and amplitude of daily temperature during these days. The number of fires during fire days varies with human population density. Areas burnt are calculated based on average wind speed, available fuel and fire duration. The model has been incorporated into the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM) and has been tested for peninsular Spain. LPJ-DGVM was modified to allow bi-directional feedback between fire disturbance and vegetation dynamics. The number of fires and areas burnt were simulated for the period 1974–94 and compared against observations. The model produced realistic results, which are well correlated, both spatially and temporally, with the fire statistics. Therefore, a relatively simple mechanistic fire model can be used to reproduce fire regime patterns in human- dominated ecosystems over a large region and a long time period.
    Type of Medium: Electronic Resource
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  • 4
    ISSN: 1365-2486
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Biology , Energy, Environment Protection, Nuclear Power Engineering , Geography
    Notes: The possible responses of ecosystem processes to rising atmospheric CO2 concentration and climate change are illustrated using six dynamic global vegetation models that explicitly represent the interactions of ecosystem carbon and water exchanges with vegetation dynamics. The models are driven by the IPCC IS92a scenario of rising CO2 (Wigley et al. 1991), and by climate changes resulting from effective CO2 concentrations corresponding to IS92a, simulated by the coupled ocean atmosphere model HadCM2-SUL. Simulations with changing CO2 alone show a widely distributed terrestrial carbon sink of 1.4–3.8 Pg C y−1 during the 1990s, rising to 3.7–8.6 Pg C y−1 a century later. Simulations including climate change show a reduced sink both today (0.6–3.0 Pg C y−1) and a century later (0.3–6.6 Pg C y−1) as a result of the impacts of climate change on NEP of tropical and southern hemisphere ecosystems. In all models, the rate of increase of NEP begins to level off around 2030 as a consequence of the ‘diminishing return’ of physiological CO2 effects at high CO2 concentrations. Four out of the six models show a further, climate-induced decline in NEP resulting from increased heterotrophic respiration and declining tropical NPP after 2050. Changes in vegetation structure influence the magnitude and spatial pattern of the carbon sink and, in combination with changing climate, also freshwater availability (runoff). It is shown that these changes, once set in motion, would continue to evolve for at least a century even if atmospheric CO2 concentration and climate could be instantaneously stabilized. The results should be considered illustrative in the sense that the choice of CO2 concentration scenario was arbitrary and only one climate model scenario was used. However, the results serve to indicate a range of possible biospheric responses to CO2 and climate change. They reveal major uncertainties about the response of NEP to climate change resulting, primarily, from differences in the way that modelled global NPP responds to a changing climate. The simulations illustrate, however, that the magnitude of possible biospheric influences on the carbon balance requires that this factor is taken into account for future scenarios of atmospheric CO2 and climate change.
    Type of Medium: Electronic Resource
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  • 5
    ISSN: 1365-2486
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Biology , Energy, Environment Protection, Nuclear Power Engineering , Geography
    Notes: We assess the role of changing natural (volcanic, aerosol, insolation) and anthropogenic (CO2 emissions, land cover) forcings on the global climate system over the last 150 years using an earth system model of intermediate complexity, CLIMBER-2. We apply several datasets of historical land-use reconstructions: the cropland dataset by Ramankutty & Foley (1999) (R&F), the HYDE land cover dataset of Klein Goldewijk (2001), and the land-use emissions data from Houghton & Hackler (2002). Comparison between the simulated and observed temporal evolution of atmospheric CO2 and δ13CO2 are used to evaluate these datasets. To check model uncertainty, CLIMBER-2 was coupled to the more complex Lund–Potsdam–Jena (LPJ) dynamic global vegetation model.In simulation with R&F dataset, biogeophysical mechanisms due to land cover changes tend to decrease global air temperature by 0.26°C, while biogeochemical mechanisms act to warm the climate by 0.18°C. The net effect on climate is negligible on a global scale, but pronounced over the land in the temperate and high northern latitudes where a cooling due to an increase in land surface albedo offsets the warming due to land-use CO2 emissions.Land cover changes led to estimated increases in atmospheric CO2 of between 22 and 43 ppmv. Over the entire period 1800–2000, simulated δ13CO2 with HYDE compares most favourably with ice core during 1850–1950 and Cape Grim data, indicating preference of earlier land clearance in HYDE over R&F. In relative terms, land cover forcing corresponds to 25–49% of the observed growth in atmospheric CO2. This contribution declined from 36–60% during 1850–1960 to 4–35% during 1960–2000. CLIMBER-2-LPJ simulates the land cover contribution to atmospheric CO2 growth to decrease from 68% during 1900–1960 to 12% in the 1980s. Overall, our simulations show a decline in the relative role of land cover changes for atmospheric CO2 increase during the last 150 years.
    Type of Medium: Electronic Resource
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  • 6
    Publication Date: 2020-07-17
    Description: Global fire-vegetation models are widely used to assess impacts of environmental change on fire regimes and the carbon cycle and to infer relationships between climate, land use and fire. However, differences in model structure and parameterizations, in both the vegetation and fire components of these models, could influence overall model performance, and to date there has been limited evaluation of how well different models represent various aspects of fire regimes. The Fire Model Intercomparison Project (FireMIP) is coordinating the evaluation of state-of-the-art global fire models, in order to improve projections of fire characteristics and fire impacts on ecosystems and human societies in the context of global environmental change. Here we perform a systematic evaluation of historical simulations made by nine FireMIP models to quantify their ability to reproduce a range of fire and vegetation benchmarks. The FireMIP models simulate a wide range in global annual total burnt area (39–536 Mha) and global annual fire carbon emission (0.91–4.75 Pg C yr−1) for modern conditions (2002–2012), but most of the range in burnt area is within observational uncertainty (345–468 Mha). Benchmarking scores indicate that seven out of nine FireMIP models are able to represent the spatial pattern in burnt area. The models also reproduce the seasonality in burnt area reasonably well but struggle to simulate fire season length and are largely unable to represent interannual variations in burnt area. However, models that represent cropland fires see improved simulation of fire seasonality in the Northern Hemisphere. The three FireMIP models which explicitly simulate individual fires are able to reproduce the spatial pattern in number of fires, but fire sizes are too small in key regions, and this results in an underestimation of burnt area. The correct representation of spatial and seasonal patterns in vegetation appears to correlate with a better representation of burnt area. The two older fire models included in the FireMIP ensemble (LPJ–GUESS–GlobFIRM, MC2) clearly perform less well globally than other models, but it is difficult to distinguish between the remaining ensemble members; some of these models are better at representing certain aspects of the fire regime; none clearly outperforms all other models across the full range of variables assessed.
    Print ISSN: 1991-959X
    Electronic ISSN: 1991-9603
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 7
    Publication Date: 2019-01-31
    Description: Diffuse light conditions can increase the efficiency of photosynthesis and carbon uptake by vegetation canopies. The diffuse fraction of photosynthetically active radiation (PAR) can be affected by either a change in the atmospheric aerosol burden and/or a change in cloudiness. During the dry season, a hotspot of biomass burning on the edges of the Amazon rainforest emits a complex mixture of aerosols and their precursors and climate-active trace gases (e.g. CO2, CH4, NOx). This creates potential for significant interactions between chemistry, aerosol, cloud, radiation and the biosphere across the Amazon region. The combined effects of biomass burning on the terrestrial carbon cycle for the present day are potentially large, yet poorly quantified. Here, we quantify such effects using the Met Office Hadley Centre Earth system model HadGEM2-ES, which provides a fully coupled framework with interactive aerosol, radiative transfer, dynamic vegetation, atmospheric chemistry and biogenic volatile organic compound emission components. Results show that for present day, defined as year 2000 climate, the overall net impact of biomass burning aerosols is to increase net primary productivity (NPP) by +80 to +105 TgC yr−1, or 1.9 % to 2.7 %, over the central Amazon Basin on annual mean. For the first time we show that this enhancement is the net result of multiple competing effects: an increase in diffuse light which stimulates photosynthetic activity in the shaded part of the canopy (+65 to +110 TgC yr−1), a reduction in the total amount of radiation (−52 to −105 TgC yr−1) which reduces photosynthesis and feedback from climate adjustments in response to the aerosol forcing which increases the efficiency of biochemical processes (+67 to +100 TgC yr−1). These results illustrate that despite a modest direct aerosol effect (the sum of the first two counteracting mechanisms), the overall net impact of biomass burning aerosols on vegetation is sizeable when indirect climate feedbacks are considered. We demonstrate that capturing the net impact of aerosols on vegetation should be assessed considering the system-wide behaviour.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 8
    Publication Date: 2018-07-19
    Description: El Niño has two different flavors, eastern Pacific (EP) and central Pacific (CP) El Niños, with different global teleconnections. However, their different impacts on the interannual carbon cycle variability remain unclear. Here we compared the behaviors of interannual atmospheric CO2 variability and analyzed their terrestrial mechanisms during these two types of El Niños, based on the Mauna Loa (MLO) CO2 growth rate (CGR) and the Dynamic Global Vegetation Model's (DGVM) historical simulations. The composite analysis showed that evolution of the MLO CGR anomaly during EP and CP El Niños had three clear differences: (1) negative or neutral precursors in the boreal spring during an El Niño developing year (denoted as yr0), (2) strong or weak amplitudes, and (3) durations of the peak from December (yr0) to April during an El Niño decaying year (denoted as yr1) compared to October (yr0) to January (yr1) for a CP El Niño, respectively. The global land–atmosphere carbon flux (FTA) simulated by multi-models was able to capture the essentials of these characteristics. We further found that the gross primary productivity (GPP) over the tropics and the extratropical Southern Hemisphere (Trop + SH) generally dominated the global FTA variations during both El Niño types. Regional analysis showed that during EP El Niño events significant anomalous carbon uptake caused by increased precipitation and colder temperatures, corresponding to the negative precursor, occurred between 30° S and 20° N from January (yr0) to June (yr0). The strongest anomalous carbon releases, largely due to the reduced GPP induced by low precipitation and warm temperatures, occurred between the equator and 20° N from February (yr1) to August (yr1). In contrast, during CP El Niño events, clear carbon releases existed between 10° N and 20° S from September (yr0) to September (yr1), resulting from the widespread dry and warm climate conditions. Different spatial patterns of land temperatures and precipitation in different seasons associated with EP and CP El Niños accounted for the evolutionary characteristics of GPP, terrestrial ecosystem respiration (TER), and the resultant FTA. Understanding these different behaviors of interannual atmospheric CO2 variability, along with their terrestrial mechanisms during EP and CP El Niños, is important because the CP El Niño occurrence rate might increase under global warming.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 9
    Publication Date: 2018-09-12
    Description: Elevated levels of tropospheric ozone, O3, cause damage to terrestrial vegetation, affecting leaf stomatal functioning and reducing photosynthesis. Climatic impacts under future raised atmospheric greenhouse gas (GHG) concentrations will also impact on the net primary productivity (NPP) of vegetation, which might for instance alter viability of some crops. Together, ozone damage and climate change may adjust the current ability of terrestrial vegetation to offset a significant fraction of carbon dioxide (CO2) emissions. Climate impacts on the land surface are well studied, but arguably large-scale modelling of raised surface level O3 effects is less advanced. To date most models representing ozone damage use either O3 concentration or, more recently, flux-uptake-related reduction of stomatal opening, estimating suppressed land–atmosphere water and CO2 fluxes. However there is evidence that, for some species, O3 damage can also cause an inertial “sluggishness” of stomatal response to changing surface meteorological conditions. In some circumstances (e.g. droughts), this loss of stomata control can cause them to be more open than without ozone interference. To both aid model development and provide empiricists with a system on to which measurements can be mapped, we present a parameter-sparse framework specifically designed to capture sluggishness. This contains a single time-delay parameter τO3, characterizing the timescale for stomata to catch up with the level of opening they would have without damage. The larger the value of this parameter, the more sluggish the modelled stomatal response. Through variation of τO3, we find it is possible to have qualitatively similar responses to factorial experiments with and without raised O3, when comparing to reported measurement time series presented in the literature. This low-parameter approach lends itself to the inclusion of ozone-induced inertial effects being incorporated in the terrestrial vegetation component of Earth system models (ESMs).
    Print ISSN: 1726-4170
    Electronic ISSN: 1726-4189
    Topics: Biology , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 10
    Publication Date: 2017-11-13
    Description: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the "global carbon budget" – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of our imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2007–2016), EFF was 9.4 ± 0.5 GtC yr−1, ELUC 1.3 ± 0.7 GtC yr−1, GATM 4.7 ± 0.1 GtC yr−1, SOCEAN 2.4 ± 0.5 GtC yr−1, and SLAND 3.0 ± 0.8 GtC yr−1, with a budget imbalance BIM of 0.6 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1. Also for 2016, ELUC was 1.3 ± 0.7 GtC yr−1, GATM was 6.1 ± 0.2 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1 and SLAND was 2.7 ± 1.0 GtC yr−1, with a small BIM of −0.3 GtC. GATM continued to be higher in 2016 compared to the past decade (2007–2016), reflecting in part the higher fossil emissions and smaller SLAND for that year consistent with El Niño conditions. The global atmospheric CO2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data indicate a renewed growth in EFF of +2.0 % (range of 0.8 % to 3.0 %) based on national emissions projections for China, USA, and India, and projections of Gross Domestic Product corrected for recent changes in the carbon intensity of the economy for the rest of the world. For 2017, initial data indicate an increase in atmospheric CO2 concentration of around 5.3 GtC (2.5 ppm), attributed to a combination of increasing emissions and receding El Niño conditions. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quéré et al., 2016; 2015b; 2015a; 2014; 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017.
    Electronic ISSN: 1866-3591
    Topics: Geosciences
    Published by Copernicus
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