120 research outputs found
Methane emissions from floodplains in the Amazon Basin: challenges in developing a process-based model for global applications
Tropical wetlands are estimated to represent about 50% of the natural
wetland methane (CH<sub>4</sub>) emissions and explain a large fraction of the
observed CH<sub>4</sub> variability on timescales ranging from
glacial–interglacial cycles to the currently observed year-to-year
variability. Despite their importance, however, tropical wetlands are poorly
represented in global models aiming to predict global CH<sub>4</sub> emissions.
This publication documents a first step in the development of a process-based
model of CH<sub>4</sub> emissions from tropical floodplains for global
applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model
(LPX hereafter) was slightly modified to represent floodplain hydrology,
vegetation and associated CH<sub>4</sub> emissions. The extent of tropical
floodplains was prescribed using output from the spatially explicit hydrology
model PCR-GLOBWB. We introduced new plant functional types (PFTs) that
explicitly represent floodplain vegetation. The PFT parameterizations were
evaluated against available remote-sensing data sets (GLC2000 land cover and
MODIS Net Primary Productivity). Simulated CH<sub>4</sub> flux densities were
evaluated against field observations and regional flux inventories. Simulated
CH<sub>4</sub> emissions at Amazon Basin scale were compared to model simulations
performed in the WETCHIMP intercomparison project. We found that LPX
reproduces the average magnitude of observed net CH<sub>4</sub> flux densities for
the Amazon Basin. However, the model does not reproduce the variability
between sites or between years within a site. Unfortunately, site information
is too limited to attest or disprove some model features. At the Amazon Basin
scale, our results underline the large uncertainty in the magnitude of
wetland CH<sub>4</sub> emissions. Sensitivity analyses gave insights into the main
drivers of floodplain CH<sub>4</sub> emission and their associated uncertainties.
In particular, uncertainties in floodplain extent (i.e., difference between
GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor
of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000,
lead to simulated Amazon-integrated emissions of
44.4 ± 4.8 Tg yr<sup>−1</sup>. Additionally, the LPX emissions are highly
sensitive to vegetation distribution. Two simulations with the same mean PFT
cover, but different spatial distributions of grasslands within the basin,
modulated emissions by about 20%. Correcting the LPX-simulated NPP using
MODIS reduces the Amazon emissions by 11.3%. Finally, due to an
intrinsic limitation of LPX to account for seasonality in floodplain extent,
the model failed to reproduce the full dynamics in CH<sub>4</sub> emissions but we
proposed solutions to this issue. The interannual variability (IAV) of the
emissions increases by 90% if the IAV in floodplain extent is accounted
for, but still remains lower than in most of the WETCHIMP models. While our
model includes more mechanisms specific to tropical floodplains, we were
unable to reduce the uncertainty in the magnitude of wetland CH<sub>4</sub>
emissions of the Amazon Basin. Our results helped identify and prioritize
directions towards more accurate estimates of tropical CH<sub>4</sub> emissions,
and they stress the need for more research to constrain floodplain CH<sub>4</sub>
emissions and their temporal variability, even before including other
fundamental mechanisms such as floating macrophytes or lateral water fluxes
Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)
The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models
Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP)
Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two.
Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for
Past and future carbon fluxes from land use change, shifting cultivation and wood harvest
Carbon emissions from anthropogenic land use (LU) and land use change (LUC) are quantified with a Dynamic Global Vegetation Model for the past and the 21st century following Representative Concentration Pathways (RCPs). Wood harvesting and parallel abandonment and expansion of agricultural land in areas of shifting cultivation are explicitly simulated (gross LUC) based on the Land Use Harmonization (LUH) dataset and a proposed alternative method that relies on minimum input data and generically accounts for gross LUC. Cumulative global LUC emissions are 72 GtC by 1850 and 243 GtC by 2004 and 27–151 GtC for the next 95 yr following the different RCP scenarios. The alternative method reproduces results based on LUH data with full transition information within <0.1 GtC/yr over the last decades and bears potential for applications in combination with other LU scenarios. In the last decade, shifting cultivation and wood harvest within remaining forests including slash each contributed 19% to the mean annual emissions of 1.2 GtC/yr. These factors, in combination with amplification effects under elevated CO2, contribute substantially to future emissions from LUC in all RCPs
Long-Term climate change commitment and reversibility: An EMIC intercomparison
This is the final version of the article. Available from the American Meteorological Society via the DOI in this record.This paper summarizes the results of an intercomparison project with Earth System Models of Intermediate Complexity (EMICs) undertaken in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). The focus is on long-term climate projections designed to 1) quantify the climate change commitment of different radiative forcing trajectories and 2) explore the extent to which climate change is reversible on human time scales. All commitment simulations follow the four representative concentration pathways (RCPs) and their extensions to year 2300. MostEMICs simulate substantial surface air temperature and thermosteric sea level rise commitment following stabilization of the atmospheric composition at year-2300 levels. The meridional overturning circulation (MOC) is weakened temporarily and recovers to near-preindustrial values in most models for RCPs 2.6-6.0. The MOC weakening is more persistent for RCP8.5. Elimination of anthropogenic CO2 emissions after 2300 results in slowly decreasing atmospheric CO2 concentrations. At year 3000 atmospheric CO2 is still at more than half its year-2300 level in all EMICs forRCPs 4.5-8.5. Surface air temperature remains constant or decreases slightly and thermosteric sea level rise continues for centuries after elimination ofCO2 emissions in allEMICs.Restoration of atmosphericCO2 fromRCPto preindustrial levels over 100-1000 years requires large artificial removal of CO2 from the atmosphere and does not result in the simultaneous return to preindustrial climate conditions, as surface air temperature and sea level response exhibit a substantial time lag relative to atmospheric CO2. © 2013 American Meteorological Society.KZ and AJW acknowledge support from the National Science and Engineering Research Council (NSERC) Discovery Grant Program. AJW acknowledges support from NSERC's G8 Research Councils Initiative on Multilateral Research Funding Program. AVE and IIM were supported by the President of Russia Grant 5467.2012.5, by the Russian Foundation for Basic Research, and by the programs of the Russian Academy of Sciences. EC, TF, HG, and GPB acknowledge support from the Belgian Federal Science Policy Office. FJ, RS, and MS acknowledge support by the Swiss National Science Foundation and by the European Project CARBOCHANGE (Grant 264879), which received funding from the European Commission's Seventh Framework Programme (FP7/2007–2013). PBH and NRE acknowledge support from EU FP7 Grant ERMITAGE 265170
Understanding the glacial methane cycle.
Atmospheric methane (CH4) varied with climate during the Quaternary, rising from a concentration of 375 p.p.b.v. during the last glacial maximum (LGM) 21,000 years ago, to 680 p.p.b.v. at the beginning of the industrial revolution. However, the causes of this increase remain unclear; proposed hypotheses rely on fluctuations in either the magnitude of CH4 sources or CH4 atmospheric lifetime, or both. Here we use an Earth System model to provide a comprehensive assessment of these competing hypotheses, including estimates of uncertainty. We show that in this model, the global LGM CH4 source was reduced by 28-46%, and the lifetime increased by 2-8%, with a best-estimate LGM CH4 concentration of 463-480 p.p.b.v. Simulating the observed LGM concentration requires a 46-49% reduction in sources, indicating that we cannot reconcile the observed amplitude. This highlights the need for better understanding of the effects of low CO2 and cooler climate on wetlands and other natural CH4 sources
Global wetland contribution to 2000-2012 atmospheric methane growth rate dynamics
Increasing atmospheric methane (CH4) concentrations have contributed to approximately 20% of anthropogenic climate change. Despite the importance of CH4 as a greenhouse gas, its atmospheric growth rate and dynamics over the past two decades, which include a stabilization period (1999–2006), followed by renewed growth starting in 2007, remain poorly understood. We provide an updated estimate of CH4 emissions from wetlands, the largest natural global CH4 source, for 2000–2012 using an ensemble of biogeochemical models constrained with remote sensing surface inundation and inventory-based wetland area data. Between 2000–2012, boreal wetland CH4 emissions increased by 1.2 Tg yr−1 (−0.2–3.5 Tg yr−1), tropical emissions decreased by 0.9 Tg yr−1 (−3.2−1.1 Tg yr−1), yet globally, emissions remained unchanged at 184 ± 22 Tg yr−1. Changing air temperature was responsible for increasing high-latitude emissions whereas declines in low-latitude wetland area decreased tropical emissions; both dynamics are consistent with features of predicted centennial-scale climate change impacts on wetland CH4 emissions. Despite uncertainties in wetland area mapping, our study shows that global wetland CH4 emissions have not contributed significantly to the period of renewed atmospheric CH4 growth, and is consistent with findings from studies that indicate some combination of increasing fossil fuel and agriculture-related CH4 emissions, and a decrease in the atmospheric oxidative sink
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