ALBERT

Description: The effects of future land use and land cover change on the chemical composition of the atmosphere and air quality are largely unknown. To investigate the potential effects associated with future changes in vegetation driven by atmospheric CO2 concentrations, climate, and anthropogenic land use over the 21st century, we performed a series of model experiments combining a general circulation model with a dynamic global vegetation model and an atmospheric chemical-transport model. Our results indicate that climate- and CO2-induced changes in vegetation composition and density between 2100 and 2000 could lead to decreases in summer afternoon surface ozone of up to 10 ppb over large areas of the northern mid-latitudes. This is largely driven by the substantial increases in ozone dry deposition associated with increases in vegetation density in a warmer climate with higher atmospheric CO2 abundance. Climate-driven vegetation changes over the period 2000–2100 lead to general increases in isoprene emissions, globally by 15% in 2050 and 36% in 2100. These increases in isoprene emissions result in decreases in surface ozone concentrations where the NOx levels are low, such as in remote tropical rainforests. However, over polluted regions, such as the northeastern United States, ozone concentrations are calculated to increase with higher isoprene emissions in the future. Increases in biogenic emissions also lead to higher concentrations of secondary organic aerosols, which increase globally by 10% in 2050 and 20% in 2100. Summertime surface concentrations of secondary organic aerosols are calculated to increase by up to 1 μg m−3 and double for large areas in Eurasia over the period of 2000–2100. When we use a scenario of future anthropogenic land use change, we find less increase in global isoprene emissions due to replacement of higher-emitting forests by lower-emitting cropland. The global atmospheric burden of secondary organic aerosols changes little by 2100 when we account for future land use change, but both secondary organic aerosols and ozone show large regional changes at the surface.

Description: The Hudson Bay Lowlands (HBL) is the second largest boreal wetland ecosystem in the world and an important natural source of global atmospheric methane. We quantify the HBL methane emissions by using the GEOS-Chem chemical transport model to simulate aircraft measurements over the HBL from the ARCTAS and pre-HIPPO campaigns in May–July 2008, together with continuous 2004–2008 surface observations at Fraserdale (southern edge of HBL) and Alert (Arctic background). The difference in methane concentrations between Fraserdale and Alert is shown to be a good indicator of HBL emissions, and implies a sharp seasonal onset of emissions in late May (consistent with the aircraft data), a peak in July–August, and a seasonal shut-off in September. The model, in which seasonal variation of emission is mainly driven by surface temperature, reproduces well the observations in summer but its seasonal shoulders are too broad. We suggest that this reflects the suppression of emissions by snow cover and greatly improve the model simulation by accounting for this effect. Our resulting best estimate for HBL methane emissions is 2.3 Tg a−1, several-fold higher than previous estimates (Roulet et al., 1994; Worthy et al., 2000).

Description: The Amazon region, being a large source of methane (CH4), contributes significantly to the global annual CH4 budget. For the first time, a forward and inverse modelling framework on regional scale for the purpose of assessing the CH4 budget of the Amazon region is implemented. Here, we present forward simulations of CH4 as part of the forward and inverse modelling framework based on a modified version of the Weather Research and Forecasting model with chemistry that allows for passive tracer transport of CH4, carbon monoxide, and carbon dioxide (WRF-GHG), in combination with two different process-based bottom-up models of CH4 emissions from anaerobic microbial production in wetlands and additional datasets prescribing CH4 emissions from other sources such as biomass burning, termites, or other anthropogenic emissions. We compare WRF-GHG simulations on 10 km horizontal resolution to flask and continuous CH4 observations obtained during two airborne measurement campaigns within the Balanço Atmosférico Regional de Carbono na Amazônia (BARCA) project in November 2008 and May 2009. In addition, three different wetland inundation maps, prescribing the fraction of inundated area per grid cell, are evaluated. Our results indicate that the wetland inundation maps based on remote-sensing data represent the observations best except for the northern part of the Amazon basin and the Manaus area. WRF-GHG was able to represent the observed CH4 mixing ratios best at days with less convective activity. After adjusting wetland emissions to match the averaged observed mixing ratios of flights with little convective activity, the monthly CH4 budget for the Amazon basin obtained from four different simulations ranges from 1.5 to 4.8 Tg for November 2008 and from 1.3 to 5.5 Tg for May 2009. This corresponds to an average CH4 flux of 9–31 mg m−2 d−1 for November 2008 and 8–36 mg m−2 d−1 for May 2009.

Description: The effects of future land use and land cover change on the chemical composition of the atmosphere and air quality are largely unknown. To investigate the potential effects associated with future changes in vegetation driven by atmospheric CO2 concentrations, climate, and anthropogenic land use over the 21st century, we performed a series of model experiments combining a general circulation model with a dynamic global vegetation model and an atmospheric chemical-transport model. Our results indicate that climate- and CO2-induced changes in vegetation composition and density could lead to decreases in summer afternoon surface ozone of up to 10 ppb over large areas of the northern mid-latitudes. This is largely driven by the substantial increases in ozone dry deposition associated with changes in the composition of temperate and boreal forests where conifer forests are replaced by those dominated by broadleaf tree types, as well as a CO2-driven increase in vegetation density. Climate-driven vegetation changes over the period 2000–2100 lead to general increases in isoprene emissions, globally by 15 % in 2050 and 36 % in 2100. These increases in isoprene emissions result in decreases in surface ozone concentrations where the NOx levels are low, such as in remote tropical rainforests. However, over polluted regions, such as the northeastern United States, ozone concentrations are calculated to increase with higher isoprene emissions in the future. Increases in biogenic emissions also lead to higher concentrations of secondary organic aerosols, which increase globally by 10 % in 2050 and 20 % in 2100. Surface concentrations of secondary organic aerosols are calculated to increase by up to 1 μg m−3 for large areas in Eurasia. When we use a scenario of future anthropogenic land use change, we find less increase in global isoprene emissions due to replacement of higher-emitting forests by lower-emitting cropland. The global atmospheric burden of secondary organic aerosols changes little by 2100 when we account for future land use change, but both secondary organic aerosols and ozone show large regional changes at the surface.

Description: European forest use for fuel, timber and food dates back to pre-Roman times. Century-scale ecological processes and their legacy effects require accounting for forest management when studying today's forest carbon sink. Forest management reconstructions that are used to drive land surface models are one way to quantify the impact of both historical and today's large scale application of forest management on today's forest-related carbon sink and surface climate. In this study we reconstruct European forest management from 1600 to 2010 making use of diverse approaches, data sources and assumptions. Between 1600 and 1828, a demand-supply approach was used in which wood supply was reconstructed based on estimates of historical annual wood increment and land cover reconstructions. For the same period demand estimates accounted for the fuelwood needed in households, wood used in food processing, charcoal used in metal smelting and salt production, timber for construction and population estimates. Comparing estimated demand and supply resulted in a spatially explicit reconstruction of the share of forests under coppice, high stand management and forest left unmanaged. For the reconstruction between 1829 and 2010 a supply-driven back-casting method was used. The method used age reconstructions from the years 1950 to 2010 as its starting point. Our reconstruction reproduces the most important changes in forest management between 1600 and 2010: (1) an increase of 593 000 km2 in conifers at the expense of deciduous forest (decreasing by 538 000 km2), (2) a 612 000 km2 decrease in unmanaged forest, (3) a 152 000 km2 decrease in coppice management, (4) a 818 000 km2 increase in high stand management, and (5) the rise and fall of litter raking which at its peak in 1853 removed 50 Tg dry litter per year.

Description: Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, either using well-founded empirical relationships or process-based models with good predictive skill. A large variety of models exist today and it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project – FireMIP, an international project to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we summarise the current state-of-the-art in fire regime modelling and model evaluation, and outline what lessons may be learned from FireMIP.

Description: Is anthropogenic soil erosion a sink or source of atmospheric carbon? The answer depends on factors beyond hillslope erosion alone because the probable fate of mobilised soil carbon evolves as it traverses the fluvial system. The transit path, residence times, and the resulting mechanisms of C loss or gain change significantly down-basin and are currently difficult to predict as soils erode and floodplains evolve – this should be a key focus of future research.

Description: Is anthropogenic soil erosion a sink or source of atmospheric carbon? The answer depends on factors beyond hillslope erosion alone because the probable fate of mobilized soil carbon evolves as it traverses the fluvial system. The transit path, residence times, and the resulting mechanisms of C-loss or gain change significantly down-basin and are currently difficult to predict as soils erode and floodplains evolve – this should be a key focus of future research.

Description: Models of vegetation dynamics that are designed for application at spatial scales larger than individual forest gaps suffer from several limitations. Typically, either a population average approximation is used that results in unrealistic tree allometry and forest stand structure, or models have a high computational demand because they need to simulate both a series of age-based cohorts and a number of replicate patches to account for stochastic gap-scale disturbances. The detail required by the latter method increases the number of calculations by two to three orders of magnitude compared to the less realistic population average approach. In an effort to increase the efficiency of dynamic vegetation models without sacrificing realism, we developed a new method for simulating stand-replacing disturbances that is both accurate and faster than approaches that use replicate patches. The GAPPARD (approximating GAP model results with a Probabilistic Approach to account for stand Replacing Disturbances) method works by postprocessing the output of deterministic, undisturbed simulations of a cohort-based vegetation model by deriving the distribution of patch ages at any point in time on the basis of a disturbance probability. With this distribution, the expected value of any output variable can be calculated from the output values of the deterministic undisturbed run at the time corresponding to the patch age. To account for temporal changes in model forcing (e.g., as a result of climate change), GAPPARD performs a series of deterministic simulations and interpolates between the results in the postprocessing step. We integrated the GAPPARD method in the vegetation model LPJ-GUESS, and evaluated it in a series of simulations along an altitudinal transect of an inner-Alpine valley. We obtained results very similar to the output of the original LPJ-GUESS model that uses 100 replicate patches, but simulation time was reduced by approximately the factor 10. Our new method is therefore highly suited for rapidly approximating LPJ-GUESS results, and provides the opportunity for future studies over large spatial domains, allows easier parameterization of tree species, faster identification of areas of interesting simulation results, and comparisons with large-scale datasets and results of other forest models.

Description: 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.