ALBERT

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.

Description: A representation of the terrestrial nitrogen cycle is introduced into the UVic Earth System Climate Model (UVic ESCM). The UVic ESCM now contains five terrestrial carbon pools and seven terrestrial nitrogen pools: soil, litter, leaves, stem and roots for both elements and ammonium and nitrate in the soil for nitrogen. Nitrogen cycles through plant tissue, litter, soil and the mineral pools before being taken up again by the plant. Biological N2 fixation and nitrogen deposition represent external inputs to the plant-soil system while losses occur via leaching. Simulated carbon and nitrogen pools and fluxes are in the range of other models and observations. Gross primary production (GPP) for the 1990s in the CN-coupled version is 129.6 Pg C a−1 and net C uptake is 0.83 Pg C a−1, whereas the C-only version results in a GPP of 133.1 Pg C a−1 and a net C uptake of 1.57 Pg C a−1. At the end of a transient experiment for the years 1800–1999, where radiative forcing is held constant but CO2 fertilisation for vegetation is permitted to occur, the CN-coupled version shows an enhanced net C uptake of 1.05 Pg C a−1, whereas in the experiment where CO2 is held constant and temperature is transient the land turns into a C source of 0.60 Pg C a−1 by the 1990s. The arithmetic sum of the temperature and CO2 effects is 0.45 Pg C a−1, 0.38 Pg C a−1 lower than seen in the fully forced model, suggesting a strong nonlinearity in the CN-coupled version. Anthropogenic N deposition has a positive effect on Net Ecosystem Production of 0.35 Pg C a−1. Overall, the UVic CN-coupled version shows similar characteristics to other CN-coupled Earth System Models, as measured by net C balance and sensitivity to changes in climate, CO2 and temperature.

Description: Ice-core records show that abrupt Dansgaard–Oeschger (D–O) climatic warming events of the last glacial period were accompanied by large increases in the atmospheric CH4 concentration (up to 200 ppbv). These abrupt changes are generally regarded as arising from the effects of changes in the Atlantic Ocean meridional overturning circulation and the resultant climatic impact on natural CH4 sources, in particular wetlands. We use two different ecosystem models of wetland CH4 emissions to simulate northern CH4 sources forced with coupled general circulation model simulations of five different time periods during the last glacial to investigate the potential influence of abrupt ocean circulation changes on atmospheric CH4 levels during D–O events. The simulated warming over Greenland of 7–9 °C in the different time periods is at the lower end of the range of 11–15 °C derived from ice cores, but is associated with strong impacts on the hydrological cycle, especially over the North Atlantic and Europe during winter. We find that although the sensitivity of CH4 emissions to the imposed climate varies significantly between the two ecosystem emissions models, the model simulations do not reproduce sufficient emission changes to satisfy ice-core observations of CH4 increases during abrupt events. The inclusion of permafrost physics and peatland carbon cycling in one model (LPJ-WHyMe) increases the climatic sensitivity of CH44 emissions relative to the Sheffield Dynamic Global Vegetation Model (SDGVM) model, which does not incorporate these processes. For equilibrium conditions this additional sensitivity is mostly due to differences in carbon cycle processes, whilst the increased sensitivity to the imposed abrupt warmings is also partly due to the effects of freezing on soil thermodynamics. These results suggest that alternative scenarios of climatic change could be required to explain the abrupt glacial CH4 variations, perhaps with a more dominant role for tropical wetland CH4 sources.

Description: Ice-core records show that abrupt Dansgaard-Oeschger climatic warming events of the last glacial period were accompanied by large increases in the atmospheric CH4 concentration (up to 200 ppbv). These abrupt changes are generally regarded as arising from the effects of changes in the Atlantic Ocean meridional overturning circulation and the resultant climatic impact on natural CH4 sources, in particular wetlands. We use two different ecosystem models of wetland CH4 emissions to simulate northern CH4 sources forced with coupled general circulation model simulations of five different time periods during the last glacial to investigate the potential influence of abrupt ocean circulation changes on atmospheric CH4 levels during D-O events. The simulated warming over Greenland of 7–9 °C in the different time-periods is at the lower end of the range of 11–15 °C derived from ice-cores, but is associated with strong impacts on the hydrological cycle, especially over the North Atlantic and Europe during winter. We find that although the sensitivity of CH4 emissions to the imposed climate varies significantly between the two ecosystem emissions models, the model simulations do not reproduce sufficient emission changes to satisfy ice-core observations of CH4 increases during abrupt events. This suggests that alternative scenarios of climatic change could be required to explain the abrupt glacial CH4 variations.

Description: Natural methane (CH4) emissions from wet ecosystems are an important part of today's global CH4 budget. Climate affects the exchange of CH4 between ecosystems and the atmosphere by influencing CH4 production, oxidation, and transport in the soil. The net CH4 exchange depends on ecosystem hydrology, soil and vegetation characteristics. Here, the LPJ-WHyMe global dynamical vegetation model is used to simulate global net CH4 emissions for different ecosystems: northern peatlands (45°–90° N), naturally inundated wetlands (60° S–45° N), rice agriculture and wet mineral soils. Mineral soils are a potential CH4 sink, but can also be a source with the direction of the net exchange depending on soil moisture content. The geographical and seasonal distributions are evaluated against multi-dimensional atmospheric inversions for 2003–2005, using two independent four-dimensional variational assimilation systems. The atmospheric inversions are constrained by the atmospheric CH4 observations of the SCIAMACHY satellite instrument and global surface networks. Compared to LPJ-WHyMe the inversions result in a significant reduction in the emissions from northern peatlands and suggest that LPJ-WHyMe maximum annual emissions peak about one month late. The inversions do not put strong constraints on the division of sources between inundated wetlands and wet mineral soils in the tropics. Based on the inversion results we adapt model parameters in LPJ-WHyMe and simulate the surface exchange of CH4 over the period 1990–2008. Over the whole period we infer an increase of global ecosystem CH4 emissions of +1.11 Tg CH4 yr−1, not considering potential additional changes in wetland extent. The increase in simulated CH4 emissions is attributed to enhanced soil respiration resulting from the observed rise in land temperature and in atmospheric carbon dioxide that were used as input. The long-term decline of the atmospheric CH4 growth rate from 1990 to 2006 cannot be fully explained with the simulated ecosystem emissions. However, these emissions show an increasing trend of +3.62 Tg CH4 yr−1 over 2005–2008 which can partly explain the renewed increase in atmospheric CH4 concentration during recent years.

Description: Climate change is leading to a disproportionately large warming in the high northern latitudes, but the magnitude and sign of the future carbon balance of the Arctic are highly uncertain. Using 40 terrestrial biosphere models for Alaska, we provide a baseline of terrestrial carbon cycle structural and parametric uncertainty, defined as the multi-model standard deviation (σ) against the mean (x) for each quantity. Mean annual uncertainty (σ/x) was largest for net ecosystem exchange (NEE) (−0.01± 0.19 kg C m−2 yr−1), then net primary production (NPP) (0.14 ± 0.33 kg C m−2 yr−1), autotrophic respiration (Ra) (0.09 ± 0.20 kg C m−2 yr−1), gross primary production (GPP) (0.22 ± 0.50 kg C m−2 yr−1), ecosystem respiration (Re) (0.23 ± 0.38 kg C m−2 yr−1), CH4 flux (2.52 ± 4.02 g CH4 m−2 yr−1), heterotrophic respiration (Rh) (0.14 ± 0.20 kg C m−2 yr−1), and soil carbon (14.0± 9.2 kg C m−2). The spatial patterns in regional carbon stocks and fluxes varied widely with some models showing NEE for Alaska as a strong carbon sink, others as a strong carbon source, while still others as carbon neutral. Additionally, a feedback (i.e., sensitivity) analysis was conducted of 20th century NEE to CO2 fertilization (β) and climate (γ), which showed that uncertainty in γ was 2x larger than that of β, with neither indicating that the Alaskan Arctic is shifting towards a certain net carbon sink or source. Finally, AmeriFlux data are used at two sites in the Alaskan Arctic to evaluate the regional patterns; observed seasonal NEE was captured within multi-model uncertainty. This assessment of carbon cycle uncertainties may be used as a baseline for the improvement of experimental and modeling activities, as well as a reference for future trajectories in carbon cycling with climate change in the Alaskan Arctic.

Description: 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 % 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. And 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.

Description: Natural methane (CH4) emissions from wet ecosystems are an important part of today's global CH4 budget. Climate affects the exchange of CH4 between ecosystems and the atmosphere by influencing CH4 production, oxidation, and transport in the soil. The net CH4 exchange depends on ecosystem hydrology, soil and vegetation characteristics. Here, the LPJ-WHyMe global dynamical vegetation model is used to simulate global net CH4 emissions for different ecosystems: northern peatlands (45°–90° N), naturally inundated wetlands (60° S–45° N), rice agriculture and wet mineral soils. Mineral soils are a potential CH4 sink, but can also be a source with the direction of the net exchange depending on soil moisture content. The geographical and seasonal distributions are evaluated against multi-dimensional atmospheric inversions for 2003–2005, using two independent four-dimensional variational assimilation systems. The atmospheric inversions are constrained by the atmospheric CH4 observations of the SCIAMACHY satellite instrument and global surface networks. Compared to LPJ-WHyMe the inversions result in a~significant reduction in the emissions from northern peatlands and suggest that LPJ-WHyMe maximum annual emissions peak about one month late. The inversions do not put strong constraints on the division of sources between inundated wetlands and wet mineral soils in the tropics. Based on the inversion results we diagnose model parameters in LPJ-WHyMe and simulate the surface exchange of CH4 over the period 1990–2008. Over the whole period we infer an increase of global ecosystem CH4 emissions of +1.11 Tg CH4 yr−1, not considering potential additional changes in wetland extent. The increase in simulated CH4 emissions is attributed to enhanced soil respiration resulting from the observed rise in land temperature and in atmospheric carbon dioxide that were used as input. The long-term decline of the atmospheric CH4 growth rate from 1990 to 2006 cannot be fully explained with the simulated ecosystem emissions. However, these emissions show an increasing trend of +3.62 Tg CH4 yr−1 over 2005–2008 which can partly explain the renewed increase in atmospheric CH4 concentration during recent years.