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: The role of different sources and sinks of CH4 in changes in atmospheric methane ([CH4]) concentration during the last 100 000 yr is still not fully understood. In particular, the magnitude of the change in wetland CH4 emissions at the Last Glacial Maximum (LGM) relative to the pre-industrial period (PI), as well as during abrupt climatic warming or Dansgaard–Oeschger (D–O) events of the last glacial period, is largely unconstrained. In the present study, we aim to understand the uncertainties related to the parameterization of the wetland CH4 emission models relevant to these time periods by using two wetland models of different complexity (SDGVM and ORCHIDEE). These models have been forced by identical climate fields from low-resolution coupled atmosphere–ocean general circulation model (FAMOUS) simulations of these time periods. Both emission models simulate a large decrease in emissions during LGM in comparison to PI consistent with ice core observations and previous modelling studies. The global reduction is much larger in ORCHIDEE than in SDGVM (respectively −67 and −46%), and whilst the differences can be partially explained by different model sensitivities to temperature, the major reason for spatial differences between the models is the inclusion of freezing of soil water in ORCHIDEE and the resultant impact on methanogenesis substrate availability in boreal regions. Besides, a sensitivity test performed with ORCHIDEE in which the methanogenesis substrate sensitivity to the precipitations is modified to be more realistic gives a LGM reduction of −36%. The range of the global LGM decrease is still prone to uncertainty, and here we underline its sensitivity to different process parameterizations. Over the course of an idealized D–O warming, the magnitude of the change in wetland CH4 emissions simulated by the two models at global scale is very similar at around 15 Tg yr−1, but this is only around 25% of the ice-core measured changes in [CH4]. The two models do show regional differences in emission sensitivity to climate with much larger magnitudes of northern and southern tropical anomalies in ORCHIDEE. However, the simulated northern and southern tropical anomalies partially compensate each other in both models limiting the net flux change. Future work may need to consider the inclusion of more detailed wetland processes (e.g. linked to permafrost or tropical floodplains), other non-wetland CH4 sources or different patterns of D–O climate change in order to be able to reconcile emission estimates with the ice-core data for rapid CH4 events.

Description: The role of different sources and sinks of CH4 in changes in atmospheric methane ([CH4]) concentration during the last 100 000 yr is still not fully understood. In particular, the magnitude of the change in wetland CH4 emissions at the last glacial maximum (LGM) relative to the pre-industrial period (PI) as well as during abrupt climatic warmings or Dansgaard-Oeschger events of the last glacial period, is largely unconstrained. In the present study, we aim to understand the uncertainties related to the parameterization of the wetland CH4 emissions models relevant to these time periods by using two wetland models of different complexity (SDGVM and ORCHIDEE). These models have been forced by identical climate fields from low resolution coupled atmosphere-ocean general circulation model (FAMOUS) simulations of these time periods. Both emissions models simulate a large decrease in emissions during LGM in comparison to PI consistent with ice core observations and previous modeling studies. The global reduction is much larger in ORCHIDEE than in SDGVM (respectively −67 and −46%), and whilst the differences can be partially explained by different model sensitivities to temperature (i.e. Q10 values), the major reason for spatial differences between the models, is the inclusion of freezing of soil water in ORCHIDEE and the resultant impact on methanogenesis substrate availability in boreal regions. Besides, a sensitivity test performed with ORCHIDEE in which the methanogenesis substrate sensitivity to the precipitations is modified to be more realistic gives a LGM reduction of −36%. The range of the global LGM decrease is still prone to uncertainty and here, we underline its sensitivity to different process parameterizations. Over the course of an idealized D-O warming, the magnitude of the change in wetland CH4 emissions simulated by the two models at global scale is very similar at around 15 Tg yr−1, but this is only around 25% of the ice-core measured changes in [CH4]. The two models do show regional differences in emissions sensitivity to climate with much larger magnitudes of Northern and Southern tropical anomalies in ORCHIDEE. However, the simulated Northern and Southern tropical anomalies partially compensate each other in both models limiting the net flux change. Future work may need to consider the inclusion of more detailed wetland processes (e.g. linked to permafrost or tropical floodplains), other non-wetland CH4 sources or different patterns of D-O climate change in order to be able to reconcile emissions estimates with the ice-core data for rapid CH4 events.

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: Earth system models are increasing in complexity and incorporating more processes than their predecessors, making them important tools for studying the global carbon cycle. However, their coupled behaviour has only recently been examined in any detail, and has yielded a very wide range of outcomes, with coupled climate-carbon cycle models that represent land-use change simulating total land carbon stores by 2100 that vary by as much as 600 Pg C given the same emissions scenario. This large uncertainty is associated with differences in how key processes are simulated in different models, and illustrates the necessity of determining which models are most realistic using rigorous model evaluation methodologies. Here we assess the state-of-the-art with respect to evaluation of Earth system models, with a particular emphasis on the simulation of the carbon cycle and associated biospheric processes. We examine some of the new advances and remaining uncertainties relating to (i) modern and palaeo data and (ii) metrics for evaluation, and discuss a range of strategies, such as the inclusion of pre-calibration, combined process- and system-level evaluation, and the use of emergent constraints, that can contribute towards the development of more robust evaluation schemes. An increasingly data-rich environment offers more opportunities for model evaluation, but it is also a challenge, as more knowledge about data uncertainties is required in order to determine robust evaluation methodologies that move the field of ESM evaluation from "beauty contest" toward the development of useful constraints on model behaviour.

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: Earth system models (ESMs) are increasing in complexity by incorporating more processes than their predecessors, making them potentially important tools for studying the evolution of climate and associated biogeochemical cycles. However, their coupled behaviour has only recently been examined in any detail, and has yielded a very wide range of outcomes. For example, coupled climate–carbon cycle models that represent land-use change simulate total land carbon stores at 2100 that vary by as much as 600 Pg C, given the same emissions scenario. This large uncertainty is associated with differences in how key processes are simulated in different models, and illustrates the necessity of determining which models are most realistic using rigorous methods of model evaluation. Here we assess the state-of-the-art in evaluation of ESMs, with a particular emphasis on the simulation of the carbon cycle and associated biospheric processes. We examine some of the new advances and remaining uncertainties relating to (i) modern and palaeodata and (ii) metrics for evaluation. We note that the practice of averaging results from many models is unreliable and no substitute for proper evaluation of individual models. We discuss a range of strategies, such as the inclusion of pre-calibration, combined process- and system-level evaluation, and the use of emergent constraints, that can contribute to the development of more robust evaluation schemes. An increasingly data-rich environment offers more opportunities for model evaluation, but also presents a challenge. Improved knowledge of data uncertainties is still necessary to move the field of ESM evaluation away from a "beauty contest" towards the development of useful constraints on model outcomes.