Significant feedbacks of wetland methane release on climate change and the causes of their uncertainty

Emissions from wetlands are the single largest source of the atmospheric greenhouse gas (GHG) methane (CH4). This may increase in a warming climate, leading to a positive feedback on climate change. For the first time, we extend interactive wetland CH4 emissions schemes to include the recently quantified, significant process of CH4 transfer through tropical trees. We constrain the parameterisations using a multi-site flux study, and biogeochemical and inversion models. This provides an estimate and uncertainty range in contemporary, large-scale wetland emissions and their response to temperature. To assess the potential for future wetland CH4 emissions to feedback on climate, the schemes are forced with simulated climate change using a 'pattern-scaling' system, which links altered atmospheric radiative forcing to meteorology changes. We perform multiple simulations emulating 34 Earth System Models over different anthropogenic GHG emissions scenarios (RCPs). We provide a detailed assessment of the causes of uncertainty in predicting wetland CH4–climate feedback. Despite the constraints applied, uncertainty from wetland CH4 emission modelling is greater that from projected climate spread (under a given RCP). Limited knowledge of contemporary global wetland emissions restricts model calibration, producing the largest individual cause of wetland parameterisation uncertainty. Wetland feedback causes an additional temperature increase between 0.6% and 5.5% over the 21st century, with a feedback on climate ranging from 0.01 to 0.11 Wm−2 K−1. Wetland CH4 emissions amplify atmospheric CH4 increases by up to a further possible 25.4% in one simulation, and reduce remaining allowed anthropogenic emissions to maintain the RCP2.6 temperature threshold by 8.0% on average

Comparison of the HadGEM2 climate-chemistry model against in situ and SCIAMACHY atmospheric methane data

Wetlands are a major emission source of methane (CH4) globally. In this study, we evaluate wetland emission estimates derived using the UK community land surface model (JULES, the Joint UK Land Earth Simulator) against atmospheric observations of methane, including, for the first time, total methane columns derived from the SCIAMACHY instrument on board the ENVISAT satellite. Two JULES wetland emission estimates are investigated: (a) from an offline run driven with Climatic Research Unit–National Centers for Environmental Prediction (CRU-NCEP) meteorological data and (b) from the same offline run in which the modelled wetland fractions are replaced with those derived from the Global Inundation Extent from Multi-Satellites (GIEMS) remote sensing product. The mean annual emission assumed for each inventory (181 Tg CH4 per annum over the period 1999–2007) is in line with other recently published estimates. There are regional differences as the unconstrained JULES inventory gives significantly higher emissions in the Amazon (by ~36 Tg CH4 yr−1) and lower emissions in other regions (by up to 10 Tg CH4 yr−1) compared to the JULES estimates constrained with the GIEMS product. Using the UK Hadley Centre's Earth System model with atmospheric chemistry (HadGEM2), we evaluate these JULES wetland emissions against atmospheric observations of methane. We obtain improved agreement with the surface concentration measurements, especially at high northern latitudes, compared to previous HadGEM2 runs using the wetland emission data set of Fung et al. (1991). Although the modelled monthly atmospheric methane columns reproduce the large-scale patterns in the SCIAMACHY observations, they are biased low by 50 part per billion by volume (ppb). Replacing the HadGEM2 modelled concentrations above 300 hPa with HALOE–ACE assimilated TOMCAT output results in a significantly better agreement with the SCIAMACHY observations. The use of the GIEMS product to constrain the JULES-derived wetland fraction improves the representation of the wetland emissions in JULES and gives a good description of the seasonality observed at surface sites influenced by wetlands, especially at high latitudes. We find that the annual cycles observed in the SCIAMACHY measurements and at many of the surface sites influenced by non-wetland sources cannot be reproduced in these HadGEM2 runs. This suggests that the emissions over certain regions (e.g. India and China) are possibly too high and/or the monthly emission patterns for specific sectors are incorrect. The comparisons presented in this paper show that the performance of the JULES wetland scheme is comparable to that of other process-based land surface models. We identify areas for improvement in this and the atmospheric chemistry components of the HadGEM Earth System model. The Earth Observation data sets used here will be of continued value in future evaluations of JULES and the HadGEM family of models

From biota to chemistry and climate: Towards a comprehensive description of trace gas exchange between the biosphere and atmosphere

Exchange of non-CO2 trace gases between the land surface and the atmosphere plays an important role in atmospheric chemistry and climate. Recent studies have highlighted its importance for interpretation of glacial-interglacial ice-core records, the simulation of the pre-industrial and present atmosphere, and the potential for large climate-chemistry and climate-aerosol feedbacks in the coming century. However, spatial and temporal variations in trace gas emissions and the magnitude of future feedbacks are a major source of uncertainty in atmospheric chemistry, air quality and climate science. To reduce such uncertainties Dynamic Global Vegetation Models (DGVMs) are currently being expanded to mechanistically represent processes relevant to non-CO2 trace gas exchange between land biota and the atmosphere. In this paper we present a review of important non-CO2 trace gas emissions, the state-of-the-art in DGVM modelling of processes regulating these emissions, identify key uncertainties for global scale model applications, and discuss a methodology for model integration and evaluation

Flexible parameter-sparse global temperature time-profiles that stabilise at 1.5C and 2.0C

The meeting of the United Nations Framework Convention on Climate Change (UNFCCC) in December 2015 committed parties to the Convention to hold the rise in global average temperature to well below 2.0 C above pre-industrial levels. It also committed the parties to pursue efforts to limit warming to 1.5 C. This leads to two key questions. First,what extent of emission reductions will achieve either target? Second, what is the benefit of the reduced climate impacts by keeping warming at or below 1.5 C? To provide answers, climate model simulations need to follow trajectories consistent with these global temperature limits. It is useful to operate models in an inverse mode to make model-specific estimates of greenhouse gas (GHG) concentration pathways consistent with the prescribed temperature profiles. Further inversion derives related emissions pathways for these concentrations. For this to happen, and to enable climate research centres to compare GHG concentrations and emissions estimates, common temperature trajectory scenarios are required. Here we define algebraic curves which asymptote to a stabilised limit, while also matching the magnitude and gradient of recent warming levels. The curves are deliberately parameter-sparse, needing prescription of just two parameters plus the final temperature. Yet despite this simplicity, they can allow for temperature overshoot and for generational changes where more effort to decelerate warming change is needed by future generations. The curves capture temperature profiles from the existing Representative Concentration Pathway (RCP2.6) scenario projections by a range of different earth system models (ESMs), which have warming amounts towards the lower levels of those that society is discussing

Spatially resolved isotopic source signatures of wetland methane emissions

We present the first spatially‐resolved wetland δ13C(CH4) source signature map based on data characterizing wetland ecosystems and demonstrate good agreement with wetland signatures derived from atmospheric observations. The source signature map resolves a latitudinal difference of ~10‰ between northern high‐latitude (mean ‐67.8‰) and tropical (mean ‐56.7‰) wetlands, and shows significant regional variations on top of the latitudinal gradient. We assess the errors in inverse modeling studies aiming to separate CH4 sources and sinks by comparing atmospheric δ13C(CH4) derived using our spatially‐resolved map against the common assumption of globally uniform wetland δ13C(CH4) signature. We find a larger interhemispheric gradient, a larger high‐latitude seasonal cycle and smaller trend over the period 2000‐2012. The implication is that erroneous CH4 fluxes would be derived to compensate for the biases imposed by not utilizing spatially‐resolved signatures for the largest source of CH4 emissions. These biases are significant when compared to the size of observed signals

Role of regional wetland emissions in atmospheric methane variability

Atmospheric methane (CH4) accounts for ~20% of the total direct anthropogenic radiative forcing by long-lived greenhouse gases. Surface observations show a pause (1999-2006) followed by a resumption in CH4 growth, which remain largely unexplained. Using a land surface model, we estimate wetland CH4 emissions from 1993 to 2014 and study the regional contributions to changes in atmospheric CH4. Atmospheric model simulations using these emissions, together with other sources, compare well with surface and satellite CH4 data. Modelled global wetland emissions vary by ±3%/yr (σ=4.8 Tg), mainly due to precipitation-induced changes in wetland area, but the integrated effect makes only a small contribution to the pause in CH4 growth from 1999 to 2006. Increasing temperature, which increases wetland area, drives a long-term trend in wetland CH4 emissions of +0.2%/yr (1999 to 2014). The increased growth post-2006 was partly caused by increased wetland emissions (+3%), mainly from Tropical Asia, Sourthern Africa and Australia

Carbon budget for 1.5 and 2oC targets lowered by natural wetland and permafrost feedbacks

Methane emissions from natural wetlands and carbon release from permafrost thaw have a positive feedback on climate, yet are not represented in most state-of-the-art climate models. Furthermore, a fraction of the thawed permafrost carbon is released as methane, enhancing the combined feedback strength. We present simulations with an intermediate complexity climate model which follow prescribed global warming pathways to stabilisation at 1.5°C or 2.0°C above pre-industrial levels by the year 2100, and that incorporates a state-of-the-art global land surface model with updated descriptions of wetland and permafrost carbon release. We demonstrate that the climate feedbacks from those two processes are substantial. Specifically, permissible anthropogenic fossil fuel CO2 emission budgets are reduced by 17-23% (47-56 GtC) for stabilisation at 1.5°C, and 9-13% (52-57 GtC) for 2.0°C stabilisation. In our simulations these feedback processes respond faster at temperatures below 1.5°C, and the differences between the 1.5°C and 2°C targets are disproportionately small. This key finding is due to our interest in transient emission pathways to the year 2100 and does not consider the longer term implications of these feedback processes. We conclude that natural feedback processes from wetlands and permafrost must be considered in assessments of transient emission pathways to limit global warming

JULES-GL7: The Global Land configuration of the Joint UK Land Environment Simulator version 7.0 and 7.2

This is the final version. Available on open access from the European Geosciences Union via the DOI in this recordData availability. The model configuration and associated forcing data are available via the indicated methods in the manuscript (see Appendix A). JULES and associated configurations are freely available for non-commercial research use as set out in the JULES user terms and conditions (http://jules-lsm.github.io/access_req/JULES_Licence.pdf, last access: 31 January 2020).Code availability. This work is based on JULES version 5.3 with specific configurations included in the form of suites. For full information regarding accessing the code and configurations, please refer to Appendix A.We present the latest global land configuration of the Joint UK Land Environment Simulator (JULES) model as used in the latest international Coupled Model Intercomparison Project (CMIP6). The configuration is defined by the combination of switches, parameter values and ancillary data, which we provide alongside a set of historical forcing data that defines the experimental setup. The configurations provided are JULES-GL7.0, the base setup used in CMIP6 and JULES-GL7.2, a subversion that includes improvements to the representation of canopy radiation and interception. These configurations are recommended for all JULES applications focused on the exchange and state of heat, water and momentum at the land surface. In addition, we provide a standardised modelling system that runs on the Natural Environment Research Council (NERC) JASMIN cluster, accessible to all JULES users. This is provided so that users can test and evaluate their own science against the standard configuration to promote community engagement in the development of land surface modelling capability through JULES. It is intended that JULES configurations should be independent of the underlying code base, and thus they will be available in the latest release of the JULES code. This means that different code releases will produce scientifically comparable results for a given configuration version. Versioning is therefore determined by the configuration as opposed to the underlying code base.BEIS and DEFRA Met Office Hadley Centre Climate ProgrammeEuropean Union Horizon 202

Comparison of the HadGEM2 climate-chemistry model against in situ and SCIAMACHY atmospheric methane data

Wetlands are a major emission source of methane (CH₄) globally. In this study, we evaluate wetland emission estimates derived using the UK community land surface model (JULES, the Joint UK Land Earth Simulator) against atmospheric observations of methane, including, for the first time, total methane columns derived from the SCIAMACHY instrument on board the ENVISAT satellite. Two JULES wetland emission estimates are investigated: (a) from an offline run driven with Climatic Research Unit–National Centers for Environmental Prediction (CRU-NCEP) meteorological data and (b) from the same offline run in which the modelled wetland fractions are replaced with those derived from the Global Inundation Extent from Multi-Satellites (GIEMS) remote sensing product. The mean annual emission assumed for each inventory (181 Tg CH₄ per annum over the period 1999–2007) is in line with other recently published estimates. There are regional differences as the unconstrained JULES inventory gives significantly higher emissions in the Amazon (by ~36 Tg CH₄ yr¯¹) and lower emissions in other regions (by up to 10 Tg CH₄ yr¯¹) compared to the JULES estimates constrained with the GIEMS product. Using the UK Hadley Centre's Earth System model with atmospheric chemistry (HadGEM2), we evaluate these JULES wetland emissions against atmospheric observations of methane. We obtain improved agreement with the surface concentration measurements, especially at high northern latitudes, compared to previous HadGEM2 runs using the wetland emission data set of Fung et al. (1991). Although the modelled monthly atmospheric methane columns reproduce the large-scale patterns in the SCIAMACHY observations, they are biased low by 50 part per billion by volume (ppb). Replacing the HadGEM2 modelled concentrations above 300 hPa with HALOE–ACE assimilated TOMCAT output results in a significantly better agreement with the SCIAMACHY observations. The use of the GIEMS product to constrain the JULES-derived wetland fraction improves the representation of the wetland emissions in JULES and gives a good description of the seasonality observed at surface sites influenced by wetlands, especially at high latitudes. We find that the annual cycles observed in the SCIAMACHY measurements and at many of the surface sites influenced by non-wetland sources cannot be reproduced in these HadGEM2 runs. This suggests that the emissions over certain regions (e.g. India and China) are possibly too high and/or the monthly emission patterns for specific sectors are incorrect. The comparisons presented in this paper show that the performance of the JULES wetland scheme is comparable to that of other process-based land surface models. We identify areas for improvement in this and the atmospheric chemistry components of the HadGEM Earth System model. The Earth Observation data sets used here will be of continued value in future evaluations of JULES and the HadGEM family of models