Description and Evaluation of an Emission‐Driven and Fully Coupled Methane Cycle in UKESM1

Abstract

Methane (CH4) is one of the most important trace gases in the atmosphere owing to its role as an exceedingly effective greenhouse gas and atmospheric pollutant. Better understanding of the global methane cycle and its interactions with the Earth system is therefore necessary for robust future projections of anthropogenic climate change and assessments of multi‐gas mitigation strategies. Here we present a newly developed methane emission‐driven Earth system model to simulate the global methane cycle fully interactively. We provide an evaluation of methane sources and sinks and a full‐cycle methane budget and its change over the historic period. We further evaluate the methane atmospheric abundance and lifetime against available observations. The new methane emission‐driven model simulates all the components of the methane cycle within observational uncertainty. We calculate a total present‐day (2000–2009 decadal average) methane source of 591 Tg(CH4) yr−1 with 197 Tg(CH4) yr−1 coming from wetlands. These sources are nearly balanced by the global methane sinks amounting to 580 Tg (CH4) yr−1; reaction of methane with the hydroxyl radical in the troposphere alone removes 525 Tg(CH4) yr−1. The imbalance between sources and sinks of 11 Tg(CH4) yr−1 represents the atmospheric methane growth rate and is in fairly good agreement with current best estimates of 5.8 Tg(CH4) yr−1 with a range of 4.9–6.6 Tg(CH4) yr−1. At present‐day the model shows a maximum systematic negative‐bias of approximately 200 ppb in the methane surface mole fraction.

Apportionment of the Pre‐Industrial to Present‐Day Climate Forcing by Methane Using UKESM1: The Role of the Cloud Radiative Effect

“…Outside of CMIP6, ESMs including UKESM1 are starting to include more interactive CH 4 cycles, with CH 4 emissions‐driven rather than concentration‐driven (Folberth et al., 2022; Kleinen et al., 2020; Ocko et al., 2018). Forcing estimates from an emissions‐based perspective, in the case of CH 4 , provide a more direct attribution of the forcing to changing emissions and have greater relevance for policy makers (Shindell et al., 2013).…”

“…Outside of CMIP6, ESMs including UKESM1 are starting to include more interactive CH 4 cycles, with CH 4 emissions-driven rather than concentration-driven (Folberth et al, 2022;Kleinen et al, 2020;Ocko et al, 2018).…”

Three Decades of Wetland Methane Surface Flux Modeling by Earth System Models‐Advances, Applications, and Challenges

“…In this context, we spotlight key developments in individual models that have universally advanced the prediction of methane fluxes from wetlands. Globally, one major motivation to simulating wetland methane emissions accurately is to predict atmospheric methane concentrations, an important model development is to dynamically couple the surface module with atmospheric chemistry (Blyth et al, 2021; Folberth et al, 2022; Heimann et al, 2020). A fully coupled ESM should be able to predict fluctuations in atmospheric methane concentration in the past (Kleinen et al, 2023).…”

“…As such, CMIP models do not include feedbacks between methane emissions and climate. Arguably, fully coupled ESMs now include biogeochemical processes regulating methane emissions in wetlands, incorporating feedbacks between climate dynamics and the global carbon cycle (Folberth et al, 2022;He et al, 2020;Nazarenko et al, 2022;Nzotungicimpaye et al, 2021). Similar to LSMs in general (Fisher & Koven, 2020), wetland modeling schemes are now becoming more complex, focusing on aspects across all temporal and spatial scales for example, either on incorporating detailed reaction networks (Sulman et al, 2023) or on coupling with the atmosphere (Folberth et al, 2022).…”

Drivers of persistent changes in the global methane cycle under aggressive mitigation action

“…In our simulations these include offshore oceanic sources, hydrates, and termites. "Surface Flux Adjustment" represents the residual methane surface exchange fluxes at each gridpoint in relation to the methane surface mole fraction derived from observations (29). A pre-industrial climatology of these residual fluxes was used to calibrate the model at simulation start, and this term remains constant throughout the entire transient simulation.…”