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An overview of the project ‘ReGAME – Reliable Global Methane Emissions estimates in a changing world’

Platt, Stephen Matthew; Myhre, Cathrine Lund; Stebel, Kerstin; Thompson, Rona Louise; Zwaaftink, Christine Groot; Pisso, Ignacio; Schneider, Philipp; Myhre , Gunnar; Hodnebrog, Øivind; Skeie, Ragnhild Bieltvedt; Hermansen, Ove; Schmidbauer, Norbert; Stohl, Andreas; Serov, Pavel; Ferré, Benedicte

Publication details

Event: Methane in a changing Arctic (Tromsø, Norway)

Date: September 14th 2022 – September 16th 2022

Here we provide an overview of the newly commenced project ‘ReGAME - Reliable Global Methane Emissions estimates in a changing world’, funded by Research Council of Norway from 2021-2025, where we combine new developments in atmospheric methane observations: isotopic ratios (deuterium and 13C in methane), and the Integrated Carbon Observation System (ICOS) ground-based station network with atmospheric models (the chemistry transport model OsloCTM, and inversion model FLEXINVERT) to understand how and why atmospheric methane levels are increasing. The project has a particular focus on understanding the state of Arctic methane reservoirs such as ocean seeps and high latitude wetlands. This includes plans for a new observing system aboard the ice breaking vessel RV Kronprins Haakon and ocean observations, e.g., dynamics of Seep fluxes assessed during 1 year of continuous measurements at a seep site the NorEMSO project, updated information on spatial seep distribution via echo sounding, as well as high resolution high-latitude inversion modeling of atmospheric methane with FLEXINVERT. Furthermore, we investigate the utility of including of satellite data (TROPOMI aboard the Sentinel 5P mission) together with ground-based data, in inversion modeling. The inclusion of satellite data into inversion models is quite novel and offers rewards by increasing spatial coverage compared to ground based networks alone, potentially reducing uncertainties in the model outputs, and challenges due to satellite data uncertainties, spatial/ temporal coverage, and handling large data fields