Quantifying the Known Unknown: Including Marine Sources of Greenhouse Gases in Climate Modeling

Researchers have recently estimated that Arctic submarine permafrost currently traps 60 billion tons of methane and contains 560 billion tons of organic carbon in seafloor sediments and soil, a giant pool of carbon with potentially large feedbacks on the climate system. Unlike terrestrial permafrost...

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Main Authors: Frederick, Jennifer M., Conley, Ethan W., Nole, Michael A., Marchitto, Thomas, Wagman, Benjamin M.
Language:unknown
Published: 2023
Subjects:
Online Access:http://www.osti.gov/servlets/purl/1889332
https://www.osti.gov/biblio/1889332
https://doi.org/10.2172/1889332
id ftosti:oai:osti.gov:1889332
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spelling ftosti:oai:osti.gov:1889332 2023-07-30T04:00:17+02:00 Quantifying the Known Unknown: Including Marine Sources of Greenhouse Gases in Climate Modeling Frederick, Jennifer M. Conley, Ethan W. Nole, Michael A. Marchitto, Thomas Wagman, Benjamin M. 2023-05-15 application/pdf http://www.osti.gov/servlets/purl/1889332 https://www.osti.gov/biblio/1889332 https://doi.org/10.2172/1889332 unknown http://www.osti.gov/servlets/purl/1889332 https://www.osti.gov/biblio/1889332 https://doi.org/10.2172/1889332 doi:10.2172/1889332 54 ENVIRONMENTAL SCIENCES 2023 ftosti https://doi.org/10.2172/1889332 2023-07-11T10:15:07Z Researchers have recently estimated that Arctic submarine permafrost currently traps 60 billion tons of methane and contains 560 billion tons of organic carbon in seafloor sediments and soil, a giant pool of carbon with potentially large feedbacks on the climate system. Unlike terrestrial permafrost, the submarine permafrost system has remained a “known unknown” because of the difficulty in acquiring samples and measurements. Consequently, this potentially large carbon stock never yet considered in global climate models or policy discussions, represents a real wildcard in our understanding of Earth’s climate. This report summarizes our group’s effort at developing a numerical modeling framework designed to produce a first-of-its-kind estimate of Arctic methane gas releases from the marine sediments to the water column, and potentially to the atmosphere, where positive climate feedback may occur. Newly developed modeling capability supported by the Laboratory Directed Research and Development (LDRD) program at Sandia National Laboratories now gives us the ability to probabilistically map gas distribution and quantity in the seabed by using a hybrid approach of geospatial machine learning, and predictive numerical thermodynamic ensemble modeling. The novelty in this approach is its ability to produce maps of useful data in regions that are only sparsely sampled, a common challenge in the Arctic, and a major obstacle to progress in the past. By applying this model to the circum-Arctic continental shelves and integrating the flux of free gas from in situ methanogenesis and dissociating gas hydrates from the sediment column under climate forcing, we can provide the most reliable estimate of a spatially and temporally varying source term for greenhouse gas flux that can be used by global oceanographic circulation and Earth system models (such as DOE’s E3SM). The result will allow us to finally tackle the wildcard of the submarine permafrost carbon system, and better inform us about the severity of future national ... Other/Unknown Material arctic methane Arctic permafrost SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) Arctic
institution Open Polar
collection SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy)
op_collection_id ftosti
language unknown
topic 54 ENVIRONMENTAL SCIENCES
spellingShingle 54 ENVIRONMENTAL SCIENCES
Frederick, Jennifer M.
Conley, Ethan W.
Nole, Michael A.
Marchitto, Thomas
Wagman, Benjamin M.
Quantifying the Known Unknown: Including Marine Sources of Greenhouse Gases in Climate Modeling
topic_facet 54 ENVIRONMENTAL SCIENCES
description Researchers have recently estimated that Arctic submarine permafrost currently traps 60 billion tons of methane and contains 560 billion tons of organic carbon in seafloor sediments and soil, a giant pool of carbon with potentially large feedbacks on the climate system. Unlike terrestrial permafrost, the submarine permafrost system has remained a “known unknown” because of the difficulty in acquiring samples and measurements. Consequently, this potentially large carbon stock never yet considered in global climate models or policy discussions, represents a real wildcard in our understanding of Earth’s climate. This report summarizes our group’s effort at developing a numerical modeling framework designed to produce a first-of-its-kind estimate of Arctic methane gas releases from the marine sediments to the water column, and potentially to the atmosphere, where positive climate feedback may occur. Newly developed modeling capability supported by the Laboratory Directed Research and Development (LDRD) program at Sandia National Laboratories now gives us the ability to probabilistically map gas distribution and quantity in the seabed by using a hybrid approach of geospatial machine learning, and predictive numerical thermodynamic ensemble modeling. The novelty in this approach is its ability to produce maps of useful data in regions that are only sparsely sampled, a common challenge in the Arctic, and a major obstacle to progress in the past. By applying this model to the circum-Arctic continental shelves and integrating the flux of free gas from in situ methanogenesis and dissociating gas hydrates from the sediment column under climate forcing, we can provide the most reliable estimate of a spatially and temporally varying source term for greenhouse gas flux that can be used by global oceanographic circulation and Earth system models (such as DOE’s E3SM). The result will allow us to finally tackle the wildcard of the submarine permafrost carbon system, and better inform us about the severity of future national ...
author Frederick, Jennifer M.
Conley, Ethan W.
Nole, Michael A.
Marchitto, Thomas
Wagman, Benjamin M.
author_facet Frederick, Jennifer M.
Conley, Ethan W.
Nole, Michael A.
Marchitto, Thomas
Wagman, Benjamin M.
author_sort Frederick, Jennifer M.
title Quantifying the Known Unknown: Including Marine Sources of Greenhouse Gases in Climate Modeling
title_short Quantifying the Known Unknown: Including Marine Sources of Greenhouse Gases in Climate Modeling
title_full Quantifying the Known Unknown: Including Marine Sources of Greenhouse Gases in Climate Modeling
title_fullStr Quantifying the Known Unknown: Including Marine Sources of Greenhouse Gases in Climate Modeling
title_full_unstemmed Quantifying the Known Unknown: Including Marine Sources of Greenhouse Gases in Climate Modeling
title_sort quantifying the known unknown: including marine sources of greenhouse gases in climate modeling
publishDate 2023
url http://www.osti.gov/servlets/purl/1889332
https://www.osti.gov/biblio/1889332
https://doi.org/10.2172/1889332
geographic Arctic
geographic_facet Arctic
genre arctic methane
Arctic
permafrost
genre_facet arctic methane
Arctic
permafrost
op_relation http://www.osti.gov/servlets/purl/1889332
https://www.osti.gov/biblio/1889332
https://doi.org/10.2172/1889332
doi:10.2172/1889332
op_doi https://doi.org/10.2172/1889332
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