A simplified, data-constrained approach to estimate the permafrost carbon-climate feedback.

We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify t...

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Main Authors: Koven, CD, Schuur, EAG, Schädel, C, Bohn, TJ, Burke, EJ, Chen, G, Chen, X, Ciais, P, Grosse, G, Harden, JW, Hayes, DJ, Hugelius, G, Jafarov, EE, Krinner, G, Kuhry, P, Lawrence, DM, MacDougall, AH, Marchenko, SS, McGuire, AD, Natali, SM, Nicolsky, DJ, Olefeldt, D, Peng, S, Romanovsky, VE, Schaefer, KM, Strauss, J, Treat, CC, Turetsky, M
Format: Article in Journal/Newspaper
Language:unknown
Published: eScholarship, University of California 2015
Subjects:
Online Access:https://escholarship.org/uc/item/7t14r7vv
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spelling ftcdlib:oai:escholarship.org/ark:/13030/qt7t14r7vv 2023-05-15T17:56:20+02:00 A simplified, data-constrained approach to estimate the permafrost carbon-climate feedback. Koven, CD Schuur, EAG Schädel, C Bohn, TJ Burke, EJ Chen, G Chen, X Ciais, P Grosse, G Harden, JW Hayes, DJ Hugelius, G Jafarov, EE Krinner, G Kuhry, P Lawrence, DM MacDougall, AH Marchenko, SS McGuire, AD Natali, SM Nicolsky, DJ Olefeldt, D Peng, S Romanovsky, VE Schaefer, KM Strauss, J Treat, CC Turetsky, M 20140423 - 20140423 2015-11-01 application/pdf https://escholarship.org/uc/item/7t14r7vv unknown eScholarship, University of California qt7t14r7vv https://escholarship.org/uc/item/7t14r7vv public Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, vol 373, iss 2054 Carbon Models Statistical Ecosystem Environmental Monitoring Freezing Chemical Feedback Computer Simulation Databases Factual Climate Change Permafrost carbon–climate feedbacks methane carbon-climate feedbacks General Science & Technology article 2015 ftcdlib 2019-12-20T23:53:31Z We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation-Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2-33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9-112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of -14 to -19 Pg C °C(-1) on a 100 year time scale. For CH4 emissions, our approach assumes a fixed saturated area and that increases in CH4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10-18%. The simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming. Article in Journal/Newspaper permafrost University of California: eScholarship
institution Open Polar
collection University of California: eScholarship
op_collection_id ftcdlib
language unknown
topic Carbon
Models
Statistical
Ecosystem
Environmental Monitoring
Freezing
Chemical
Feedback
Computer Simulation
Databases
Factual
Climate Change
Permafrost
carbon–climate feedbacks
methane
carbon-climate feedbacks
General Science & Technology
spellingShingle Carbon
Models
Statistical
Ecosystem
Environmental Monitoring
Freezing
Chemical
Feedback
Computer Simulation
Databases
Factual
Climate Change
Permafrost
carbon–climate feedbacks
methane
carbon-climate feedbacks
General Science & Technology
Koven, CD
Schuur, EAG
Schädel, C
Bohn, TJ
Burke, EJ
Chen, G
Chen, X
Ciais, P
Grosse, G
Harden, JW
Hayes, DJ
Hugelius, G
Jafarov, EE
Krinner, G
Kuhry, P
Lawrence, DM
MacDougall, AH
Marchenko, SS
McGuire, AD
Natali, SM
Nicolsky, DJ
Olefeldt, D
Peng, S
Romanovsky, VE
Schaefer, KM
Strauss, J
Treat, CC
Turetsky, M
A simplified, data-constrained approach to estimate the permafrost carbon-climate feedback.
topic_facet Carbon
Models
Statistical
Ecosystem
Environmental Monitoring
Freezing
Chemical
Feedback
Computer Simulation
Databases
Factual
Climate Change
Permafrost
carbon–climate feedbacks
methane
carbon-climate feedbacks
General Science & Technology
description We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation-Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2-33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9-112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of -14 to -19 Pg C °C(-1) on a 100 year time scale. For CH4 emissions, our approach assumes a fixed saturated area and that increases in CH4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10-18%. The simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming.
format Article in Journal/Newspaper
author Koven, CD
Schuur, EAG
Schädel, C
Bohn, TJ
Burke, EJ
Chen, G
Chen, X
Ciais, P
Grosse, G
Harden, JW
Hayes, DJ
Hugelius, G
Jafarov, EE
Krinner, G
Kuhry, P
Lawrence, DM
MacDougall, AH
Marchenko, SS
McGuire, AD
Natali, SM
Nicolsky, DJ
Olefeldt, D
Peng, S
Romanovsky, VE
Schaefer, KM
Strauss, J
Treat, CC
Turetsky, M
author_facet Koven, CD
Schuur, EAG
Schädel, C
Bohn, TJ
Burke, EJ
Chen, G
Chen, X
Ciais, P
Grosse, G
Harden, JW
Hayes, DJ
Hugelius, G
Jafarov, EE
Krinner, G
Kuhry, P
Lawrence, DM
MacDougall, AH
Marchenko, SS
McGuire, AD
Natali, SM
Nicolsky, DJ
Olefeldt, D
Peng, S
Romanovsky, VE
Schaefer, KM
Strauss, J
Treat, CC
Turetsky, M
author_sort Koven, CD
title A simplified, data-constrained approach to estimate the permafrost carbon-climate feedback.
title_short A simplified, data-constrained approach to estimate the permafrost carbon-climate feedback.
title_full A simplified, data-constrained approach to estimate the permafrost carbon-climate feedback.
title_fullStr A simplified, data-constrained approach to estimate the permafrost carbon-climate feedback.
title_full_unstemmed A simplified, data-constrained approach to estimate the permafrost carbon-climate feedback.
title_sort simplified, data-constrained approach to estimate the permafrost carbon-climate feedback.
publisher eScholarship, University of California
publishDate 2015
url https://escholarship.org/uc/item/7t14r7vv
op_coverage 20140423 - 20140423
genre permafrost
genre_facet permafrost
op_source Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, vol 373, iss 2054
op_relation qt7t14r7vv
https://escholarship.org/uc/item/7t14r7vv
op_rights public
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