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

Autor:	Koven CD; Earth Sciences Division, Lawrence Berkeley National Lab, Berkeley, CA, USA cdkoven@lbl.gov., Schuur EA; Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, USA., Schädel C; Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, USA., Bohn TJ; Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, USA School of Earth and Space Exploration, Arizona State University, Tempe, AZ, USA., Burke EJ; Met Office Hadley Centre, Exeter, UK., Chen G; Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA., Chen X; Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, USA., Ciais P; Laboratoire des Sciences du Climat et de l'Environnement (LSCE CEA-CNRS-UVSQ), Gif-sur-Yvette, France., Grosse G; Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Periglacial Research Unit, Potsdam, Germany., Harden JW; United States Geological Survey, Menlo Park, CA, USA., Hayes DJ; Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA., Hugelius G; Department of Physical Geography, Bolin Centre of Climate Research, Stockholm University, Stockholm, Sweden., Jafarov EE; National Snow and Ice Data Center, University of Colorado, Boulder, CO, USA., Krinner G; Laboratoire de Glaciologie et Géophysique de l'Environnement, CNRS and Université Grenoble Alpes, Grenoble 38041, France., Kuhry P; Department of Physical Geography, Bolin Centre of Climate Research, Stockholm University, Stockholm, Sweden., Lawrence DM; Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO, USA., MacDougall AH; School of Earth and Ocean Sciences, University of Victoria, Victoria, British Columbia, Canada., Marchenko SS; Geophysical Institute Permafrost Laboratory, University of Alaska, Fairbanks, AK, USA., McGuire AD; US Geological Survey, Alaska Cooperative Fish and Wildlife Research Unit, University of Alaska Fairbanks, Fairbanks, AK, USA., Natali SM; Woods Hole Research Center, Falmouth, MA, USA., Nicolsky DJ; Geophysical Institute Permafrost Laboratory, University of Alaska, Fairbanks, AK, USA., Olefeldt D; Department of Renewable Resources, University of Alberta, Edmonton, Alberta, Canada., Peng S; Laboratoire des Sciences du Climat et de l'Environnement (LSCE CEA-CNRS-UVSQ), Gif-sur-Yvette, France Laboratoire de Glaciologie et Géophysique de l'Environnement, CNRS and Université Grenoble Alpes, Grenoble 38041, France., Romanovsky VE; Geophysical Institute Permafrost Laboratory, University of Alaska, Fairbanks, AK, USA., Schaefer KM; National Snow and Ice Data Center, University of Colorado, Boulder, CO, USA., Strauss J; Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Periglacial Research Unit, Potsdam, Germany., Treat CC; United States Geological Survey, Menlo Park, CA, USA., Turetsky M; Department of Integrative Biology, University of Ontario, Guelph, Ontario, Canada.
Jazyk:	angličtina
Zdroj:	Philosophical transactions. Series A, Mathematical, physical, and engineering sciences [Philos Trans A Math Phys Eng Sci] 2015 Nov 13; Vol. 373 (2054).
DOI:	10.1098/rsta.2014.0423
Abstrakt:	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. (© 2015 The Authors.)
Databáze:	MEDLINE
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