Variability in the sensitivity among model simulations of permafrost and carbon dynamics in the permafrost region between 1960 and 2009

Research output: Contribution to journalArticle

Abstract

A significant portion of the large amount of carbon (C) currently stored in soils of the permafrost region in the Northern Hemisphere has the potential to be emitted as the greenhouse gases CO2 and CH4 under a warmer climate. In this study we evaluated the variability in the sensitivity of permafrost and C in recent decades among land surface model simulations over the permafrost region between 1960 and 2009. The 15 model simulations all predict a loss of near-surface permafrost (within 3 m) area over the region, but there are large differences in the magnitude of the simulated rates of loss among the models (0.2 to 58.8 × 103 km2 yr−1). Sensitivity simulations indicated that changes in air temperature largely explained changes in permafrost area, although interactions among changes in other environmental variables also played a role. All of the models indicate that both vegetation and soil C storage together have increased by 156 to 954 Tg C yr−1 between 1960 and 2009 over the permafrost region even though model analyses indicate that warming alone would decrease soil C storage. Increases in gross primary production (GPP) largely explain the simulated increases in vegetation and soil C. The sensitivity of GPP to increases in atmospheric CO2 was the dominant cause of increases in GPP across the models, but comparison of simulated GPP trends across the 1982–2009 period with that of a global GPP data set indicates that all of the models overestimate the trend in GPP. Disturbance also appears to be an important factor affecting C storage, as models that consider disturbance had lower increases in C storage than models that did not consider disturbance. To improve the modeling of C in the permafrost region, there is the need for the modeling community to standardize structural representation of permafrost and carbon dynamics among models that are used to evaluate the permafrost C feedback and for the modeling and observational communities to jointly develop data sets and methodologies to more effectively benchmark models.

Details

Authors
  • A. David McGuire
  • Charles Koven
  • David M. Lawrence
  • Joy S. Clein
  • Jiangyang Xia
  • Christian Beer
  • Eleanor Burke
  • Guangsheng Chen
  • Xiaodong Chen
  • Christine Delire
  • Elchin Jafarov
  • Andrew H. MacDougall
  • Sergey Marchenko
  • Dmitry Nicolsky
  • Shushi Peng
  • Annette Rinke
  • Kazuyuki Saito
  • Ramdane Alkama
  • Theodore J. Bohn
  • Philippe Ciais
  • Bertrand Decharme
  • Altug Ekici
  • Isabelle Gouttevin
  • Tomohiro Hajima
  • Daniel J. Hayes
  • Duoying Ji
  • Gerhard Krinner
  • Dennis P. Lettenmaier
  • Yiqi Luo
  • John C. Moore
  • Vladimir Romanovsky
  • Christina Schädel
  • Kevin Schaefer
  • Edward A G Schuur
  • Tetsuo Sueyoshi
  • Qianlai Zhuang
Organisations
External organisations
  • Lawrence Berkeley National Laboratory
  • University Grenoble Alpes
  • Beijing Normal University
  • Arizona State University
  • Broad Institute
  • University of Alaska Fairbanks
  • National Center for Atmospheric Research
  • East China Normal University
  • Stockholm University
  • Met Office Hadley Centre for Climate Change
  • Oak Ridge National Laboratory
  • University of Washington, Seattle
  • Météo France (Centre De Météorologie Spatiale)
  • University of Colorado
  • University of Victoria
  • Japan Agency for Marine-Earth Science and Technology
  • Laboratoire des Sciences du Climat et de l'Environnement
  • The French National Centre for Scientific Research (CNRS)
  • University of Oklahoma
  • Northern Arizona University
  • Purdue University
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Climate Research

Keywords

  • carbon cycle, climate change, permafrost, permafrost carbon feedback, sensitivity, soil carbon
Original languageEnglish
Pages (from-to)1015-1037
Number of pages23
JournalGlobal Biogeochemical Cycles
Volume30
Issue number7
Publication statusPublished - 2016
Publication categoryResearch
Peer-reviewedYes