Trends in the Global Net Land Sink and Their Sensitivity to Environmental Forcing Factors: Results From the Multi-Scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP)

Tuesday, 16 December 2014: 4:00 PM
Deborah N Huntzinger1, Christopher R Schwalm1, Anna M Michalak2, Yaxing Wei3, Robert B Cook3, Kevin M Schaefer4, Andrew R Jacobson5, Muhammad Altaf Arain6, Philippe Ciais7, Joshua B Fisher8, Daniel J Hayes3, Maoyi Huang9, Suo Huang6, Akihiko Ito10, Atul Jain11, Huimin Lei9, Chaoqun Lu12, Fabienne Maignan7, Jiafu Mao3, Nicholas Parazoo13, Shushi Peng7, Changhui Peng14, Benjamin Poulter15, Daniel M Ricciuto3, Xiaoying Shi3, Hanqin Tian12, Ning Zeng16, Fang Zhao17, Qiuan Zhu18 and Weile Wang19, (1)Northern Arizona University, Flagstaff, AZ, United States, (2)Carnegie Institution for Science, Washington, DC, United States, (3)Oak Ridge National Laboratory, Oak Ridge, TN, United States, (4)University of Colorado, National Snow and Ice Data Center, Boulder, CO, United States, (5)University of Colorado at Boulder, Boulder, CO, United States, (6)McMaster University, Hamilton, ON, Canada, (7)CEA Saclay DSM / LSCE, Gif sur Yvette, France, (8)Jet Propulsion Lab, Pasadena, CA, United States, (9)Pacific NW Nat'l Lab-Atmos Sci, Richland, WA, United States, (10)CGER-NIES, Tsukuba, Japan, (11)University of Illinois at Urbana Champaign, Urbana, IL, United States, (12)Auburn University at Montgomery, Auburn, AL, United States, (13)NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States, (14)University of Quebec at Montreal UQAM, Montreal, QC, Canada, (15)Montana State University, Bozeman, MT, United States, (16)Univ Maryland, College Park, MD, United States, (17)University of Maryland, College Park, MD, United States, (18)Northwest A&F University, Yangling, China, (19)CSUMB & NASA/AMES, Seaside, CA, United States
Predictions of future climate depend strongly on trends in net uptake or release of carbon by the land biosphere. However, model estimates of the strength of the net global land sink during the Industrial Era vary widely. Here we evaluate results from an ensemble of uncoupled models taken from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) and forced by the same input fields. When compared to estimates inferred from atmospheric CO2 observations (i.e., fossil fuel emission + net land use change - atmospheric increase - ocean uptake), MsTMIP models estimate, on average, a stronger global net land uptake of carbon (e.g., -0.3 to 8.7 Pg C/yr from 2000 to 2010, where a negative flux represents a net release to the atmosphere). Some models consistently show the land surface as a net source of carbon to the atmosphere, which is inconsistent with the other terms in the global anthropogenic CO2 budget. In addition, regional differences in land carbon exchange are compared across models and to estimates derived from atmospheric inversions and inventory based approaches. Using the semi-factorial simulations of the MsTMIP activity, we examine how model estimates of the cumulative global net land sink diverge over the period 1900 to 2010, and the degree to which model sensitivity to forcing factors contribute to this divergence. We link differences in estimates of the cumulative land sink back to each model’s sensitivity to climate variability, CO2 fertilization, nitrogen limitation, and net land-use change. Throughout the 110-year time period, the strength of carbon uptake in most models appears to be strongly sensitive to atmospheric CO2 concentrations (CO2 fertilization effect). The strength of this relationship, however, varies across models depending on model structure (e.g., stronger CO2 fertilization effect in models without an interactive nitrogen cycle with N limitations) and across decades (e.g., strong sensitivity of net flux to increasing atmospheric CO2 concentrations after 1970s).


Huntzinger et al. (2014) NACP MsTMIP - Part 1: Overview and Experimental Design. www.geosci-model-dev.net/6/2121/2013/

Wei et al. (2014) NACP MsTMIP: Global and North American Driver Data for Multi-Model Intercomparison. DOI:  10.3334/ORNLDAAC/1220