Natural variability in a stable, 1000-yr global coupled climate-carbon cycle simulation

Author Posting. © American Meteorological Society 2006. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 19 (2006): 3033–3054, doi:10.1175/JCLI3783.1.A new 3D global coupled carbon–climate model is presented in the framework of the Community Climate System Model (CSM-1.4). The biogeochemical module includes explicit land water–carbon coupling, dynamic carbon allocation to leaf, root, and wood, prognostic leaf phenology, multiple soil and detrital carbon pools, oceanic iron limitation, a full ocean iron cycle, and 3D atmospheric CO2 transport. A sequential spinup strategy is utilized to minimize the coupling shock and drifts in land and ocean carbon inventories. A stable, 1000-yr control simulation [global annual mean surface temperature ±0.10 K and atmospheric CO2 ± 1.2 ppm (1σ)] is presented with no flux adjustment in either physics or biogeochemistry. The control simulation compares reasonably well against observations for key annual mean and seasonal carbon cycle metrics; regional biases in coupled model physics, however, propagate clearly into biogeochemical error patterns. Simulated interannual-to-centennial variability in atmospheric CO2 is dominated by terrestrial carbon flux variability, ±0.69 Pg C yr−1 (1σ global net annual mean), which in turn reflects primarily regional changes in net primary production modulated by moisture stress. Power spectra of global CO2 fluxes are white on time scales beyond a few years, and thus most of the variance is concentrated at high frequencies (time scale 20 yr), global net ocean CO2 flux is strongly anticorrelated (0.7–0.95) with the net CO2 flux from land; the ocean tends to damp (20%–25%) slow variations in atmospheric CO2 generated by the terrestrial biosphere. The intrinsic, unforced natural variability in land and ocean carbon storage is the “noise” that complicates the detection and mechanistic attribution of contemporary anthropogenic carbon sinks.This work was supported by NCAR, NSF ATM-9987457, NASA EOS-IDS Grant NAG5-9514, NASA Carbon Cycle Program Grant NAG5-11200, Lawrence Berkeley National Laboratory LDRD, and the WHOI Ocean and Climate Change Institute