4.7 Article

Scale-Dependent Performance of CMIP5 Earth System Models in Simulating Terrestrial Vegetation Carbon*

Journal

JOURNAL OF CLIMATE
Volume 28, Issue 13, Pages 5217-5232

Publisher

AMER METEOROLOGICAL SOC
DOI: 10.1175/JCLI-D-14-00270.1

Keywords

-

Funding

  1. U.S. Department of Energy, Terrestrial Ecosystem Sciences [DE SC0008270]
  2. U.S. National Science Foundation (NSF) [DBI 0850290, EPS 0919466, DEB 0743778, DEB 0840964, EF 1137293]
  3. Center for Climate Dynamics and Research Council of Norway through Project EVA [229771]
  4. Division Of Environmental Biology
  5. Direct For Biological Sciences [0840964] Funding Source: National Science Foundation

Ask authors/readers for more resources

Model intercomparisons and evaluations against observations are essential for better understanding of models' performance and for identifying the sources of uncertainty in their output. The terrestrial vegetation carbon simulated by 11 Earth system models (ESMs) involved in phase 5 of the Coupled Model Intercomparison Project (CMIP5) was evaluated in this study. The simulated vegetation carbon was compared at three distinct spatial scales (grid, biome, and global) among models and against the observations (an updated database from Olson et al.'s Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation: A Database). Moreover, the underlying causes of the differences in the models' predictions were explored. Model-data fit at the grid scale was poor but greatly improved at the biome scale. Large intermodel variability was pronounced in the tropical and boreal regions, where total vegetation carbon stocks were high. While 8 out of 11 ESMs reproduced the global vegetation carbon to within 20% uncertainty of the observational estimate (560 +/- 112 Pg C), the simulated global totals varied nearly threefold between the models. The goodness of fit of ESMs in simulating vegetation carbon depended strongly on the spatial scales. Sixty-three percent of the variability in contemporary global vegetation carbon stocks across ESMs could be explained by differences in vegetation carbon residence time across ESMs (P < 0.01). The analysis indicated that ESMs' performance of vegetation carbon predictions can be substantially improved through better representation of plant longevity (i.e., carbon residence time) and its respective spatial distributions.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available