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Anders Ahlström

Anders Ahlström

Senior lecturer

Anders Ahlström

Sources of uncertainty in modeled land carbon storage within and across three MIPs : Diagnosis with three new techniques

Author

  • Sha Zhou
  • Junyi Liang
  • Xingjie Luc
  • Qianyu Lid
  • Lifen Jiang
  • Yao Zhang
  • Christopher R. Schwalm
  • Joshua B. Fisher
  • Jerry Tjiputra
  • Stephen Sitch
  • Anders Ahlström
  • Deborah N. Huntzinger
  • Yuefei Huang
  • Guangqian Wang
  • Yiqi Luo
Show all

Summary, in English

Terrestrial carbon cycle models have incorporated increasingly more processes as a means to achieve more-realistic representations of ecosystem carbon cycling. Despite this, there are large across-model variations in the simulation and projection of carbon cycling. Several model intercomparison projects (MIPs), for example, the fifth phase of the Coupled Model Intercomparison Project (CMIP5) (historical simulations), Trends in Net Land-Atmosphere Carbon Exchange (TRENDY), and Multiscale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), have sought to understand intermodel differences. In this study, the authors developed a suite of new techniques to conduct post-MIP analysis to gain insights into uncertainty sources across 25 models in the three MIPs. First, terrestrial carbon storage dynamics were characterized by a three-dimensional (3D) model output space with coordinates of carbon residence time, net primary productivity (NPP), and carbon storage potential. The latter represents the potential of an ecosystem to lose or gain carbon. This space can be used to measure how and why model output differs. Models with a nitrogen cycle generally exhibit lower annual NPP in comparison with other models, and mostly negative carbon storage potential. Second, a transient traceability framework was used to decompose any given carbon cycle model into traceable components and identify the sources of model differences. The carbon residence time (or NPP) was traced to baseline carbon residence time (or baseline NPP related to the maximum carbon input), environmental scalars, and climate forcing. Third, by applying a variance decomposition method, the authors show that the intermodel differences in carbon storage can be mainly attributed to the baseline carbon residence time and baseline NPP (>90% in the three MIPs). The three techniques developed in this study offer a novel approach to gain more insight from existing MIPs and can point out directions for future MIPs. Since this study is conducted at the global scale for an overview on intermodel differences, future studies should focus more on regional analysis to identify the sources of uncertainties and improve models at the specified mechanism level.

Department/s

  • Dept of Physical Geography and Ecosystem Science
  • MERGE: ModElling the Regional and Global Earth System
  • BECC: Biodiversity and Ecosystem services in a Changing Climate

Publishing year

2018-04-01

Language

English

Pages

2833-2851

Publication/Series

Journal of Climate

Volume

31

Issue

7

Document type

Journal article

Publisher

American Meteorological Society

Topic

  • Geosciences, Multidisciplinary

Keywords

  • Carbon cycle
  • Land surface model
  • Model evaluation/performance

Status

Published

ISBN/ISSN/Other

  • ISSN: 0894-8755