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Diagnosis and quantification of climatic sensitivity of carbon fluxes in ensemble global ecosystem models

Weile Wang, CSUMB&NASA/ARC, weile.wang@gmail.com (Presenter)
Hirofumi Hashimoto, CSUMB&NASA/ARC, hirofumi.hashimoto@gmail.com
Jun Xiong, NASA Postdoctoral Program Fellow, jun.xiong1981@gmail.com
Ranga Babu Myneni, Boston University, rmyneni@bu.edu
Ramakrishna R. Nemani, NASA ARC, rama.nemani@nasa.gov

Terrestrial ecosystem models are primary scientific tools to extrapolate our understanding of ecosystem functioning from point observations to global scales as well as from the past climatic conditions into the future. However, no model is nearly perfect and there are often considerable structural uncertainties existing between different models. Ensemble model experiments thus become a mainstream approach in evaluating the current status of global carbon cycle and predicting its future changes. In such applications, a key task is to quantify the sensitivity of the simulated carbon fluxes to climate variations and changes. Here we develop a systematic framework to address this question solely by analyzing the inputs and the outputs from the models. The principle of our approach is to assume the long-term (~30 years) average of the inputs/outputs as a quasi-equlibrium of the climate-vegetation system while treat the anomalies of carbon fluxes as responses to climatic disturbances. In this way, the corresponding relationships can be largely linearized and analyzed using conventional time-series techniques. This method is used to characterize three major aspects of the vegetation models that are mostly important to global carbon cycle, namely primary production, biomass dynamics, and ecosystem respiration. We apply this analytical framework to quantify the climatic sensitivity of an ensemble of models including CASA, Biome-BGC, LPJ as well as several other DGVMs from previous studies, all driven by the CRU-NCEP climate dataset. The detailed analysis results are reported in this study.

Presentation Type:  Poster

Session:  Other   (Tue 11:30 AM)

Associated Project(s): 

  • Nemani, Rama: Understanding and predicting continental-scale disturbances with prognostic and diagnostic models: bark beetle outbreaks in North America ...details

Poster Location ID: 291

 


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