Optimization of a prognostic biosphere model for terrestrial biomass and atmospheric CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; variability

M Saito,S Maksyutov,A Ito

doi:10.5194/gmd-7-1829-2014

Optimization of a prognostic biosphere model for terrestrial biomass and atmospheric CO&lt;sub&gt;2&lt;/sub&gt; variability

M Saito, S Maksyutov + Show 1 more

Open Access

https://doi.org/10.5194/gmd-7-1829-2014

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Abstract

Abstract. This study investigates the capacity of a prognostic biosphere model to simulate global variability in atmospheric CO2 concentrations and vegetation carbon dynamics under current environmental conditions. Global data sets of atmospheric CO2 concentrations, above-ground biomass (AGB), and net primary productivity (NPP) in terrestrial vegetation were assimilated into the biosphere model using an inverse modeling method combined with an atmospheric transport model. In this process, the optimal physiological parameters of the biosphere model were estimated by minimizing the misfit between observed and modeled values, and parameters were generated to characterize various biome types. Results obtained using the model with the optimized parameters correspond to the observed seasonal variations in CO2 concentration and their annual amplitudes in both the Northern and Southern Hemispheres. In simulating the mean annual AGB and NPP, the model shows improvements in estimating the mean magnitudes and probability distributions for each biome, as compared with results obtained using prior simulation parameters. However, the model is less efficient in its simulation of AGB for forest type biomes. This misfit suggests that more accurate values of input parameters, specifically, grid mean AGB values and seasonal variabilities in physiological parameters, are required to improve the performance of the simulation model.

Highlights

The terrestrial biosphere generally absorbs CO2 from the atmosphere, and its annual global carbon uptake rate is considered to be similar to that of the ocean (Tans et al, 1990)
The reanalysis/assimilation data sets released by the Japan Meteorological Agency (JMA) and the Japan 25-year reanalysis (JRA-25)/JMA Climate Data Assimilation System (JCDAS) (Onogi et al, 2007) are used to force the Vegetation Integrative SImulator for Trace gases (VISIT) simulation
The prior value of χ 2 that is weighted by number of data points for atmospheric CO2, above-ground biomass (AGB), and net primary productivity (NPP) is 7.80

Summary

Introduction

The terrestrial biosphere generally absorbs CO2 from the atmosphere, and its annual global carbon uptake rate is considered to be similar to that of the ocean (Tans et al, 1990). Many studies have attempted to accurately quantify the total carbon exchange rate between the terrestrial biosphere and the atmosphere and to determine the role of the terrestrial biosphere in the global carbon cycle (e.g., Schimel, 1995; Field et al, 1998). Cramer et al (1999) compared 17 biosphere models and found that global terrestrial net primary productivity (NPP) calculated by the models ranged from approximately 40 to 65 Pg C yr−1 and that the models yielded different NPP spatial distributions. Even at regional scales, Ichii et al (2010) reported large differences in the magnitudes of annual gross primary productivity (GPP) and ecosystem respiration generated by nine simulation models. The discrepancies revealed by the systematic comparisons between different biosphere models indicate that the current biosphere models are still in need of improvement (Friedlingstein et al, 2006; Jung et al, 2007; Sitch et al, 2008)

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Conclusion