Atmospheric inversion of surface carbon flux with consideration of the spatial distribution of US crop production and consumption

J M Chen,F Deng,G Mo,T O West,J W Fung

doi:10.5194/bg-12-323-2015

Abstract

Abstract. In order to improve quantification of the spatial distribution of carbon sinks and sources in the conterminous US, we conduct a nested global atmospheric inversion with detailed spatial information on crop production and consumption. County-level cropland net primary productivity, harvested biomass, soil carbon change, and human and livestock consumption data over the conterminous US are used for this purpose. Time-dependent Bayesian synthesis inversions are conducted based on CO2 observations at 210 stations to infer CO2 fluxes globally at monthly time steps with a nested focus on 30 regions in North America. Prior land surface carbon fluxes are first generated using a biospheric model, and the inversions are constrained using prior fluxes with and without adjustments for crop production and consumption over the 2002–2007 period. After these adjustments, the inverted regional carbon sink in the US Midwest increases from 0.25 ± 0.03 to 0.42 ± 0.13 Pg C yr−1, whereas the large sink in the US southeast forest region is weakened from 0.41 ± 0.12 to 0.29 ± 0.12 Pg C yr−1. These adjustments also reduce the inverted sink in the west region from 0.066 ± 0.04 to 0.040 ± 0.02 Pg C yr−1 because of high crop consumption and respiration by humans and livestock. The general pattern of sink increases in crop production areas and sink decreases (or source increases) in crop consumption areas highlights the importance of considering the lateral carbon transfer in crop products in atmospheric inverse modeling, which provides a reliable atmospheric perspective of the overall carbon balance at the continental scale but is unreliable for separating fluxes from different ecosystems.

Highlights

Human activities have greatly modified the global carbon cycle through fossil fuel consumption, cement production, and land use (Canadell et al, 2007; Le Quéré et al, 2013)
If signal-to-noise ratio (SNR) is less than unity, the resulting change due to an agricultural adjustment is less than the uncertainty, and the signal is within the noise level of the results
One set of experiments utilizes the prior flux that is annually neutralized for each region before the adjustments, and the other set utilizes the prior flux without the neutralization

Summary

Introduction

Human activities have greatly modified the global carbon cycle through fossil fuel consumption, cement production, and land use (Canadell et al, 2007; Le Quéré et al, 2013). Due to the complexity and heterogeneity of land cover, it has been a challenge to estimate the spatial distribution and magnitude of terrestrial carbon sources and sinks. Our ability to project the carbon cycle and estimate its influence on climate will remain limited if we cannot resolve the current carbon source and sink distribution patterns and provide plausible mechanistic explanations for the patterns. In this regard, regional studies that focus on the spatial distribution of carbon dynamics would be a useful direction for improving our understanding of the global carbon cycle. GFEDv2 (Randerson et al, 2007) BEPS model (Chen et al, 2012; Ju et al, 2006)

Objectives

Results

Discussion

Conclusion