Relationships between large‐scale circulation patterns and carbon dioxide exchange by a deciduous forest

Relationships between large‐scale circulation patterns and carbon dioxide exchange by a deciduous forest
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DOI:
10.1029/2010jd014738
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发表时间:
2011-02
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通讯作者:
Jingyong Zhang;Lingyun Wu;G. Huang;M. Notaro
Jingyong Zhang;Lingyun Wu;G. Huang;M. Notaro
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文献类型:
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作者:
Jingyong Zhang;Lingyun Wu;G. Huang;M. Notaro

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[1] In this study, we focus on a deciduous forest in central Massachusetts and investigate the relationships between global climate indices and CO2 exchange using eddy-covariance flux measurements from 1992 to 2007. Results suggest that large-scale circulation patterns influence the annual CO2 exchange in the forest through their effects on the local surface climate. Annual gross ecosystem exchange (GEE) in the forest is closely associated with spring El Nino–Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO), previous fall Atlantic Multidecadal Oscillation (AMO), and previous winter East Pacific–North Pacific (EP-NP) pattern. Annual net ecosystem exchange (NEE) responds to previous fall AMO and PDO, while annual respiration (R) is impacted by previous fall ENSO and Pacific/North American Oscillation (PNA). Regressions based on these relationships are developed to simulate the annual GEE, NEE, and R. To avoid problems of multicollinearity, we compute a “Composite Index for GEE (CIGEE)” based on a linear combination of spring ENSO and PDO, fall AMO, and winter EP-NP and a “Composite Index for R (CIR)” based on a linear combination of fall ENSO and PNA. CIGEE, CIR, and fall AMO and PDO can explain 41, 27, and 40% of the variance of the annual GEE, R, and NEE, respectively. We further apply the methodology to two other northern midlatitude forests and find that interannual variabilities in NEE of the two forests are largely controlled by large-scale circulation patterns. This study suggests that global climate indices provide the potential for predicting CO2 exchange variability in the northern midlatitude forests.