4.7 Article

Recent global CO2 flux inferred from atmospheric CO2 observations and its regional analyses

期刊

BIOGEOSCIENCES
卷 8, 期 11, 页码 3263-3281

出版社

COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/bg-8-3263-2011

关键词

-

资金

  1. Natural Sciences and Engineering Research Council of Canada (NSERC)
  2. Natural Sciences and Engineering Research Council
  3. Meteorological Service Canada (MSC)
  4. CFCAS [GR-646]

向作者/读者索取更多资源

The net surface exchange of CO2 for the years 2002-2007 is inferred from 12 181 atmospheric CO2 concentration data with a time-dependent Bayesian synthesis inversion scheme. Monthly CO2 fluxes are optimized for 30 regions of the North America and 20 regions for the rest of the globe. Although there have been many previous multiyear inversion studies, the reliability of atmospheric inversion techniques has not yet been systematically evaluated for quantifying regional interannual variability in the carbon cycle. In this study, the global interannual variability of the CO2 flux is found to be dominated by terrestrial ecosystems, particularly by tropical land, and the variations of regional terrestrial carbon fluxes are closely related to climate variations. These interannual variations are mostly caused by abnormal meteorological conditions in a few months in the year or part of a growing season and cannot be well represented using annual means, suggesting that we should pay attention to finer temporal climate variations in ecosystem modeling. We find that, excluding fossil fuel and biomass burning emissions, terrestrial ecosystems and oceans absorb an average of 3.63 +/- 0.49 and 1.94 +/- 0.41 PgC yr(-1), respectively. The terrestrial uptake is mainly in northern land while the tropical and southern lands contribute 0.62 +/- 0.47, and 0.67 +/- 0.34 PgC yr(-1) to the sink, respectively. In North America, terrestrial ecosystems absorb 0.89 +/- 0.18 PgC yr(-1) on average with a strong flux density found in the south-east of the continent.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据