An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data
An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data
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DOI：
10.5194/acp-19-14721-2019
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发表时间：
2019-12-11
影响因子：
6.3
通讯作者：
Parker, Robert J.
中科院分区：
文献类型：
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作者：
Lunt, Mark F.;Palmer, Paul I.;Parker, Robert J.
热带生态系统的甲烷（CH 4）排放及其对气候变化的响应是与全球CH 4收支相关的最大不确定性之一。从历史上看，这是由于缺乏泛热带实地测量，这在非洲尤其严重。由于其上级空间覆盖范围，大气CH（4）柱的卫星观测可以帮助缩小热带CH（4）排放收支的一些不确定性。我们使用日本温室气体观测卫星（GOSAT）和嵌套版本的GEOS-Chem大气化学和传输模型（0.5度x 0.625度）的大气CH 4（XCH 4）的代理柱检索来推断2010年至2016年热带非洲的排放量。代理检索XCH 4的散射由于云和气溶胶比完整的物理检索不太敏感，但该方法假设二氧化碳（CO2）的全球分布是已知的。我们探索的敏感性推断后验排放量的系统误差的来源，通过使用两个不同的XCH 4数据产品，确定使用不同的模式CO2字段。我们使用分层贝叶斯框架从GOSAT XCH 4数据推断每月排放量，使我们能够报告年度平均值的季节周期和趋势。我们发现，2010年至2016年期间，热带非洲的平均排放量范围为76（74-78）至80（78-82）Tg yr（-1），具体取决于所使用的XCH 4替代数据，北方半球非洲的差异大于南半球非洲。我们发现一个强大的积极的线性趋势，热带非洲CH 4排放量为我们的7年研究期，值为1.5（1.11.9）Tg年（-1）或2.1（1.7-2.5）Tg年（-1），这取决于在代理检索中使用的CO2数据产品。这一线性排放趋势约占这一时期全球排放增长率的三分之一。这一增长的很大一部分是由于2011年至2015年期间南苏丹的排放量短期增加了3 Tg yr（-1）。使用卫星陆地表面温度异常和测高数据，我们发现这种增加CH 4排放量是一致的湿地范围的增加，由于增加流入的白色尼罗河，虽然数据表明，Sudd在我们的逆温期开始时非常干燥。我们发现北方非洲的排放具有很强的季节性，季节性排放高峰的时间与地下水储存的季节性高峰相一致。相比之下，我们发现，从刚果盆地的湿地面积的后验CH 4排放量几乎是恒定的，在湿地范围内的时间变化较小，并显着小于先验估计。
Emissions of methane (CH4) from tropical ecosystems, and how they respond to changes in climate, represent one of the biggest uncertainties associated with the global CH(4 )budget. Historically, this has been due to the dearth of pan-tropical in situ measurements, which is particularly acute in Africa. By virtue of their superior spatial coverage, satellite observations of atmospheric CH(4)columns can help to narrow down some of the uncertainties in the tropical CH(4)emission budget. We use proxy column retrievals of atmospheric CH4 (XCH4) from the Japanese Greenhouse gases Observing Satellite (GOSAT) and the nested version of the GEOS-Chem atmospheric chemistry and transport model (0.5 degrees x 0.625 degrees) to infer emissions from tropical Africa between 2010 and 2016. Proxy retrievals of XCH4 are less sensitive to scattering due to clouds and aerosol than full physics retrievals, but the method assumes that the global distribution of carbon dioxide (CO2) is known. We explore the sensitivity of inferred a posteriori emissions to this source of systematic error by using two different XCH4 data products that are determined using different model CO2 fields. We infer monthly emissions from GOSAT XCH4 data using a hierarchical Bayesian framework, allowing us to report seasonal cycles and trends in annual mean values. We find mean tropical African emissions between 2010 and 2016 range from 76 (74-78) to 80 (78-82) Tg yr(-1), depending on the proxy XCH4 data used, with larger differences in Northern Hemisphere Africa than Southern Hemisphere Africa. We find a robust positive linear trend in tropical African CH4 emissions for our 7-year study period, with values of 1.5 (1.11.9) Tg yr(-1) or 2.1 (1.7-2.5) Tg yr(-1), depending on the CO2 data product used in the proxy retrieval. This linear emissions trend accounts for around a third of the global emissions growth rate during this period. A substantial portion of this increase is due to a short-term increase in emissions of 3 Tg yr(-1) between 2011 and 2015 from the Sudd in South Sudan. Using satellite land surface temperature anomalies and altimetry data, we find this increase in CH4 emissions is consistent with an increase in wetland extent due to increased inflow from the White Nile, although the data indicate that the Sudd was anomalously dry at the start of our inversion period. We find a strong seasonality in emissions across Northern Hemisphere Africa, with the timing of the seasonal emissions peak coincident with the seasonal peak in ground water storage. In contrast, we find that a posteriori CH4 emissions from the wetland area of the Congo Basin are approximately constant throughout the year, consistent with less temporal variability in wetland extent, and significantly smaller than a priori estimates.