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Sensitivity of inverse estimation of annual mean CO 2 sources and sinks to ocean‐only sites versus all‐sites observational networks
Author(s) -
Patra Prabir K.,
Gurney Kevin R.,
Denning A. Scott,
Maksyutov Shamil,
Nakazawa Takakiyo,
Baker David,
Bousquet Philippe,
Bruhwiler Lori,
Chen YuHan,
Ciais Philippe,
Fan Songmiao,
Fung Inez,
Gloor Manuel,
Heimann Martin,
Higuchi Kaz,
John Jasmin,
Law Rachel M.,
Maki Takashi,
Pak Bernard C.,
Peylin Philippe,
Prather Michael,
Rayner Peter J.,
Sarmiento Jorge,
Taguchi Shoichi,
Takahashi Taro,
Yuen ChiuWai
Publication year - 2006
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2005gl025403
Subject(s) - environmental science , sensitivity (control systems) , flux (metallurgy) , range (aeronautics) , atmospheric sciences , atmospheric models , inverse , climatology , meteorology , atmosphere (unit) , geology , mathematics , geography , chemistry , materials science , geometry , organic chemistry , electronic engineering , engineering , composite material
Inverse estimation of carbon dioxide (CO 2 ) sources and sinks uses atmospheric CO 2 observations, mostly made near the Earth's surface. However, transport models used in such studies lack perfect representation of atmospheric dynamics and thus often fail to produce unbiased forward simulations. The error is generally larger for observations over the land than those over the remote/marine locations. The range of this error is estimated by using multiple transport models (16 are used here). We have estimated the remaining differences in CO 2 fluxes due to the use of ocean‐only versus all‐sites (i.e., over ocean and land) observations of CO 2 in a time‐independent inverse modeling framework. The fluxes estimated using the ocean‐only networks are more robust compared to those obtained using all‐sites networks. This makes the global, hemispheric, and regional flux determination less dependent on the selection of transport model and observation network.