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Using CO 2 spatial variability to quantify representation errors of satellite CO 2 retrievals
Author(s) -
Alkhaled A. A.,
Michalak A. M.,
Kawa S. R.
Publication year - 2008
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 - 10.1029/2008gl034528
Subject(s) - environmental science , satellite , remote sensing , depth sounding , inversion (geology) , spatial distribution , data assimilation , spatial variability , image resolution , meteorology , geology , computer science , statistics , mathematics , physics , paleontology , oceanography , structural basin , astronomy , artificial intelligence
Satellite measurements of column‐averaged CO 2 dry‐air mole fraction (X CO2 ) will be used in inversion and data assimilation studies to improve the precision and resolution of current estimates of global fluxes of CO 2 . Representation errors due to the mismatch in spatial scale between satellite retrievals and atmospheric transport models contribute to the uncertainty associated with flux estimates. This study presents a statistical method for quantifying representation errors as a function of the underlying spatial variability of X CO2 and the spatial distribution of retrieved soundings, without knowledge of the true X CO2 distribution within model gridcells. Representation errors are quantified globally using regional X CO2 spatial variability inferred using the PCTM/GEOS‐4 model and a hypothetical atmospheric transport model with 1° × 1° resolution, 3 km 2 retrieval footprints, and two different sounding densities.