Abstract
Abstract. Between July and November 2008, simultaneous observations were conducted by several orbiting instruments that monitor carbon monoxide in the atmosphere, among them the Infrared Atmospheric Sounding Instrument (IASI) and Measurements Of Pollution In The Troposphere (MOPITT). In this paper, the concentration retrievals at about 700 hPa from these two instruments are successively used in a variational Bayesian system to infer the global distribution of CO emissions. Starting from a global emission budget of 479 Tg for the considered period, the posterior estimate of CO emissions using IASI retrievals gives a total of 643 Tg, which is in close agreement with the budget calculated with version 3 of the MOPITT data (649 Tg). The regional totals are also broadly consistent between the two inversions. Even though our theoretical error budget indicates that IASI constrains the emissions slightly less than MOPITT, because of lesser sensitivity in the lower troposphere, these first results indicate that IASI may play a major role in the quantification of the emissions of CO.
Highlights
The launch of a weather satellite, like METOP, generates new information flows about the atmosphere and the Earth surface with applications beyond Numerical Weather Prediction
Since the beginning of this century, several instruments have provided information about the atmospheric concentrations of carbon monoxide CO, a key molecule to inform about the impact of human activities on the evolution of the composition of the atmosphere: Measurements Of Pollution In The Troposphere (MOPITT) (Deeter et al, 2003), Atmospheric Chemistry Experiment-FTS (ACE-FTS) (Clerbaux et al, 2005), Tropospheric Emission Spectrometer (TES) (Luo et al, 2007), SCanning Imaging Absorption spectroMeter for Atmospheric ChartograpHY (SCIAMACHY) (Buchwitz et al, 2007) and Infrared Atmospheric Sounding Instrument (IASI)
H is the chemistrytransport model (CTM) LMDz-SACS described coupled with the averaging kernels of the satellite retrievals. xb are the prior fluxes described in Sect. 2.3 with error statistics defined by the covariance matrix B. y are the observations of Section 2.4, the error statistics of which are represented by the covariance matrix R
Summary
The launch of a weather satellite, like METOP, generates new information flows about the atmosphere and the Earth surface with applications beyond Numerical Weather Prediction. The exploitation of such data usually leads to feeding them to data assimilation systems, where they co-. By a simplified chemistry module (Chevallier et al, 2009). This multi-species system includes the simplified chemistrytransport model (CTM) LMDz-SACS and its adjoint (Pison et al, 2009), optimizing the four main reactive species of the methane oxidation chain (CH4, CO, formaldehyde HCHO and OH).
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