Articles | Volume 17, issue 4
Research article
28 Feb 2017
Research article |  | 28 Feb 2017

Fast retrievals of tropospheric carbonyl sulfide with IASI

R. Anthony Vincent and Anu Dudhia

Abstract. Iterative retrievals of trace gases, such as carbonyl sulfide (OCS), from satellites can be exceedingly slow. The algorithm may even fail to keep pace with data acquisition such that analysis is limited to local events of special interest and short time spans. With this in mind, a linear retrieval scheme was developed to estimate total column amounts of OCS at a rate roughly 104 times faster than a typical iterative retrieval. This scheme incorporates two concepts not utilized in previously published linear estimates. First, all physical parameters affecting the signal are included in the state vector and accounted for jointly, rather than treated as effective noise. Second, the initialization point is determined from an ensemble of atmospheres based on comparing the model spectra to the observations, thus improving the linearity of the problem. All of the 2014 data from the Infrared Atmospheric Sounding Interferometer (IASI), instruments A and B, were analysed and showed spatial features of OCS total columns, including depletions over tropical rainforests, seasonal enhancements over the oceans, and distinct OCS features over land. Error due to assuming linearity was found to be on the order of 11 % globally for OCS. However, systematic errors from effects such as varying surface emissivity and extinction due to aerosols have yet to be robustly characterized. Comparisons to surface volume mixing ratio in situ samples taken by NOAA show seasonal correlations greater than 0.7 for five out of seven sites across the globe. Furthermore, this linear scheme was applied to OCS, but may also be used as a rapid estimator of any detectable trace gas using IASI or similar nadir-viewing instruments.

Short summary
A fast method to estimate trace gases using the IASI sensor is presented and applied to tropospheric carbonyl sulphide (OCS). This rapid approach neglects non-linear effects, which introduces an 11 % error on average when estimating OCS but is significantly faster than iterative methods. All of the IASI data from 2014 were analysed to show seasonal and spatial trends in OCS. These results were compared to ground samples taken from seven different NOAA sites across the globe.
Final-revised paper