Optimal Estimation of the Carbonyl Sulfide Surface Flux Through Inverse Modeling of TES Observations

Abstract:

Carbonyl sulfide (OCS) is the most abundant sulfur gas in the troposphere with a global averaging mixing ratio of about 500 part per trillion (ppt). The ocean is the primary source of OCS, emitting OCS directly or its precursors, carbon disulfide and dimethyl sulfide. The most important atmospheric sink of OCS is uptake by terrestrial plants via photosynthesis. Although the global budget of atmospheric OCS has been studied, the global integrated OCS fluxes have large uncertainties, e.g. the uncertainties of the ocean fluxes are as large as 100% or more and a large missing ocean sources required to balance the global budgets.

A first tropical ocean map of the free tropospheric OCS has been developed using retrieval data from radiance measurements from the AURA Tropospheric Emission Spectrometer (TES). The monthly mean ocean data has been evaluated to estimate the biases and uncertainties in the TES OCS against aircraft profiles from the HIPPO campaign and ground data from the NOAA Mauna Loa site. We found the TES OCS data to be consistent (within the calculated uncertainties) with NOAA ground observations and HIPPO aircraft measurements and it captured the seasonal and latitudinal variations observed by these in situ data within the estimated uncertainties.

In this study, we first update bottom-up estimate of global source and sinks of atmospheric OCS. The global forward simulations of atmospheric OCS using updated bottom-up fluxes with GEOS-Chem show improvement of the seasonal variation over multiple NOAA ground stations in both north and south hemispheres. Inverse analysis of surface fluxes from TES OCS data will provide further constraints to estimate the missing ocean source and understand the enhanced OCS over eastern Asia and west Pacific, which could be driven by wind, Asian outflow, a mystery process, or a combination of all of the above.

The investigation will provide the fundamental measurements and analysis needed to estimate the missing source in the sulfur cycle and provide the framework for extending the TES algorithm to land retrievals, which can be used directly in studies of carbon-climate feedbacks.