A33H-3299:
Constraints on methane emissions from future geostationary remote sensing measurements
Wednesday, 17 December 2014
Nicolas Bousserez1, Daven K Henze1, Walter Andre Perkins1 and John R Worden2, (1)University of Colorado at Boulder, Boulder, CO, United States, (2)NASA Jet Propulsion Laboratory, Pasadena, CA, United States
Abstract:
The GEOstationary Coastal and Air Pollution Events (GEO-CAPE) mission aims to put atmospheric chemistry sensors into geostationary orbit in the 2020 time frame. Multiple observations per day over North America would provide unprecedented constraints for top-down estimates of trace gase emissions. As there are multiple instruments being considered for such a mission, there is a crucial need for characterizing the degree to which spectral design impacts the mission’s capability to address key scientific questions. In this study, we assess constraints on methane (CH4) emissions over the United States for three different instrument configurations. Results are presented for an Observing System Simulation Experiment (OSSE) based on a 4D-Var inversion which uses a GEOS-Chem nested simulation at 0.5°x0.66° over North America. Two XCH4 column retrievals based on existing infrared measurements are considered, one from the Thermal Emission Spectrometer (TES), and one from the Greenhouse Gases Observing SATellite (GOSAT)). A newly proposed CH4 profile retrieval from a multi-spectral instrument is also tested. Full resolution posterior errors for these three inversion configurations are estimated using a computationally efficient stochastic algorithm. Large error reductions (>60%) over broad areas were obtained when using the multi-spectral CH4 retrievals. The GOSAT CH4 retrievals provided smaller constraints on the CH4 emissions (error reductions <40%), while the TES configuration was associated with the smallest information content (error reductions <20%). We quantify the spatial scales at which different instruments could separate CH4 emissions from different sources and the value of the emissions constraints as a function of the emissions magnitudes. These results also demonstrate that using observations from a multi-spectral instrument significantly mitigate the influence of biases in the boundary conditions on the inversion compared to other instruments.
