On the use of satellite-derived CH4:CO2 columns in a joint inversion of CH4 and CO2 fluxes.

Thursday, 17 December 2015
Poster Hall (Moscone South)
Sudhanshu Pandey1, Sander Houweling2, Maarten C Krol3, Thomas Röckmann3 and Ilse Aben4, (1)Netherlands Institute for Space Research, Earth, Utrecht, Netherlands, (2)Utrecht University, IMAU, Utrecht, 3584, Netherlands, (3)Utrecht University, Utrecht, Netherlands, (4)Netherlands Institute for Space Research, Utrecht, Netherlands
We present a method for assimilating CH4:CO2 measurements from satellites for inverse modeling of CH4 and CO2 fluxes in TM5-4DVAR inverse modeling system. Unlike conventional proxy approach, in which retrieved CH4:CO2 ratios are multiplied by model derived total column CO2 and only the resulting CH4 is assimilated, our method assimilates the ratio of CH4 and CO2 directly and is therefore called the ratio method. It is a dual tracer inversion, in which surface fluxes of CH4 and CO2 are optimized simultaneously. The optimization of CO2 fluxes turns the hard constraint of prescribing model derived CO2 fields into a weak constraint on CO2, which allows us to account for uncertainties in CO2.

First, the method was successfully tested in a synthetic inversion setup. We show that the ratio method is able to reproduce assumed true CH4 and CO2 fluxes starting from a prior, which is derived by perturbing the true fluxes randomly. We compare the performance of the ratio method with that of the traditional proxy approach and the use of only surface measurements for estimating CH4 fluxes. Then, we assimilate real GOSAT ratio and proxy observations. We do two proxy inversions with CO2 fields from separate models and quantify the impact of differences in the model on the posterior CH4 fluxes. Atmospheric fields from the posterior emissions of all inversions are validated with independent aircraft measurements. We find that the posterior fields of ratio inversion are in better agreement with aircraft data than both proxy inversions, especially in the regions with poor surface measurements coverage of CO2. This confirms that systemic biases from model derived CO2 have significant impact on proxy inversions results.