A41I-0201
A Mesoscale Modeling Framework for Assessing Inversion Uncertainty Due to Atmospheric Transport in XCO2 Atmospheric Inversions
Thursday, 17 December 2015
Poster Hall (Moscone South)
Martha P Butler1, Thomas Lauvaux1, Junjie Liu2, Aijun Deng1, Colm Sweeney3,4, Kenneth J Davis5 and Kevin W Bowman6, (1)Pennsylvania State University Main Campus, University Park, PA, United States, (2)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (3)NOAA, Earth System Research Laboratory, Boulder, CO, United States, (4)Cooperative Institute for Research in Environmental Sciences, Boulder, CO, United States, (5)The Pennsylvania State Unviersity, Department of Meteorology, University Park, PA, United States, (6)Jet Propulsion Laboratory, Pasadena, CA, United States
Abstract:
Assessing the impact on the uncertainty of inversion results that can be attributed to transport error continues to be a challenge. Here we present results from our effort to quantify the atmospheric transport contribution to the uncertainty in the optimized fluxes of the NASA JPL CMS-Flux global 4 x 5-degree GOSAT XCO2 satellite inversion for CO2 in 2010. We embed the PSU WRF-Chem mesoscale model, at 30 km resolution in the North American domain, in the CMS-Flux posterior solution (with tracers incorporating the optimized biosphere fluxes, prior fluxes for other components of the carbon cycle, and boundary conditions), creating a coupled WRF-CMS modeling system. Using alternative WRF model physics and perturbations to the meteorological driver data, we create an ensemble of WRF-Chem forward simulations. The ensemble WRF outputs, together with the global model solution, provide a rich data set which can be analyzed for meteorological bias (with WMO atmospheric soundings), for XCO2 bias (with simulated ACOS GOSAT XCO2), and CO2 profile bias (with NOAA aircraft profile and in situ observations). Meteorological impacts on CO2 fields at pressure levels in the atmosphere used in XCO2 averaging kernels will also be shown. This analysis framework is transferable to other atmospheric tracers and space-based sensors, such as global atmospheric inversions using OCO-2 XCO2. This work is a contribution of the “Quantification of the sensitivity of NASA CMS Flux inversions to uncertainty in atmospheric transport” project of the NASA Carbon Monitoring System.
