Keppel-Aleks, Gretchen: University of Michigan (Project Lead)
Project Funding:
2015 - 2018
NRA: 2014 NASA: OCO-2 Science Team for the OCO-2 Mission
Funded by NASA
Abstract:
Accurate flux inference from OCO-2 XCO2 observations requires improved characterization of model and data uncertainties, including the representativeness of the narrow OCO-2 track to larger atmospheric scales and the spatiotemporal correlations in XCO2. Whereas previous work has relied on models to characterize these uncertainties, high resolution TCCON and now OCO-2 data now provide us the opportunity to confront model assumptions with observations. Our goal in seeking membership on the OCO-2 science team is to understand the relative imprint that surface fluxes and atmospheric transport leave on L2 XCO2 observations so that the observations can be used for surface flux inference. We will leverage several types of complementary observations, including OCO-2 and ground-based XCO2 observations and surface CO2 observations, systematically to quantify the spatial and temporal representativeness of OCO-2 measurements using a forward atmospheric transport modeling framework. We will apply the information gained toward a comparison of Southern Hemisphere XCO2 observations from OCO-2 with realistic model runs using reanalysis atmospheric transport and hindcast surface fluxes. We will then examine the sensitivity of simulated XCO2 and surface CO2 fields to specific processes using careful chosen perturbations to our mechanistic flux models. Specific objectives of this research are to: 1. Formulate a method to assign representation errors in an inverse modeling framework based on a joint analysis of space- and ground-based XCO2 . 2. Account for correlations among XCO2 to facilitate proper weighting of column and surface observations when considered simultaneously in an inversion. 3. Evaluate the sensitivity of Southern Hemisphere OCO-2 observations to mechanisms that govern Southern Ocean and tropical carbon fluxes. We anticipate two major deliverables from the project: first, we will provide a mathematical framework that can be used by the inverse modeling community for robust description of error covariance structures. This framework will provide a method to quantify representation error based on the spatial and temporal variations inferred from analysis of ground- and space-based XCO2, and a method to weight OCO-2 XCO2 observations when inverted simultaneously with surface observations. Second, we will provide direction for improving estimates of Southern Hemisphere carbon fluxes, in particular sensitivities of atmospheric CO2 observations to several important, but at present under-constrained, processes in the Southern Ocean. Our proposed research cuts across many of the tasks laid out in the research announcement. Our improved uncertainty quantification and examination of transportinduced errors in XCO2 will facilitate flux inversion analysis using OCO-2 data. Moreover, our analysis of Southern Hemisphere XCO2 data from OCO-2 will provide improved constraints on individual flux mechanisms in the Southern Ocean and an improved understanding of the role of prior flux uncertainty on inversions of the data. We also note that our proposal extensively leverages the validation data from TCCON in which NASA has made significant investments.
Publications:
Crowell, S. M. R., Randolph Kawa, S., Browell, E. V., Hammerling, D. M., Moore, B., Schaefer, K., Doney, S. C. 2018. On the Ability of Space-Based Passive and Active Remote Sensing Observations of CO2
to Detect Flux Perturbations to the Carbon Cycle. Journal of Geophysical Research: Atmospheres. 123(2), 1460-1477. DOI: 10.1002/2017JD027836
Glover, D. M., Doney, S. C., Oestreich, W. K., Tullo, A. W. 2018. Geostatistical Analysis of Mesoscale Spatial Variability and Error in SeaWiFS and MODIS/Aqua Global Ocean Color Data. Journal of Geophysical Research: Oceans. 123(1), 22-39. DOI: 10.1002/2017JC013023
More details may be found in the following project profile(s):
