The Impact of Prior Biospheric Models on Global CO2 Flux Estimates when Assimilating OCO-2 Retrievals
Abstract
The processes controlling atmosphere-terrestrial biosphere carbon exchange are currently not fully understood, resulting in biospheric flux models having significant differences in biospheric CO2 fluxes. The Orbiting Carbon Observatory 2 (OCO-2) satellite mission allows for the improved understanding of the exchange of carbon between terrestrial ecosystems and the atmosphere. Currently, there are numerous global flux inversion models using multiple different biospheric CO2 flux models as prior information for "top-down" estimates of biospheric CO2 exchange when assimilating OCO-2 data. When comparing the results of the biospheric CO2 fluxes from these inverse models assimilating identical OCO-2 data, a spread among posterior optimized CO2 flux estimates is evident. This spread can be due to numerous factors (e.g., transport model error, data quality, assumed error statistics, etc.) including the impact from the assumed prior fluxes and error statistics. This study assesses the impact of different global biospheric CO2 flux models, when applied as prior information, on the "top-down" estimates of global terrestrial CO2 fluxes when assimilating OCO-2 data. We conduct a series of Observing System Simulation Experiments (OSSEs) using synthetic CO2 column-average dry air mole fraction (XCO2) retrievals sampled at OCO-2 satellite spatio-temporal variability and the four-dimensional variational assimilation system with the GEOS-Chem global chemical transport model to estimate CO2 net ecosystem exchange (NEE) fluxes. We investigate the impact of the prior biospheric model in CO2 flux inversions using the NASA-CASA, CASA-GFED, SiB-4, and LPJ models as the prior flux information in our OSSE framework. With all other variables remaining consistent, the inter-model spread of posterior NEE estimates, when applying the four individual prior models, is regarded as the potential impact of the prior flux assumptions in inverse modeling studies using OCO-2 data. We will present the results from these OSSEs and sensitivity simulations quantifying the impact of the prior flux model, prior error statistics, and observing modes of OCO-2 on NEE flux estimates. This work provides insight of how to better interpret "top-down" flux estimates of greenhouse gases when assimilating satellite data.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.A43N3329P
- Keywords:
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- 0315 Biosphere/atmosphere interactions;
- ATMOSPHERIC COMPOSITION AND STRUCTUREDE: 0322 Constituent sources and sinks;
- ATMOSPHERIC COMPOSITION AND STRUCTUREDE: 0414 Biogeochemical cycles;
- processes;
- and modeling;
- BIOGEOSCIENCESDE: 0428 Carbon cycling;
- BIOGEOSCIENCES