Prior biosphere model impact on global terrestrial CO2 fluxes estimated from OCO-2 retrievals

• Published in: Atmospheric chemistry and physics Vol. 19; no. 20; pp. 13267 - 13287
• Main Authors: Philip, Sajeev, Johnson, Matthew S., Potter, Christopher S, Genovesse, Vanessa, Baker, David F., Haynes, Katherine D., Henze, Daven K., Liu, Junjie, Poulter, Benjamin
• Format: Journal Article
• Language: English
• Published: Goddard Space Flight Center European Geosciences Union / Copernicus Publications 28.10.2019; Copernicus GmbH; Copernicus Publications
• Subjects: Assimilation; Biosphere; Biosphere models; Carbon dioxide; Carbon dioxide flux; Chemical transport; Computer simulation; Dry air; Earth Resources And Remote Sensing; Estimates; Fluctuations; Fluxes; Intercomparison; Organic chemistry; Regions; Southern Hemisphere; Statistical methods; Statistics; Terrestrial environments; Tropical environments; Uncertainty
• ISSN: 1680-7316; 1680-7324
• DOI: 10.5194/acp-19-13267-2019

This study assesses the impact of different state of the art global biospheric CO2 flux models, when applied as prior information, on inverse model “top-down” estimates of terrestrial CO2 fluxes obtained when assimilating Orbiting Carbon Observatory 2 (OCO-2) observations. This is done with a series of observing system simulation experiments (OSSEs) using synthetic CO2 column-average dry air mole fraction (XCO2) retrievals sampled at the OCO-2 satellite spatiotemporal frequency. The OSSEs utilized a 4-D variational (4D-Var) assimilation system with the GEOS-Chem global chemical transport model (CTM) to estimate CO2 net ecosystem exchange (NEE) fluxes using synthetic OCO-2 observations. The impact of biosphere models in inverse model estimates of NEE is quantified by conducting OSSEs using the NASA-CASA, CASA-GFED, SiB-4, and LPJ models as prior estimates and using NEE from the multi-model ensemble mean of the Multiscale Synthesis and Terrestrial Model Intercomparison Project as the “truth”. Results show that the assimilation of simulated XCO2 retrievals at OCO-2 observing modes over land results in posterior NEE estimates which generally reproduce “true” NEE globally and over terrestrial TransCom-3 regions that are well-sampled. However, we find larger spread among posterior NEE estimates, when using different prior NEE fluxes, in regions and seasons that have limited OCO-2 observational coverage and a large range in “bottom-up” NEE fluxes. Seasonally averaged posterior NEE estimates had standard deviations (SD) of ∼10 % to ∼50 % of the multi-model-mean NEE for different TransCom-3 land regions with significant NEE fluxes (regions/seasons with a NEE flux ≥0.5 PgC/yr). On a global average, the seasonally averaged residual impact of the prior model NEE assumption on the posterior NEE spread is ∼10 %–20 % of the posterior NEE mean. Additional OCO-2 OSSE simulations demonstrate that posterior NEE estimates are also sensitive to the assumed prior NEE flux uncertainty statistics, with spread in posterior NEE estimates similar to those when using variable prior model NEE fluxes. In fact, the sensitivity of posterior NEE estimates to prior error statistics was larger than prior flux values in some regions/times in the tropics and Southern Hemisphere where sufficient OCO-2 data were available and large differences between the prior and truth were evident. Overall, even with the availability of spatiotemporally dense OCO-2 data, noticeable residual differences (up to ∼20 %–30 % globally and 50 % regionally) in posterior NEE flux estimates remain that were caused by the choice of prior model flux values and the specification of prior flux uncertainties.