Abstract
Using an Observing System Simulation Experiment (OSSE), we investigate the impact of JAXA Greenhouse gases Observing SATellite ‘IBUKI’ (GOSAT) sampling on the estimation of terrestrial biospheric flux with the NASA Carbon Monitoring System Flux (CMS-Flux) estimation and attribution strategy. The simulated observations in the OSSE use the actual column carbon dioxide (XCO2) b2.9 retrieval sensitivity and quality control for the year 2010 processed through the Atmospheric CO2 Observations from Space algorithm. CMS-Flux is a variational inversion system that uses the GEOS-Chem forward and adjoint model forced by a suite of observationally constrained fluxes from ocean, land and anthropogenic models. We investigate the impact of GOSAT sampling on flux estimation in two aspects: 1) random error uncertainty reduction and 2) the global and regional bias in posterior flux resulted from the spatiotemporally biased GOSAT sampling. Based on Monte Carlo calculations, we find that global average flux uncertainty reduction ranges from 25% in September to 60% in July. When aggregated to the 11 land regions designated by the phase 3 of the Atmospheric Tracer Transport Model Intercomparison Project, the annual mean uncertainty reduction ranges from 10% over North American boreal to 38% over South American temperate, which is driven by observational coverage and the magnitude of prior flux uncertainty. The uncertainty reduction over the South American tropical region is 30%, even with sparse observation coverage. We show that this reduction results from the large prior flux uncertainty and the impact of non-local observations. Given the assumed prior error statistics, the degree of freedom for signal is ~1132 for 1-yr of the 74 055 GOSAT XCO2 observations, which indicates that GOSAT provides ~1132 independent pieces of information about surface fluxes. We quantify the impact of GOSAT's spatiotemporally sampling on the posterior flux, and find that a 0.7 gigatons of carbon bias in the global annual posterior flux resulted from the seasonally and diurnally biased sampling when using a diagonal prior flux error covariance.
Highlights
Because of the crucial role of carbon dioxide (CO2) in forcing climate (e.g., Mann et al., 1998) and the uncertainties related to carbon-climate feedbacks in global models (e.g., Cox et al, 2000; Friedingstein et al, 2006), it is essential to monitor how CO2 is changing and what processes are causing these changes
We expect that the assimilation of XCO2 observations especially glint observations over these oceanic regions could have a significant impact on the estimate of South American tropical terrestrial biosphere flux. 4 Discussion and Conclusions In this paper, we describe the variational inversion system developed as part of the Carbon Monitoring System (CMS) Flux estimation and attribution (CMS-Flux), and demonstrate the performance of this system in the context of an Observing System Simulation Experiment (OSSE)
Using the same coverage and sensitivity as the real Atmospheric CO2 observations from Space (ACOS)-gases Observing SATellite “IBUKI” (GOSAT) b2.9 observations for 2010, we further discuss the impact of GOSAT spatiotemporally biased sampling on the net flux estimation, and the impact of remote observations on tropical flux estimation, where the GOSAT has sparse observation coverage. The results from this OSSE help us understand the impact of the unique ACOS-GOSAT spatiotemporal sampling on flux estimation
Summary
Because of the crucial role of carbon dioxide (CO2) in forcing climate (e.g., Mann et al., 1998) and the uncertainties related to carbon-climate feedbacks in global models (e.g., Cox et al, 2000; Friedingstein et al, 2006), it is essential to monitor how CO2 is changing and what processes are causing these changes. NASA initiated the Carbon Monitoring System (CMS) (http://carbon.nasa.gov/, http://cmsflux.jpl.nasa.gov/) integrated Emission/Uptake Flux Pilot project in 2010 to explore the capability of global modeling, assimilation, and observations to attribute changes in atmospheric CO2 to spatially resolved fluxes. The purpose of this paper is to describe the formulation and integrity of the atmospheric inversion system used in the NASA CMS Flux estimation and attribution (CMS-Flux). CO2 fluxes estimated from observation-constrained terrestrial and oceanic carbon models are used to force an atmospheric transport model, after which atmospheric inversion refines the fluxes to match atmospheric CO2 observations.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
