Abstract
Abstract. We have developed an ensemble Kalman Filter (EnKF) to estimate 8-day regional surface fluxes of CO2 from space-borne CO2 dry-air mole fraction observations (XCO2) and evaluate the approach using a series of synthetic experiments, in preparation for data from the NASA Orbiting Carbon Observatory (OCO). The 32-day duty cycle of OCO alternates every 16 days between nadir and glint measurements of backscattered solar radiation at short-wave infrared wavelengths. The EnKF uses an ensemble of states to represent the error covariances to estimate 8-day CO2 surface fluxes over 144 geographical regions. We use a 12×8-day lag window, recognising that XCO2 measurements include surface flux information from prior time windows. The observation operator that relates surface CO2 fluxes to atmospheric distributions of XCO2 includes: a) the GEOS-Chem transport model that relates surface fluxes to global 3-D distributions of CO2 concentrations, which are sampled at the time and location of OCO measurements that are cloud-free and have aerosol optical depths <0.3; and b) scene-dependent averaging kernels that relate the CO2 profiles to XCO2, accounting for differences between nadir and glint measurements, and the associated scene-dependent observation errors. We show that OCO XCO2 measurements significantly reduce the uncertainties of surface CO2 flux estimates. Glint measurements are generally better at constraining ocean CO2 flux estimates. Nadir XCO2 measurements over the terrestrial tropics are sparse throughout the year because of either clouds or smoke. Glint measurements provide the most effective constraint for estimating tropical terrestrial CO2 fluxes by accurately sampling fresh continental outflow over neighbouring oceans. We also present results from sensitivity experiments that investigate how flux estimates change with 1) bias and unbiased errors, 2) alternative duty cycles, 3) measurement density and correlations, 4) the spatial resolution of estimated flux estimates, and 5) reducing the length of the lag window and the size of the ensemble. At the revision stage of this manuscript, the OCO instrument failed to reach its orbit after it was launched on 24 February 2009. The EnKF formulation presented here is also applicable to GOSAT measurements of CO2 and CH4.
Highlights
CO2 surface fluxes inferred from atmospheric CO2 concentrations by inverting models of atmospheric transport have led to substantial improvements in our understanding of the contemporary carbon cycle (e.g., Bousquet et al, 2000)
We focus our observation system simulation experiment (OSSE) on quantifying the science capabilities of realistic distributions of XCO2 measurements from space-borne sensors
We developed an ensemble Kalman Filter (EnKF) to estimate 8-day regional surface fluxes of CO2 from space-borne CO2 dry-air mole fraction observations (XCO2 ) and evaluated the approach using a series of synthetic experiments, in preparation for data from the NASA Orbiting Carbon Observatory (OCO)
Summary
CO2 surface fluxes inferred from atmospheric CO2 concentrations by inverting models of atmospheric transport have led to substantial improvements in our understanding of the contemporary carbon cycle (e.g., Bousquet et al, 2000). Recent studies have used variational data assimilation methods with synthetic OCO observations to show that these data have the potential to estimate weekly and daily surface CO2 fluxes at model grid scales of order 3.75◦ in longitude and 2.5◦ in latitude (Baker et al, 2006; Chevallier et al, 2007a; Chevallier, 2007b). These studies (1) assumed a constant measurement error (1–2 ppmv), and (2) used a flat weighting function to convert the model vertical CO2 profiles into XCO2.
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