Estimating surface CO 2 fluxes from space-borne CO 2 dry air mole fraction observations using an ensemble Kalman Filter
By Liang Feng, Paul I. Palmer, H. Bösch, Sarah L. Dance. 2008
172 citations recorded by the source corpus.
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
Subfields: Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/94ba532e9c83ef99d313855b12a4b02c30dc910b
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In Atmospheric Science
- Takemasa Miyoshi
- Paul O. Wennberg
- David Crisp
- Christopher W. O'Dell
- Brendan M. Fisher
- Annmarie Eldering
- Matthäus Kiel
- Eugenia Kalnay
In Global and Planetary Change
- Takemasa Miyoshi
- Paul I. Palmer
- Liang Feng
- Paul O. Wennberg
- David Crisp
- Christopher W. O'Dell
- Brendan M. Fisher
- Annmarie Eldering
Citations in the corpus
- Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm (2018, background): “1 CASA EnKF GEOS-Chem Feng et al. (2009) Jena CarboScope s04_v3.”
- “Variable localization” in an ensemble Kalman filter: Application to the carbon cycle data assimilation (2011, methodology): “Peters et al. [2005, 2007] have assimilated observations from the ground‐based stations whereas Feng et al. [2009] have used simulated observations of satellite data, Orbiting Carbon Observatory (OCO) [Crisp et al., 2004].”