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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Short summary
Carbon monoxide (CO) is an atmospheric constituent gas. The estimate of the distribution of is in accurate due to insufficient knowledge about the distribution and magnitude of the CO flux. In this paper we show that accounting for the uncertainty in the flux leads to a better estimate of CO distribution. This research is the first step towards developing a flux estimation system for green house gases.
Preprints
https://doi.org/10.5194/gmd-2020-219
https://doi.org/10.5194/gmd-2020-219

Submitted as: development and technical paper 18 Aug 2020

Submitted as: development and technical paper | 18 Aug 2020

Review status: a revised version of this preprint is currently under review for the journal GMD.

The Environment and Climate Change Canada Carbon Assimilation System (EC-CAS v1.0): demonstration with simulated CO observations

Vikram Khade1,2, Saroja M. Polavarapu1, Michael Neish1, Pieter L. Houtekamer1, Dylan B. A. Jones2, Seung-Jong Baek1, Tailong He2, and Sylvie Gravel1 Vikram Khade et al.
  • 1Environment and Climate Change Canada, 4905 Dufferin Street, Toronto, Canada, M3H 5T4
  • 2Department of Physics, University of Toronto, 60 St. George Street, Toronto, Canada, M5S 1A7

Abstract. In this study, we present the development of a new coupled weather and greenhouse gas (GHG) data assimilation system based on Environment and Climate Change Canada's (ECCC's) operational Ensemble Kalman Filter (EnKF). The estimated meteorological state is augmented to include three chemical constituents: CO2, CO and CH4. Variable localization is used to prevent the direct update of meteorology by the observations of the constituents and vice versa. Physical localization is used to damp spurious analysis increments far from a given observation. Perturbed flux fields are used to account for the uncertainty in CO due to error in the fluxes. The system is demonstrated for the estimation of 3-dimensional CO states using simulated observations from a variety of networks. First, a hypothetically dense uniformly distributed observation network is used to demonstrate that the system is working. More realistic observation networks based on surface hourly observations, and space-based observations provide a demonstration of the complementarity of the different networks and further confirm the reasonable behaviour of the coupled assimilation system. Having demonstrated the ability to estimate CO distributions, this system will be extended to estimate surface fluxes in the future.

Vikram Khade et al.

 
Status: final response (author comments only)
Status: final response (author comments only)
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Vikram Khade et al.

Vikram Khade et al.

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Short summary
Carbon monoxide (CO) is an atmospheric constituent gas. The estimate of the distribution of is in accurate due to insufficient knowledge about the distribution and magnitude of the CO flux. In this paper we show that accounting for the uncertainty in the flux leads to a better estimate of CO distribution. This research is the first step towards developing a flux estimation system for green house gases.
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