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

• Main Authors: V. Khade, S. M. Polavarapu, M. Neish, P. L. Houtekamer, D. B. A. Jones, S.-J. Baek, T.-L. He, S. Gravel
• Format: Article
• Language: English
• Published: Copernicus Publications 2021-05-01
• Series: Geoscientific Model Development
• Online Access: https://gmd.copernicus.org/articles/14/2525/2021/gmd-14-2525-2021.pdf

<p>In this study, we present the development of a new coupled weather and carbon monoxide (<span class="inline-formula">CO</span>) data assimilation system based on the Environment and Climate Change Canada (ECCC) operational ensemble Kalman filter (EnKF). The estimated meteorological state is augmented to include <span class="inline-formula">CO</span>. 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 surface flux fields are used to account for the uncertainty in <span class="inline-formula">CO</span> due to errors in the surface fluxes. The system is demonstrated for the estimation of three-dimensional <span class="inline-formula">CO</span> 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 behavior of the coupled assimilation system. Having demonstrated the ability to estimate <span class="inline-formula">CO</span> distributions, this system will be extended to estimate surface fluxes in the future.</p>