The environment and climate change canada carbon assimilation system (ec-cas v1.0): Demonstration with simulated co observations

Abstract

In this study, we present the development of a new coupled weather and carbon monoxide (CO) data assimila tion system based on the Environment and Climate Change Canada (ECCC) operational ensemble Kalman filter (EnKF). The estimated meteorological state is augmented to include CO. Variable localization is used to prevent the direct up date of meteorology by the observations of the constituents and vice versa. Physical localization is used to damp spuri ous analysis increments far from a given observation. Per turbed surface flux fields are used to account for the uncer tainty in CO due to errors in the surface fluxes. The system is demonstrated for the estimation of three-dimensional CO states using simulated observations from a variety of net works. First, a hypothetically dense, uniformly distributed observation network is used to demonstrate that the system is working. More realistic observation networks, based on sur face hourly observations, and space-based observations pro vide a demonstration of the complementarity of the different networks and further confirm the reasonable behavior of the coupled assimilation system. Having demonstrated the abil ity to estimate CO distributions, this system will be extended to estimate surface fluxes in the future.