Development of an Online Ozone and UV Index Prediction System

A new forecast system is developed at Environment and Climate Change Canada (ECCC) in order to produce near-real-time, hourly fields of stratospheric ozone and the UV index. Based on the operational global deterministic NWP suite, the system includes a data assimilation component which ingests total-column and partial-column ozone observations from a number of satellite sensors such as GOME-2, OMPS and SBUV/2. Pre-processing of the data consists of spatial thinning, active bias correction and a background check against a short-term forecast. A linearized ozone chemistry scheme (LINOZ) has been incorporated into the forecast model (GEM, Global Environmental Multiscale), allowing it to directly provide the UV index as well as the three-dimensional stratospheric ozone. The resulting UV index is a robust, gridded output, which is expected to replace the currently operational product, computed through an empirical, offline approach. Such an integrated system supports two-way interaction between the ozone and the temperature through tracer advection and radiative heating, and continuously ensures consistency between the ozone field, the UV index and the model dynamics/physics. Standard forecast scores against radiosonde data and against analyses demonstrate a small but persistent improvement in the temperature structure, particularly in the stratosphere, compared to a control system with no ozone assimilation and an imposed, seasonally-varying ozone field. The relative impact of ozone assimilation and of online prediction are assessed, and the new UV index is evaluated through comparisons with the operational product and with ground-based observations. This work is part of a larger effort at ECCC involving chemical data assimilation for air quality and NWP applications.