1. Data assimilation/Fusion Directions for ARQI & AQRD V. Bouchet, Manager, AQRD/ARQI

2. Page 2 – October 26, 2015 Data assimilation/fusion - Meeting objectives To present recent advancements in Canadian science and on-going or upcoming projects associated with the integration of observed (surface, upper air and satellite) and modelled air quality data using techniques such as assimilation, objective analysis or fusion, with the objective to improve the following areas: –Emissions –air quality forecasting –representation/mapping of past and current ambient air quality conditions (including in the context of exposure) and mapping of associated fields (ex: deposition) To discuss projects, approaches/methodologies, gaps, resources and timings with a view to coordinate R&D efforts contributing to Environment Canada’s programs.

3. Page 3 – October 26, 2015 ARQI/AQRD Data assimilation/fusion objectives Development of best estimates of the state of ambient air quality (concentrations/emissions) Ambient levels –Best atmospheric composition analyses as its relates to AQ (with an emphasis on lower tropospheric levels) –Using all sources of data that are informative ▪integration of surface, upper air and satellite as appropriate –Use of upper atmospheric level data to inform model –Timeframe: real-time and short-term (past year) reanalyses with a view of developing capacity to deliver on-going product ▪RT: reliable and continuous sources of data ▪Short-term: Same method as RT, with validated data - Climatologies to be built from on-going work Emissions –Best emission estimates and/or trends and/or corrections –Timeframe: targeting monthly at first, and improving overtime With EC model Scale: regional to local

4. Page 4 – October 26, 2015 ARQI/AQRD Data assimilation/fusion objectives Improvement to air quality & health forecasting program –Analyses as initial conditions or emission corrections –Data assimilation ▪Using sources of data that improve skill ▪Integration of surface, upper air and satellite as appropriate –Timeframe: real-time - reliable and continuous sources of data –Scale: Global as needed to achieve regional scale With EC & assimilation systems –3D-var, EnKF, EnVar, 4D-Var Weather forecast improvements: –where they can be achieved with work targeted at AQ program

5. Page 5 – October 26, 2015 ARQI program vision Our strength: strong expertise in prognostic modelling for air quality at the regional scale We do global scale as it relates to our regional objectives, where needed to inform regional domain (intercontinental transport & longer time scales, upper atmosphere transport), where needed because that is the scale from which information can be derived (some satellite information, initial assimilation work) –Use collaborations to get there Local scale – as natural extension of regional work targeting exposure

6. Page 6 – October 26, 2015 Point for discussion Performance level of model? –Need for further validation? –Are there missing processes that are critical gaps in using/assimilated the various sources of data? What data are used for validation? Need for sequencing addition of data? How do we transfer the methodology? –Parallel implementation? –Periods of cross-comparison?

7. Page 7 – October 26, 2015 Points for discussion Data acquisition and archiving for research needs, for operational stream ? –Data format/standard for archives and access