Arthur Mizzi
Assistant Research Professor • Air Quality

Office: ECME 279

Research Interests

Regional ensemble chemical weather forecasting, data assimilation and emissions adjustment; assimilation of Compact Phase Space Retrievals’ (CPSRs) from satellite observing platforms; regional multi-constituent data assimilation with emissions adjustment

I am the developer of WRF-Chem/DART,Ìýa regional ensemble chemical weather forecast/data assimilation system that is used throughout North America, WesternÌýEurope and Asia. My research focuses on regional chemical data assimilation, multi-constituent chemical data assimilation, development of efficient assimilation strategies for satellite retrievals profilesÌýand emissions adjustment. I developed the Compact Phase Space RetrievalÌý(CPSR) compression/rotation algorithm for efficient assimilation of satellite retrieval profiles. Using CPSRs in chemical weather forecasting/data assimilation reduces the storage and computation costs for assimilating retrieval profiles by more than 50% depending on the retrieval product without loss of information or forecast skill.

Societal Impact

My research together with that of my collaborators shows that regional multi-constituent chemical data assimilation with emissions adjustment improves forecast skill and predictability (the time period over which the forecast has significantly improved skill) for air quality forecasts. Federal and state air resources managers can use the increased skill and predictability to better protect human health and the environment with greater lead times.

Select Publications

  • Ma, C., T. Wang,ÌýA. P. Mizzi, and J. L. Anderson, B., Zhuang, M. Xie, R. Wu, 2019:Ìý Multiconstituent data assimilation with WRF-Chem/DART: Potential for adjusting anthropogenic emissions and improving air quality over eastern China.ÌýJournal of Geophysical Research: Atmospheres,Ìý124, 7393-7412, https:/doi.org/10.1029ÌýP.2019jD03042.
  • Mizzi, A. P., D. P. Edwards, and J. L. Anderson, 2018: Assimilating compact phase space retrievals (CPSRs): Comparison with independent observations (MOZAICÌýin situÌýand IASI retrievals) and extension to assimilation of truncated retrieval profiles.ÌýGeosci. Model Dev.,Ìý11,Ìý3727-3745.
  • Mizzi, A. P.,ÌýA. F. Arellano, D. P. Edwards, J. L. Anderson, and G. G. Pfister, 2016: Assimilating compact phase space retrievals of atmospheric composition with WRF- Chem/DART: A regional chemical transport/ensemble Kalman filter data assimilation system.ÌýGeosci. Model Dev.Ìý9, 1-14.