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Saroja Polavarapu

Adjunct Professor

Department of Physics, University of Toronto
60 St. George Street, Toronto
Ontario, CANADA M5S 1A7

Tel: (416) 978-xxxx Fax: (416) 978-8905
E-mail: saroja@atmosp.physics.utoronto.ca or saroja.polavarapu@ec.gc.ca

Atmospheric Physics

Data assimilation; Kalman filtering; Four-Dimensional Variational Assimilation; Three-Dimensional Variational Assimilation, Optimal Interpolation; Initialization; gravity wave control with digital filters.




B.Sc., York (1982); M.Sc., Toronto (1984); Ph.D., Toronto (1989) ; Post-Doctoral Fellow, Meteorological Service of Canada (1990-1); Research Scientist, Data Assimilation and Satellite Meteorology Division, Meteorological Service of Canada (1992-).

Research Interests

Middle Atmosphere Data assimilation for climate applications.
The goal of this work is to combine model forecasts from the Canadian Middle Atmosphere Model ( CMAM) and available observations to produce a ``best'' estimate of the atmosphere for climate diagnostics. The 3-Dimensional Variational (3DVAR) assimilation scheme used by the Meteorological Service of Canada (MSC) to produce operational weather forecasts provides the data assimilation component. Observations include conventional tropospheric data (radiosondes, aircraft, surface stations, ships, buoys, TOVS radiances and cloud drift winds from GOES satellites), and will include middle atmosphere data from satellites (i.e. MLS, HRDI, SWIFT ). This work is one of two projects that comprise MSC's Middle Atmosphere Initiative . It is also a part of the Global Chemistry for Climate (GCC) project.

Chemical Data assimilation.
CMAM is a comprehensive climate model with fully interactive chemistry, radiation and dynamics. Thus, in addition to assimilating dynamical variables, we plan to assimilate chemical data from satellites (i.e. MLS, OSIRIS) to obtain a ``best'' estimate of ozone and related species.

Science in support of Canadian satellite instrument developers.
With a reasonable depiction of the atmospheric state up to 80 km (the top of the mesosphere), CMAM analyses would be able to provide a background estimate for satellite retrievals. The CMAM Data Assimilation group (CMAM-DA) is involved with the Canadian SWIFT (Stratospheric Wind Interferometer For Transport Studies) instrument, and plans to assimilate wind and temperature data when the satellite is launched in 2007.




Research Papers Courses





This site is maintained by Saroja Polavarapu.
Last updated May 11, 2001.