Research Interests

Tomoko Matsuo's main research interest is the design and development of statistical inferential methodologies for Earth and Geospace environmental observations, including the modeling of spatio-temporal random scalar and vector fields and designing sequential Monte Carlo methods for high-dimensional dynamical systems. She is fascinated by the process of unearthing and characterizing underlying statistical and physical properties hidden in data by means of statistical inference. Data assimilation is a good example of such a process.

Her research focuses on data assimilation of various types of remotely sensed and in-situ measurements into numerical models of Earth and Geospace systems, encompassing the Earth's whole atmosphere, ionosphere and magnetosphere. She is also interested in integrating design and development of engineering systems into geophysical modeling and prediction. Data assimilation provides an excellent framework for such investigation, and facilitates optimizing the instrumentation design and deployment of observing systems. Other areas of interest include the quantification of predictability of the whole atmosphere and ionosphere through applications of the dynamical systems theory, estimation theory, and information theory.

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Biographical Sketch

After completing training in Physics and Atmospheric Sciences in 2003, Tomoko Matsuo invested time to build expertise in statistics and data assimilation. She has received unique training in statistics as part of an NSF program to build collaborative research and training between statistics and the geosciences at NCAR's Institute of Mathematics Applied to Geosciences through 2007.

While working at NOAA's Space Weather Prediction Center as a Research Associate in CU Boulder's Cooperative Institute for Research in Environmental Sciences from 2007 to 2016, she has developed original and independent research programs centered on data assimilation of remotely sensed and in-situ data of the Earth's upper atmosphere and near-Earth space, as a Principal Investigator with funding from the NSF, NASA, AFOSR and AFRL. She has been a Principal Investigator or Co-Investigator on 14 funded proposals.

Because of the interdisciplinary nature of data assimilation research, she collaborates widely across disciplinary boundaries with space physicists, atmospheric scientists, engineers, and statisticians. She has advised and co-advised 11 graduate students on topics of geophysical application of data assimilation and spatial statistics.

She has been actively recruited to give talks and lead sessions at national and international meetings, including 20 invited talks over last 5 years. She has served on high-level external and internal committees, including the NSF Coupling, Energetics and Dynamics of Atmospheric Regions, Science Steering committee (2012-2015), the NSF Geospace Section Committee of Visitors (2014), the NASA Heliophysics Advisory Committee (2017-current), the AGU Basu United States Early Career Award committee (2017-current), the University of Colorado Boulder's international strategy committee (2017-current), and the advisory board for the University of Colorado Boulder's Center for Research Data and Digital Scholarship (2017-current).

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Hello, I'm Tomoko Matsuo