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Climate and Space Sciences and Engineering
Climate and Space Sciences and Engineering
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Research > Theory & Computational Methods > Statistical Methods & Data Assimilation
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Statistical Methods & Data Assimilation

With the tremendous growth in the numbers and types of observations, and the increasing sophistication of atmospheric models, it is imperative to develop techniques that make optimal use of both. Research at Climate & Space involves both the development of new data assimilation techniques, as well as use of proven statistical methods. We evaluate models, produce optimally merged model and observation datasets, and prepare for future satellite platforms. 

One particular research area in Climate & Space and the UM Department of Civil & Environmental Engineering is geostatistical inverse modeling and geostatistical sampling design. The latter provides optimal spatial and temporal information about the distribution of measured air pollutants or trace gases and helps investigate the Earth’s carbon cycle.

Faculty

Darren de Zeeuw
Richard Frazin
Xianglei Huang
Xianzhe Jia
Justin Kasper
Aaron Ridley
Christopher Ruf
Igor Sokolov
Bart van der Holst
College of Engineering | University of Michigan
Climate and Space Sciences and Engineering

Climate & Space Research Building
University of Michigan
2455 Hayward Street
Ann Arbor, MI 48109-2143

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