Cooperative Institute for Research in Environmental SciencesCooperative Institute for Research in Environmental Sciences at the University of Colorado Boulder

Mark Miesch

(He/Him)

Research Scientist III

Education

1998 Ph.D. (Astrophysics), University of Colorado, Boulder, CO
1991 B.S. (Applied Physics), Michigan Technological University, Houghton, MI

mark.miesch@noaa.gov

Phone

307-438-9522

Research Interests

I have diverse research experience and interests, including space weather, the solar wind, coronal mass ejections, the solar cycle, solar and stellar internal dynamics, dynamo theory, magnetohydrodynamics, data assimilation, numerical methods, high-performance computing, machine learning, and public outreach. Born and raised in suburban Detroit, I went to college in Michigan's Upper Penninsula. I fell in love with the west after a few student internships at Los Alamos National Laboratory in New Mexico. That experience motivated me to come to the University of Colorado in Boulder to graduate school over 30 years ago. I have lived and worked in Boulder for most of the time since then, apart from postdoctoral appointments at NASA Goddard Space Flight Center in Maryland and the University of Cambridge in the UK. After 17 years as a research scientist at NCAR's High Altitude Observatory (HAO), I was fortunate enough to get in on the ground level as a member of the core development team for the Joint Effort for Data assimilation Integration (JEDI) project at UCAR's Joint Center for Satellite Data Assimilation. JEDI is a next-generation data assimilation system that is designed for terrestrial weather forecasting but is adapable enough to apply to a wide range of physical systems, including space weather. I came to CIRES and NOAA's Space Weather Prediction Center in 2021. For a list of publications, see my google scholar page.

Current Research

As a member of the solar and solar wind modeling team at NOAA's Space Weather Prediction Center (SWPC), I work to improve our capability to forecast space weather events such as coronal mass ejections and geomagnetic storms. This involves identifying promising models from the research community and transitioning them to space weather operations. I'm interested in a variety of innovative modeling approaches, from the assimilation of coronal and in situ data into solar wind models to so-called "gray box" approaches that combine physics-based models with machine learning algorithms. I am also a SWPC subject matter expert on the solar cycle, the solar interior, and the solar dynamo. This includes managing and developing operational products to better predict the progression of future solar activity on time scales of months, years, and even decades.