Publications per year
Publications per year
Personal profile
Research interests
Seth Linden is a software engineer with deep knowledge and passion for atmospheric science; skilled in computer programming, system development, brainstorming and project leadership. He has been working full-time at the National Center for Atmospheric Science (NCAR) for the last 25 years, since 2001. Seth has a Master’s Degree in Atmospheric Science from the University of Colorado at Boulder and also a B.A. in Physics from CU Boulder. He is one of the remaining primary engineers behind RAL’s highly regarded statistical forecast system called DICast (Dynamic Integrated Forecast), which is used in many projects including all road-weather decision support systems (MDSS) and NCAR’s Pikalert system. DICast is an A.I. based statistical forecast engine that combines many NWP models to create highly tuned weather forecasts at specific locations so Seth is an expert in NWS model data. He is currently the Primary Investigator (P.I.) for the Climavision DICast project, the Denver International Airport MDSS project and the Frost RWIS Pikalert project. Seth is passionate about forecasting weather and creating smart forecasting systems.
Related documents
Education/Academic qualification
Atmospheric Science, No Degree, SUNY College at Oneonta
Computer Engineering, Certificate, University of Colorado Boulder
Atmospheric Science, MS, University of Colorado Boulder
Physics, BA, University of Colorado Boulder
Profile Keywords
- forecast systems, road weather, models, snowfall
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The Model Evaluation Tools (MET) at the core of METplus - Recent Additions and Enhancements
Halley Gotway, J., Jensen, T. L., Soh, H., McCabe, G. P., Prestopnik, J., Opatz, J., Kalb, C. P., Adriaansen, D. R., Biswas, M. K., Hertneky, T. J., Harrold, M. A., Linden, S. & Albo, D., Jan 1 2023, p. 8B.2.Research output: Abstract › Paper
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A comprehensive wind power forecasting system integrating artificial intelligence and numerical weather prediction
Kosovic, B., Haupt, S. E., Adriaansen, D., Alessandrini, S., Wiener, G., Monache, L. D., Liu, Y., Linden, S., Jensen, T., Cheng, W., Politovich, M. & Prestopnik, P., Mar 2 2020, In: Energies. 16, 3, 1372.Research output: Contribution to journal › Article › peer-review
Open Access74 Scopus citations -
Combining artificial intelligence with physics-based methods for probabilistic renewable energy forecasting
Haupt, S. E., McCandless, T. C., Dettling, S., Alessandrini, S., Lee, J. A., Linden, S., Petzke, W., Brummet, T., Nguyen, N., Kosović, B., Wiener, G., Hussain, T. & Al-Rasheedi, M., Apr 1 2020, In: Energies. 13, 8, 1979.Research output: Contribution to journal › Article › peer-review
Open Access70 Scopus citations -
Impacts of assimilating observations from connected vehicles into a numerical weather prediction model
Siems-Anderson, A., Lee, J. A., Brown, B., Wiener, G. & Linden, S., Nov 2020, In: Transportation Research Interdisciplinary Perspectives. 8, 100253.Research output: Contribution to journal › Article › peer-review
Open Access11 Scopus citations -
Machine learning for applied weather prediction
Haupt, S. E., Cowie, J., Linden, S., McCandless, T., Kosovic, B. & Alessandrini, S., Dec 24 2018, Proceedings - IEEE 14th International Conference on eScience, e-Science 2018. Institute of Electrical and Electronics Engineers Inc., p. 276-277 2 p. 8588666. (Proceedings - IEEE 14th International Conference on eScience, e-Science 2018).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
50 Scopus citations