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Mountain Weather Prediction: Phenomenological Challenges and Forecast Methodology

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Abstract

This chapter summarizes the modern practice of weather analysis and forecasting in complex terrain with special emphasis placed on the role of humans. Weather in areas of complex terrain affects roughly half of the world’s land surface, population, and surface runoff, and frequently poses a threat to lives and property. Mountain weather phenomena also impact a diverse group of users, which may have both beneficial and detrimental implications on societal and economic levels.

Advances in forecast skill derive not only from advances in numerical weather prediction, geophysical observations, and cyber infrastructure, but also improvements in the utilization of these advances by operational weather forecasters. Precipitation skill scores during the past two decades, for example, show that operational weather forecasters have maintained a consistent threat score advantage over numerical precipitation forecasts. Although the role of human forecasters is evolving, for many applications, the so-called “human-machine mix” continues to provide an improved product over what can be produced by automated systems alone. To produce the best forecasts possible for the benefit of society, it is crucial for the mountain meteorologist to possess an in-depth knowledge of mountain weather phenomena and the tools and techniques used for atmospheric observations and prediction in complex terrain.

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Acknowledgments

We thank the participants in the 2008 AMS/COMET/MSC Mountain Weather Workshop: Bridging the Gap between Research and Forecasting for 4 days of lectures and discussion that stimulated this chapter, as well as our editors and chapter coauthors and their contributions to this book. Thanks are also extended to the Grand Junction NWS staff, Jeffrey Manion, and three anonymous reviewers for their contributions to the manuscript. Contributing author Steenburgh acknowledges the support of the National Science Foundation under grant ATM-0627937 and the National Weather Service under a series of grants provided by the C-STAR program. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation or National Weather Service.

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Authors and Affiliations

  1. National Weather Service, 2844 Aviators Way, Grand Junction, CO, 81506, USA

    Michael P. Meyers

  2. Department of Atmospheric Sciences, University of Utah, Salt Lake City, UT, USA

    W. James Steenburgh

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  1. Michael P. Meyers
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  2. W. James Steenburgh
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Correspondence to Michael P. Meyers .

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Editors and Affiliations

  1. University of California, Berkeley, Davis Hall 621, Berkeley, 94720-1710, USA

    Fotini K. Chow

  2. , Dpt. of Environmental Sciences, University of Virginia, McCormick Rd. 291, Charlottesville, 22904-4123, Virginia, USA

    Stephan F.J. De Wekker

  3. Meteorological Service of Canada, Burrard Street 401, Vancouver, V6C 3S5, Canada

    Bradley J. Snyder

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Meyers, M.P., Steenburgh, W.J. (2013). Mountain Weather Prediction: Phenomenological Challenges and Forecast Methodology. In: Chow, F., De Wekker, S., Snyder, B. (eds) Mountain Weather Research and Forecasting. Springer Atmospheric Sciences. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4098-3_1

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