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David M. Schultz

Researcher at University of Manchester

Publications -  297
Citations -  9072

David M. Schultz is an academic researcher from University of Manchester. The author has contributed to research in topics: Cold front & Medicine. The author has an hindex of 48, co-authored 262 publications receiving 8086 citations. Previous affiliations of David M. Schultz include University of Oklahoma & University of Washington.

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A review of operational, regional-scale, chemical weather forecasting models in Europe

TL;DR: In this article, chemical weather forecasting models are described and compared on regional and continental scales in Europe, and the most prominent gaps of knowledge are highlighted for the following selected focus areas: emission inventories, the integration of numerical weather prediction and atmospheric chemical transport models, boundary conditions and nesting of models, data assimilation of the various chemical species, improved understanding and parameterization of physical processes, better evaluation of models against data and the construction of model ensembles.
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Evolution of the U.S. Tornado Database: 1954–2003

TL;DR: In this paper, a simple least squares linear regression was fitted to the annual number of tornado reports and the F1 and greater Fujita-scale record was used in determining a big tornado day.
Journal Article

Spinal cord stimulation for patients with failed back surgery syndrome: a systematic review

TL;DR: This systematic review evaluating the effectiveness of SCS in relieving chronic intractable pain of failed back surgery syndrome indicated the evidence to be Level II-1 or II-2 for clinical use on a long-term basis.

FORECASTER'S FORUM The Use of Moisture Flux Convergence in Forecasting Convective Initiation: Historical and Operational Perspectives

TL;DR: In this article, a scale analysis shows that surface MFC is directly proportional to the horizontal mass convergence field, allowing MFC to be highly effective in highlighting mesoscale boundaries between different air masses near the earth's surface that can be resolved by surface data and appropriate grid spacing.