Open AccessA Fingerprinting Technique for Major Weather Events
Author(s) -
Benjamin Root,
Paul Knight,
George S. Young,
Steven J. Greybush,
Richard H. Grumm,
Ron Holmes,
Jeremy D. Ross
Publication year - 2007
Publication title -
journal of applied meteorology and climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.079
H-Index - 134
eISSN - 1558-8432
pISSN - 1558-8424
DOI - 10.1175/jam2509.1
Subject(s) - numerical weather prediction , mesoscale meteorology , computer science , weather forecasting , cluster analysis , meteorology , anomaly (physics) , range (aeronautics) , weather patterns , model output statistics , weather prediction , data mining , environmental science , machine learning , geology , geography , climate change , oceanography , physics , materials science , composite material , condensed matter physics
Advances in numerical weather prediction have occurred on numerous fronts, from sophisticated physics packages in the latest mesoscale models to multimodel ensembles of medium-range predictions. Thus, the skill of numerical weather forecasts continues to increase. Statistical techniques have further increased the utility of these predictions. The availability of large atmospheric datasets and faster computers has made pattern recognition of major weather events a feasible means of statistically enhancing the value of numerical forecasts. This paper examines the utility of pattern recognition in assisting the prediction of severe and major weather in the Middle Atlantic region. An important innovation in this work is that the analog technique is applied to NWP forecast maps as a pattern-recognition tool rather than to analysis maps as a forecast tool. A technique is described that employs a new clustering algorithm to objectively identify the anomaly patterns or “fingerprints” associated with past events. The potential refinement and applicability of this method as an operational forecasting tool employed by comparing numerical weather prediction forecasts with fingerprints already identified for major weather events are also discussed.