Intellectual Property Office
Non-Confidential Disclosures
“A Fingerprinting Technique for Major Weather Events”
PSU Invention Disclosure No. 2006-3254
Field of the Invention/Key Words:
Weather prediction; pattern recognition
Links:
http://www.met.psu.edu/dept/faculty/Knight.htm
http://www.ipo.psu.edu
Inventors:
B. Root, G. Young & P. Knight
Background:
Advances in numerical weather prediction have occurred on numerous fronts, from sophisticated physics packages in the latest mesoscale models to multi-model 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 data sets and faster computers has made pattern recognition of major weather events a feasible means of statistically enhancing the value of numerical forecasts. The existing technology is limited in that it does not use a comprehensive historical database and its statistical attributes to relate previous significant weather events to the likely occurrence (risk) of future significant events. The degree of interest is quickly growing in the application of sophisticated statistical techniques to readily identify the likelihood of significant weather events. There is a need for a system which can offer an objective assessment of the risk of major weather events and its disruptive effects as much as 10 days ahead of time.
Invention description:
This invention is an evolution in the field of objective meteorological prediction. Pattern recognition and forecast analogs have recently offered a paradigm for predicting major weather events. The basic premise is that major weather events have repeatable and specific atmospheric anomaly fields. A method has been developed which uses pattern recognition in assisting the prediction of severe and major weather. A new technique employing a clustering algorithm to objectively identify the anomaly weather patterns or “fingerprints” associated with past events. This tool can eventually be used as an operational forecasting tool employed by comparing numerical weather prediction forecasts to fingerprints already identified for major weather events.
Advantages:
- Minimize risk in areas such as agriculture, utilities and surface transportation
- Broadens applications of artificial intelligence in the field of operational weather prediction
- Uses distinct weather patterns or “fingerprints” associated with any major weather event type
Contact:
Bradley A. Swope
Sr. Technology Licensing Officer
The Pennsylvania State University
113 Technology Center
University Park, PA 16802
Phone: (814) 863-5987
Fax: (814) 865-3591
E-mail: bradswope@psu.edu |
