Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Progress and Developments of Downburst Prediction Applications of GOES

Progress and Developments of Downburst Prediction Applications of GOES The National Environmental Satellite, Data, and Information Service (NESDIS) Center for Satellite Applications and Research (STAR) has developed and evaluated a suite of products that assess convective storm–generated downburst potential derived from Geostationary Operational Environmental Satellite-13–15 ( GOES-13 – 15 ). The existing suite of downburst prediction algorithms employs the GOES sounder to calculate risk based on conceptual models of favorable environmental thermodynamic profiles for downburst occurrence. A diagnostic nowcasting product, the Microburst Windspeed Potential Index (MWPI), is designed to identify attributes of a favorable downburst environment: 1) the presence of large CAPE and 2) the presence of a surface-based or elevated mixed layer with a large temperature lapse rate. This paper provides an updated assessment of the MWPI algorithm, presents case studies demonstrating effective operational use of the MWPI product, and presents validation results for the Great Plains and mid-Atlantic coastal region of the United States. MWPI data were collected for downburst events that occurred during the convective seasons of 2007–13 and were validated against surface observations of convective wind gusts as recorded by wind sensors in high quality mesonetworks over the southern Great Plains and the Chesapeake Bay region. Favorable validation results include a correlation greater than 0.6 and low mean error (<0.1 knot (kt; where 1 kt = 0.51 m s −1 )) between MWPI values and measured confirmed downburst wind speeds over contrasting climate regions of the continental United States. Case studies over the mid-Atlantic region and northern Florida highlight the adaptability of the MWPI algorithm to severe convective storm forecasting and warning operations. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Weather and Forecasting American Meteorological Society

Progress and Developments of Downburst Prediction Applications of GOES

Weather and Forecasting , Volume 30 (5) – Sep 4, 2014

Loading next page...
 
/lp/american-meteorological-society/progress-and-developments-of-downburst-prediction-applications-of-goes-3PEC8NZnlf

References

References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.

Publisher
American Meteorological Society
Copyright
Copyright © 2014 American Meteorological Society
ISSN
0882-8156
eISSN
1520-0434
DOI
10.1175/WAF-D-14-00106.1
Publisher site
See Article on Publisher Site

Abstract

The National Environmental Satellite, Data, and Information Service (NESDIS) Center for Satellite Applications and Research (STAR) has developed and evaluated a suite of products that assess convective storm–generated downburst potential derived from Geostationary Operational Environmental Satellite-13–15 ( GOES-13 – 15 ). The existing suite of downburst prediction algorithms employs the GOES sounder to calculate risk based on conceptual models of favorable environmental thermodynamic profiles for downburst occurrence. A diagnostic nowcasting product, the Microburst Windspeed Potential Index (MWPI), is designed to identify attributes of a favorable downburst environment: 1) the presence of large CAPE and 2) the presence of a surface-based or elevated mixed layer with a large temperature lapse rate. This paper provides an updated assessment of the MWPI algorithm, presents case studies demonstrating effective operational use of the MWPI product, and presents validation results for the Great Plains and mid-Atlantic coastal region of the United States. MWPI data were collected for downburst events that occurred during the convective seasons of 2007–13 and were validated against surface observations of convective wind gusts as recorded by wind sensors in high quality mesonetworks over the southern Great Plains and the Chesapeake Bay region. Favorable validation results include a correlation greater than 0.6 and low mean error (<0.1 knot (kt; where 1 kt = 0.51 m s −1 )) between MWPI values and measured confirmed downburst wind speeds over contrasting climate regions of the continental United States. Case studies over the mid-Atlantic region and northern Florida highlight the adaptability of the MWPI algorithm to severe convective storm forecasting and warning operations.

Journal

Weather and ForecastingAmerican Meteorological Society

Published: Sep 4, 2014

References