Coastal Meteorology and Atmospheric Prediction Group
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    • Convection over the Northeast U.S.
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    • Ensemble Forecasting and Post-Processing
    • Mesoscale & Microphysical Structure of Winter Storms Over the NEUS
    • Orographic Precipitation
    • Offshore Wind- IMPOWR
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Coastal Meteorology and Atmospheric Prediction Group 

What is C.O.M.A.P?

The COMAP group focuses on improving the understanding and forecasting  of meteorological phenomena in the coastal margins of North America. Many near-shore features, such as severe convective storms, storm surge, land/sea breeze circulations, orographic flows and precipitation, and marine clouds/fog in a marine environment are challenging to forecast.  Our more recent efforts have focussed on the regional/future climate of extreme weather events over the Northeast U.S.

These phenomena are investigated using conventional data, field study observations, as well as atmospheric (Weather Research and Forecasting model) and ocean (ADCIRC and SWAN) models combined with the latest data assimilation (EnKF) approaches. We use CMIP5, statistical models, and nested WRF runs to determine how extreme weather will change in a future climate.
Group photo from 2010
Group photo from 2011
Group photo from 2012
Group photo from 2013
​Group photo from 2014
​Group photo from 2015

Recent news 

  • Welcome to the latest COMAP members Fall 2017 (Keenan Fryer and Rui Zhang)!
  • Congratulations to the following COMAP members who received their degrees (Sara Ganetis -- Ph.D. May 2017; Xinxia Song -- M.S. August 2017)!
  • Check out the SBU-WRF, a real-time two-member WRF ensemble developed and maintained by the COMAP Group!
  • Friday Weather Discussions will be held Friday's at 4:00 PM in the Meteorology Lab (End. 139). Check out the weather discussion link for more info.
  • IMPOWR Field Program is the August 2016 cover story in the Bull. Amer. Meteor. Soc. For more info
  • Doppler Radar for Education and Mesoscale Studies (DREAMS) Project:
    17 June - 8 July 2013 (Click here for project blog)
SoMAS Homepage

Recent conferences

​AMS 17th Conference on Mesoscale  Processes, 24-27 July 2017, San Diego, CA
  • Brian Colle and Sara Ganetis: Environmental Conditions Associated With Different Snow Band Structures within Northeast U.S. Winter Storms
  • Brian Colle and Sara Ganetis:  Multi-bands in the Comma Head of the 26-27 December 2010 Northeast U.S. Winter Storm
  • Sandra Yuter (NC State), Brian Colle, and Sara Ganetis, and co-authors: Snow Bands and Velocity Waves within Northeast U.S. Coastal Winter Storms
  • Matt Miller (NC State), Sandra Yuter, Brian Colle, and co-authors. Complex Aggregates Within Coastal Northeast Winter Storms
AMS 28th Conference on Weather Analysis and Forecasting / 24th Conference on Numerical Weather Prediction, 23-26 January 2017, Seattle, WA
  • Sara Ganetis: Environmental Conditions Associated With Different Snow Band Structures within Northeast U.S. Winter Storms
  • Sara Ganetis: Investigation of Multi-bands in the Comma Head of the 26-27 December 2010 Northeast U.S. Winter Storm
​AMS 17th Mountain Meteorology Conference. 27 June - 1 July 2016 Burlington, VT 
  • Brian Colle: Comparison of Simulated Orographic Precipitation Structures Using Different Microphysical Schemes With OLYMPEX Field Program Observations
Northeast Regional Operational Workshop XVI, 4-5 November 2015, Albany, NY
  • Brian Colle: Applying Fuzzy Clustering Analysis to Assess Uncertainty and Ensemble System Performance for Cool Season High-Impact Weather
  • Michael Erickson: Development of a Webpage to Diagnose Ensemble Cyclone Track Uncertainty with Additional Supporting Graphics
  • Sara Ganetis: Evaluation of WRF Simulated Multi-bands over the Northeast U.S. Using Varied Initial Conditions and Physics
  • Nathan Korfe: Exploring Multi-Model Ensemble Performance in Extratropical Cyclones over Eastern North America and the Western Atlantic Ocean
  • Nicholas Leonardo: High Resolution Simulations of an Extreme Precipitation Event over Long Island on 13 August 2014
  • Taylor Mandelbaum: Using Model Climatology to Develop a Confidence Metric for Operational Forecasting

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