Steven Michael Naegele

Steven Michael Naegele

  • Ph.D. Graduate Student
3450 Mitchell Ln
Boulder, CO 80301
Email: svn5241@psu.edu
Phone: (303) 497-2802

Education:

  1. B.S. - 2015 - Atmospheric Sciences - University of Illinois at Urbana-Champaign
  2. M.S. - 2018 - Meteorology - Penn State

Biography:

Overview

My research interests include cloud microphysics, microphysical modeling, radar meteorology, boundary layer processes, and machine learning. For my Master's degree, I worked on using polarimetric signatures to identify different hydrometeor types and microphysical processes within a winter cyclone. I also used a numerical weather model to assess how well it simulated these microphysical processes. I am now comparing wind climatology in Kuwait to model reforecasts, with plans of building an AI to provide wind forecasts for a Kuwaiti wind farm.

Other Research Experience

NCAR -- ASP (Advanced Study Program) (Summer 2016)

  • microphysical modeling under the guidance of Drs. Trude Eidhammer and Greg Thompson
  • ran a sensitivity study of a simulated nor'easter to snow/graupel transition in the WRF model 

NCAR -- SOARS (Significant Opportunities in Atmospheric Research and Science) (Summer 2014, 2015)

  • microphysical modeling under the guidance of Drs. Sarah Tessendorf, Trude Eidhammer, and Greg Thompson
  • ran the WRF model to study the sensitivity of simulated squall lines to the microphysical representation of graupel

University of Illinois - Undergraduate research (Fall 2014)

  • ran the Straka Atmospheric Model to simulate the development of shallow cumulus clouds and the effects of entrainment on their liquid water content under different environmental conditions

OWLeS (Ontario Winter Lake-effect Systems) project (December 2013-January 2014)

  • participated in a field project that studied the thermodynamic, mesoscale, and microscale structure of lake-effect snow bands
  • operated the Doppler on Wheels (DOW) mobile radars and transected snow bands with instrumented mobile mesonet vehicles
  • forecasted lake-effect bands via daily forecast briefings