Leader & “Bridge-Builder”
Named New Employee of Month
Prins, a meteorologist with contagious enthusiasm, is
NOAA’s new Employee of the Month. Recognized globally as a
scientific leader in the field of fire detection, Elaine was
nominated by her team members for exemplary service over the
past two years. She is on NOAA's National Environmental Satellite,
Data, and Information Service (NESDIS) team at the University
of Wisconsin, Madison.
also raises orchids and, with her husband, Ken Bywaters, teaches
youth classes at her church, where encouraging voluntarism
is high on her list. She speaks frequently to budding meteorologists.
is a great team player,” said Greg Withee, assistant administrator
for satellite and information services. “She builds bridges
not only within NESDIS, but also across agencies such as NOAA,
NASA, and the Department of Defense, and countries like Brazil,
Canada, Japan, and several in Europe.”
Acting Team Leader of the Advanced Satellite Products Team
in Madison for two years, Elaine developed the first automated
technique for detecting fires using geostationary satellite
data. Her technique for detecting fires has proven to be a
valuable tool in the detection and monitoring of fire outbreaks
in the Western Hemisphere. Without any manual guidance, her
technique corrects for atmospheric conditions such as smoke
or semi-transparent clouds. It also indicates the locations
of fires and their approximate size.
in part to the highly successful research program she led,
NOAA’s Geostationary Operational Environmental Satellite (GOES),
traditionally used for monitoring weather, has been described
as now monitoring for weather and fires. Elaine recently presented
her work at the Regional Fire Workshop hosted by the National
Space Development Agency of Japan in Tokyo, Japan.
organizational and leadership skills, she recently organized
a group of scientists from the Advanced Satellite Products
Team and the Cooperative Institute for Meteorological Satellite
Studies to fulfill an urgent request for simulations of the
proposed GOES Advanced Baseline Imager. After two weeks of
research, including multi-sensor data analysis and modeling,
a robust presentation of characteristics for volcanic eruptions,
fires and clouds was delivered.