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CIRA Fellow

Yoo-Jeong Noh

Senior Research Scientist/Scholar

Mailing Address:
Yoo-Jeong Noh
Cooperative Institute for Research in the Atmosphere
Colorado State University
1375 Campus Delivery
Fort Collins, CO 80523-1375
  • Office Location:
    CIRA Room 13
  • 970-491-8907
About Me:

Yoo-Jeong Noh received her BSc in Atmospheric Science from Yonsei University and MS in Environmental Engineering (Environmental heat transfer/fluid mechanics) from Pohang University of Science and Technology. She had professional experiences on precipitation analysis using TRMM and surface observations, and numerical modeling (WRF and MM5) while working at the Meteorological Research Institute/Korea Meteorological Administration and the Global Environment Laboratory/Yonsei University in Korea. After receiving her PhD degree in Meteorology from Florida State University, she joined CIRA in 2006 and continues to work on satellite cloud/precipitation measurements as a Research Scientist following her two year postdoc research. Her areas of research interest include developing cloud/precipitation algorithms using active/passive satellite data and in-situ observations, radiative transfer modeling, and studies on mixed-phase clouds and turbulence detection for aviation weather applications.

My Work/Projects:

Past Work

Wednesday, March 12, 2014

Satellite-based 3D cloud structure estimation using multiple satellite sensors (JPSS VIIRS and GOES-R ABI)
Satellite cloud data applications for aviation users
JPSS VIIRS CAL/VAL: Validate VIIRS cloud base height products with CloudSat for various cloud types and produce matchup data
Detection of supercooled liquid water-topped mixed phase clouds from multispectral satellite observations
In situ aircraft measurements of mixed-phase clouds
Multi-satellite observations of boundary layer clouds over the Arctic Ocean
GOES-R proxy radiance data study: Generate GOES-R ABI synthetic imagery using CIRA radiative transfer model and CRTM from WRF simulations
A snowfall retrieval algorithm development based on Bayes’ theorem using high frequency microwave satellite data