Research Scientist III
B.S. in Meteorology, Pennsylvania State University
My research interests include clouds and precipitation, and using remote sensing to better observe these quantities and ultimately improve their representation in satellite products and models. I am also interested in the application of machine learning to atmospheric science problems.
I develop algorithms and products for the NOAA/NASA Advanced Baseline Imager (ABI) on the GOES satellite series, JPSS VIIRS, and the NASA CloudSat Cloud Profiling Radar. I also lead NOAA’s GeoXO research and exploratory project at CIRA, and am the Project Manager and co-PI of the CIRA OVERCAST project sponsored by the Office of Naval Research.
For more details, see my website at https://www.engr.colostate.edu/~jhaynes.
Clouds and precipitation / Remote sensing – Wednesday, March 12, 2014
Using multispectral and data fusion approaches to improve our ability to detect and quantify cloud height with passive satellite sensors (GOES ABI, VIIRS, GeoXO); improving detection of multiple layered cloud systems and cloud base for aviation applications
Improving our understanding of global precipitation processes; development of the CloudSat precipitation retrieval (2C-PRECIP-COLUMN)
Cloud and precipitation remote sensing; millimeter wavelength radar and lidar systems (the spaceborne CloudSat and CALIPSO platforms)
Evaluation and improvement of numerical forecast model representations of clouds and precipitation; development of a radar forward model software package to simulate radar reflectivity profiles at microwave frequencies