Parts of the U.S. Government are closed. This site will not be updated; however NOAA websites and social media channels necessary to protect lives and property will be maintained. See https://www.weather.gov for critical weather information. To learn more, see https://www.commerce.gov.
Bob Kuligowski received a B.S.
degree in Meteorology from Penn State University in 1991. Following three
years as an operational weather forecaster at Accu-Weather, Inc., he
returned to Penn State for graduate work, receiving his M.S. in Meteorology
in 1996. To enhance his background in hydrology, he then switched to the
Department of Civil and Environmental Engineering at Penn State for his
Ph.D., which was completed in 2000. His primary research interest is in
estimating and predicting precipitation, as evidenced by his Master's
work on using artificial neural networks to predict short-term precipitation
from recent observations, and his Ph.D. work on assimilating satellite-based
sounding estimates into a mesoscale numerical weather prediction model to
improve fine-scale precipitation forecasts.
Bob has been a Meteorologist at NOAA/NESDIS/STAR since November 1999
and performs research and development on satellite-based rainfall
estimation and nowcasting tools.
Developed the Self-Calibrating Multivariate Precipitation
Retrieval (SCaMPR), which retrieves rain rate estimates using infrared
data from geostationary satellites for flash flood applications;
calibration is automatically updated in real time using microwave-
based rainfall rate estimates as target data. This algorithm has been
running experimentally over the United States since November 2004 and
a version of it will be the next-generational rainfall rate algorithm
for GOES-R. Recent improvements include a correction for subcloud
evaporation, and additional improvements are currently being
Improving Ensemble Tropical Rainfall Potential (eTRaP), which
predicts 0-24h rainfall for tropical systems by extrapolating
satellite-estimated rainfall along the official forecast storm track
for an ensemble of satellite sensors and forecast tracks. Additional
sensors are being added to the ensemble, and the orographic correction
from the Rainfall Climatology and Persistence (R-CLIPER) model is also
being added to the ensemble members.
Collaborating with the Hydrologic Research Center to provide
satellite-derived rainfall rates as input to a Global Flash Flood
Guidance system which provides forecasts of flash flood
Co-chairing the Flood Pilot of the Committee on Earth Observing
Satellites (CEOS) Working Group on Disasters, which will be conducting
several demonstration projects to improve the connection between
producers and potential users of flood-related satellite data.