Assimilation of Satellite Microwave Observations in the Rainband of Hurricanes using a Novel Bayesian Monte Carlo Technique

OneNOAA Science Seminar Series

Sponsor: STAR Science Seminars

Presenter:
Isaac Moradi, NASA

Sponsor:
STAR Science Seminar Series

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Abstract: We propose a novel Bayesian Monte Carlo Integration (BMCI) technique to retrieve the profiles of temperature, water vapor, and cloud liquid/ice water content from microwave cloudy measurements in the rainbands of tropical cyclones (TC). These retrievals then can either be directly used by meteorologists to analyze the structure of TCs or be assimilated into numerical models to provide accurate initial conditions for the NWP models. The BMCI technique is applied to the data from the Advanced Technology Microwave Sounder (ATMS) onboard Suomi National Polar-orbiting Partnership (NPP) and Global Precipitation Measurement (GPM) Microwave Imager (GMI).

About the Speaker: Dr. Isaac Moradi is a remote sensing scientist with over fifteen years of experience specializing in radiative transfer modeling; Observing System Simulation Experiments (OSSE); data assimilation; satellite data analysis and bias correction; atmospheric humidity and ice clouds; inverse methods and retrieving geophysical variables from satellite observations; solar radiation resource assessment; quality assurance of solar radiation and in-situ radiosonde measurements; and developing new instrument concepts especially for measuring tropospheric humidity. Please also see https://science.gsfc.nasa.gov/sed/bio/isaac.moradi

POC:
Stacy Bunin, stacy.bunin@noaa.gov

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{Isaac Moradi, NASA}