Data Assimilation & Prediction

(COMPLETED) Assimilation of Moisture and Precipitation Observations in Cloudy Regions of Hurricane Inner Core Environments to Improve Hurricane Intensity, Structure and Precipitation

Project Period: July 1, 2014 to June 30, 2017
Principal Investigator(s): Christian Kummerow (CSU) and Milija Zupanski
Other Investigator(s): Vijay Tallapragada (NOAA/NCEP/EMC), Sid Boukabara (NOAA/NESDIS/STAR), Mark DeMaria (NOAA/NCEP/NHC), Richard J. Pasch (NOAA/NCEP/NHC), Lewis Grasso (CSU/CIRA), Paula Brown (CSU/Atmos)

Postdoc(s): Ting-Chi Wu

Sponsor(s): National Oceanic and Atmospheric Administration (NOAA)


Hurricane intensity, structure, and precipitation are fundamentally related to clouds and moisture. Although several different types of observations can impact the prediction of hurricanes, satellite measurements of water vapor, clouds, and precipitation in the hurricane inner core environment may have the most direct impact. Such observations include satellite radiances (e.g., MHS, AMSU, ATMS/CrIS, GOES imager), and high-resolution satellite precipitation products (e.g., NASA GPM). However, NOAA operations are currently not assimilating the majority of satellite information in the hurricane core and near-core environment.


We propose to use these observations together with advanced data assimilation in cloudy regions of the hurricane inner core applied to NOAAs operational hurricane prediction model to evaluate the potential to improve the analysis and prediction of hurricane intensity, structure, and precipitation. We propose to


  1. adopt and optimize a regional ensemble-based data assimilation algorithm for assimilation of satellite moisture-affected radiances and custom GPM rainfall product,
  2. develop this capability for the NOAA operational HWRF system for assimilation in the core, and near-core environment, and
  3. evaluate the impact of these products on the analysis and prediction of hurricane intensity, structure, and precipitation.

This research is in synergy with the NASA GPM project and several NOAA-sponsored projects conducted at CIRA that include JCSDA, HFIP, and GOES-R Risk Reduction.