Milija Zupanski Senior Research Scientist CIRA Fort Collins Project 1 Assimilation of Moisture and Precipitation Observations in Cloudy Regions of Hurricane Inner Core Environments to Improve Hurricane Intensity, Structure and Precipitation CIRA Principal Investigators:Christian Kummerow and Milija Zupanski In partnership with:Vijay Tallapragada (NOAA/NCEP/EMC) Mark DeMaria (NOAA/NCEP/NHC) Richard Pasch (NOAA/NCEP/NHC) Sid Boukabara (NOAA/NESDIS/STAR/JCSDA) CIRA/ATS contribution:Ting-Chu Wu, Paula Brown, Louis Grasso, Karina Apodaca, Yoonjin Lee Activity period:1 July 2014 30 June 2017 Project Description The scientific focus of this project is to o develop the capability to assimilate satellite moisture/precipitation data in near-core and hurricane core environment for use by NOAA operational HWRF model, and o evaluate the impact on the analysis and prediction of hurricane intensity, structure, and precipitation. We plan to achieve this by: (1)adopting and optimizing a regional ensemble-based data assimilation algorithm for assimilation of satellite moisture-affected radiances and custom GPM rainfall product, and (2)developing this capability for the NOAA operational hurricane WRF (HWRF) modeling system for assimilation in the core, and near- core environment GPM GOES-R Highlight of recent results: Impact of assimilating TRMM hydrometeor retrievals in HWRF 3 km nest (Leslie 2012) Next step: Assimilation of combined all-sky satellite radiances (ATMS, CRIS) and customized GPM/TRMM moisture/precipitation data to improve precipitation forecast Analysis increments (analysis-minus-guess) valid 1800 UTC 31 Aug 2012 Surface pressure (hPa)Moisture (kg/kg) Positive impact: decrease of surface pressure, increase of moisture From Ting-Chi Wu Project 2 Incorporating the GOES-R Geostationary Lightning Mapper Assimilation into the GSI for use in the NCEP Global System CIRA Principal Investigator:Milija Zupanski In partnership with:John Derber (NOAA/NCEP/EMC) CIRA contribution:Karina Apodaca Activity period:1 July 2014 30 June 2016 Project Description The scientific focus of this project is to o develop the capability to assimilate GOES-R Geostationary Lightning Mapper (GLM) observations in the NOAA/NCEP global data assimilation system (GDAS) We plan to achieve this by: o adopting and optimizing the GLM lightning observation operator that is suited for NOAA global forecasting and data assimilation, and o incorporating the lightning observation operator in NOAA global data assimilation system Highlight of recent results: Impact of lightning data assimilation on 3-hour forecast of lightning LIGHT Observed GOES-15 Infrared CTL Next step: Continue development of interfaces with GSI Improved representation of storm structure through more accurate location and intensity of lightning activity Tropical storm Ivo (2013) (1)CTL: NOAA/NCEP data assimilation algorithm (no lightning) (2) LIGHT: same as CTL, but with assimilation of lightning From Karina Apodaca Summary Unique opportunity to use NOAA operational systems, with direct NOAA support and feedback o Gridpoint Statistical Interpolation (GSI) data assimilation o Hurricane WRF model o Global Forecasting System (GFS) model Contribute to improving NOAA data assimilation capabilities o Assimilation of lightning with models that do not permit clouds o Assimilation of cloud hydrometeor retrievals (ice, liquid, mixed) o Assimilation of precipitation-affected satellite radiances Innovative research in introducing new observation types o NOAA GOES-R GLM o NASA GPM customized retrieval product