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Assimilation of GLM data using HVEDAS

Assimilation of GLM data using HVEDAS. Title : Utility of GOES-R Geostationary Lightning Mapper (GLM) using hybrid variational-ensemble data assimilation in regional applications Lead: Milija Zupanski, CIRA Main Participants : Louie Grasso, CIRA John Knaff, STAR/RAMMB

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Assimilation of GLM data using HVEDAS

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  1. Assimilation of GLM data using HVEDAS • Title: Utility of GOES-R Geostationary Lightning Mapper (GLM) using hybrid variational-ensemble data assimilation in regional applications • Lead: • Milija Zupanski, CIRA • Main Participants: • Louie Grasso, CIRA • John Knaff, STAR/RAMMB • Outside Collaboration: • Stephen Lord, NCEP/EMC • Motivation: • Combine GOES-R data with current operational data • Focus on Geostationary Lightning Mapper (GLM) • Assess the utility of GLM in future NOAA operational environment, based on the use of a hybrid variational-ensemble data assimilation system (HVEDAS) • Examine the benefit of combining GLM data with other data available today in NOAA operations 1

  2. Research Goals: • Develop a capability to use GOES-R Geostationary Lightning Mapper (GLM) observations in a prototype hybrid variational-ensemble data assimilation system (HVEDAS) and evaluate its impact in regional data assimilation. • In order to enhance the GLM utility, combine GLM assimilation with assimilation of all-sky microwave (MW) satellite radiance observations. (Both types of observations have a potential to introduce relevant information related to cloud microphysics and thus impact the analysis and prediction of severe storms and other extreme weather events). • Evaluate assimilation of GLM proxy data using NOAA operational system components and a prototype HVEDAS. • Demonstrate the utility of the GOES-R GLM in severe weather data assimilation. 2

  3. Methodology and system components: • (1) Basic setup: - Interface the WRF-NMM modeling system with MLEF to assimilate NCEP current operational observations. - Use the NCEP Gridpoint Statistical Interpolation (GSI) as observation operator. - Use the Community Radiative Transfer Model (CRTM) for assimilation of radiances (clear-sky and all-sky). • (2) Develop/adapt the GLM forward operator for use in GLM (LLDN) data assimilation. - Depends on the model’s microphysics scheme complexity. - No dynamical link between cloud microphysics and static electricity. - Need to rely on regressions. • Future plans: If there is NOAA interest in further investigation/implementation of GLM observations in data assimilation, support such an effort in collaboration with EMC. More detailed information on the poster

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