Gridpoint Statistical Interpolation (GSI)/Ensemble Kalman Filter (EnKF) are operational data assimilation systems, open to contributions from scientists and software engineers from both operations and research. The development and maintenance of NOAA GSI/EnKF data assimilation systems are coordinated and managed by the Data Assimilation Review Committee (DARC), which incorporates all major GSI/EnKF data assimilation development teams in the United States within a unified community framework. DARC established a code review and transition process for all GSI/EnKF developers, reviews proposals for code commits to the GSI/EnKF repository and ensures that coding standards and tests are being fulfilled. Once DARC approves, the contributed code is committed to the GSI/EnKF code repository and available for operational implementation and public release.
The Developmental Testbed Center (DTC) Data Assimilation (DA) Team serves as a bridge between the research and operational communities by making the operational data assimilation system available as a community resource and by providing a mechanism to commit innovative research to the operational code repository. Prospective code contributors can contact the DTC DA helpdesk to prepare, integrate, and document the expected impact of their code and ensure that any proposed code change meets GSI coding standards. They can also apply to the DTC Visitor Program for their DA research and code transition.
Since the code transition procedures were established, the DTC DA team has helped many researchers contribute code to the repository:
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NOAA/GSD and NCAR MMM scientists improved chemical initial conditions for WRF-Chem and GO-CART forecasts by using WRF-Chem and GOCART as background to analyze surface measurements of fine particulate matter (PM2.5) and MODerate resolution Imaging Spectroradiometer (MODIS) total Aerosol Optical Depth at a wavelength of 550 nm. These functions are available through the DTC GSI release and have been used by many researchers including Barbara Scherllin-Pirscher from the Central Institute for Meteorology and Geodynamics, Vienna, Austria. Scherllin-Pirscher is a DTC visitor working to further enhance GSI chemical analysis by assimilating vertical light detection and ranging (LIDAR) measurements to improve the vertical aerosol representation in WRF-Chem forecasts.
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The DTC hosted Mengjuan Liu from the Shanghai Meteorological Service to study how to use GSI to improve the surface data analysis. Liu found the conventional observation operator can introduce large representativeness errors when surface conditions are inhomogeneous, such as on coastlines. An improved forward model for surface observation along the coastline was developed and added to GSI repository. This new forward observation operator was used in the recent operational Rapid Refresh/High-Resolution Rapid Refresh (RAP/HRRR) update.
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The DTC Visitor Program hosted Ting-Chi Wu from CIRA/CSU to add the capability to assimilate solid-water content path (SWCP) and liquid-water content path (LWCP), which are satellite retrieved hydrometeor observations from Global Precipitation Measurement (GPM) from the Goddard PROFiling algorithm (GPROF).
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The DTC Visitor Program hosted Karina Apodaca from CIRA/CSU to incorporate two new lightning flash rate observation operators suitable for the Geostationary Operational Environmental Satellite (GOES)/Global Lightning Mapper (GLM) instrument in the GSI variational data assimilation framework. One operator accounts for coarse resolution and simplified cloud microphysics in the global model to evaluate the impact of lightning observations on the large-scale environment around and prior to storm initiation. Another forward operator for use with non-hydrostatic, cloud-resolving models permits the inclusion of precipitating and non-precipitating hydrometeors as analysis control variables.
The GSI/EnKF code commit procedures established by DARC and the DTC successfully moves innovative contributions into the repository. The DTC and its Visitor Program is a great resource for the research community to introduce new techniques and model components to advance numerical weather prediction technology.
Contributed by Ming Hu and Chunhua Zhou.
