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In-Kind Research - Air Force Weather Agency

Air Force Weather Agency - JTOP Projects
  Title Description Principal Investigator /
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Fiscal Year 2009
1 Begin operational transition of AFWA models to GSI data assimilation system Assessment of LOE required to fully transition WRF, LIS, cloud and other specialized atmospheric and land models to GSI data assimilation system S. Rugg RuggS@offutt.af.mil
2 Evaluate science needed for cloud property assimilation Cloud models require specification of cloud properties/composition for optimal accuracy. This effort will determine science enhancements needed to existing AFWA cloud analysis model and what new satellite sensors/channels are needed to specify cloud properties. J. Cetola Jeffrey.Cetola@offutt.af.mil
Fiscal Year 2011
3 AF Funded Visiting Scientists 1.5 FTE visiting scientists funded via DTC statement of work and one FTE via separate SOW. Two FTEs are on-site at JCSDA headquarters (NCEP) and .5 FTE at DTC in Boulder. Focus is GSI community code maintenance, V&V, configuration management, support for GSI transition at AFWA, and GSI 4DVar development collaboration with NASA & NCAR. J. Zapotocny zapotocj@offutt.af.mil
4 Build the GSI-ARW FSO (Forecast Sensitivity to Observations) tool Couple the adjoint sensitivity algorithm of GSI with the WRF adjoint model to build the GSI-ARW FSO (Forecast Sensitivity to Observations) tool. Computing observation impact with one-month long experiments using the GSI-ARW FSO tool. S. Rugg RuggS@offutt.af.mil
5 Define & Develop verification metrics for new cloudy assimilation capability A solid verification package is central to the development of a new cloud analysis capability. It helps to address sensitive questions such as the choice of a suitable physics package, the tuning of the microphysics parameterization, the importance of balance in the initial conditions, etc. J. Cetola Jeffrey.Cetola@offutt.af.mil
6 Develop an initial capability for directly assimilating MODIS radiance data Develop an operator for MODIS radiance data assimilation and perform seasonal verification testing S. Rugg RuggS@offutt.af.mil
7 Observation error tuning based on Desroziers et al. (2005) for GSI Develop a new algorithm for observation error tuning using OMB, OMA and AMB statistics and compare results with old method. S. Rugg RuggS@offutt.af.mil
8 Update GEN_BE software for cloud parameters Deliver a version of the GEN_BE software with the capability to compute simple background error covariances for cloud parameters J. Cetola Jeffrey.Cetola@offutt.af.mil
9 Update the WRF TL/ADJ code Complete the coupling of WRF non-linear and TL/ADJ code with the GSI data assimilation system to create a WRF-ARW based 4DVAR GSI initial capability. Leverage NASA/GMAO effort on GSI 4DVar. Perform initial testing of the WRF/GSI 4DVar prototype. J. Cetola Jeffrey.Cetola@offutt.af.mil
10 Work with the DART group to get the radiance assimilation capability integrated in the community DART system. Unify the current DART data formats for conventional data and compare the current DART QC results with those from PrepBufr and from OBSPROC. Work on radiance bias correction in DART. Test the radiance assimilation for DART over the tropical Atlantic and compare resulting analyses against existing retrospective WRF/DART analyses for the same period that use only conventional observations. S. Rugg RuggS@offutt.af.mil
Fiscal Year 2012
11 Develop an initial capability for directly assimilating SSMIS radiance data Develop an operator for SSMIS radiance data assimilation and perform seasonal verification testing S. Rugg RuggS@offutt.af.mil
Modified February 1, 2012 10:02 PM
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