News & Updates
October 17,2012
FY13 FFO
In-Kind Research - Air Force Weather Agency
| Title | Description | Principal Investigator / Point of Contact |
||
|---|---|---|---|---|
| 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 |
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