News & Updates
October 17,2012
FY13 FFO
In-Kind Research - U.S. Navy
| Title | Description | Principal Investigator / Point of Contact |
||
|---|---|---|---|---|
| Fiscal Year 2011 | ||||
| 1 | High Performance Computing | Provide high performance computing resources at FNMOC for testing and transitioning software to operations at FNMOC | M. Clancy | -- |
| 2 | High Performance Computing | Provide high performance computing resources and software system/data support at NRL and on the DOD HPC network for development and evaluation of science and technology for improved use of satellite data in Navy data assimilation systems. | P. Phoebus | -- |
| 3 | Coordinated Assimilation of Observations from NPP and JPSS (SP-JCSDA) | Coordinate NRL-specific tasks with JCSDA partners to ensure that US operational centers are well prepared to assimilate NPP data operationally; year 3 emphasizes final testing of prep routines and monitoring software, Cal/Val participation, transition of diagnostics, monitoring tools, adjoint-based observation impact system. | S. Swadley | -- |
| 4 | Suitability of CrIS, ATMS and VIIRS for Data Assimilation and Numerical Weather Prediction (SP-CrIMSS) | Complete steps required for day-one passive assimilation and monitoring of CrIMSS radiances, using VIIRS radiances to provide ancillary info on clouds, aerosols and surface properties. Perform data impact experiments. | N. Baker | -- |
| 5 | Microwave Imager/Sounder Sensor (MIS) Program (SP- ) | -- | S. Swadley | -- |
| 6 | Nonlinear Atmospheric Data Assimilation (6.1-Nonlinear) | Derive and test advanced nonlinear data assimilation algorithms that are firmly based on modern inverse problem theory. | N. Baker | -- |
| 7 | Achieving Superior Tropical Cyclone Intensity Forecasts by Improving the Assimilation of High-Resolution Satellite Data into Mesoscale Prediction Models (6.2-NOPP_TC_DA) | Quantify how best to utilize multiple satellite datasets in applications to TC structure/intensity prediction, using advanced data assimilation and high-resolution forecast models | J. Doyle | -- |
| 8 | High-Altitude Data Assimilation for NWP (6.2-Alpha AR) | Develop stratosphere and mesosphere assimilation capabilities using data from new operational and research satellite sensors; include trace gas assimilation. | K. Hoppel (DC) S. Swadley (MRY) | -- |
| 9 | Aerosol Observability and Data Assimilation Investigations in Support of Atmospheric Composition Forecasts (6.2-AeroObs) | Application of model ensemble methods to understand data representativeness as well as error uncertainty and propagation for atmospheric composition data; address fundamental observability questions; investigate flow-dependent correlation models and vertical variability; | J. Reid | -- |
| 10 | Atmospheric Characterization for Oceanography (6.2-ACO) | Develop next-generation ocean color and temperature retrievals from space through use of aerosol analyses to explicitly correct ocean retrievals for aerosol contamination | D. Westphal | -- |
| 11 | Quality Assessment of VIIRS Aerosol EDRs for Aerosol Optical Depth (SP- ) | -- | A. Kuciauskus | -- |
| 12 | VIIRS Proxy Data and Calibration/Validation (SP- ) | -- | E. Hyer | -- |
| 13 | Aerosol Optical Product Verification and Validation (6.4-AeroVV) | Verification and validation of NPP retrievals of spectral aerosol optical depth and particle fine/coarse fraction; compare EDRs with in situ observations in areas not otherwise evaluated (SE Asia) | J. Reid | -- |
| 14 | Aerosol Satellite Data Assimilation (6.4-AeroNP) | Develop assimilation methods appropriate for VIIRS prior to NPP launch. Retrievals initially, followed by direct radiance assimilation longer term. Transition improved QC algorithms to remove biases and cloud contamination in MODIS AOD. Monitor and validate DA algorithms over land and ocean. | D. Westphal | -- |
| 15 | Targeting in the Nonlinear Regime (6.2-NLTarget) | Identify specific deficiencies in current atmospheric analyses that cause forecast-skill dropouts and develop new methods to improve the assimilation of regular and targeted ovservations to improve the problem | R. Langland | -- |
| 16 | SST Data Assimilation (6.4-SkinSST) | Test and implement assimilation methods for physical retrievals of infrared skin SST from VIIRS and microwave SST from MIS, using AVHRR and MODIS, WINDSAT and AMSR-E as potential proxies. Develop semi-analytical skin-SST retrieval algorithm for AVHRR satellite radiances. | J. Cummings | -- |
| 17 | Advanced IR sounder assimilation (6.4 AdvIR) | Develop assimilation methods for advanced IR sounders having very high spectral resolution, particularly those with collocated microwave sounders. Assimilation of radiance principle components; AIRS/IASI surface sensitive channels; advanced spatial and spectral thinning; cloudy radiance assimilation; water vapor radiances. | B. Ruston | -- |
| 18 | Current and Future Sensor Exploitation (6.4-DA) | Enhance NAVDAS and NAVDAS-AR for geostationary satellite observations and GPS-RO bending angle; maintain and update SSMIS UPP; improve moisture assimilation | N. Baker | -- |
| 19 | Variational Ocean Data Assimilation (6.4-DA) | Continue evaluation of impact of AMSR-E, SEVIRI, AATSR. Begin evaluating assimilation of skin SST radiance retrievals, starting with AVHRR; evaluate covariances derived from assimilative ensemble wave model system; include improved SWH bias corrections for altimeter data derived from buoy data. | J. Cummings | -- |
| 20 | Ozone Mapping and Profile Suite (6.4-OMPS) | Test and implement operational ozone assimilation capabilities for the Navy's operational NWP systems. Use SBUV/2 and MLS retrievals to develop the preliminary observation error estimates and QC procedures for OMPS prior to launch of NPP | B. Campbell | -- |
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