Wednesday, 10 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
In part of this study, several strategies for assimilating CYGNSS ocean surface wind speed observations are examined. In the first approach, CYGNSS is assimilated as wind speed observations, following the same methodology used for SSMIS winds. The next two approaches converted CYGNSS wind speed to wind vectors, using NAVGEM sea level pressure fields (following Holton, 1979), and using NAVGEM 10-m wind fields with the AER Variational Analysis Method. Finally, these methods are compared to CYGNSS wind speed assimilation using multiple outer loops with NAVGEM Hybrid 4DVar. Preliminary results support the earlier studies suggesting that NAVDAS-AR wind speed assimilation is sub-optimal.
The assimilation of Delay Doppler Maps (DDMs) into the NAVy Global Environmental Model (NAVGEM) is also examined. The purpose of assimilating DDMs is to avoid the calibration errors currently present in real time CYGNSS wind observations. DDMs are level 1 product of the CYclone Global Navigation Satellite System (CYGNSS) that are available in addition to the traditional level 2 ocean surface wind and MSS observations and will be assimilated using the NRL Hybrid 4Dvar assimilation system. This research will be approached by first verifying the background DDMs simulated using Garrison’s et al. Extended Kalman Filter (EKF) and generated using 10-meter wind fields from Hybrid 4Dvar NAVGEM cycling. Alternatively, NAVGEM 10 meter winds in addition to EKF produced Mean Square Slope (MSS) fitted to Katzberg’s wind relation will be verified against CYGNSS, ASCAT, WINDSCAT, SSMIS, and in-situ observations. These verifications will help to inform on CYGNSS observation errors, quality control, and “superobbing”.
The assimilation of Delay Doppler Maps (DDMs) into the NAVy Global Environmental Model (NAVGEM) is also examined. The purpose of assimilating DDMs is to avoid the calibration errors currently present in real time CYGNSS wind observations. DDMs are level 1 product of the CYclone Global Navigation Satellite System (CYGNSS) that are available in addition to the traditional level 2 ocean surface wind and MSS observations and will be assimilated using the NRL Hybrid 4Dvar assimilation system. This research will be approached by first verifying the background DDMs simulated using Garrison’s et al. Extended Kalman Filter (EKF) and generated using 10-meter wind fields from Hybrid 4Dvar NAVGEM cycling. Alternatively, NAVGEM 10 meter winds in addition to EKF produced Mean Square Slope (MSS) fitted to Katzberg’s wind relation will be verified against CYGNSS, ASCAT, WINDSCAT, SSMIS, and in-situ observations. These verifications will help to inform on CYGNSS observation errors, quality control, and “superobbing”.
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