ROMS California modeling system Horizontal resolution: 3.3 km Vertical resolution: 40 sigma layers Atmospheric forcing: Daily 5-km NAM 00 UTC forecasts (NOAA/NCEP) Data Assimilatio n: multi-scale 3DVAR (satellite SST and SSH, SIO glider/Argo T/S profiles, HF radar surface currents, ship SSTs, M1 mooring T/S) Real-time Nowcasts : every 6 hours - 03, 09,15, 21 UTC: Jan 2009 - present. With CoSINE biogeochemistry: Sept 2013 – present. Forecasts : Daily 72 hour forecast from 03 UTC. CeNCOOS SCCOOS Assimilation Impact of Physical Data on the California Coastal Ocean Circulation and Biogeochemistry Yi Chao, Remote Sensing Solutions (RSS)/UCLA; John D. Farrara, RSS; Fei Chai, University of Maine; Hongchun Zhang, UCLA
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ROMS California modeling system Horizontal resolution: 3.3 km
Vertical resolution: 40 sigma layers
Atmospheric forcing: Daily 5-km NAM
00 UTC forecasts (NOAA/NCEP)
Data Assimilation: multi-scale 3DVAR (satellite SST and SSH, SIO glider/Argo T/S profiles,
Assimilation Impact of Physical Data on the California Coastal Ocean Circulation and Biogeochemistry
Yi Chao, Remote Sensing Solutions (RSS)/UCLA; John D. Farrara, RSS; Fei Chai, University of Maine; Hongchun Zhang, UCLA
The Multi-Scale Three-Dimensional Variational Data Assimilation Scheme
• Sparse Vertical Profile sampling
• High Resolution Remote Sensing
• High Resolution Coastal Ocean Model
Li, Z., J. C. McWilliams, K. Ide, J. D. Farrara (2015), A Multiscale Variational Data Assimilation Scheme: Formulation and Illustration. Mon. Wea. Rev., 143, 3804–3822. doi: http://dx.doi.org/10.1175/MWR-D-14-00384.1. Li, Z., J. C. McWilliams, K. Ide and J. D. Farrara (2015), Coastal Ocean data assimilation using a multi-scale three-dimensional variational scheme. Ocean Dynamics, 65, 1001-1015. doi: 10.1007/s10236-015-0850-x.
• Multi-scale 3DVAR scheme uses partitioned cost functions for two scales, which are
solved sequentially (large scale first)
• Uses multi-decorrelation length scales (of approximately 65 and 10 km) to
construct background error covariances for the two scales
• Effectiveness of the assimilation of both sparse and high resolution observations is