Variational SST assimilation using another model's adjoint: the AVRORA SHOC assimilation system Chaojiao Sun, Peter Oke, Alexander Kurapov
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1 Variational SST assimilation using another model's adjoint: the AVRORA SHOC assimilation system Chaojiao Sun, Peter Oke, Alexander Kurapov 21 August 2014 OCEANS AND ATMOSPHERE FLAGSHIP
2 The AVRORA SHOC ocean data assimilation system o o o o Part of the ONR funded project to develop a hybrid ensemble variational data assimilation system to improve short range coastal ocean prediction The AVRORA variational representer code (developed at OSU): The Advanced Variational Regional Ocean Representer Analyzer a set of stand alone adjoint and tangent linear model codes, Numerically and algorithmically consistent with the Regional Ocean Modelling System (ROMS) The AVRORA grid is based on ROMS grid configuration, which is the terrain following sigma coordinate Flexibility designing model error covariances, data functionals The Sparse Hydrodynamic Ocean Code (SHOC): a coastal ocean model (developed at CSIRO; Hetzfeld, 2006) uses z coordinate system Does not have its own tangent linear (TL) and adjoint (ADJ) models A case study: seasonal upwelling off the Bonney Coast in South Australia AVRORA SHOC Chaojiao Sun Page 2
3 SHOC has been configured for domains around Australia (Hetzfeld and Oke, 2010) (P. Oke) AVRORA SHOC Chaojiao Sun Page 3
4 AVRORA has been applied to the real time coastal ocean forecast system off Oregon (A. Kurapov) AVRORA SHOC Chaojiao Sun Page 4
5 AVRORA SHOC Chaojiao Sun Page 5 (A. Kurapov)
6 AVRORA SHOC Chaojiao Sun Page 6 (A. Kurapov)
7 AVRORA SHOC Chaojiao Sun Page 7 (A. Kurapov)
8 AVRORA SHOC Chaojiao Sun Page 8 (A. Kurapov)
9 The representer method (Bennette, 2002) AVRORA SHOC Chaojiao Sun Page 9
10 Preconditioning (Egbert, 1997) Computing a subset of representers to form the full representer matrix AVRORA SHOC Chaojiao Sun Page 10
11 AVRORA SHOC assimilation forecast cycle Computational cost of minimizations: Preconditioning: about 300 representers are computed (1 ADJ + 1 TL run) a massively parallel task Minimization: using the conjugate gradient method (about 25 ADJ + TL iterations) Presentation title Presenter name Page 11
12 Experiment details: 3 km horizontal resolution for both forecast and analysis Nonlinear model: SHOC (50 vertical layers) Boundary conditions: 10 km global ocean BLUELink Reanalysis Atmospheric fluxes: ERA interim Reanalysis Experiment period: 1 month (February 2012) Tangent linear and adjoint models: AVRORA (40 vertical layers) Sliding time windows: 4 day forecast, 2 day assimilation window Steps: SHOC free run (No DA) are converted to the AVRORA grid two days of SHOC output on the AVRORA grid as background two days of OSTIA SST reanalysis are assimilated (~10,000 obs) This new IC is converted from AVRORA grid back to SHOC grid to make a new 4 day forecast with SHOC Presentation title Presenter name Page 12
13 A case study: coastal upwelling off the Bonney Coast (David Griffin and IMOS) AVRORA SHOC Chaojiao Sun Page 13
14 AVRORA SHOC Chaojiao Sun Page 14 (Courtesy of David Griffin and IMOS)
15 HF radar and surface currents (Courtesy of Lucy Wyatt and IMOS) AVRORA SHOC Chaojiao Sun Page 15
16 Costal upwelling index at Bonney Coast AVRORA SHOC Chaojiao Sun Page 16
17 Modelling seasonal upwelling off the Bonney Coast in South Australia with the SHOC ocean model AVRORA SHOC Chaojiao Sun Page 17
18 Assimilation results Analysis - Background AVRORA SHOC Chaojiao Sun Page 18
19 Satellite SST SHOC SST DA SST AVRORA SHOC Chaojiao Sun Page 19
20 Satellite SST Model SST (no DA) FCST SST DA SST AVRORA SHOC Chaojiao Sun Page 20
21 Satellite SST Model SST (no DA) FCST SST DA SST AVRORA SHOC Chaojiao Sun Page 21
22 Satellite SST Model SST (no DA) FCST SST DA SST AVRORA SHOC Chaojiao Sun Page 22
23 SST RMSE AVRORA SHOC Chaojiao Sun Page 23
24 Discussion and conclusions 1. We have successfully assimilated satellite SST observations with the AVRORA SHOC ocean data assimilation system. AVRORA is a set of variational data assimilation codes developed for a different ocean model (ROMS), while SHOC does not have its own TL and ADJ codes. The major technical hurdle was the correct conversion of model output between two different grids once that was done properly, the system works 2. This opens the door for explore the potential of combining ensemble method with variational method in a new way. 3. We hope to demonstrate feasibility of this approach to other ocean models. 4. We hope to develop a hybrid Ensemble variational (EnVar) system for coastal ocean prediction. AVRORA SHOC Chaojiao Sun Page 24
25 Acknowledgment o Andy Steven (CSIRO) o Lars Nerger (AWI) o Arnold Hemink (TU Delft) o Martin Verlaan (Deltares) o Farhan Razwi (CSIRO) o Emlyn Jones (CSIRO) o Philip Gillibrand (CSIRO) o Kenji Shimizu (CSIRO) AVRORA SHOC Chaojiao Sun Page 25
26 Thank you CSIRO Oceans and Atmosphere Flagship Dr Chaojiao Sun Research Scientist t e chaojiao.sun@csiro.au w CSIRO OCEANS AND ATMOSPHERE FLAGSHIP
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