WP 5 Integration Validation IFREMER NERSC NIERSC ODL
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WP 5: Integration & Validation IFREMER, NERSC, NIERSC, ODL, NAVTOR, NERC
4 Tasks, 2 Deliverables • T 5. 1: Validation of remote sensing products – IFREMER, NERSC, NIERSC, ODL – Months 13 -24 • T 5. 2: Validation of the wave model – IFREMER – Months 13 -24 • T 5. 3: Validation of the sea ice model – NERSC, NIERSC, NERC – Months 13 -24
4 Tasks, 2 Deliverables • T 5. 4: Integration – NAVTOR, NERSC – Months 13 -24 • D 5. 1: Validation reports – NERSC – Month 24 • D 5. 2: Upgraded software – Nav. Tracker & Nav. Planner to include waves-in-ice and ice forecasts – NAVTOR – Month 24
Total contributions from partners
Task 5. 1: Validation of remote sensing products • Validate independent satellite data from WP 4 against each other and available in-situ data. 1. SAR wave spectra (ODL) near MIZ: ice-free SAR wave spectra far MIZ: simple wave sensor (3 -axis accelerometer) developed in SWARP (ready 2015) Other buoys – – – 2. Ice classification (MIZ area) – • – • from scatterometers/radiometers (Ifremer) Low resolution (25 km) from SAR/optical images (NIERSC) High resolution
5. 1 Validation of the wave model Task 5. 2: Validation of the wave a) wave parameters model Generic validation of wave parameters: • Altimeters (Hs & mss ): in ice-free water • Permanent buoys: general context (Iceland + Barents Sea ) rms error for Hs (%) Ardhuin et al. 2010 (Prévimer) WIFAR 2012 + other field data validation: • Detailed estimation of spectra, specific validation of wave attenuation rates SAR-derived attenuation rates
5. 1 Validation of the wave model Task 5. 2: Validation of the wave model Fluxes to ice, ocean and atmosphere: b) fluxes to ice, ocean & atmosphere Wave energy balance ↔ wave momentum balance • Relevance for atmospheric forcing? • Input to the ice model (extra drag on ice) ? • Forced vs coupled modeling → implementation of OASIS 3 -MCT in WW 3. • Possible additional runs with IFS+WAM for wind stress diagnostics. • Validation of all « operational centers » with permanent buoys:
Task 5. 3: Validation of the sea ice model • In-situ data from cruises (August-September 2012 & September 2013) – Two 5 -day periods of drift, recording acceleration in 3 axes. – Other data: local thickness, wind, temperature, ambient noise – High resolution SAR for navigation (2013); wide swath SAR (2012, 2013)
Task 5. 3: Validation of the sea ice model • MIZ? Can make out at least 1 floe about 100 m in the ‘pack’. • Need to look at the floe size distribution in the pack to see what the lines correspond to.
Task 5. 3: Validation of the sea ice model • Model results compared to SAR (red lines). • Concentration (AMSR 2, 3. 125 km grid), thickness=1. 5 m. • Black lines: Dmax=100 m (Left), 110 m (Right)
Task 5. 3: Validation of the sea ice model • Model results compared to SAR (red lines). • Concentration (AMSR 2, 3. 125 km grid), thickness=2. 5 m. • Black lines: Dmax=130 m (Left), 150 m (Right)
Task 5. 3: Validation of the sea ice model • Other possible data sets – Beaufort Sea 2011 -2013 (Hwang et al, 2013): 18 SAR images analysed for FSD – Australian Antarctic SIPEX 2 expedition (Sep-Nov 2012): Wave measurements (Kohout) and FSD/thickness observations (video by Toyota) – Images/analysis from WP 4
Task 5. 4: Integration • Making waves-in-ice forecast stable – eg. back-up options if some input data is unavailable. • Converting model outputs to correct format/grid – NAVTOR uses GRIB 1 or GRIB 2 (General Regularlydistributed Information in Binary form). • Transferal of model outputs to NAVTOR servers. • Upgrading Nav. Tracker/Nav. Planner to include wave/ice information.
