WP5: Integration & Validation IFREMER, NERSC, NIERSC, ODL, NAVTOR, NERC.

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Presentation transcript:

WP5: Integration & Validation IFREMER, NERSC, NIERSC, ODL, NAVTOR, NERC

4 Tasks, 2 Deliverables T5.1: Validation of remote sensing products – IFREMER, NERSC, NIERSC, ODL – Months T5.2: Validation of the wave model – IFREMER – Months T5.3: Validation of the sea ice model – NERSC, NIERSC, NERC – Months 13-24

4 Tasks, 2 Deliverables T5.4: Integration – NAVTOR, NERSC – Months D5.1: Validation reports – NERSC – Month 24 D5.2: Upgraded software – NavTracker & NavPlanner 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 WP4 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 (25km) – from SAR/optical images (NIERSC) High resolution

Generic validation of wave parameters: Altimeters (Hs & mss ): in ice-free water Permanent buoys: general context (Iceland + Barents Sea ) WIFAR 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 a) wave parameters Ardhuin et al Ardhuin et al (Prévimer) rms error for Hs (%) Task 5.2: Validation of the wave model

Fluxes to ice, ocean and 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 OASIS3-MCT in WW3. Possible additional runs with IFS+WAM for wind stress diagnostics. Validation of all « operational centers » with permanent buoys: 5.1 Validation of the wave model b) fluxes to ice, ocean & atmosphere Task 5.2: Validation of the wave model

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 100m 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 (AMSR2, 3.125km grid), thickness=1.5m. Black lines: D max =100m (Left), 110m (Right)

Task 5.3: Validation of the sea ice model Model results compared to SAR (red lines). Concentration (AMSR2, 3.125km grid), thickness=2.5m. Black lines: D max =130m (Left), 150m (Right)

Task 5.3: Validation of the sea ice model Other possible data sets – Beaufort Sea (Hwang et al, 2013): 18 SAR images analysed for FSD – Australian Antarctic SIPEX2 expedition (Sep-Nov 2012): Wave measurements (Kohout) and FSD/thickness observations (video by Toyota) – Images/analysis from WP4

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 GRIB1 or GRIB2 (General Regularly- distributed Information in Binary form). Transferal of model outputs to NAVTOR servers. Upgrading NavTracker/NavPlanner to include wave/ice information.