IFREMER NERSC NIERSC ODL NAVTOR NERC 4 Tasks 2 Deliverables T51 Validation of remote sensing products IFREMER NERSC NIERSC ODL Months 1324 T52 Validation of the wave model IFREMER ID: 285957
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Slide1
WP5: Integration & Validation
IFREMER, NERSC, NIERSC, ODL, NAVTOR, NERCSlide2
4 Tasks, 2 Deliverables
T5.1: Validation of remote sensing products
IFREMER, NERSC, NIERSC, ODL
Months 13-24
T5.2: Validation of the wave model
IFREMER
Months 13-24
T5.3: Validation of the sea ice model
NERSC, NIERSC, NERC
Months 13-24Slide3
4 Tasks, 2 Deliverables
T5.4: Integration
NAVTOR, NERSC
Months 13-24
D5.1: Validation reports
NERSC
Month 24
D5.2:
Upgraded software
NavTracker
&
NavPlanner
to include waves-in-ice and ice forecasts
NAVTOR
Month 24Slide4
Total contributions from partnersSlide5
Task 5.1: Validation of remote sensing products
Validate independent satellite data from WP4 against each other and available in-situ data
.
SAR wave spectra (ODL)
n
ear MIZ: ice-free SAR wave spectra
f
ar MIZ: simple wave sensor (3-axis accelerometer) developed in SWARP (ready 2015
)
Other buoys
Ice
classification (MIZ area)
from
scatterometers
/radiometers (
Ifremer
)
Low resolution (25km)
from SAR/optical images (NIERSC
)
High resolutionSlide6
Generic
validation of wave parameters:
Altimeters (Hs & mss ): in ice-free water
Permanent buoys: general context (Iceland + Barents Sea )
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
a) wave parameters
Ardhuin
et al. 2010
Ardhuin
et al. 2010
(Prévimer)
rms error for Hs (%)
Task 5.2: Validation of the wave modelSlide7
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 modelSlide8
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)Slide9
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. Slide10
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)Slide11
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)Slide12
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 SIPEX2 expedition (Sep-Nov 2012):
Wave measurements (
Kohout
) and FSD/thickness observations (video by Toyota
)
Images/analysis from WP4Slide13
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.