In order to accurately estimate polar air/sea fluxes, sea ice drift and then ocean circulation, global ocean models should make use of ice edge, sea ice.

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Presentation transcript:

In order to accurately estimate polar air/sea fluxes, sea ice drift and then ocean circulation, global ocean models should make use of ice edge, sea ice concentration and sea ice motion data. Ifremer/CERSAT provides daily remote-sensed ice parameters from radiometers and scatterometers. An improved Merged QuikSCAT/SSMI (and also ASCAT/SSMI) drift product is available, this product not only improves the data density but it also widens the time period when satellite data can be used, thus reducing the summer data gap. Ifremer/CERSAT provides a unique database of 17 winter time series of sea ice drift data. These products are validated with in situ data and they are easily available. These routinely produced concentrations and drifts data are used for assimilation in models, in particular in FOAM and TOPAZ and Mercator-Ocean operational systems. AMSR-E derived drifts are also available from Ifremer/CERSAT. They are more accurate than Merged drifts for small displacements because of the enhanced ground resolution of the sensor. They are not presently used in global models because of scattered patches of missing drift and present less drift data density, in particular for early fall and early spring. They should be used for regional studies. Conclusion IFREMER/CERSAT products available atftp://ftp.ifremer.fr/ifremer/cersat/products/gridded/psi-drift/ ftp://ftp.ifremer.fr/ifremer/cersat/products/gridded/psi-concentration/and Introduction The Arctic and its sea ice coverage are considered as sensitive indicators of climate change. Moreover, this region plays a key role in many processes impacting European climate. There is therefore a requirement to regularly monitor this remote area from space. Satellite data provides daily and global sea ice parameters such as sea ice concentration, extent, type and drift. These data can be used to improve numerical models of the sea ice – ocean – climate system. The geophysical parameters presented here are sea ice concentration, extent and drift routinely inferred from radiometers and scatterometer data at Ifremer/CERSAT. Ice type is not an operational product and it is not presented here. These geophysical parameters have been tested for assimilation in sea-ice model (LIM), sea-ice-ocean model (FOAM), TOPAZ and Mercator-Ocean operational systems. A new dataset of interpolated drift, presented here, would be very useful for models. localisation of ice ridges/polynias localisation of the Marginal Ice Zone drift concentration extent type estimation of air/sea fluxes numerical models of climate evolution numerical models of ocean circulationestimation of the salinity gradient SEA ICE SATELLITE DATA FOR MODELS Fanny GIRARD-ARDHUIN, Denis CROIZE-FILLON IFREMER, LOS/CERSAT, BP 70, Plouzané, France Special Sensor Microwave Imager (SSM/I) radiometer Sea ice concentration and extent Arctic and Antarctic sea ice concentration from SSM/I. Arctic monthly concentration (March 2007). Antarctic daily concentration (Sept. 15 th 2007). from NSIDC daily maps of brightness temperature using ASI algorithm (IUP Brëmen) Pixel resolution : 12,5 km Since 1992 Daily, monthly + climatology Blind area of 254 km radius Sensitive to relative humidity and atmospheric conditions concentration = percentage of the surface covered by sea ice extent = area where concentration is higher than 15% Merged product Validation of the Merged fields over 5 winters (IABP buoys) : variance difference (drift 3 day lag) = km 2, of which km 2 are related to pixel size (δ²/6) SeaWinds/QuikSCAT scatterometer Special Sensor Microwave Imager (SSM/I) radiometer + IFREMER algorithm from NASA from NSIDC 3 day-lag 6 day-lag 30 days Global scale Merged sea ice drift Merged sea ice drift at 6 day-lag (April 25– 1 st May, 2007). Drift vectors less than one pixel are marked with a cross. Identical drift for SSM/I H and V polarizations and QuikSCAT. Identical drift for 2 channels. Selection or validation of any sample. Density of valid data for a winter ( ). SSM/I 85 GHz H polarization. SSM/I 85 GHz V polarization. QuikSCAT. Merged product. SSM/I 85 GHz H SSM/I 85 GHz V QuikSCAT Merged drift data Better data density for the Merged Increases the number of valid vectors and the time window (fall and spring) New datasets : missing values filled Merged sea ice drift Monthly filled merged sea ice drift (right) compared with the merged sea ice drift (left). October day-lag 30 day-lag Increases the number of data in particular in October, worst period of estimation Drift data density for the monthly drift product ( ). Merged drift. Filled Merged product. Merged drift has a better data density since 1999 (QuikSCAT data with SSM/I) Better data density for the interpolated dataset (about 80% data density) Pixel resolution of initial data : 12,5 km Drift grid spacing: 62,5 km Daily except melt season QuikSCAT since 1999/ASCAT since 2007 SSM/I since 1992 Arctic sea ice drift combining AMSR-E H and V polarizations for 3 day-lag (April 24 th - April 27 th 2007). Drift vectors less than one pixel are marked with a cross. Identical drift for H & V polarizations. Selection of one channel. variance difference (drift 3 day lag) = km 2, of which km 2 are related to pixel size Advanced Microwave Scanning Radiometer (AMSR-E) Validation over a winter (IABP buoys) : to be mainly used for regional models Drift data density for a winter ( ) for AMSR-E drift and Merged drift. produced by IUP Brëmen using JAXA data IFREMER algorithm 2 day-lag 3 day-lag 6 day-lag Regional sea ice drift Pixel resolution of initial data : 6,25 km Drift grid spacing : 31,25 km Daily except melt season Since 2002 Blind area (84 km radius) Sensitive to relative humidity and atmospheric conditions Less data density compared with Merged product More data gap patches But useful for 2 day drift estimation (low drift) Now replaced by ASCAT Continuity with ASCAT/MetOp data