1. GHRSST HL_TAG meeting Copenhagen, March 2010 Validation of L2P products in the Arctic Motivation: Consistent inter-satellite validation of L2p SST observations have been lacking for high latitudes. Validation of 7 satellite products for high latitudes Open ocean Close to ice CASSTA algorithm performance

2. GHRSST HL_TAG meeting Copenhagen, March 2010 In situ observations Drifting buoys obtained from Coriolis Daily data in netcdf, Atlantic/Pacific/Indian basins Gross error quality control Checked against climatology

3. GHRSST HL_TAG meeting Copenhagen, March 2010 Satellite Observations SensorSatelliteResolution AATSRENVISAT1 km AVHRR SAF NARNOAA 17+182 km AVHRR (NAVO GAC)NOAA 184 km AVHRRMETOP_A1 km ModisAqua1 km ModisTerra1 km AMSR-EAqua25 km O&SI-SAF and GHRSST L2P products Single Sensor Error Specific biases has been applied All observations have been converted to subskin SST (adding 0.2 for AATSR and MODIS)

4. GHRSST HL_TAG meeting Copenhagen, March 2010 High Latitude L2P validation Validation procedure Run every night creating a simple matchup database Additional quality control on in situ data Climatology check against Pathfinder 4 km nighttime monthly Redundancy check No use of blacklist at the moment – will come Matchups Within 4 hours and 15 km Separate quality levels 3, 4 and 5 Distance to ice edge from OSI SAF ice edge product

5. GHRSST HL_TAG meeting Copenhagen, March 2010 Level 2 Validation results, overall bias Data from November 2009 to March 2010 Spatial matchup window: 15 km, temporal = 2 hours Modis data from sst4 algorithm, only one month Red = quality flag 3 Blue = quality flag 4 Green = quality flag 5 Metop_A matchups

6. GHRSST HL_TAG meeting Copenhagen, March 2010 Level 2 Validation results, overall stddev Red = quality flag 3 Blue = quality flag 4 Green = quality flag 5 Number of Matchups

7. GHRSST HL_TAG meeting Copenhagen, March 2010 Validation statistics as a function of distance How does the matchup distance influence the error statistics ?

8. GHRSST HL_TAG meeting Copenhagen, March 2010 Scatter plots Only best quality flags shown. Significantly different error characteristics for the different products Metop_AAMSR-E SAF-NARModis-TModis-A NAVO-G AATSR

9. GHRSST HL_TAG meeting Copenhagen, March 2010 Temporal correlation of errors Daily mean biases computed for Nordic Seas (sat-in situ ) 106 days Metop-A and AMSR-E Temporal autocorrelation computed Temporal scales of errors 4-7 days for AMSR-E < 1 day for METOP_A

10. GHRSST HL_TAG meeting Copenhagen, March 2010 L2 Validation results, temporal validation 5 days averages, using data +-5 days Large difference between products Temporal changes in mean bias relatively constant Temporal variation in AMSR-E bias Metop-A very stable in time

11. GHRSST HL_TAG meeting Copenhagen, March 2010 L2 Validation results, spatial validation Metop_A Navo-GAC AMSR-E SAF-NAR Bias Std

12. GHRSST HL_TAG meeting Copenhagen, March 2010 Level 2 Validation, ice effects OSI-SAF edge product used to calculate matchup distance from ice Modis contaminated, No matchups north of 80 deg N Several products have a warm bias close to the ice edge (as expected with overcompensating) Validation points within 150 km from ice edge

13. GHRSST HL_TAG meeting Copenhagen, March 2010 Composite Arctic SST algorithm (CASSTA) CASSTA was developed by Víncent et al., 2008 (see Gorms talk) 3 regions with different algorithms (North Open Water Polynya) –Open ocean –Transition zone –Ice Different algorithms classified by the T4 Vincent, et al.,(2008), Arctic waters and marginal ice zones: A composite Arctic sea surface temperature algorithm using satellite thermal data, J. Geophys. Res., 113, C04021, doi:10.1029/2007JC004353. CASSTA, McClain and IST algorithm (from Vincent et al., 2008)

14. GHRSST HL_TAG meeting Copenhagen, March 2010 Arctic L2 SST –Validate and Update CASSTA coefficients, compare with the NLSST algorithm –Coefficient derived for NOAA 12 –Use the existing L2 monitoring setup to validate Metop CASSTA –CASSTA ocean algorithm shows to cold in comparison with Metop_A L2P –Longer timeseries needed to validate MIZ algorithm performance Cassta Ocean alg Cassta MIZ algMetop L2P SST

15. GHRSST HL_TAG meeting Copenhagen, March 2010 DMI plans of more in situ obs –DMI talked with Ian Robinson and Fred Wimmer about buying an ISAR for the high latitude validations (SST and IST) –Has to be tested this autumn in freezing conditions –Several projects in the high Arctic related to Ice surface temperatures and Marginal Ice zones. –Icebreaker cruise on 2011. –Floating ice mass balance buoys with thermistor chains with 4 cm interval will be put out by SAMS and DMI in the multiyear ice.

16. GHRSST HL_TAG meeting Copenhagen, March 2010 Conclusion The DMI processing system validates 7 L2P satellite products against independent drifting buoy obs. Validation system performs quality control on in situ data, but do not use blacklists at the moment The general statistics shows enhanced errors in the Arctic Ocean compared to lower latitudes open ocean Metop_A performs very well, Modis and AMSR-E data should be used with care High latitude issues: –Very important to know validation statistics before using the data –Enhanced satellite errors close to ice edge Results based upon 3 winter month, error stats will probably change with warmer weather

17. GHRSST HL_TAG meeting Copenhagen, March 2010 L2 Validation, Latitudinal validation Statistics binned for every 2.5 degrees AMSRE, Metop and NAVO – GAC show little variation with latitude Modis Aqua/Terra and AATSR show some latitudinal variation