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Arctic SST Algorithms

Arctic SST Algorithms. Validation of 6 operational SST products in Arctic High latitude algorithm developments (CCI round robin ) Validation of CCI products Conclusions /Challenges F uture work. Arctic conditions. Arctic Ocean is a challenging region for SST:

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Arctic SST Algorithms

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  1. Arctic SST Algorithms • Validation of 6 operational SST products in Arctic • High latitudealgorithmdevelopments (CCI roundrobin) • Validation of CCI products • Conclusions/Challenges • Future work

  2. Arctic conditions • Arctic Ocean is a challenging region for SST: • Persistent cloudiness • Sea Ice • Complex atmosphere • Few in situ data • Extended periods with twilight, day and night only • -> These issues make SST retrievals challenging

  3. Validation of operational products

  4. In situ coverage • Majority of validationresults from Nordic Seas and Barentssea • I.e. Validationresults NOT representative of innerArctic • In situcoverage from Høyer et al, 2012

  5. Validation results • 6 operational products • Solar elevation angles with AATSR, Metop-A and AMSR-E

  6. High latitude algorithms within CCI

  7. Regional vs global coefficients, Arctic Ocean • Daytime : NLSST • Nighttime: SST_3.7 • Sensors: NOAA 17, 18, 19 and Metop-A (2006-2010) • Results from independent test data set. • NOAA-19 has much fewer match-ups than others. • Largest improvements for daytime algorithms • Reduced regional bias in most cases compared to global algorithms

  8. Atmospheric temperature effects • Arctic Ocean • Much more temperature inversions in Arctic compared to Southern Ocean. • Tinv = (Tair_900 – Tair_surf) correlated with SST error • Southern Ocean

  9. Atmospheric profiles • High variability in Arctic associated with anomalous atmospheric profiles, not the case in the Southern Ocean • Both for negative and positive outliers Good (blue) : < -+0.5*RMS Bad (red) : > -+2*RMS Tair_900 - Tair_surf

  10. CCI product validation for high latitudes

  11. High latitude validation results • L2 and L3U products validated • Arctic > 60 deg N • Southern Ocean < 50 deg S • Limited data available for several sensors Spatial coverage, AVHRR-12 + 17 Number of Match-ups

  12. Overall results • Satellite – in situ • Median and stddev • Generally small biases • Significant negative bias for AVHRR 18 • Larger stddev in Arctic than Southern Ocean Timeline of match-ups

  13. Solar zenith angle dependency • AATSR dependence upon water vapour and solar zenith angle • Cold summer bias for AVHRRs

  14. TCWV dependency • AATSR dependence upon water vapour and solar zenith angle • Cold summer bias for AVHRRs

  15. Summary/Challenges • SST products (AATSR, AVHRRs and AMSR-E) have in general larger errors in the Arctic, compared to Global and Southern Ocean performance • Biases generally depend upon Solar Zenith angle and TCWV • AVHRR biases found in operational products as well as ESA CCI products • Regional AVHRR coefficients can improve biases, largest improvements in daytime algorithms. • Limited in ”reference” situ observations in inner Arctic • Arctic NWP profiles with ”large SST errors” are more humid and warmer than profiles from ”low SST errors”

  16. Future work • Continue the validation and errorcharacterisation of Arctic SST products. • Write up the paper on CCI highlatitudealgorithms • Collect in situ data set for highArcticvalidation • Look for alternative SST products: • Develop MW OE Sea Ice and SST processor for AMSR-E and AMSR2 • Develop and validateMetop-A SST + IST product

  17. High latitude DMI-ISAR deployments • 7 week deployed at ODEN icebreaker • Autonomous deployment July-November 2013 • Planned • Activ circumpolar expedition (2014, 2015) • RAL line, Denmark-Greenland

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