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Remko Scharroo Altimetrics LLC, Cornish, NH

Global and regional sea level change from multi-satellite altimeter data. Remko Scharroo Altimetrics LLC, Cornish, NH Laury Miller NOAA Laboratory for Satellite Altimetry, Silver Spring, MD Andy Ridout and Seymour Laxon Centre for Polar Observation & Modelling, University College London, UK.

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Remko Scharroo Altimetrics LLC, Cornish, NH

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  1. Global and regional sea level change from multi-satellite altimeter data Remko ScharrooAltimetrics LLC, Cornish, NH Laury MillerNOAA Laboratory for Satellite Altimetry, Silver Spring, MD Andy Ridout and Seymour LaxonCentre for Polar Observation & Modelling, University College London, UK

  2. Sea level change measurements • Tide gauges • Long record: up to 150 years • Poor global sampling: mainly close to land (especially gauges with long-term records) • Affected by subsidence and GIA (post-glacial rebound) • Altimetry • 13 year quality record • Near global sampling (inclination and ice cover) • Marginally affected by GIA • Influenced by reference frame due to orbit • Hard to maintain stability at sub-mm/year level

  3. Consistent? 0.7±1.5 1.5±0.5 Sea level change budget (1910-1990) • IPCC 2001

  4. ! ! ! Multi-Satellite Data Set

  5. Sea Level Change Database • GSLR Database: Step 1 • Edit data for quality, using limits on SLA, SWH, SWH, etc. • Combine data per “cycle” per 1x1 degree cell • Keep ascending and descending separate • Store average latitude, longitude, SLA, dry tropo, wet tropo, etc., per cell • This significantly reduces the size of the database, facilitating research • TX, J1: 9.92 days • GFO: 8.54 days • E1/E2/N1: 7.75 days Means of: • lat, lon • SLA • dry tropo • wet tropo • iono • inv baro • ....

  6. t in years since 2000 Creating Time Series • Determine global average per “cycle” • Use all averaged points i • Weight by the original number of points in cell i • Weight by latitude • Remove occasional outlier cycle from database 3-monthboxcar

  7. Data Weighting

  8. t in years since 2000 Merging Time Series • Estimate offset per satellite • Single trend and annual cycle

  9. Merged Time Series • Global sea level trend: 3.20 mm/year • Time series match extremely well

  10. Merged Time Series • Common annual signal (4.77 mm amplitude) removed • All time series within 8 mm from each other

  11. Estimating Local Sea Level Trends • 5-Parameter fit • a = offset for ascending • d = offset for descending • Absorbs geographically correlated errors • Setup normal equations • All “cycles”, each cell • Spread normal equations • Gaussian σ = 1º • Smoothes results • Allows results in rarified areas

  12. Local Sea Level Change • Jason-1 Cycle 26-137 (Sep 2002 – Oct 2005) • Period coincides with TOPEX Phase B • Inconsistent picture; very large extremes • Is Jason-1 to blame? Or is period too short? Jason-1 TOPEX

  13. Local Sea Level Change • ERS-2 Cycle 0-76 (Apr 1995 – Aug 2002) • Rather consistent picture, despite relatively short period • Large extremes, particularly in Kuroshio • Is ERS-2 to blame? Or is period too short? ERS-2 TOPEX

  14. Local Sea Level Change • ERS-1/2, Envisat (Sep 1992 – Feb 2006) • Very consistent features • All latitudes show sea level rise, except around 45ºN • Sea level drop confined to N-Indian Ocean, Kuroshio, Gulfstream E1/E2/N1 TX/J1

  15. Local Sea Level Change • ERS-1/2, TOPEX, GFO, Jason-1 and Envisat(Apr 1992 – Feb 2006) • Very consistent features • All latitudes show sea level rise, except around 45ºN • Sea level drop confined to N-Indian Ocean, Kuroshio, Gulfstream

  16. Annual cycle: Amplitude and phase

  17. IB Annual cycle: Amplitude and phase • Direct impact of IB on annual cycle • Annual cycle in IB is significant (7 mm amplitude) • Reduces annual cycle, particularly in North Pacific

  18. IB Mean • Indirect impact of IB on annual cycle • Extremely large mean near Antarctica (~30 cm) • Becomes more prominent in Austral Summer when sea ice retreats and more ocean altimetry is available • Not applying IB introduces fake annual cycle in global MSL

  19. IB Rate of change • No impact of significance on sea level change rate • Only 0.08 mm/year • No regional effects

  20. Creating an Arctic Ocean data set • Specular echoes • Originate from leads and thin new ice • Separated from diffuse and complex echoes • OCOG retracking (Peacock, Laxon, Ridout) Specular Complex Diffuse

  21. SSB for Arctic data set • OCOG retracker does not provide wave height • Use backscatter as proxy for wave height • Determine SSB as difference between sea heights from OPR and OCOG retracker • Reasonably good fit for SWH < 6 m

  22. Arctic Sea level change • Good comparison between OPR and OCOG in permanently open region • Unique results in ice covered regions • Sea level drop of ~2 mm/year OPR OCOG

  23. Arctic sea level: Annual signal • High amplitude signals in some coastal regions • High in late September (minimum ice cover) Amp Phase

  24. Conclusions • Global multi-satellite sea level change • Rate over last 14 years is about 3.2 mm/yr • Clear regional differences in rates • Difference decrease when lengthening period • Is this decadal variability? • However, some systematic variations remain • IB should be considered properly • Arctic sea level change from ERS-2 • Specular data retracked • Much better coverage than OPR data • Arctic sea level drops by 2 mm/yr

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