Student lead paper discussion #1

1. Student lead paper discussion #1 David Prado Oct. 8 2012

2. Paper 1 Antarctic Sea Ice: 1972-1975 John N. Rayner and David A. Howarth 1979

3. Research Objective(s) - ?

4. Research Objective(s) • The use of Nimbus V (launch Dec. 11, 1972) to determine sea ice extent and variability. Important because Nimbus V is the first continuous monitoring polar orbiting satellite.

5. Methods - ?

6. Methods • Determine Minimum latitude/highest ice extent (MINL) and Maximum latitude/lowest extent (MAXL). • Based on 155K brightness isotherm (NASA measurements used to validate) is assumed to be 15% sea ice concentration. • 15.5 mm emissivity values: • Old ice – 0.8 • First year ice – 0.95 • Sea water – 0.4 • All results are based on the extremes (Feb and Sept).

8. Results/Conclusions - ?

9. Results/Conclusions • Based changes on a harmonic wave fit to the data (average outer boundary at 63.75o S yielding approximately 12.5 million km2). • First harmonic fits 70% of the winter change in sea ice.

10. > 70% of variance

11. Results/Conclusions • Based changes on a harmonic wave fit to the data (average outer boundary at 63.75o S yielding approximately 12.5 million km2). • First harmonic fits 70% of the winter change in sea ice. • Smooth varying of MAXL at 68o to 69o S and MINL at 60o S. • Found pack ice to vary from ~3 to ~20 million km2.

12. Results/Conclusions – con’t. • Transition from cold temperature (ice growth) to warm temperature (ice loss) is asymmetrical which is attributed to polynyas. • Very rapid ice edge retreat when polynyas form (up to 330 km/day). • MINL is reached at different times (clockwise pattern around pole). • General trends expected to be persistent from year to year (i.e., asymmetrical grow/decay cycle).

19. Paper 2 ICESat measurements of sea ice freeboard and estimates of sea ice thickness in the Weddell Sea Zwally, H.J., Yi, D., Kwok, R., and Zhao, Y. 2008

20. Research Objective(s) - ?

21. Research Objective(s) • Determine F (freeboard – total surface elevation above local sea level) from ICESat measurements.

23. Research Objective(s) • Determine F (freeboard – total surface elevation above local sea level) from ICESat measurements. • Estimate sea ice thickness from F, densities (snow, water, sea ice), and snow depth (AMSR-E). • Compare distribution and velocity (AMSR-E) of sea ice for spatial/temporal patterns.

24. Methods - ?

25. Methods • Compute local sea level from ICESat. • 20 km running average along track.

27. Methods • Compute local sea level from ICESat. • 20 km running average along track. • Compare local sea level areas (minimum elevations) to Envisat images.

29. Methods • Compute local sea level from ICESat. • 20 km running average along track. • Compare local sea level areas (minimum elevations) to Envisat images. • Calculate Freeboard (surface elevation about local sea level) for ICESat track. • Determine sea ice thickness based on density equation.

30. Pw= 1023.9 kg m-3 Ps = 300 kg m-3 PI = 915.1 kg m-3 F = Freeboard height Ts = Snow depth TI = Ice thickness

31. Methods • Compute local sea level from ICESat. • 20 km running average along track. • Compare local sea level areas (minimum elevations) to Envisat images. • Calculate Freeboard (surface elevation about local sea level) for ICESat track. • Determine sea ice thickness based on density equation. • Create snow/ice property maps and histograms.

32. Results/Conclusions - ?

33. Results/Conclusions • Freeboard distribution shows similar pattern to sea ice thickness distribution (modified by snow depth). • Very limited observations

35. Results/Conclusions • Freeboard distribution shows similar pattern to sea ice thickness distribution (modified by snow depth). • Very limited observations • Thickness estimates show similar results to previous field observations in May-June but are less than field measurements in Oct-Nov.

37. Results/Conclusions • Freeboard distribution shows similar pattern to sea ice thickness distribution (modified by snow depth). • Very limited observations • Thickness estimates show similar results to previous field observations in May-June but are less than field measurements in Oct-Nov. • Estimated deviation from geoid (EGM 96) showed a similar patterns for different years and seasons. • Attribute deviation to uncertainties in static geoid.

39. Results/Conclusions – con’t. • AMSR-E derived sea ice motion shows clockwise rotation during the study time period. • This causes a “piling up” of thicker sea ice along the southern portion of the Antarctic Peninsula which is observed in all four periods. • Thicker ice in the northern Weddell sea is multi-year ice being pushed away from the Peninsula by the clockwise movement.

41. Sources of ERROR - ?

42. Sources of ERROR • Laser echo energy reduction by clouds.

44. Sources of ERROR • Laser echo energy reduction by clouds. • Averaging over footprint (70m). • Ocean swell effects on pack ice field. • Snow properties (dielectric constant/density).

45. Take home message • Satellite sensors from 1972/1975 to 2004/2005 • Nimbus V (ESMR) • Spatial resolution: 28.05 km (50o s) to 31.5 km (pole) • Spectral resolution: 19.225 to 19.457 GHz • ICESat (GLAS) • Spatial resolution: 70 m footprint 172 m along track spacing • Vertical error: 2 cm

46. Take home message – con’t. • Satellites have become highly specialized with improved precision. • Nimbus V was the first satellite to allow for study of Antarctic sea ice with near daily resolution. • Rayner and Howarth described general patterns and trends in the distribution of sea ice both spatially and temporally and calculated maximum and minimum sea ice area. • Zwally et al. demonstrated the ability of ICESat (laser altimeter) to estimate freeboard and sea ice thickness on a year round scale with greatly improved spatial coverage.