student lead paper discussion #1
DESCRIPTION
Student lead paper discussion #1. David Prado Oct. 8 2012. Paper 1. Antarctic Sea Ice: 1972-1975 John N. Rayner and David A. Howarth 1979. Research Objective(s ) - ?. Research Objective(s). The use of Nimbus V (launch Dec. 11, 1972) to determine sea ice extent and variability. - PowerPoint PPT PresentationTRANSCRIPT
Student lead paper discussion #1
David PradoOct. 8 2012
Antarctic Sea Ice: 1972-1975John N. Rayner and David A. Howarth1979
Paper 1
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.
Research Objective(s)
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).
Methods
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.
Results/Conclusions
> 70% of variance
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.
Results/Conclusions
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).
Results/Conclusions – con’t.
ICESat measurements of sea ice freeboard and estimates of sea ice thickness in the Weddell SeaZwally, H.J., Yi, D., Kwok, R., and Zhao, Y.2008
Paper 2
Research Objective(s) - ?
Determine F (freeboard – total surface elevation above local sea level) from ICESat measurements.
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.
Research Objective(s)
Methods - ?
Compute local sea level from ICESat.◦ 20 km running average along track.
Methods
Compute local sea level from ICESat.◦ 20 km running average along track.
Compare local sea level areas (minimum elevations) to Envisat images.
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.
Methods
Pw = 1023.9 kg m-3 Ps = 300 kg m-3
PI = 915.1 kg m-3
F = Freeboard heightTs = Snow depthTI = Ice thickness
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.
Methods
Results/Conclusions - ?
Freeboard distribution shows similar pattern to sea ice thickness distribution (modified by snow depth).◦ Very limited observations
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.
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.
Results/Conclusions
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.
Results/Conclusions – con’t.
Sources of ERROR - ?
Laser echo energy reduction by clouds.
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).
Sources of ERROR
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
Take home message
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.
Take home message – con’t.