Progress of operational processing chain for sea ice albedo and melt pond

fractionL. Istomina, G. Heygster

Contents

1.Validation datasets

2.Processing chain extension

3.Surface discrimination

4.Improvement of MODIS cloud mask over snow

1. CASIE (2009, Ny Alesund, aerial)

2. Polashenski & Perovich (2008-2010, Chukchi sea, in situ & aerial)

3. HOTRAX (2005, transpolar. ship, helicopter) http://www.arcticice.org/hotraxweb/index.htm

4. MELTEX (2008, Beaufort sea, aerial)

5. ICESCAPE (2010, 2011, Beaufort & Chukchi sea, ship)

1. Validation datasets

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1. CASIE

Flights from Ny-Ålesund • 1. Determine the degree to which ice-roughness

monitoring via remote sensing can detect basic changes in ice conditions such as ice thickness and ice age.

• 2. Investigate relationships between ice roughness and factors affecting the loss or maintenance of the perennial ice cover.

• 3. Determine how roughness varies as a function of different kinematic conditions and ice properties.

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CASIESeveral thousand photographs

Geolocation needs to be done

No explicit cloud record

Test for SIERRA aircraft and payload

Many more instruments:

• Nadir Spectrometer (FOV ~ 1 Degree, 4K Channels, 300nm – 1000nm)

• Zenith Spectrometer (FOV ~ 180° 3K Channels, 300nm– 1000nm)• Nadir Pyranometer (FOV ~ 180)• Zenith Pyranometer (FOV ~ 180)• 2 Nadir Pyrometers (FOV ~ 1)

• CT-08.K6• CT-08,85 (Haze Filtered)

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SIERRA Aircraft Payloads

• Image: Courtesy U Alaska

-44.699

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2. Polashenski & Perovich 2008-2011, Chukchi Sea

• ~ 6 locations, 20 days, pure surface types • Spectral and integrated albedo• Surface type• Photo

• Transect each 5 m along 200 m • Spectral and

integrated albedo• Surface description

• Snow/pond depth

PhD thesis C. Polashenski• Photos: Chris Petrich

2. Polashenski & Perovich 2008-2011, Chukchi Sea

PhD thesis C. Polashenski

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3.-5. HOTRAX, MELTEX, ICESCAPE

• PhD thesis C. Polashenski

3. HOTRAX (2005, transpolar. ship, helicopter) http://www.arcticice.org/hotraxweb/index.htm

4. MELTEX (2008, Beaufort sea, aerial)

5. ICESCAPE (2010, 2011, Beaufort & Chukchi sea, ship)

• MELTEX and HOTRAX:• Melt ponds derived from

satellite data (Rösel, Kaleschke, Birnbaum 2011)

Rösel, Kaleschke, Birnbaum 2011

2. Processing chain extension

Left: MODIS RGB, Beaufort sea, 27 Jun 2009. very melted conditions, according to Polashenski. Right: SGSP snow albedo retrieval cannot retrieve albedo over such surfaces.

Processing chain has been extended to accommodate one more map type – “ice albedo”.Currently the retrieval algorithm is the averaging of MODIS reflectance of 3 visible bands (1,2,3). Can be easily substituted with a more accurate retrieval when available. The processing to achieve melt pond fraction product is going to be constructed in a similar way.

3. Surface discrimination

Left: Spectral albedo of various snow and ice surfaces (Grenfell, Perovich, 2004). Vertical lines show MODIS bands useful for surface discrimination.Right: Ratio of MODIS bands 5 and 4 is able to indicate melted areas.

4. Cloud mask improvement

Left: RGB image of a scene in Beaufort sea May, 3rd, 2009.Right: Cloud screened albedo product is visibly contaminated with clouds. In some cases, MODIS cloud mask over snow might be improved.

Left: Standard cirrus tests use different emissivity of ice crystals at 10.8 and 12 μm, but over snow this does not work as surface has same features.Right: 10.8-12 μm BT difference related to 12 μm BT. Thin clouds over snow and snow are not possible to discriminate.

MODIS cloud mask over snow includes VIS (660nm) and H2O(1.38, 6.7μm) thresholds as tests for clouds (also high, Ci). Two BT differences, 11 μm with 13.3 μm(CO2) and 6.7μm are used for inversions. BT(11μm – 3.9μm) threshold is tuned for dense clouds, but has the potential to work based on reflectance part, not BT!

from Hori et al, 2006 Khlopenkov et al, 2006

Left: 550nm (x-axis) and 1.6 μm (y-axis) also cannot provide reliable snow-cirrus discrimination.Solution: Use 3.7 μm BT combined with BT (12 μm) to calculate atmospheric reflectance at 3.7 μm according to Allen 1989, Spangenberg 2001. This approach is used to retrieve coarse mode of aerosol over snow (Istomina et al., 2011) and has the potential to detect also thin cirrus and water clouds which have too little density to be seen in BT (12 μm).

Khlopenkov et al, 2006

Gao et al, 1998