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

Progress of operational processing chain for sea ice albedo and melt pond fraction. L. Istomina, G. Heygster. Contents. Validation datasets Processing chain extension Surface discrimination Improvement of MODIS cloud mask over snow. 1. Validation datasets.

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

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  1. Progress of operational processing chain for sea ice albedo and melt pond fraction L. Istomina, G. Heygster

  2. Contents • Validation datasets • Processing chain extension • Surface discrimination • Improvement of MODIS cloud mask over snow

  3. 1. Validation datasets • CASIE (2009, Ny Alesund, aerial) • Polashenski & Perovich (2008-2010, Chukchi sea, in situ & aerial) • 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)

  4. 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.

  5. CASIE Several 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)

  6. SIERRA Aircraft Payloads -44.699 • Image: Courtesy U Alaska

  7. 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

  8. 2. Polashenski & Perovich 2008-2011, Chukchi Sea PhD thesis C. Polashenski

  9. 3.-5. HOTRAX, MELTEX, ICESCAPE • 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) • PhD thesis C. Polashenski Rösel, Kaleschke, Birnbaum 2011

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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, 11μm with 13.3 μm(CO2) and 6.7μmare 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: 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.

  15. Khlopenkov et al, 2006 Gao et al, 1998 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 μmaccording to Allen 1989, Spangenberg2001. 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).

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