Microwave Remote Sensing of Sea Ice
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1 Microwave Remote Sensing of Sea Ice What is Sea Ice? Passive Microwave Remote Sensing of Sea Ice Basics Sea Ice Concentration Active Microwave Remote Sensing of Sea Ice Basics Sea Ice Type Sea Ice Motion
2 Basics - I Elachi, C., Introduction to the Physics and Techniques of Remote Sensing, Wiley Series in Remote Sensing, John Wiley & Sons, New York, 1987.
3 Basics II: Planck 1 Plancks Law describes the spectral density of radiation emitted by a so-called blackbody with temperature T at frequency f. This law is valid for the entire frequency range. Spectral radiation (Blackbody spectral brightness) Frequency (Surface) Temperature of the emitting body Speed of light (in vacuum) Plancks constant Boltzmanns constant
4 Basics III: Planck 2 For low microwave frequencies Plancks Law can be simplified (Rayleight-Jeans Law) Taking into account: A blackbody is defined as an idealized, perfectly opaque material that absorbs electromagnetic energy at all frequencies while reflecting none the physical temperature of a blackbody T equals its brightness temperature T B which in the microwave frequency range is given by:
5 Basics IV: Planck 3 Grey bodies reflect electromagnetic energy at certain frequencies; accordingly absorption & emission can be Direction dependent Polarization dependent Consequently, in the microwave frequency range, the brightness temperature is smaller than the physical temperature & a function of the emissivity of the emitting body Emissivity Polarization Sensor incidence angle
6 Basics V: Emissivity 1 Via the relation: emissivity at frequency f the following relations can be obtained: for the emissivities at horizontal (h) and vertical (v) polarization and at incidence angle Θ. This applies for brightness temperatures, i.e. for measurements of the thermal emission of electromagnetic radiation in the microwave (and also infrared) frequency range.
7 Basics VI: Emissivity 2 Relation between reflection coefficients as a function of incidence angle & frequency and the complex dielectric constant (assuming specular reflection ) with:
8 Complex dielectric constant Allows to quantify emissive capabilities of & penetration depth of radiation into a material Can be regarded as frequency-dependent measure for the dielectric loss and/or the electric conductivity Rule-of-thumb: Basics VII: Emissivity 3 Dry materials and/or materials with low salinity & high porosity have a low dielectric constant, i.e. 1 (dry snow, multiyear ice) Wet/humid materials and/or material with a high salinity have a high dielectric constant, i.e. > 5 (wet snow, young sea ice)
9 Basics VIII Ulaby et al., Microwave Remote Sensing Active and Passive, Vol III, Artech House Inc., 1986.
10 Basics IX: Penetration Depth 1 Open water: few millimeters Sea ice: very variable & frequency, incidence angle and ice type dependend Firstyear ice, 5 GHz: 15 cm, 20 GHz: 3 cm Multiyear ice, 5 GHz: 35 cm, 20 GHz: 9 cm Much larger penetration depth for freshwater ice Snow may influence penetration depth Ulaby et al., Microwave Remote Sensing Active and Passive, Vol III, Artech House Inc., 1986.
11 Basics X: Penetration Depth 2 Much smaller for wet than for dry snow because of increasing electric loss: 5 GHz, 1%: 30 cm, 6%: 4 cm 18 GHz, 1%: 10 cm, 6%: <1cm Ulaby et al., Microwave Remote Sensing Active and Passive, Vol III, Artech House Inc., 1986.
12 Basics XI: More? Yes! Is this all? No! Surface roughness & internal roughness cause scattering Atmosphere causes attenuation, emission & scattering Ulaby et al., Microwave Remote Sensing Active and Passive, Vol I, Addison-Wesley Publishing Company, London, 1981.
13 Basics XII: Atmosphere 1 Gloersen et al., Arctic and Antarctic sea ice, Satellite passive microwave observations and analysis, NASA SP-511, NASA, Washington, D.C., 1992.
14 Basics XIII: Atmosphere 2 70K 21K 10K 85 GHz 37 GHz 19 GHz Ulaby et al., Microwave Remote Sensing Active and Passive, Vol I, Addison-Wesley Publishing Company, London, 1981 (modified).
15 Basics XIV: Atmosphere 3 Microwave brightness temperature change as a function of integrated water vapor content (x-axis) and cloud liquid water content (yaxis) as modeled for 85 GHz SSM/I Top) calm water surface with a surface emissivity of 0.5 Bottom) wind-roughened water surface with a surface emissivity of 0.73; this is equivalent to about 50% ice cover. Kern, S., Ph.D. Thesis, 2001
16 Basics XV: Sensors 1 Left) View of the Special Sensor Microwave / Imager (SSM/I), right) schematic view of its viewing geometry
17 Basics XV: Sensors 2 SSM/I f [GHz] H,V V H,V H,V Polarization Sampling [km] 43x69 40x50 29x37 13x15 FOV [km] Advanced Microwave Scanning Radiometer (AMSR-E) f [GHz] H,V H,V H,V V H,V H,V Polarization Sampling [km] 43x75 29x51 16x27 18x32 8x14 4x6 FOV [km]
18 Methods & Parameters - I Parameters to be derived: Sea Ice Concentration (areal fraction covered by sea ice) + Area + Extent Sea Ice Motion Sea Ice Type Snow depth on sea ice
19 Methods & Parameters - II Open water: High dielectric constants & high reflectivity low emissivity Sea ice (FY): Low dielectric constants & low reflectivity high emissivity. Microwave Remote Sensing of Sea Ice, edited by F.D. Carsey, American Geophysical Union (AGU) Monograph 68, pp 29-46, AGU, Washington D.C., 1992.
20 Methods & Parameters - III Different Methods Visible: 100% 0% v bright dark reflected sun light Infrared: Surface Temperature warm cold 0% 100% Microwave: 100% 0% warm cold Surface Temperature times emissivity
21 Methods & Parameters - IV T h (f)= 213 K C=? Ice: C=1 T h,i (f)= 250 K from in-situ observations from in-situ observations Water: T h,w (f)= C=0 150 K Fraction 0,68 Fraction 0,32 C=0.68 or 68% Basics: C: T p,i (f) & T p,w (f): T p (f): T p (f) = C T p,i (f) + (1 - C) T p,w (f) Partial sea ice concentration Typical brightness temperatures (Tie points) Observed brightness temperature
22 Methods & Parameters VI: Comiso 1 Algorithm 1 to calculate the total sea ice concentration from SSM/I 19 & 37 GHz data: Basic equation: C I : total ice concentration; T I & T O : tie points (as brightness temperature) of sea ice & open water; T B : actual brightness temperature. Bootstrap Technique (see next slight) frequency mode: 19 & 37 GHz data, same polarization polarization mode: h & v polarization, one frequency Equation for Bootstrap algorithm: I I O O
23 Methods & Parameters VII: Comiso 2 100% ice 80% ice 0% ice a) Scatterplot of brightness temperatures at 19 & 37GHz; b) Scheme of Bootstrap technique: line CD: open water, line BA: 100 % ice, T: actual brightness temperature pair; Coefficients a, b, α, and β: tie points. Gloersen et al., Arctic and Antarctic sea ice, Satellite passive microwave observations and analysis, NASA SP-511, NASA, Washington, D.C., (modified)
24 Methods & Parameters - V Open water: High dielectric constants & high reflectivity low emissivity Sea ice (FY): Low dielectric constants & low reflectivity high emissivity. Large (small) polarization difference for open water (sea ice) at this incidence angle (50 ) Microwave Remote Sensing of Sea Ice, edited by F.D. Carsey, American Geophysical Union (AGU) Monograph 68, pp 29-46, AGU, Washington D.C., 1992.
25 Methods & Parameters VIII: NASA-Team 1 Algorithm 2 to calculate the sea ice concentration (total and multiyear) from SSM/I 19 and 37 GHz data: Normalized brightness temperature polarization difference (also: polarization ratio) using 19 GHz data (carries main ice concentration information) Normalized brightness temperature frequency difference (also: gradient ratio) using 37 & 19 GHz data (carries ice type information: old ice & firstyear ice)
26 Methods & Parameters IX: NASA-Team 2 Fractions of first-year ice and multiyear ice can be written as linear combination of P and G as follows: Coefficients F, D, & M from in-situ measurements of P & G over 100% open water, firstyear ice and multiyear ice (tie points). Total ice concentration: Sum of these two fractions. Developed for SMMR, modified for SSM/I & AMSR-E. Southern Ocean: Ice types A & B rather than firstyear & multiyear ice.
27 Methods & Parameters X: NASA-Team 3 100% FY ice 100% MY ice Weather filter Schematic view of NASA Team algorithm tie point triangle: open water (OW), first-year (FY) and multiyear ice (MY). Gloersen et al., Arctic and Antarctic sea ice, Satellite passive microwave observations and analysis, NASA SP-511, NASA, Washington, D.C., (modified)
28 Methods & Parameters XI: Quality 1 Comiso and Steffen, Studies of Antarctic sea ice concentration from satellite data and their applications, J. Geophys. Res., 106(C12), 31,361-31,385, 2001.
29 Methods & Parameters XII: Quality 2 Comiso and Steffen, Studies of Antarctic sea ice concentration from satellite data and their applications, J. Geophys. Res., 106(C12), 31,361-31,385, 2001.
30 Methods & Parameters XIII: Quality 3 Far left: Broadband albedo (Operational Linescan System (OLS)); black boxes: location of boxes 1, 2, 3shown in middle & right. Middle left: Sea ice concentration derived from the OLS image. Right: SSM/I sea ice concentration using the NASA-Team (left image) & the COMISO-Bootstrap algorithm (right image). Comiso and Steffen, Studies of Antarctic sea ice concentration from satellite data and their applications, J. Geophys. Res., 106(C12), 31,361-31,385, 2001.
31 Methods & Parameters XIV: Quality 4 Above: Tiepoint triangle for NASA-Team algorithm Right: Impact of varying ice conditions (mixture of multi- and first-year ice) together with schematic tiepoint triangle (Fuhrhop et al., 1998, Fig. 4) Lower Layer Snow Grain Diameter: mm Upper Layer Snow Grain Diameter: mm Upper Layer Snow Density: g/cm³
32 Methods & Parameters XV: Quality 5 100% 80% 50% 20% Impact of varying atmospheric conditions for NASA-Team tiepoint triangle (Oelke, IJRS, 1997 (top right); Fuhrhop et al., TGRS, 1998 (bottom right)); L: clear sky but 10m/s wind speed. Values of GR > 0.05 are typically flagged: C < 15% Snow cloud: kg/m² Water vapor + cloud: kg/m², kg/m² Wind speed: 0 25 m/s
33 End of second part!
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