Microwave Remote Sensing of Sea Ice - UTSA€¦ · Ulaby et al., Microwave Remote Sensing –...

Microwave Remote Sensing of Sea Ice, October 25, 2010, San Antonio, Texas, USAStefan Kern, KlimaCampus / CliSAP, University of Hamburg, Hamburg, Germany

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


Elachi, C., Introduction to the Physics and Techniques of Remote Sensing, Wiley Series in Remote Sensing, John Wiley & Sons, New York , 1987.

Basics - I


Plancks‘ Law describes the spectral density of radiationemitted by a so-called blackbody with temperature T at frequency f. This law is valid for the entire frequencyrange.

Spectral radiation (Blackbody spectral brightness)Frequency(Surface) Temperature of the emitting bodySpeed of light (in vacuum)Plancks‘ constantBoltzmanns‘ constant

Basics – II: Planck 1


For low microwave frequencies Plancks‘ Law can besimplified (Rayleight-Jeans Law)

Taking into account:

„A blackbody is defined as an idealized, perfectlyopaque material that absorbs electromagnetic energy at all frequencies while reflecting none“

the physical temperature of a blackbody T equals itsbrightness temperature TB which in the microwavefrequency range is given by:

Basics – III: Planck 2


Grey bodies reflect electromagnetic energy at certainfrequencies; accordingly absorption & emission can be

• Direction dependent

• Polarization dependent

Consequently, in the microwave frequency range, thebrightness temperature is smaller than the physicaltemperature & a function of the emissivity of theemitting body

Emissivity

Polarization

Sensor incidence angle

Basics – IV: Planck 3


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. formeasurements of the thermal emission of electromagnetic radiation in the microwave (and also infrared) frequency range.

Basics – V: Emissivity 1


Relation between reflection coefficients as a functionof incidence angle & frequency and the complexdielectric constant (assuming specular reflection …)

with:

Basics – VI: Emissivity 2


Complex dielectric constant

Allows to quantify emissive capabilities of & penetrati ondepth of radiation into a material

Can be regarded as frequency-dependent measure forthe dielectric loss and/or the electric conductivity

Rule-of-thumb:

• 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 (wetsnow, young sea ice)

Basics – VII: Emissivity 3


Ulaby et al., Microwave Remote Sensing – Active and P assive, Vol III, Artech House Inc., 1986.

Basics – VIII


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 penetrationdepth for freshwater ice

Snow may influencepenetration depth


Basics – IX: Penetration Depth 1


Much smaller for wetthan for dry snowbecause of increa-sing electric loss:

5 GHz, 1%: 30 cm, 6%: 4 cm

18 GHz, 1%: 10 cm, 6%: <1cm


Basics – X: Penetration Depth 2


Ulaby et al., Microwave Remote Sensing – Active and P assive, Vol I, Addison-Wesley Publishing Company, London, 1981.

Is this all?

No!

Surface roughness & “internal” roughness cause scattering

Atmosphere causes attenuation, emission & scattering

Basics – XI: More? … Yes!


Gloersen et al., Arctic and Antarctic sea ice, 1978-19 87. Satellite passive microwaveobservations and analysis, NASA SP-511, NASA, Washin gton, D.C., 1992.

Basics – XII: Atmosphere 1


Ulaby et al., Microwave Remote Sensing – Active and P assive, Vol I, Addison-Wesley Publishing Company, London, 1981 (modi fied).

70K

21K

10K

19 GHz

37 GHz

85 GHz

Basics – XIII: Atmosphere 2


Microwave brightnesstemperature change as a function of integrated watervapor content (x-axis) and cloud liquid water content (y-axis) as modeled for 85 GHz SSM/I

Top) calm water surface witha surface emissivity of 0.5

Bottom) wind-roughenedwater surface with a surfaceemissivity of 0.73; this isequivalent to about 50% icecover.

Kern, S., Ph.D. Thesis, 2001

Basics – XIV: Atmosphere 3


Left) View of the Special Sensor Microwave / Imager(SSM/I), right) schematic view of its viewing geometry

Basics – XV: Sensors 1


• SSM/I

FOV [km]

Sampling [km]

Polarization

f [GHz]

13x1529x3740x5043x69

12.5252525

H,VH,VVH,V

85372219

Advanced Microwave Scanning Radiometer (AMSR-E)

43x75

10

H,V

7

29x51

10

H,V

11

FOV [km]

Sampling [km]

Polarization

f [GHz]

4x68x1418x3216x27

5101010

H,VH,VVH,V

89362419

Basics – XV: Sensors 2


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


Methods & Parameters - II

Microwave Remote Sensing of Sea Ice, edited by F.D. Carsey, American Geophysical Union (AGU) Monograph 68, pp 2 9-46, AGU,

Washington D.C., 1992.

Open water: �� High dielectric constants & high reflectivity �� lowemissivity

Sea ice (FY): �� Low dielectric constants & low reflectivity �� high emissivity.


Different Methods

• Visible:

• Infrared:

• Microwave:

vbright dark

reflected sun light

Surface Temperature

warm cold

„warm“ „cold“

Surface Temperature timesemissivity

Methods & Parameters - III

100% 0%

100% 0%

0% 100%


Basics: T p(f) = C Tp,i(f) + (1 - C) Tp,w(f)

• C: Partial sea ice concentration

• Tp,i(f) & T p,w(f): Typical brightness temperatures (Tie points)

• Tp(f): Observed brightness temperature

Th(f)= 213 K C=?

Th,i(f)= 250 K

Th,w(f)= 150 K

Ice: C=1

Water: C=0

Fraction0,68

C=0.68 or

68%Fraction

0,32

from in-situ observations

from in-situ observations

Methods & Parameters - IV


Algorithm 1 to calculate the total sea ice concentrationfrom SSM/I 19 & 37 GHz data:

• Basic equation:

CI: total ice concentration; TI & TO: tie points (as bright-ness temperature) of sea ice & open water; TB: actualbrightness 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: O

OII

Methods & Parameters – VI: Comiso 1


a) Scatterplot of brightness temperatures at 19 & 37GH z; b) Scheme of Bootstrap technique: line CD: open water, line BA: 100 % ice, T: actualbrightness temperature pair; Coefficients a, b, αααα, and ββββ: tie points.

Gloersen et al., Arctic and Antarctic sea ice, 1978-19 87. Satellite passive microwaveobservations and analysis, NASA SP-511, NASA, Washin gton, D.C., 1992. (modified)

0% ice

100% ice

80% ice

Methods & Parameters – VII: Comiso 2


Methods & Parameters - V

Microwave Remote Sensing of Sea Ice, edited by F.D. Carsey, American Geophysical Union (AGU) Monograph 68, pp 2 9-46, AGU,

Washington D.C., 1992.

Open water: �� High dielectric constants & high reflectivity �� lowemissivity

Sea ice (FY): �� Low dielectric constants & low reflectivity �� high emissivity.

Large (small)polarization differencefor open water (seaice) at this incidenceangle (50°)


Algorithm 2 to calculate the sea ice concentration (total and multiyear) from SSM/I 19 and 37 GHz data:

• Normalized brightness temperature polarizationdifference (also: polarization ratio) using 19 GHz data(carries main ice concentration information)

• Normalized brightness temperature frequencydifference (also: gradient ratio) using 37 & 19 GHz data(carries ice type information: old ice & firstyear ice)

Methods & Parameters – VIII: NASA-Team 1


Fractions of first-year ice and multiyear ice can bewritten 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.

Methods & Parameters – IX: NASA-Team 2


Gloersen et al., Arctic and Antarctic sea ice, 1978-19 87. Satellite passive microwaveobservations and analysis, NASA SP-511, NASA, Washin gton, D.C., 1992. (modified)

Schematic view of NASA Team algorithm tie point triangle : open water (OW), first-year (FY) and multiyear ice (MY).

100% FY ice

100% MY ice

Weatherfilter

Methods & Parameters – X: NASA-Team 3


Comiso and Steffen, Studies of Antarctic sea ice concent ration from satellite dataand their applications, J. Geophys. Res., 106(C12), 31,361-31,385, 2001.

Methods & Parameters – XI: Quality 1



Methods & Parameters – XII: Quality 2


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 imag e.

Right: SSM/I sea ice concentration using the NASA-Team (l eftimage) & the COMISO-Bootstrap algorithm (right image).


Methods & Parameters – XIII: Quality 3


Above: Tiepoint trianglefor NASA-Team algorithm

Right: Impact of varyingice conditions (mixture of multi- and first-year ice) together with schematictiepoint triangle ( Fuhrhopet al., 1998, Fig. 4 )

Upper LayerSnowDensity:0.1 – 0.3 g/cm³

Upper LayerSnow GrainDiameter:0.55 – 1.05 mm

Lower LayerSnow GrainDiameter:1.3 – 1.8 mm

Methods & Parameters – XIV: Quality 4


Impact of varying atmo-spheric conditions forNASA-Team tiepointtriangle ( Oelke, IJRS, 1997 (top right); Fuhrhop et al., TGRS, 1998 (bottomright) ); L: clear sky but10m/s wind speed.

Values of GR > 0.05 aretypically flagged: C < 15%

Wind speed: 0 –25 m/s

Snowcloud: 0 –0.4 kg/m²

Water vapor + cloud:0.6-13 kg/m², 0-0.5 kg/m²

80%100%

50%20%

Methods & Parameters – XV: Quality 5


End of second part!

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