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Satellite Remote SensingSIO 135/SIO 236

Lecture 11: Passive MicrowaveRemote Sensing

Helen Amanda Fricker

Passive Microwave Radiometry

• Microwave region: 1-200 GHz (0.15-30cm)• Uses the same principles as thermal remote sensing• Multi-frequency/multi-polarization sensing• Weak energy source so need large IFOV and wide

bands

• Related more closely to classical optical and IRsensors than to radar (its companion activemicrowave sensor)

• Recall the "windows" of low opacity, which allow the transmission of onlycertain EMR (caused by the absorption spectra of the gasses in theatmosphere)

• Atmospheric attenuation of microwave radiation is primarily throughabsorption by H20 & O2 - absorption is strongest at the shortest wavelength.Attenuation is very low for λ > 3 cm (f < 10 GHz). In general µwave radiationis not greatly influenced by cloud or fog, especially for λ > 3 cm.

microwave

Passive Microwave Radiometry

microwave

Passive Microwave Radiometry

• The microwave portion of the electromagnetic spectrum includeswavelengths from 0.1 mm to > 1 m. It is more common to refer tomicrowave radiation in terms of frequency, f, rather than wavelength, λ.• The microwave range is approx. 300 GHz to 0.3 GHz.• Most radiometers operate in the range 0.4-35 GHz (0.8-75 cm).

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• Thermal radiation is emitted by allobjects above absolute zero• In many cases the spectrum of thisradiation (i.e. intensity vs wavelength)follows the idealized black-body radiationcurve

Stefan-Boltzmann law: Total energy emittedover time by a black body is proportional to T4

Wiens displacement law: The wavelengthof the spectral peak is proportional to T-1

Thermal Radiation Rayleigh-Jeans approximationConvenient and accurate description for spectral radiance forwavelengths much greater than the wavelength of the peak inthe black body radiation formula i.e. λ >> λmax

Approximation is better than 1% when hc/λkT << 1or λT > 0.77 m K.

For example, for a body at 300˚K, the approximation is validwhen λ > 2.57 mm; in other words this approximation is goodwhen viewing thermal emissions from the Earth over themicrowave band.

Rayleigh-Jeans Approximation

• k is Planck’s constant, c is the speed oflight, ε is emissivity, T is kinetic temperature

• This approximation only holds for λ >> λmax

• (e.g. λ > 2.57mm @300 K)

!

L" = #2kcT

"4

spectral radiance isa linear function ofkinetic temperature

a constant

Planck’s lawDescribes the amplitude of radiation emitted (i.e., spectral radiance) froma black body. It is generally provided in one of two forms; Lλ(λ) is theradiance per unit wavelength as a function of wavelength λ and L ν(ν) isthe radiance per unit frequency as a function of frequency ν.

The first form is:

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Planck’s lawTo relate the two forms and establish L ν(ν), we take the derivative of Lwith respect to ν using the chain rule:

Since λ = c/ν, so that

which gives:

• Microwave radiometers can measure the emittedspectral radiance received (Lλ)

• This is called the brightness temperature and islinearly related to the kinetic temperature of thesurface

• The Rayleigh-Jeans approximation provides a simplelinear relationship between measured spectralradiance temperature and emissivity

Microwave Brightness Temperature

At the long wavelengths,of the microwave region,the relationship betweenspectral emittance andwavelength can beapproximated by astraight line.

εT is also called the “brightnesstemperature” typically shown as TB

!

TB

="4

2kcL"

Microwave Brightness Temperature

4

!

Tb

= "Tkin

Microwave Brightness Temperature

• So passive microwave brightness temperatures can beused to monitor temperature as well as properties related toemissivity

• In the microwave region, materials have large variations inemissivity

• Brightness temperature can be related to kinetictemperature through the emissivity of the material, i.e. itsability to emit radiation.

Soil

brig

htne

ss te

mpe

ratu

re

snow water equivalent

Soil

DrySnow

Wet snow is a strong absorber/emitter

Snow Emissivity Example

Soil

WetSnow

(1)

(2)

(3)

dry snow

Microwave Radiometers

• Advanced Microwave Sounding Unit (AMSU) 1978-present

• Scanning Multichannel Microwave Radiometer (SMMR) 1981- 1987

• Special Sensor Microwave/Imager (SSM/I) 1987-present

• Tropical Rainfall Measuring Mission (TRMM) 1997-present

• Advanced Microwave Scanning Radiometer (AMSR-E) 2002-present

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Passive Microwave Radiometry

• Passive microwave sensors use an antenna (“horn”) todetect photons at microwave frequencies which are thenconverted to voltages in a circuit

• Scanning microwave radiometers– mechanical rotation of mirror focuses microwave

energy onto horns

Comparative Operating Characteristics of SMMR, SSM/I, and AMSR Parameter (Nimbus-7)

SMMR (DMSP-F08,F10, F11,F13) SSM/I

(Aqua) AMSR-E

Time Period

1978 to 1987 1987 to Present 2002 to Present

Frequencies (GHz)

6.6, 10.7, 18, 21, 37 19.3, 22.3, 36.5, 85.5 6.9, 10.7, 18.7,

23.8, 36.5, 89.0

Sample Footprint Sizes (km):

148 x 95 (6.6 GHz)

27 x 18 (37 GHz)

37 x 28 (37 GHz)

15 x 13 (85.5 GHz)

74 x 43 (6.9 GHz)

14 x 8 (36.5 GHz)

6 x 4 (89.0 GHz)

Passive Microwave Applications

• Soil moisture• Snow water equivalent• Sea-ice extent, concentration and type (and lake ice)• Sea surface temperature• Atmospheric water vapor• Surface wind speed• Cloud liquid water• Rainfall rate

only over the oceans

D

H

R

Φr

Example radiometer

sin φr = λ/D

R = 2 H λ /D

H = 800 km

λ = 1cm

D = 1m

==> R = 16 km

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Monitoring Temperatures with Passive Microwave

• Sea surfacetemperature

• Land surfacetemperature

Passive Microwave Sensing of Land SurfaceEmissivity Differences

• Microwave emissivity is a function of the “dielectricconstant”

• Most earth materials have a dielectric constant in therange of 1 to 4 (air=1, vegetation=3, ice=3.2)

• Dielectric constant of liquid water is 80• Thus, moisture content strongly affects emissivity

(and therefore brightness temperature)• Surface roughness also influences emissivity

Passive Microwave Sensing of Land SurfaceEmissivity Differences

SSM/INorthernHemispheresnow waterequivalent(mm ofwater)

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• At frequencies less than 50 GHz there is little effect of clouds and fogon EMR (it “sees through” clouds)

• So PM can be used to monitor the land surface under cloudy conditions• In atmospheric absorption bands, PM is used to map water vapour, rain

rates, clouds etc.

Atmospheric Effects Atmospheric Mapping

• Mappingglobalwatervapor

• 85 GHz

Passive Microwave Sensing of Rain

• Over the ocean:

– Microwave emissivity of rain (liquid water) is about 0.9– Emissivity of the ocean is much lower (0.5)– Changes in emissivity (as seen by the measured brightness

temperature) provide and estimate of surface rain rate

• Over the land surface:

– Microwave scattering by frozen hydrometeors is used as ameasure of rain rate

– Physical or empirical models relate the scattering signatureto surface rain rates

Rainfall frompassive microwavesensors:

Accumulatedprecipitation fromthe TropicalRainfall MeasuringMission (TRMM)Similar to SSM/I

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Passive Microwave Remote Sensing from Space

• Penetration through non-precipitating clouds

• Radiance is linearly relatedto temperature (i.e. theretrieval is nearly linear)

• Highly stable instrumentcalibration

• Global coverage and wideswath

• Larger field of views (10-50 km) compared toVIS/IR sensors

• Variable emissivity overland

• Polar orbiting satellitesprovide discontinuoustemporal coverage atlow latitudes (need tocreate weeklycomposites)

Advantages Disadvantages • Sea ice is frozen seawater floating on the ocean surface

• Sea-ice has an insulating effect on the ocean (traps heat) &affects the Earth’s albedo

• Some sea ice is semi-permanent, persisting from year to year,and some is seasonal, melting and refreezing from season toseason.

• The sea ice cover reaches its minimum extent at the end ofeach summer and the remaining ice is called the perennial icecover.

• Passive microwave data have shown that the spatial extent ofthe Arctic sea-ice cover is shrinking

Sea-ice

Measures thermal emissions - as for Thermal IR, but atlonger wavelengths.Rayleigh-Jeans approximation:

TB = Ts ε (λ, θ)

Large contrast in ε of open ocean (~0.4 @18 GHz) & sea ice(~0.9 @ 18 GHz)

Sea Ice Extent

Combine 19 & 37GHz data Sea Ice Concentration

Passive Microwave Remote Sensing from Space

Lubin & Massom (2007), after Comiso (1985)

Sea-ice monitoring

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Massom (in press) after Svendsen et al. (1993)

Emissivities of sea-ice types and open water atmicrowave frequencies

Suppose we measure the thermal emissions at 10 GHz in a polarocean which has a mixture of open seawater, young sea ice, and oldsea ice. It is a warm day so both the ice and water are at the meltingpoint.

At 10 GHz (~3 cm), the EMR waves penetrate ~1 mm into theseawater and ~1 m into the ice.

Emissivities: seawater = 0.4young ice = 0.95old ice = 0.85

Brightness temperature observed by the radiometer aboard thespacecraft will reflect the variations in the emissivity of the surface.This is an excellent way to monitor the ice cover of the polar oceansand discriminate first-year ice from multi-year ice.

Sea-ice monitoring

Tb

The Passive Microwave Radiometer is the “Bread and Butter” Sensorfor Measuring Sea-Ice Concentration and Extent

~3 million km2 ~19 million km2

In Operation Since 1973

DMSP SSM/I Monthly Means

But Penetrates Cloud and Darkness, + Complete Daily CoveragePoor Spatial Resolution (25km)

Including theannual growth

and decay cycle& its variability.

January

FebruaryMarch April MayJuneJulyAugustSeptemberOctoberNovemberDecember

Courtesy Leanne Armand

Sea-ice monitoring

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First views of seasonal waxing and waning in 1973. Almost daily since.

Antarctic: ~3 to 19 million km2

Arctic: ~8 to 15 million km2

Carsey, 1992

March June Sept. Dec.

Satellite AMSR-E data (courtesy J. Comiso, NASA GSFC)

Oct 2002

3 million km2 19 million km2

February 2002

Satellite-derived maps of Sea Ice Concentration

Sea-ice monitoring

• Hemispheric time series back to1978, uninterrupted by cloud &darkness.

• Routine availability (NSIDC),uninterrupted by cloud & darkness

• Different algorithms – “Bootstrap” &NASA Team – see recommendationsin Report.

• Different datasets – recommendGSFC combined SMMR-SSM/I(internal consistency + good qualitycontrols).

SSM/I25 km res.

Data courtesy NSIDC

Sea-ice extent and concentration

More structural detail

Ross Sea

SSM/I, 25 km res. (NSIDC)

Aug 31, 2006

AMSR-E, 6.25 km res. (U Bremen)

Since 2002, also AMSR-E

12.5-20 km res (NASA/NSIDC)

6.25 km res (Univ Bremen)

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RossSea.

Monthly Mean DMSP SSM/I Ice Concentration and Motion Map, July 1999

SSM/I & AMSR12.5/25 km Resolution

East Wind Drift

Mertz Glacier Polynya

Massom et al., 2003Parkinson, 2005

Ice Season LengthClimatological Day of Ice Advance

+ Retreat (1979-2002)

Stammerjohn et al., 2008.

Relatively long annual expansion (Feb-Oct),most rapid March-June, then rapid decay (Nov-Jan)

NB Apparent recent “redistribution” to the Ross Sea from the Amundsen-Bellingshausen Seas.

We are losing the ice cover fast

Climatology (1979-2000)

Summer 2007: A new record low

Stroeve et al. 2008

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• Climate models suggest once the sea ice cover is thinned sufficiently, a strong “kick” from natural variability can initiate a rapid slide towards ice-free conditions in summer (e.g. Holland et al., 2006).

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1

2

3

4

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6

7

8

9

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1900 1920 1940 1960 1980 2000 2020 2040 2060 2080 2100

Year

Ice

Exte

nt (m

illio

n sq

-km

)

CCSM3 modelsimulationObservations

Model drop1.8 million sq km, 2024–2025

Observed drop1.6 million sq km, 2006–2007

September Sea Ice Extent

Sea-ice monitoring

• Mean thickness (70-90N) in CCSM3 before abruptchange: 1.71 m

• Mean thickness (70-90N) from ICESat in Spring 2007:1.75 m (data from D. Yi and J. Zwally)

Sea-ice monitoring

But the trendacceleratesfurther from -10.7to -11.8%/decade

Sea-ice monitoring

Yet, no new record lowin 2008

Sea-ice monitoring

Predictions for the future

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Ice sheet surface melt monitoring

PMW sensors detect dramatic rise in emissivity associated with the onset of melt

Amount of surface melting on Antarctic ice shelves