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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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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