1. Satellite Remote Sensing SIO 135/SIO 236 Passive Microwave Remote Sensing

3. Passive Microwave Radiometry
Recall the "windows" of low opacity, which allow the transmission of only certain EMR (caused by the absorption spectra of the gasses in the atmosphere)
Atmospheric attenuation of μwave radiation is primarily through absorption by H20 & O2 - absorption is strongest at the shortest wavelength; attenuation is low for λ > 3 cm.
μwave radiation is not greatly influenced by cloud or fog, especially for λ > 3 cm.

4. Passive Microwave Radiometry
The microwave portion of the electromagnetic spectrum includes wavelengths from 0.1 mm to > 1 m. It is more common to refer to microwave 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 GHz ( cm).

5. Passive Microwave Radiometry
Microwave region: GHz ( cm)
Uses the same principles as thermal remote sensing
Uses multi-frequency/multi-polarization (H and V)
Weak energy source so need large IFOV and wide bands
IFOV Instantaneous field of view
Related more closely to classical optical and IR sensors than to radar (its companion active microwave sensor)

6. Thermal Radiation
Thermal radiation is emitted by all objects above absolute zero
In many cases the spectrum of this radiation (i.e. intensity vs wavelength) follows the idealized black-body radiation curve
Stefan-Boltzmann law: Total energy emitted over time by a black body is proportional to T4
Wiens displacement law: The wavelength of the spectral peak is proportional to T-1

7. Rayleigh-Jeans approximation
Convenient and accurate description for spectral radiance for wavelengths much greater than the wavelength of the peak in the black body radiation formula i.e.  >> max
Approximation is better than 1% when hc/kT << 1
or λT > 0.77 m K.
For example, for a body at 300˚K, the approximation is valid when λ > 2.57 mm; in other words this approximation is good when viewing thermal emissions from the Earth over the microwave band.
In physics, the Rayleigh–Jeans law attempts to describe the spectral radiance of electromagnetic radiation at all wavelengths from a black body at a given temperature through classical arguments.

8. At the long wavelengths, of the microwave region, the relationship between spectral emittance and wavelength can be approximated by a straight line.

9. Rayleigh-Jeans approximation
a constant
spectral radiance is a linear function of kinetic temperature
k is Planck’s constant, c is the speed of light, e is emissivity, T is kinetic temperature
This approximation only holds for l >> lmax
(e.g. l > K)

10. Microwave Brightness Temperature
Microwave radiometers can measure the emitted spectral radiance received (Ll)
This is called the brightness temperature Tb and is linearly related to the kinetic temperature of the surface
Rayleigh-Jeans approx. provides a simple linear relationship between measured spectral radiance temperature & emissivity
Brightness temperature is related to kinetic temperature through the emissivity of the material, i.e. its ability to emit radiation.
 Passive microwave brightness temperatures can be used to monitor temperature & properties related to emissivity

11. Passive Microwave Sensing of Land Surface Emissivity Differences
In the microwave region, materials have large variations in emissivity (e)
e is a function of the “dielectric constant”
Most Earth materials have a dielectric constant in the range of 1 to 4 (air=1, vegetation=3, ice=3.2)
Dielectric constant of liquid water is 80, so moisture content strongly affects e (& therefore Tb)
Surface roughness also affects e

12. Passive Microwave Sensing of Land Surface Emissivity Differences

13. Snow Emissivity Example
Soil
Dry
Snow
brightness temperature
(2)
snow water equivalent
Wet
Snow
Soil
Soil
(1)
(3)
Wet snow is a strong
absorber/emitter

14. Evolution of passive microwave sensors

15. Microwave Radiometers
Passive microwave sensors use an antenna (“horn”) to detect photons at microwave frequencies which are then converted to voltages in a circuit
Mechanical rotation of mirror focuses microwave energy onto horns -- “scanning microwave radiometers”
Scanning mechanism has evolved over the years

16. Microwave Radiometers
Advanced Microwave Sounding Unit (AMSU) 1978-present
Scanning Multichannel Microwave Radiometer (SMMR)
Special Sensor Microwave/Imager (SSM/I) 1987-present
Tropical Rainfall Measuring Mission (TRMM) 1997-present
Advanced Microwave Scanning Radiometer (AMSR-E) 2002-present

17. Example radiometer sin fr = /D R = 2 H  /D H = 800 km = 1cm D = 1m
==> R = 16 km

18. Passive Microwave Remote Sensing from Space
Advantages
Disadvantages
Penetration through non-precipitating clouds
Radiance is linearly related to temperature (i.e. the retrieval is nearly linear)
Highly stable instrument calibration
Global coverage and wide swath
Larger field of views (10-50 km) compared to VIS/IR sensors
Variable emissivity over land
Polar orbiting satellites provide discontinuous temporal coverage at low latitudes (need to create weekly composites)

19. Applications of Passive Microwave remote sensing
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

20. Monitoring Temperatures with Passive Microwave
Land surface temperature
Sea surface temperature

21. Monitoring Temperatures with Passive Microwave
Recall that in the microwave region, the relationship between energy and brightness temperature is approx. linear so that a given change in emitted energy due to a change in emissivity for example, results in a similar change in brightness temperature.
Large contrast between land and ocean surfaces in terms of observed brightness temperatures. Differences commonly are on order of 100 K.

22. Monitoring Temperatures with Passive Microwave
The changes seen over land, while smaller, are nevertheless instrumental in extracting information on surface type related to soil type, soil moisture, snow cover, and sea ice.
Land surface brightness temperatures have changed by relatively small amounts, but that the oceans now appear only 50K warmer.

23. SSM/I Northern Hemisphere snow water equivalent
(mm of water)

24. Atmospheric Effects
At frequencies less than 50 GHz there is little effect of clouds and fog on 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.

25. Mapping global water vapor
Atmospheric Mapping
Mapping global water vapor
85 GHz

26. 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 a measure of rain rate
Physical or empirical models relate the scattering signature to surface rain rates

27. Rainfall from passive microwave sensors:
Accumulated precipitation from the Tropical Rainfall Measuring Mission (TRMM)
Similar to SSM/I

28. What is sea-ice?
Sea ice is frozen seawater floating on the ocean surface
Sea-ice has high albedo (ice-albedo feedback), an insulating effect on the ocean (traps heat) & its formation contributes to formation of deep ocean waters
Some sea ice is semi-permanent, persisting from year to year, and some is seasonal, melting and refreezing from season to season.
The sea ice cover reaches its minimum extent at the end of each summer and the remaining ice is called the perennial ice cover.

29. SIO 115 Ice in the Climate System – Helen A Fricker
What is sea-ice?
Sea ice is frozen sea water that floats on the ocean surface: it forms and grows in the ocean
Floating ice that originates from glaciers and icebergs is not sea ice.
Some sea ice is semi-permanent, persisting from year to year (“multi-year ice”) and some is seasonal, melting and refreezing from season to season.
SIO 115 Ice in the Climate System – Helen A Fricker

30. SIO 115 Ice in the Climate System – Helen A Fricker
What is sea-ice?
The sea ice cover reaches its minimum extent at the end of each summer and the remaining ice is called the perennial ice cover.
First year ice is 1-2 m thick, multi-year ice (10 years old) is 5-6 m.
For most of the year, sea ice is typically covered with snow.
Julia says not true anymore – thickest seen recently is <4m.
SIO 115 Ice in the Climate System – Helen A Fricker

31. Why is sea-ice important?
Sea-ice affects the Earth’s albedo (ice-albedo feedback)
SIO 115 Ice in the Climate System – Helen A Fricker

32. Albedos of basic thick sea-ice surface types
SIO 115 Ice in the Climate System – Helen A Fricker

33. SIO 115 Ice in the Climate System – Helen A Fricker
Ice albedo feedback
Perovich & Richter-Menge (2008)
Non-linear processes & impacts
SIO 115 Ice in the Climate System – Helen A Fricker

34. Passive Microwave Remote Sensing from Space
Measures thermal emissions - as for Thermal IR, but at longer wavelengths.
Rayleigh-Jeans approximation:
TB = Ts e (l, q)
Large contrast in e of open ocean GHz) & sea ice 18 GHz)
Sea Ice Extent
Combine 19 & 37GHz data
Sea Ice Concentration

35. Emissivities of sea-ice types and open water at microwave frequencies
Massom (in press) after Svendsen et al. (1993)

36. Monitoring Sea Ice Extent
Measures thermal emissions, using brightness temperature TB
TB = e Ts
Large contrast in e:
open ocean GHz)
& sea ice 18 GHz)
Sea Ice Extent
Combine 19 & 37GHz data
Sea Ice Concentration
SIO 115 Ice in the Climate System – Helen A Fricker

37. Sea-ice monitoring
Suppose we measure the thermal emissions at 10 GHz in a polar ocean which has a mixture of open seawater, young sea ice, and old sea ice. It is a warm day so both the ice and water are at the melting point.
At 10 GHz (~3 cm), EMR waves penetrate ~1 mm into the seawater and ~1 m into the ice.
Emissivities: seawater = 0.4
young ice = 0.95
old ice = 0.85
Brightness temperature observed by the radiometer aboard the spacecraft will reflect the variations in the emissivity of the surface. This is an excellent way to monitor the ice cover of the polar oceans and discriminate first-year ice from multi-year ice. Tb

38. Monitoring Sea Ice Extent
Lubin & Massom (2007), after Comiso (1985)
SIO 115 Ice in the Climate System – Helen A Fricker

39. Sea-ice extent and concentration
Hemispheric time series back to 1978, uninterrupted by cloud & darkness.
Routine availability (NSIDC), uninterrupted by cloud & darkness
Different algorithms – “Bootstrap” & NASA Team – see recommendations in Report.
Different datasets – recommend GSFC combined SMMR-SSM/I (internal consistency + good quality controls).
SSM/I
25 km res.
Data courtesy NSIDC

40. AMSR-E, 6.25 km res. (U Bremen)
Monitoring Sea Ice Extent
SSM/I, 25 km res. (NSIDC)
km res (NASA/NSIDC)
Ross Sea
Aug 31, 2006
AMSR-E, 6.25 km res. (U Bremen)
Since 2002, also AMSR-E
6.25 km res (Univ Bremen)
More structural detail
SIO 115 Ice in the Climate System – Helen A Fricker

41. Including the annual growth and decay cycle & its variability.
Sea-ice monitoring
Including the annual growth and decay cycle & its variability.
February
March
April
May
June
July
August
September
October
November
December
January
Courtesy Leanne Armand

42. The Passive Microwave Radiometer is the “Bread and Butter” Sensor
for Measuring Sea-Ice Concentration and Extent
~3 million km2
~19 million km2
DMSP SSM/I
Monthly Means
In Operation Since 1973
Poor Spatial Resolution (25km)
But Penetrates Cloud and Darkness, + Complete Daily Coverage

43. SIO 115 Ice in the Climate System – Helen A Fricker
Seasonal variation in sea ice extent
Extends over ~7-10% of the Earth’s ocean surface
Satellite passive microwave
sensors have provided daily view
since 1979
Maximum: March
~16 million km2
Minimum: Sept
~7 million km2
Large seasonality: Annual growth-decay cycle represents one of greatest seasonal changes of any climate parameter
Area of Australia ~7.7 million km2
Area of Antarctica ~14 million km2
Maximum: Sept
~19 million km2
Minimum: Feb
~3 million km2
SIO 115 Ice in the Climate System – Helen A Fricker

44. SIO 115 Ice in the Climate System – Helen A Fricker
Seasonal variation in sea ice extent
Satellite-derived maps of Sea Ice Concentration
Satellite AMSR-E data (courtesy J. Comiso, NASA GSFC)
Oct 2002
3 million km2
19 million km2
February 2002
Area of Antarctica
~14 million km2
Area of Australia ~7.7 million km2
Sea ice covers a vast area of Southern Ocean (up to 40%)
SIO 115 Ice in the Climate System – Helen A Fricker

45. SIO 115 Ice in the Climate System – Helen A Fricker
Seasonal variation in sea ice extent
First views of seasonal waxing and waning in Almost daily since.
March
June
Sept.
Dec.
Arctic: ~7 to 16 million km2
Antarctic: ~3 to 19 million km2
Carsey, 1992
SIO 115 Ice in the Climate System – Helen A Fricker

46. Changes in Arctic sea-ice extent
1979–2009 sea-ice extent sea ice extent
SIO 115 Ice in the Climate System – Helen A Fricker
Credit: Julienne Stroeve

47. Changes in Arctic sea-ice extent
Stroeve et al. 2008
SIO 115 Ice in the Climate System – Helen A Fricker
Credit: Julienne Stroeve

48. We are losing the ice cover fast
Changes in Arctic sea-ice extent
We are losing the ice cover fast
SIO 115 Ice in the Climate System – Helen A Fricker
Credit: Julienne Stroeve

49. Time series of Arctic sea-ice extent
Source (Graph): W. Meier & J. Stroeve (NSIDC)
Passive Microwave Remote Sensing (SMMR & SSM/I)
Passive Microwave Remote Sensing Instruments - SMMR and SSM/I
NASA launched the Scanning Multichannel Microwave Radiometer (SMMR) in 1978, and the Defense Meteorological Satellite Program (DMSP) launched the first of the Special Sensor Microwave/Imager (SSM/I) sensors in 1987.
Mean sea ice anomalies, : Sea ice extent departures from monthly means for the Northern Hemisphere. For January 1953 through December 1979, data have been obtained from the UK Hadley Centre and are based on operational ice charts and other sources. For January 1979 through July 2009, data are derived from passive microwave (SMMR / SSM/I).
SIO 115 Ice in the Climate System – Helen A Fricker

50. Changes in Arctic sea-ice extent
Sep – Minimum Sea Ice Extent
Total: 4.3 million sq. km
Source for Map and Graph: NSIDC
Credit: Sinead Farrell
Trend = (+/- 3.3) % per decade (NSIDC)
Minimum extent: 4.60 million square kilometers on September 19, 2010
Climatological Average: 7.04 million sq. km.
Sept min. was 39% lower than the 4.3 million sq. km.
Sept was 5.4 million sq. km.
Oct 1, 2010 : freeze up had begun in earnest and ice extent returned to 5.44 million sq. km.
SIO 115 Ice in the Climate System – Helen A Fricker

51. Rate of decline -14%/decade

52. Seasonal difference in ice loss
2015 Lowest Winter Maximum Recorded
2015 4th Lowest Summer Minimum Recorded
-2.6% per decade
-13.4% per decade

53. SIO 115 Ice in the Climate System – Helen A Fricker

54. Changes in Arctic sea-ice extent
Sep – Minimum Sea Ice Extent
Total: 4.3 million sq. km
Source for Map and Graph: NSIDC
Credit: Sinead Farrell
Trend = (+/- 3.3) % per decade (NSIDC)
Minimum extent: 4.60 million square kilometers on September 19, 2010
Climatological Average: 7.04 million sq. km.
Sept min. was 39% lower than the 4.3 million sq. km.
Sept was 5.4 million sq. km.
Oct 1, 2010 : freeze up had begun in earnest and ice extent returned to 5.44 million sq. km.
SIO 115 Ice in the Climate System – Helen A Fricker

55. Changes in Arctic sea-ice extent
Sep – Minimum Sea Ice Extent
Total: 4.3 million sq. km
Source for Map and Graph: NSIDC
Credit: Sinead Farrell
Trend = (+/- 3.3) % per decade (NSIDC)
Minimum extent: 4.60 million square kilometers on September 19, 2010
Climatological Average: 7.04 million sq. km.
Sept min. was 39% lower than the 4.3 million sq. km.
Sept was 5.4 million sq. km.
Oct 1, 2010 : freeze up had begun in earnest and ice extent returned to 5.44 million sq. km.
SIO 115 Ice in the Climate System – Helen A Fricker

56. Changes in Arctic sea-ice extent
Further loss of old ice in 2010
SIO 115 Ice in the Climate System – Helen A Fricker

57. Changes in sea-ice extent: Arctic vs Antarctic
Fig. 7: Sea ice extent in Arctic and Antarctic, showing monthly mean values at the time of minimum annual extent (Arctic: September; Antarctic: February). Plot is based on
passive-microwave remote-sensing data processed at the National Snow and Ice Data Center (2008). The dashed lines show trends derived from a linear regression model. For
the Arctic data, the model explains 59 % of the variance and corresponds to a reduction
702 in ice extent of 0.72 x 106 km2 decade–1 (95-% confidence interval: ±0.24 x 106 km2
decade–1). For the Antarctic data, the model explains 6 % of the variance and corresponds
704 to an increase in ice extent of 0.10 x 106 km2 decade–1 (95-% confidence interval: ±0.15 x
106 km2 decade–1).
Why should we be concerned about sea ice changes?
Sea ice responds rapidly to weather & sensitive to climate change - significantly enhances the global effect of change
SIO 115 Ice in the Climate System – Helen A Fricker

58. Changes in Antarctic sea-ice extent
Source for Map and Graph: NSIDC
Credit: Sinead Farrell
Minimum extent usually in March
Can be -20 to +30 percent relative to the long-term mean
Lowest minimum year was 2006
Highest minimum was 2008
BUT considerable regional contrasts/variability
SIO 115 Ice in the Climate System – Helen A Fricker

59. SSM/I & AMSR 12.5/25 km Resolution Mertz Glacier Polynya
Monthly Mean DMSP SSM/I Ice Concentration and Motion Map, July 1999
SSM/I & AMSR
12.5/25 km Resolution
East Wind Drift
Mertz Glacier Polynya
Ross
Sea.
Massom et al., 2003

60. Climatological Day of Ice Advance
Parkinson, 2005
Ice Season Length
Climatological Day of Ice Advance
+ Retreat ( )
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.

61. Snow Emissivity Example
Soil
Dry
Snow
brightness temperature
(2)
dry snow
snow water equivalent
Wet
Snow
Soil
Soil
(1)
(3)
Wet snow is a strong
absorber/emitter

62. Monitoring surface melting with passive microwave
SSM/I brightness temperature Tb (19.35 GHz, horizontal polarization) measured over two areas: continuous line reports data measured over an area where melting occurs during summer where dashed line and black dots refer to an area where no melting is occurring. Tedesco, 2009.

63. Greenland: change in albedo during melt season
Graphics from Jason Box; MODIS data from D. Hall and J. Stroeve, NSIDC
SIO 115 Ice in the Climate System – Helen A Fricker

64. Greenland: increasing surface melting
SIO 115 Ice in the Climate System – Helen A Fricker

65. Greenland: increasing surface melting
SIO 115 Ice in the Climate System – Helen A Fricker

66. Greenland: increasing surface melting
SIO 115 Ice in the Climate System – Helen A Fricker

67. Ice sheet surface melt monitoring
Passive microwave sensors detect dramatic rise in emissivity associated with the onset of melt
Map of maximum areal extent of surface melt (pink) on the GrIS for 1992 and 2002 derived from analysis of Numbus-7 SMMR and DMSP SSM/I data
Centre is time series of max annual melt extents for GrIS from the same data.
While 1992 represents the lowest extent over the 24-year period, seasonal melt in 2002 began earlier than usual and progressed higher up on the ice sheet than at any time over the period analysed. In NE Greenland, the melt extended beyoind an elevation of 2000m (white line) i.e. into a region that normally remains too cold for melting. GrIS summit is 3,340m ASL.

68. Greenland: increasing surface melting
SIO 115 Ice in the Climate System – Helen A Fricker

69. Greenland: increasing surface melting
SIO 115 Ice in the Climate System – Helen A Fricker

70. Ice sheet surface melt monitoring
Mean annual melt duration (days)
Map of mean annual duration (in days) of circum-Antarctic
ice sheet and shelf melt derived from analysis of Nimbus 7 SMMR and DMSP
SSM/I brightness temperature data for the period From Torinesi et
al. (2003).
Amount of surface melting on Antarctic ice shelves