ESM 266: Passive microwave remote sensing. Jeff Dozier. Frequency-wavelength relation. Generally in the microwave part of the spectrum we use frequency instead of wavelength Typically measured in s –1 , called Hertz (Hz) Most often Gigahertz (GHz) = 10 9 Hz. Microwave band codes.
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ESM 266: Passive microwave remote sensing Jeff Dozier
Frequency-wavelength relation • Generally in the microwave part of the spectrum we use frequency instead of wavelength • Typically measured in s–1, called Hertz (Hz) • Most often Gigahertz (GHz) = 109Hz
Advantages of passive microwave remote sensing • Sees through clouds at lower frequencies • Long heritage, various instruments since 1978 • Emissivity sensitive to state of surface, particularly moisture • Soil moisture • Snow-water equivalent • (water is ~80× as absorptive as ice at these frequencies, whereas in visible through infrared, water and ice have similar absorption coefficients) • But, because of small amount of energy emitted, pixel size must be large
Planck equation = f(frequency,Temperature) Planck radiation at20,000 GHz is 36,000greater than at 37 GHz,so pixels at lower frequenciesmust be bigger
Rayleigh-Jeans approximation to Planck equation • Linear relation between Planck radiation and frequency, on a log-log plot, suggests a power function http://en.wikipedia.org/wiki/Taylor_series
The really useful simplification involves emissivity and brightness temperature • Emissivity varies with frequency and polarization
EOS Aqua satellite (afternoon overpass) • Six instruments, 3 in microwave • AIRS • CERES • AMSR-E, Advanced Microwave Scanning Radiometer for EOS • AMSR also flies on ADEOS-II (Japanese) • AMSU, Advanced Microwave Sounding Unit • HSB, Humidity Sounder for Brazil • MODIS
Sea ice from AMSR, Sea of Okhotsk Sea ice, 18 Jan 2003 Motion vectors, 10hrs
AMSR-E products • 6 frequencies, 12 channels (dual polarization), from 6.9-89 GHz • Precipitation rate • Cloud water • Water vapor • Sea-surface winds • Sea-surface temperature • Sea ice • Snow-water equivalent • Soil moisture
Earth-viewing side Aqua Prior to Launch Space-viewing side
Aqua’s Delta II Rocket (photos by Bill Ingalls)
The Aqua Sounding Suite Humidity Sounder for Brazil (HSB) Atmospheric Infrared Sounder (AIRS) Advanced Microwave Sounding Unit (AMSU; two units) AMSU A1 AMSU A2
Key Improvements Anticipated from AIRS/AMSU/HSB Data • Atmospheric temperatures to accuracies of 1 K in 1-km layers. • Atmospheric humidities to 10 % in 2-km layers. • Resultant improved weather forecasting. Launch of a radiosonde
Sample AIRS Infrared Spectra a. Data from all 2378 AIRS infrared channels for one footprint off the west coast of South Africa, June 13, 2002, 1:30 UTC. 500 1000 1500 2000 2500 wavenumber (cm-1) 20 10 6.7 5 4 wavelength (m) b. Detail showing the leftmost 128 of the 2378 channels in plot a.
Texas Thunderstorms as Seen in AMSU and HSB Imagery, June 16, 2002 AMSU Ch. 2 (31.4 GHz) AMSU Ch. 3 (50.3 GHz) AMSU Ch. 4 (52.8 GHz) AMSU Ch. 5 (53.94 GHz) HSB Ch. 2 (150 GHz) HSB Ch. 3 (183±1 GHz) HSB Ch. 4 (183±3 GHz) HSB Ch. 5 (183±7 GHz)
Rain Rate Images from AMSU/HSB June 16, 2002 Scandinavia South central U.S.
Hurricane Alma, west of Mexico, May 29, 2002, from HSB and AIRS HSB 150 GHz data AIRS Visible/Near IR data (images courtesy of the AIRS Science Team)
Surface Conditions and Moisture Streams in the Vicinity of Northern Europe, July 20, 2002 Surface Conditions from AMSU Moisture Streams from HSB
Global Sea Surface Temperatures from AMSR-E, June 2-4, 2002 (image courtesy of NASDA)
Typhoon in the East China Sea July 4, 2002, from AMSR-E Japan China AMSR-E image, 2:26 a.m. Japan Standard Time (JST). Taiwan Philippines
Precipitation over the Eastern U.S. and Vicinity, from AMSR-E and the TRMM Microwave Imager (TMI), June 5, 2002 TMI Total Rainfall AMSR-E Total Rainfall (images courtesy of Chris Kummerow and Bob Adler)
Global Sea Ice Coverage June 2-4, 2002 (top) and July 21-22, 2002 (bottom), from AMSR-E
Sample Record to be Extended with the AMSR-E Data: North Polar Sea Ice Extents Ice extent deviations from the Nimbus 7 SMMR and DMSP SSMI (extended from Parkinson et al., 1999)
AMSR products and algorithms • AMSR Algorithm Theoretical Basis Documents • Land surface parameters • Soil moisture, surface temperature, vegetation water • Brightness temperatures • Ocean • Sea-surface temperature, wind speed, water vapor, cloud water • Rainfall (works best over oceans) • Sea ice • Concentration, temperature, snow on sea ice • Nice graphic from New York Times on sea ice decline • Snow water equivalent • For dry snow, snow reduces apparent brightness temperature from soil • For wet snow, mainly detects that snow is wet