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Remote Sensing of the Ocean and Atmosphere:

Remote Sensing of the Ocean and Atmosphere:. John Wilkin. jwilkin@rutgers.edu IMCS Building Room 214C 609-630-0559. Sea Surface Temperature. http://www.ssec.wisc.edu/data/sst. Polar Orbiting Environmental Satellites (POES) Office of Satellite Operations. http://www.oso.noaa.gov/poesstatus.

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Remote Sensing of the Ocean and Atmosphere:

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  1. Remote Sensing of the Oceanand Atmosphere: John Wilkin jwilkin@rutgers.eduIMCS Building Room 214C609-630-0559 Sea SurfaceTemperature

  2. http://www.ssec.wisc.edu/data/sst

  3. Polar Orbiting Environmental Satellites (POES) Office of Satellite Operations http://www.oso.noaa.gov/poesstatus

  4. Polar Orbiting Environmental Satellites (POES) Office of Satellite Operations http://www.oso.noaa.gov/poesstatus

  5. All the in situ temperature observations in Australia waters since 1950

  6. sensor Stratosphere volcanic aerosols Troposphere upwelled atmospheric radiance clouds tropospheric aerosols sun glint water vapor T Emitted surface radiance Ocean TS buoy Tb

  7. Relative atmospheric transmission plotted vs. decreasing wavelength 10-12 mm 3.5-4.1 mm

  8. Relative atmospheric transmission plotted vs. increasing wavelength 10-12 mm 3.5-4.1 mm

  9. Sensitivity of brightness to change in blackbody temperature Brightness temperature difference due to atmosphere brightness of 300K blackbody 3.5 μm 10 μm 12 μm wavelength

  10. Wavelength bands used for IR SST imaging • Require high transmittance(low absorption) in atmosphere (i.e. a “window”) • Need significant emittance at black-body temperature typical of the ocean • Preferably high sensitivity of radiance to change in SST • Wavelengths typically used in practice: • AVHRR band 3B ~ 3.7 mm (MODIS band 20) night-time SST • AVHRR bands 4 and 5 ~10.8 and ~12 mm (MODIS 31 and 32) for day and night SST using split window algorithm

  11. Absorption coefficient for pure water as a function of wavelength λ of the radiation. At 11 μm, IR exitance comes from top 30 μm of ocean 1 μm 2 μm http://oceanworld.tamu.edu/resources/ocng_textbook/chapter06/chapter06_10.htm

  12. Night time weak winds and strong winds (anytime) case Day time weak winds case See also Fig 7.4 in Martin

  13. Irradiance observed at Top of Atmosphere (TOA) • Sum of: • radiation emitted and reflected by sea surface … reduced by attenuation in atmosphere (absorption and scattering) • emission by the atmosphere itself • Reflectance: • AVHRR Band 3 ~12% of SST emittance (so best used for night-time SST only) • AVHRR Bands 4 and 5 ~0.001% of SST but has more atmosphere emission)

  14. Converting multi-channel irradiance to SST data

  15. Correcting for the atmosphere

  16. Example: cloud flagging of data on IMCS OPeNDAP data server for the “Bigbight” region from Cape Hatteras to Nova Scotia http://tashtego.marine.rutgers.edu:8080/thredds/cool/avhrr/catalog.xml int cloud_mask(time, lat, lon) ; cloud_mask:missing_value = -999 ; cloud_mask:long_name = "Cloud_mask" ; cloud_mask:_FillValue = -999 ; cloud_mask:Convention = ” 0=passed 1=failed time test 2=failed low temp test 4=failed high gradient test 8=failed climatology test; Logical tests are summed" ; cloud_mask:documentation = ” “A measurement fails the time test if it is more than 2 degrees cooler than the median of the satellite passes in the previous 24 hrs;\n", "A measurement fails the low temp test if it is more than 2 standard deviations colder than any other measurement in that image;\n", "A measurement fails the high gradient test if its temperature gradient is greater than 2 standard deviations of all gradients in the image;\n", "A measurement fails the climatology test if the temperature is more than 5 degrees colder than the climatologies calculated by NSIPP AVHRR Pathfinder and Erosion Global 9km SST Climatology (Casey, Cornillon). A description of this climatology can be found at ftp://podaac.jpl.nasa.gov/pub/ documents/dataset_docs/nsipp_climatology.htm;\n", "If any measurement is fails a test, all neighboring measurements within 3km are also automatically failed." ;

  17. Night time weak winds and strong winds (anytime) case Day time weak winds case See also Fig 7.4 in Martin

  18. http://www.aoml.noaa.gov/phod/dac/gdp_drifter.php

  19. Global SST bias monitoring (monitored sensor minus reference sensor at the colocated points for each day): * in solid blue, time series of the bias between the sensor raw sst (without any correction applied) and the reference sst * In green, time series of the bias between the sensor sst (with SSES correction as provided in L2 files) and the reference sst * in dashed blue, bias between the sensor adjusted sst (with SSES correction and intercalibration adjustment) and the reference * in red, bias between the adjusted sst (with SSES correction and intercalibration adjustment) and the Odyssea optimal interpolation * the histogram plots the number of sensor/reference match-ups available each day

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