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1 Lecture 17 Ocean Remote Sensing 9 December 2008.

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Presentation on theme: "1 Lecture 17 Ocean Remote Sensing 9 December 2008."— Presentation transcript:

1 1 Lecture 17 Ocean Remote Sensing 9 December 2008

2 2 Final Exam Friday – December 19 1:30-3:30 2/3 from lectures 12-17, 1/3 from previous lectures (focusing on topic areas covered in the first 2 exams)

3 3 Office Hours Not available this afternoon – Office hours on Thurs, Dec 11 Can meet Thurs/Fri, Dec 11/12 by appointment Not available Mon-Thurs, Dec 15-19

4 4 Ocean Chlorophyll/Production SAR Ocean Observations

5 5 Lecture Topics 1.Geographic perspectives on importance of oceanic processes 2.SAR Ocean Observations 3.Global SST data products 4.Sea surface topography 5.Monitoring El Nino with satellite data 6.Monitoring ocean productivity

6 6 Geographic perspectives on importance of oceanic processes Influences of oceans on continental climates Large-scale oceanic circulation

7 7

8 8 http://orbit-net.nesdis.noaa.gov/arad/gpcp/colormaps.html

9 9

10 10

11 11 Geographic perspectives on importance of oceanic processes Influences of oceans on continental climates Large-scale oceanic circulation

12 12

13 13 1.Ocean current drivers 2.Ocean current modifiers –Continents –Coriolis effect

14 14

15 15

16 16 Thermocline

17 17 Currents are also influenced by the rotation of the earth This rotation causes a natural deflection of currents Clockwise in the Northern Hemisphere Counter clockwise in the Southern Hemisphere This is called the coriolis effect

18 18 Lecture Topics 1.Geographic perspectives on importance of oceanic processes 2.SAR Ocean Applications 3.Global SST data products 4.Sea surface topography 5.Monitoring El Nino with satellite data 6.Monitoring ocean productivity

19 19 Microwave backscatter from water surfaces results from Bragg Scattering from small surface waves – Many processes alter the Bragg wavelength, and thus cause changes in EM energy detected by SARs

20 20 SAR Ocean Applications Detection of oil slicks Monitoring surface gravity waves Monitoring internal waves Detection of bottom features

21 21 Airborne SAR Imagery of Oil Spills Oil on water surface dampens formation of short wavelength Bragg Waves

22 22 Seasat SAR (L-band) image of an oil spill U.S. Coast Guard deploys airborne SAR systems for detection of oil spills in coastal waters

23 23 Tilt and hydrodynamic modulation by gravity waves

24 24 Airborne SAR imagery of gravity waves

25 25 Monochromatic light Monochromatic light is diffracted as it passes through a narrow slit Degree of diffraction ~ 1 / slot width

26 26 SAR Image of gravity waves digital

27 27 SAR Image of gravity waves In a fourier transform, the distance between the peaks of energy is proportional to the wavelength of the imaged gravity waves, and a line connecting the peaks represents the direction of the waves

28 28

29 29 Seasat SAR image of gravity waves

30 30 Internal Wave Formation

31 31 Internal Wave Formation

32 32 Surface Hydrodynamic Modulation by Internal Waves

33 33 Internal Waves

34 34 Airborne SAR Images of Internal Waves

35 35 ERS C-VV SAR image collected off of west African Coast

36 36 ERS C-VV SAR image collected off of Galopagos Islands showing internal waves

37 37 Seasat SAR Image of Natucket Shoals

38 38

39 39 Hydrodynamic Modulation by Bottom Feature/Current Interactions

40 40

41 41

42 42 Hydrodynamic Modulation Current slows downCurrent speeds up

43 43 Current Direction

44 44 Lecture Topics 1.Geographic perspectives on importance of oceanic processes 2.SAR Ocean Applications 3.Global SST data products 4.Sea surface topography 5.Monitoring El Nino with satellite data 6.Monitoring ocean productivity

45 45 Figure 4 in Njoku and Brown, Sea Surface Temperature, pages 237-249

46 46

47 47 Global Sea Surface Temperature Products Data are compiled over a weekly or monthly period Algorithms to remove cloud-contaminated pixels are applied to data Average SST for the remaining pixels are calculated Data are resampled to a coarse resolution (e.g, 36 km) Data are interpolated to fill in missing pixels http://www.osdpd.noaa.gov/PSB/EPS/SST/ al_climo_mon.html

48 48

49 49 AVHRR Sea Surface Temperature Map

50 50 MODIS Sea Surface Temperature Map

51 51 SST Map SST Anomaly Map

52 52

53 53 Lecture Topics 1.Geographic perspectives on importance of oceanic processes 2.SAR Ocean Applications 3.Estimating Sea Surface Temperature (SST) with AVHRR 4.Global SST data products 5.Sea surface topography 6.Monitoring El Nino with satellite data 7.Monitoring ocean productivity

54 54 Altimeters Altimeters measure round-trip travel time of microwave radar pulse to determine distance to sea surface! From this (and additional info) we can determine the dynamic sea surface topography

55 55 Spaceborne Scatterometer Resolution = 50 km Obtains measurements looking upwind, cross- wind, and downwind Empirical Algorithms used to estimate wind speed and direction

56 56

57 57 Lecture Topics 1.Geographic perspectives on importance of oceanic processes 2.SAR Ocean Applications 3.Global SST data products 4.Sea surface topography 5.Monitoring El Nino with satellite data 6.Monitoring ocean productivity

58 58 Thermocline

59 59 Thermocline

60 60 Movies of SST and Elevation Anomalies

61 61 Lecture Topics 1.Geographic perspectives on importance of oceanic processes 2.SAR Ocean Applications 3.Estimating Sea Surface Temperature (SST) with AVHRR 4.Global SST data products 5.Sea surface topography 6.Monitoring El Nino with satellite data 7.Monitoring ocean productivity

62 62 SeaWiFs Launched 1997 2800 km swath 1.1 x 1.1 km pixel

63 63 Example SeaWifs Chlorophyll Algorithms Chl = 10 (a + bR) Algorithm 1 - R = log (R443/R550) Algorithm 2 – R = log [(R520 + R565)/R490]

64 64

65 65

66 66

67 67 Data obtained from ORBIMAGE at: http://seawifs.gsfc.nasa.gov/cgibrs/seawifs_ browse.pl?dy=11627&tp=MO&lev=2&hp=

68 68 Monthly Composite

69 69

70 70


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