1. Remote Sensing of the Hydrosphere

2. The Hydrologic Cycle 70% of Earth is covered by oceans and surface freshwater Residence time varies from seconds to millennia

3. Ocean Remote Sensing Sea surface temperature Sea surface height Ocean color Wind and waves

4. Sea Surface Temperature (SST) Thermal sensors (e.g. AVHRR, MODIS) –good spatial resolution and accuracy –incomplete spatial coverage –long heritage (>20 years) –obscured by clouds –atmospheric corrections are required –measures SST to a water depth of 10  m Passive microwave sensors (e.g. TRMM, SSM/I) –lower spatial resolution and accuracy than w/thermal –good spatial coverage –long heritage (>20 years) –clouds are transparent –relatively insensitive to atmospheric effects –measures SST to a water depth of 1 mm –sensitive to surface roughness (waves) –sensitive to heavy precip.

5. AVHRR TRMM Microwave Imager Differences in Spatial Coverage (white pixels are areas of no data)

6. AVHRR image of Gulf Stream (5 km gridding) MODIS image of Gulf Stream (1 km gridding)

7. Sea Surface Height Sea surface height changes with wind patterns, ocean currents, ocean temperature (thermal expansion) Radar altimeter used to measure changes in sea surface height (timing of radar pulse gives distance between sensor and surface)

8. Sea Surface Height TOPEX/POSEIDON –launched in 1992 and still operating –measures SSH between 66 o N lat and 66 o S lat –C and Ku band altimeters –Sea surface height accurate to 4.2 cm –data available for free from http://podaac.jpl.nasa.gov Jason-1 (similar to TOPEX/POSEIDON) –launched in December 2001 –some data are now available for free from http://podaac.jpl.nasa.gov

10. Ocean Color Ocean color is a measure of biological activity –phytoplankton (produce chlorophyll) –dissolved and particulate matter Used to measure: –biological productivity –marine optical properties –interaction of winds and currents with ocean biology –human influences on the marine environment Remote sensing of ocean color uses multispectral data

11. Ocean Color Sensors Coastal Zone Color Scanner (CZCS) –October 1978 - June 1986 –1 km and 4 km gridded data –data products available for free from http://daac.gsfc.nasa.gov/data/dataset/CZCS/index.html Seaviewing Wide Field-of-view Scanner (SeaWIFS) –since September 1997 –1 km and 4 km gridded data –data products available for free for scientific use from http://daac.gsfc.nasa.gov/data/dataset/SEAWIFS Moderate Resolution Imaging Spectroradiometer (MODIS) –since February 2000 –1 km gridded data –data products available for free from http://daac.gsfc.nasa.gov/data/dataset/MODIS

12. MODIS chlorophyll data MODIS Quality Assurance data Revised MODIS chlorophyll data lt. blue=good data dk.blue=questionable purple=cloud red=bad data

13. Ocean Winds Ocean wind measurements are needed for understanding and predicting severe weather patterns Winds modulate energy transfer between the atmosphere and ocean Waves are the expression of momentum transfer from atmosphere to ocean Surface roughness can be monitored using SAR “Scatterometry” is a new method of measuring backscattered return from a SAR

14. Ocean Wind Sensors, I. NASA Scatterometer (NSCAT) –produced data from Sept 1996 - June 1997 –C-band –50 km grid resolution QuikSCAT SeaWinds scatterometer –launched in June 1999 –C-band –12.5 and 25 km spatial resolution for wind vectors –measures winds of 3- 20 ms -1, with 2 ms -1 accuracy Data from NSCAT and QuikSCAT are available for free from http://podaac.jpl.nasa.gov

15. How Scatterometry Works Microwave radar signal is transmitted to ocean surface Pulses are scattered by waves –Rougher surface = more scattering Near-surface wind speed is computed from radar backscatter Orientation of wind ripples indicate wind direction

17. Ocean Wind Sensors, II. Radar Altimeters measure sea surface height Areas of convergence and divergence are mapped Examples of radar altimeters: –TOPEX/Poseidon –ERS-1 and ERS-2

18. TOPEX data show waves developing in Pacific

19. Two days later, a surfer at Mavericks (Half Moon Bay, California) rides the huge waves

20. ERS-2 SAR image of waves the next day. SAR measures wave direction and wave height

21. Lakes Monitoring changes in surface water extent –Lake Chad

22. Water level fluctuations in Lake Chad, Nigeria AVHRR, 1997 Landsat MSS, 1973

23. Rivers Flooding –extent of surface waters –floodplain mapping

24. Mekong Delta flooding using multi-temporal MODIS data Mapping the extent of surface waters for large flood events allows improved mapping of floodplains

25. Southeast Asian Flooding in summer 2000 NASA global flood monitoring system operated through the Dartmouth Flood Observatory Data collected from MODIS 8-day composites Used to locate hardest hit areas for United Nations relief efforts

26. Tropical Rainfall Monitoring Mission (TRMM) maps areas of heavy precipitation between 50 o N and 50 o S. Near real time capability (daily maps) Flooding in southern Texas

27. Snow cover Mapping Passive microwave –25 km grid scale –weekly data available since October 1978 –daily data available since January 2000 AVHRR –1 km grid scale –weekly data available since October 1966 MODIS –500m grid scale –data available since February 2000 All data available for free from http://nsidc.org/data

28. Snow covered area from MODIS –daily and 8-day composite global snow cover products –500 m spatial resolution –available for free from http://nsidc.org/data/m od10_l2.html http://nsidc.org/data/m od10_l2.html March 25, 2003 Colorado Blizzard (blue=snow, white=cloud)

29. MODIS Snow Standard Product, Colorado, 15 Feb 2002 snow cloud no snow 25% of actual snow covered area is incorrectly classified as cloud

30. MODIS fractional snow cover, Colorado, 15 Feb 2002 90-100% 70-90% 50-70% 30-50% 10-30% 0-10% Vegetation obscures snow

31. Glaciers Global Land Ice Monitoring from Space (GLIMS) Uses ASTER data to map –glacier extent –snow line –glacier topography Synthetic Aperture Radar –Used to map glacier zones –Interferometry used to map glacier velocity

32. ASTER image of Patagonian glacier in Chile