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Infrared and Microwave Remote Sensing of Sea Surface Temperature

Infrared and Microwave Remote Sensing of Sea Surface Temperature. Gary A. Wick NOAA Environmental Technology Laboratory January 14, 2004. Outline. Motivation Basic SST Retrieval Methods Current Multi-Sensor Merging Efforts. Why SST?. Boundary Condition Weather Models

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Infrared and Microwave Remote Sensing of Sea Surface Temperature

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  1. Infrared and Microwave Remote Sensing of Sea Surface Temperature Gary A. Wick NOAA Environmental Technology Laboratory January 14, 2004

  2. Outline • Motivation • Basic SST Retrieval Methods • Current Multi-Sensor Merging Efforts

  3. Why SST? • Boundary Condition • Weather Models • Estimation of Heat Content and Heat Flux • Climate Monitoring and Change Detection • Naval Operations

  4. Climate Anomalies Courtesy: NOAA Climate Diagnostics Center

  5. Why Satellites? Courtesy: R. Reynolds, NOAA NCDC

  6. Desired Accuracy • WCRP (1985) - Tropics • 0.3 K on 2° grid every 15 days • Robinson et al. (1984) - Global SST Monitoring • 0.05 K on 5° grid every 15 days • NPOESS SST EDR Objectives • 0.1 K uncertainty at ~4 km resolution

  7. Definition of SST • Interface SST • Skin SST • Sub-skin SST • Near-Surface SSTor SSTDepth

  8. Radiative Transfer Equation

  9. Methods for SST Retrieval • Thermal Infrared • Passive Microwave

  10. Infrared Retrievals • Strengths • High Accuracy • High Resolution • Long Heritage (over 20 years) • Weaknesses • Obscured by Clouds • Atmospheric Corrections Required

  11. Microwave Retrievals • Strengths • Clouds Transparent • Relatively Insensitive to Atmospheric Effects • Weaknesses • Sensitive to Surface Roughness • Poorer Accuracy (?) • Poorer Resolution

  12. Spatial Coverage Differences

  13. Infrared Retrieval Technique • Cloud Detection • Atmospheric Correction • Multi-Channel SST • TS = T1 + g(T1 - T2) • Multi-Frequency • Multiple View

  14. Algorithm Refinements • Additional path length term • NLSST • Use of multiple frequencies AND multiple view angles • Independent estimate of water vapor content • Iterative solution for both SST and e

  15. Microwave Retrieval Technique Courtesy: Remote Sensing Systems

  16. Infrared Sensors • AVHRR • ATSR • GOES Imager • MODIS • Others • GMS • SEVIRI • VIRS

  17. Microwave Sensors • TMI • AMSR • WindSat

  18. Multi-Sensor Blended SST • Current Projects • Key Issues • Sample Results

  19. GODAE High-Resolution SST Pilot Project • Provide rapidly and regularly distributed, global, multi-sensor, high-quality SST products at a fine spatial and temporal resolution • Most promising solution to combine complementary infrared and passive microwave satellite measurements with quality controlled in situ observations from ships and buoys • www.ghrsst-pp.org

  20. Next Generation SST • Created by Hiroshi Kawamura, Tohoku University, Japan • http://www.ocean.caos.tohoku.ac.jp/~adeos/sst/

  21. Blended SST Issues • Different product resolutions • Different sensor error characteristics • Different sampling times and effective depths • Merging techniques

  22. Error Characteristics – Overall Accuracy

  23. Observed Differences Between Infrared and Microwave Products Comparisons between the products show complex spatial and temporal differences

  24. Sources of Product Differences

  25. Diurnal Warming Effects

  26. Skin Layer Effects Courtesy: S. Castro, U. Colorado Courtesy: P. Minnett, U. Miami

  27. Blended Infrared andMicrowave SST Using derived corrections, the infrared and microwave SST products can be more accurately merged into a new enhanced product. Accuracy of Merged Product vs. Buoys Strong winds off Somalia cause perceived overcooling and large swath edge effects are visible. Diurnal warming effects are aliased into the product if not corrected.

  28. Analyzed SST Product Analysis Characteristics • Daily global (40 N – 40 S) 0.25 degree • Referenced to nighttime predawn value • Based on Reynolds and Smith Optimal Interpolation • Relative product uncertainties derived from difference analyses

  29. Analyzed Product Accuracy Summary Refined diurnal corrections are the most needed improvement

  30. Summary • Complementary infrared and microwave SST products provide the opportunity for cross-validation and improved SST • Multiple sensor-related and geophysical effects lead to complex differences between the products • Optimal blending of the products requires careful treatment of the differences • Is blending correct?

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