1. Radiometry and Uncertainties from SORTIE (Spectral Ocean Radiance Transfer Investigation and Experiment) Kenneth Voss and Howard Gordon, Univ. of Miami Marlon Lewis, Scott McLean and Mike Twardowski, WetSat Carol Johnson, NIST Mark Yarbrough, Stephanie Flora and Mike Feinholz, Moss Landing Marine Lab Chuck Trees, NURC, NATO (SORTIE also includes Ron Zaneveld, Andrew Barnard, Susanne Craig) 2008 NASA Carbon Cycle and Ecosystems Joint Science Workshop, May 1

2. Sortie Goals To test radiometric techniques to augment the current vicarious calibration methods. The basic idea is to use measurements of inherent optical properties (IOP’s) to extend the radiometric measurements and determine subpixel variability To determine the suitability/ability to collect a usable vicarious calibration data set in Case II waters, in the best possible case.

3. SORTIE method Start with the very well characterized radiometric instrumentation Collect a complete suite of radiometric and apparent optical property (AOP) measurements during overpass time (Lu, Ed, L( ,  ), KLu, KEd, +) Collect IOP’s synchronous with these measurements, and then use a towed vehicle to investigate the IOP field around the measurement site before and/or after the overpass

4. First experiment in Hawaii, second in San Diego Start with clear water experiment, cross-over with MOBY and the MOBY team (experiment done last March) – If you can’t make clear water work, Case II is crazy Move to coastal region, San Diego (experiment done in January) – More difficult optical field (variation in IOP’s within pixel) – Important for vicarious cal…different “colored” sources…out of band issues accentuated

5. Hawaii experiment Cross over with the MOBY buoy, the “gold standard” for vicarious calibration Vicarious calibration in clear water, clear atmosphere Laboratory component, before field work, to set a baseline….if it doesn’t work in the lab why expect it to work at sea.

6. Responsivity uncertainties from laboratory calibration: Temperature uncertainty is after correction, as is stray light.

8. HyperOCR Uncertainty Budget (Lu) – Preliminary Uncertainty Component (%)412.4 nm 442.7 nm 498.8 nm 530.3 nm 547.1 nm 665.1 nm Comments Radiometric Calibration NIST Spectral Irradiance1.051.041.010.980.970.92 NIST Report Reflectance Target (0/45)1.52 Labsphere Report Transfer to HyperOCR Radiometric Transfer1.73 SIRREX-7 TM - typical uncertainty estimate Interpolation000000 4 Point Lagrange – no change in original data Reproducibility0.460.760.810.890.911.04 Pre-post SORTIE-1 cals Wavelength Accuracy0.280.270.180.150.130.07 0.06nm accuracy Stray Light0.100.090.080.020.040.09 3 SIRCUS realizations in SLC matrices Temperature0.010.000.010.020.030.07 estimate of uncertainty in thermal correction at 25.5C Combined Standard Uncertainty (Lab) 2.592.65 2.662.69%

9. Laboratory comparison experiment Compare MOBY and Satlantic E and L instruments Look at radiometric calibration sources Look at filtered sources, which can point out issues with out-of-band or stray light. If it doesn’t work at sea, data set gives another place to look.

10. Some examples, L from MOBY and Satlantic HPL

11. Colored Radiance source

12. Irradiance, standard calibration source

13. At Sea comparison Obviously harder….as close to contemporaneous as possible (within 900m) Newest Satlantic algorithm (see Scott McLean’s poster) Day shown was very clear (cloud free) and calm

14. MOBY and Satlantic Hyperpro

15. Different view

16. Still working….. But the SORTIE data set, very high quality IOP and AOP, gives us all sorts of other places to explore: – Nurads Radiance distribution with MASCOT VSF (and other Wetlabs IOP’s) – Inversion of Satlantic profile to get IOP’s to compare with measurements

17. Predicting Radiance distribution with VSF

18. Inversion techniques to go from AOP’s to IOP’s Based on algorithms detailed in: – H.R. Gordon and G.C. Boynton, “A radiance - irradiance inversion algorithm for estimating the absorption and backscattering coefficients of natural waters: Stratified water bodies”, Applied Optics 37, 3886-3896 (1998). – G.C. Boynton and H.R. Gordon, “An irradiance inversion algorithm for absorption and backscattering coefficients: Improvement for very clearwaters” Applied Optics, 41, 2224—2227 (2002). Really sensitive to reflectance and gradients (K) so is not dependent on absolute radiometry

19. Example inversion of single wavelength Fairly constant offset on order of 0.005 m-1, within published instrument uncertainties

20. Hyperspectral bb and a inversion

21. Hyper spectral c from inversion(?) No real reason it should be this good. b estimate depends on phase function assumed..

22. San Diego Experiment Have most of the data processed, not all Some very good days a good contrast to the Hawaii data set in terms of optical properties in the water.

23. Conclusions These are preliminary results. Still determining, in a collaborative manner, if there are areas for improvement. The laboratory intercomparisons between MOBY, Satlantic, NIST radiance and irradiance sensors are quite good and within 2%, well within the instrumental uncertainty budget. There are some biases between MOBY and HyperPro derived water-leaving radiances in the field data, which remain unexplained at this point, but are likely due to differences in deployment and environmental variations. Measured IOP's plus RTE (both Gordon and Morel approaches) provide excellent estimates of the upwelled radiance distribution. The inversion of the HyperPro AOP profiles provides a remarkably good agreement with direct measurements of IOP's. While the agreement for c is fortuitous, the agreement with a and bb emphasizes the excellent calibration (and baseline correction) of the AC-9 for use in these very clear waters. Next step is to apply same approach to San Diego Data set. We will be doing another field experiment in the fall in the Ligurian Sea, near the Bousolle site.