1. Sea surface temperature gradient comparisons from MODIS and AVHRR sensors Ed Armstrong 1, Grant Wagner, Jorge Vazquez, Mike Chin, Gregg Foti, Ben Holt, Melissa Haltuch 2, Carrie Holt 3 1 NASA Jet Propulsion Laboratory, California Institute of Technology 2 NOAA-Fisheries, Northwest Fisheries Science Centre, Seatt le, WA 3 Pacific Biological Station, Fisheries and Oceans Canada, Nanaimo, Canada NASA Sea Surface Temperature Science Team Meeting Seattle, WA 8-10 Nov 2010 Copyright 2010 California Institute of Technology. Government Sponsorship Acknowledged.

2. Goals Compare and contrast SST gradients extracted from daily L3 MODIS Aqua and AVHRR Pathfinder (N17, N18) 4 km, seasonal scales. Time series is 2003-2009 Gulf Stream and California Current study areas Builds off previous SST gradient and frontal probability time series work for AVHRR Pathfinder Uses a Sobel filter applied to daily daytime and nighttime data and averaged to monthly and seasonal scales Pathfinder gradient products currently available online from 1982-2009 in netCDF

3. Seasonal gradient study areas MODIS Aqua and AVHRR Pathfinder seasonal SST gradient and frontal probability. 2003-2009.

4. A comparison of gradients Monterey Bay

5. Average gradients in CC study region

6. Cloud free coverage

7. Gradients near C. Mendocino

8. Average gradients in CC study region

10. Average gradients in Gulf Stream study region

11. Cloud free coverage

12. SST Gradient variability

13. SST gradient correlation (pixel-to-pixel)

14. Gradient differences (pixel-to- pixel)

15. MODIS/AVHRR comparison MODIS: more channels for improved cloud screening MODIS 12 bit vs 10 bit data telemetry MODIS: 50% lower noise equivalent temperature MODIS: 4 km pixels averages all 1 km pixels while AVHRR GAC sub samples in along-track and only averages in crosstrack Yet: Same channels, similar algorithm for SST derivation for both radiometers

16. MODIS SST gradient products 2003-2009 available at seasonal interval for Aqua Monthly products and Terra product not yet processed “Bias” adjustment to Pathfinder products ?? More research is needed, ideally with some in situ SST data Similar issues may be apparent when comparing L2 to L3 derived gradients Ideally we want to work with the channel brightness temperatures. But not available globally.

17. Applications

18. 18 Improving the management of Pacific hake (Merluccius productus) by integrating satellite information into models of spatial distribution Melissa Haltuch 1 and Carrie Holt 2 1 NOAA-Fisheries, Northwest Fisheries Science Centre, Seattle, WA, USA 2 Pacific Biological Station, Fisheries and Oceans Canada, Nanaimo, BC, Canada Peterson Field Guide to Pacific Coast Fishes, 1983

19. 19 Hake Survey 1995 1998 2001 2003 2005 2007

20. 20 Results Contour of relative hake abundance SSTs gradients (ΔºC) 2005 Hypothesis 1: mesoscale features

21. 21 Results Hypothesis 1: mesoscale features Model predicting log(abundance) AICΔAICLogL ~ 1 + depth + age302816-1507 ~1 + depth + age + Fronts 302312-1504 ~1 + depth + age + Fronts + Fronts*depth 30110-1496

22. Additional SST products 1980s-present Level 2 AVHRR Pathfinder for US Coast at 1 km (P. Cornillon) Pathfinder v6 Level 3 MUR Level 4 (blended) SST at 1 km daily. Presently 2008-present but eventually 1980s-present (M. Chin)

23. Summary Differences in satellite radiometer derived SST gradients are likely due to a number of factors Instrument differences (e.g., noise) Processing artifacts (e.g., cloud clearing, gridding) Oceanographic features MODIS appears to have significantly improved sensitivity in comparison to AVHRR series But what is the real truth ? There are challenges to sorting out the various effects (processing, instrument) on the gradient calculation. Need comparisons to other radiometers including in situ data There is a growing community for SST applications