1. MODIS Sea-Surface Temperatures for GHRSST-PP Robert H. Evans & Peter J. Minnett Otis Brown, Erica Key, Goshka Szczodrak, Kay Kilpatrick, Warner Baringer, Sue Walsh Rosenstiel School of Marine and Atmospheric Science University of Miami Robert H. Evans & Peter J. Minnett Otis Brown, Erica Key, Goshka Szczodrak, Kay Kilpatrick, Warner Baringer, Sue Walsh Rosenstiel School of Marine and Atmospheric Science University of Miami US GHRSST Meeting. November 28, 2005

2. Outline GHRSST MODIS division of effort Status of MODIS SST MODIS approach to SSES Initial observations – Space and Time resolution of sst analysis fields has important implications for sst retrieval coverage and quality – High latitude summer bias and standard deviation are likely too large. Available in situ data are sparse Conclusions

3. July, 2005 formation of MODIS SST processing team (JPL, OBPG - GSFC, Miami) Division of effort: Miami - algorithm development, cal/val, base code development OBPG (Bryan Franz) integrate code into OBPG processing, process MODIS Terra, Aqua; day, night; global 1km; SST, SST4; transfer files to JPL JPL PO.DAAC (J. Vazquez, E. Armstrong) - convert OBPG files into L2P, add remaining fields, ice mask, distance to clouds…, transfer files to Monterrey Real Time MODIS for GHRSST

4. MODIS Collection 5 changes Time dependant SST and SST4 algorithm coefficients Time dependant Mirror side corrections (Terra only) Improved cloud flagging - use of a more stringent Reynolds test - day 865nm reflectance for clouds & aerosols - night sst, sst4 comparison for clouds & aerosols Change in map file resolution from SMI power of 2 projections to a true 4km, 36 km and 1 degree and maps to better assist incorporation of MODIS SST data into models.

5. Aqua Collection 4 & 5 SST & SST4 residuals

6. Aqua Collection 5 validation Statistics

7. Terra Collection 4 & 5 Mirror Side 1 & 2 residuals

8. TERRA MODIS Collection 5 validation Statistics

9. MODIS Single Sensor Error Statistics Approach Bias and Standard Deviation Hypercube Hypercube dimensions (partitioning of Match-up database) : - Time- quarter of year (4) - Latitude band (5): "60S to 40S" "40S to 20S" "20S to 20N" "20N to 40N" "40N to 60N" - Sat Zenith angle intervals (4): "0 to 30 deg" "30+ to 40 deg" "40+ to 50 deg" "50+ deg" - Surface temperature intervals (8): 5 degree intervals - Channel difference intervals:SST(3), SST4(4) ch31-32 (SST): 0.7 2.0, >2.0 ch22-23 (SST4) 0.5 degree intervals: -0.5 0, >0 ->0.5, >0.5 - Quality level (2) cube created only for ql=0 and 1 Note for ql2 and 3 the bias and standard deviation are each fixed to a single value No interpolation between adjacent cells in Hypercube

10. February 1May 1 October 31August 1 11-12 μm nighttime Terra SST 1 day per calendar quarter Every other orbit shown to eliminate orbit overlap 2005

11. February 1May 1 October 31August 1 11-12 μm SST Ql=0 bias 1 day per calendar quarter No ice mask Hypercube residuals relative to in situ obs Hypercube residuals relative to in situ obs

12. February 1May 1 October 31August 1 11-12 μm SST DT analysis 1 day per calendar quarter Modis Terra-Reynolds DT analysis relative to Reynolds OI DT analysis relative to Reynolds OI

13. Median -0.4 Quality 0 Quality 1 Quality 0 Quality 1 Predicted bias DT Median -0.1 Predicted bias Quality 0 & 1 Terra SST Global Bias from Hypercube and DT analysis Sat - buoy Oct 31, 2005 night Sat - Reynolds OI Oct 31, 2005 night

14. all Ql=0 Challenge of using SST analysis field as reference SST4 night Terra Oct 31, 2005 - Top Left Hypercube bias -Bottom Left DT analysis bias -Top Right Areal coverage using OI-Sat<3K -Bottom Right Areal coverage using all pixels High gradient, mesoscale variability not represented by OI Contemporaneous higher resolution analysis (better than 25km desired)

15. February 1May 1 October 31August 1 11-12 μm SST Standard deviation 1 day per calendar quarter

16. Conclusions -New monthly coefficients removed seasonal bias trends, Terra mirror side trends coefficients delivered for Terra, now available for Aqua -SST4 rms order 0.35C, SST order 0.45 -SST4 less affected by dust aerosols, water vapor -Improved quality filtering removed cold clouds and significant dust aerosol concentrations -Introduction of SSES hypercube provides insight into bias and standard deviation trends as a function of time, latitude, temperature, satellite zenith angle, brightness temperature difference as a proxy for water vapor and retrieval quality level -Hypercube developed and tested for Terra, in progress for Aqua -Base code for SST and SST4 delivered to OBPG -Delivery of Hypercube code in progress

17. END

18. August 1 2005 Laptev Sea

19. MODIS SST - Reynolds

20. February 1May1 October 31August 1 4um SST bias 1 day per calendar quarter

21. February 1May1 October 31August 1 4 um SST standard deviation 1 day per calendar quarter

22. February 1May1 October 31August 1 4 um SST DT analysis 1 day per calendar quarter Modis Terra-Reynolds

23. February 1May1 October 31August 1 4um SST 1 day per calendar quarter

24. Atmospheric correction algorithms The form of the daytime and night-time algorithm is: SST = c 1 + c 2 * T 11 + c 3 * (T 11 -T 12 ) *T sfc + c 4 * (sec (θ)-1 )* (T 11 -T 12 ) where T n are brightness temperatures measured in the channels at n  m wavelength, T sfc is a ‘climatological’ estimate of the SST in the area, and θ is the satellite zenith angle. This is based on the Non-Linear SST algorithm. (See Walton, C. C., W. G. Pichel, J. F. Sapper and D. A. May,1998, “The development and operational application of nonlinear algorithms for the measurement of sea surface temperatures with the NOAA polar-orbiting environmental satellites.” Journal of Geophysical Research, 103, 27,999-28,012.) The night-time algorithm, using two bands in the 4  m atmospheric window is: SST4 = c 1 + c 2 * T 3.9 + c 3 * (T 3.9 -T 4.0 ) + c 4 * (sec (θ)-1) Note: the coefficients in each expression are different.

25. October 31 2005 MODIS TERRA Night Bias 11-12 μm Best Quality QL=0 SST 11-12μm

26. Bias 11-12um Stdev October 31 2005 MODIS TERRA Night Best Quality QL=0

27. Bias 11-12 um October 31 2005 MODIS TERRA Night Best Quality QL=0 DT 11-12 um Modis-Reynolds

28. October 31 2005 MODIS TERRA Night Bias 4 u Best Quality QL=0 SST 4um Bias 4 um

29. October 31 2005 MODIS TERRA Night Best Quality QL=0 Bias 4 um Stdev4 um

30. October 31 2005 MODIS TERRA Night Best Quality QL=0 DT 4um Bias 4 um DT 4 um Modis-Reynolds

31. Histogram QL=0 Predicted Bias SST October 1 2005 Histogram QL=0 DT analysis Terra SST -Reynolds October 1 2005

32. Histogram QL=1 Predicted Bias SST October 1 2005 Histogram QL=1 DT analysis Terra SST -Reynolds October 1 2005