Blended SST Analysis Changes and Implications for the Buoy Network

1. Blended SST Analysis Changes and Implications for the Buoy Network Richard W. Reynolds*, Kenneth S. Casey+, Thomas M. Smith* & Huai-Min Zhang* * NOAA’s National Climatic Data Center + NOAA’s National Oceanographic Data Center • Plans for New SST Analysis • 2. Impact of New Analysis on In Situ SST Network

2. Optimum Interpolation (OI) SST AnalysisReynolds et al. (2002) • Data: in situ (ship and buoy) and operational satellite (AVHRR) observations blended for global coverage • Record: November 1981 to present • Resolution: weekly on 1o spatial grid • Analysis method: preliminary satellite bias corrections followed by OI analysis

3. Real-Time, Global SST (RTG_SST)Thiébaux et al. (2003) • Similarities with respect to Reynolds et al., OI • Same data: ship, buoy, day and night AVHRR • Same weekly AVHRR satellite bias correction • Differences with respect to Reynolds et al. • Run daily instead of weekly • 0.5o spatial resolution instead of 1o • Correlation scales smaller • 100 km to 400 km instead of 400 km to 1000 km • Started in May 2001

4. SST Comparisons:Chelton and Wentz (2005) Included 3-day SST and SST gradient comparisons in 6 high gradient regions for • Reynolds et al. Analysis • RTG_SST Analysis • AVHRR data averages • AMSR-E data averages • The AMSR-E instrument produces global microwave SST satellite retrievals beginning in June 2002

5. 29 Jan 2003: SST and SST Gradients • From the figure note: • Sparse AVHRR coverage • Complete AMSR-E coverage except near land • Gradient features lightly smoothed in RTG_SST and heavily smoothed in Reynolds • SST gradients are not shown in AVHRR • AMSR-E not used in Reynolds or RTG_SST • Results suggest that many SST features evolve slowly

6. Pathfinder SST for Month of Jan 2003 • From the figure note: • Top Panel: Number of nights of data • Number of nights is small (<5) in Gulf Stream • Bottom Panel: Average Pathfinder SST • Highest gradients missing • However, Chelton and Wentz (2005) show RTG-SST has better skill than Reynolds et al.

7. Plans to Improve Reynolds et al. OI Pilot Study • Recompute higher resolution version • Temporal Resolution: Daily • Spatial Resolution: 0.25o • Data • AVHRR pathfinder data • Ship and buoy in situ data • Initial period 2003 • Use constant spatial e-folding scales • Compare with AMSR-E and other independent in situ data • Weekly large-scale satellite bias correction using in situ data needed for all satellites • Bias procedure recently upgraded to an OI analysis differences (in situ -satellite). This better smoothes biases in time

8. Plans to Improve Reynolds et al. OIExtended Effort • Recompute daily OI spatial correlation scales • Analyze from January 1985 to present • January 1985 is the present start of AVHRR Pathfinder • Add new satellite products to OI • AMSR, TMI and eventually MODIS and ATSR • Present limitations • Diurnal cycle not resolved by daily analysis • Spatial grid resolution only 0.25o • Skin bulk differences not included • All input data sets to be saved and available to users at original resolution so that limitations can be corrected in later versions

9. In Situ Network Needed to Correct Satellite Biases Method Used to Simulate Biases OI analysis used with bias correction For Jan 1990 to Dec 2002 Climatology is first guess (FG) Satellite SSTs are simulated at actual data locations using EOFs of Biases with random temporal function Satellite EOFs scaled to absolute maximum of 2oC Buoy data are simulated on different grids RMS differences computed between the simulated OI and First Guess over time If there were no buoy data, the RMS residual would be equal to the absolute value of the EOF If there were complete buoy and/or ship sampling, the RMS would be 0

10. Potential Satellite Bias Error (PSBE) • PSBS shown as a function of buoy density • Potential is used because if satellite data have no biases, no buoy data are needed • Satellite biases scaled so that PSBS without buoys is 2oC • Bias Goal is 0.5oC • Goal exceeded if Buoy Density is 2/10o box Goal: 0.5oC 2

11. Equivalent Buoy Density "Equivalent Buoy " defined by: Number of Ships/7 + Number of Buoys Because ships are nosier than buoys, 7 ships equals 1 buoy

12. Potential Satellite Bias Error (PSBE) Max PSBE = 2oC SST Error (Co) Goal: 0.5oC Better Goal: 0.2oC Year

13. Weekly OI AnomalyAverage: 30oS-30oNOI analyses without bias correction • 3 OI Analyses • AVHRR only • TMI only • TMI + AVHRR • AVHRR only OI has negative bias relative to TMI only OI • Roughly -0.5oC from Oct 2000 - Feb 2003; End of NOAA-14 • Combined TMI + AVHRR intermediate to other OIs 13

14. Potential Satellite Bias Error (PSBE) Worst Case Estimates:NO In Situ Data • 2oC PSBE for AVHRR alone • 1.5oC PSBE: for 2 infrared sensors • 1oC when biases from instruments, independent errors • 2oC when biases from physical processes, not independent errors • 1oC for microwave and infrared sensors • Biases are independent • These estimates need to be tested!

15. Potential Satellite Bias Error (PSBE) • PSBS shown as a function of buoy density • "+" Satellite biases scaled so that PSBS without buoys is 2oC • "O" Satellite biases scaled so that PSBS without buoys is 1oC Goal: 0.5oC Better Goal: 0.2oC 2

16. Potential Satellite Bias Error (PSBE) Max PSBE = 2oC SST Error (Co) Goal: 0.5oC Better Goal: 0.2oC Max PSBE = 1oC Year

17. Summary • Improved OI analysis to be computed • Daily on 1/4o spatial grid • Using in situ and multiple satellite data • Bias errors only impacted when satellite retrieval errors are independent • Potential Satellite Bias Error (PSBE) introduced With current in situ network • PSBE ~ 0.6oC using 1 satellite • PSBE ~ 0.4oC using 2 satellites with independent errors satellite 17 April 2005 Climate Observation Program NOAA’s National Climatic Data Center