1. The AATSR sensor and its in-flight performance Chris Mutlow (1), Gary Corlett (2) and Dave Smith (1) (1) Earth Observation and Atmospheric Science Division, Rutherford Appleton Laboratory (2) Earth Observation Science, University of Leicester

2. 2 The Along Track Scanning Radiometer (ATSR) Programme  Primary objective to measure Sea Surface Temperature (SST) with an accuracy of 0.3 K (±1σ limit)  Thermal and visible data for atmospheric and land studies (e.g. temperature, vegetation, aerosols, clouds)  Provision of a long-term dataset for global climate change studies  ATSR-1 (ERS-1) 09/1991 - 03/00  ATSR-2 (ERS-2) 04/95 – Still working  AATSR (Envisat) 03/02 - Operational

3. 3 ATSR Programme Timeline

4. 4 Long Term (A)ATSR Data Record  14 year record of ATSR infrared data from 1991 when ATSR-1 was launched until today This provides a traceable global SST record from 1991 to today Sensors cross-calibrated  10 year record of visible data available from the launch of ATSR-2 in 1995 until today Calibrated using on-board VISCAL systems  Reprocessing is underway to put ATSR-1 and ATSR-2 data into a common AATSR “Envisat-style” format See Matt Pritchard’s talk on Tuesday

5. 5 What is (A)ATSR?  Imaging infrared and visible radiometer on ENVISAT Similar channels to AVHRR & MODIS.  Dual view (nadir and 55° to nadir) Along-track scanning, two views of same scene at different angles, for better atmospheric correction  On-board calibration 2 on-board black bodies for IR calibration VISCAL unit for visible channel calibration (see first talk after coffee break)  500 km swath  1 km IFOV at nadir  Stirling Cycle Coolers, cooling low noise detectors to 80K, for optimum signal-to-noise ratios

6. 6 Nominal Channel Centre Primary Application 0.55  m Chlorophyll 0.66  m Vegetation 0.87  m Vegetation 1.6  m Cloud Clearing 3.7  m SST Retrieval 10.8  m SST/LST Retrieval 12.0  m SST/LST Retrieval (A)ATSR Spectral Channels Red: ATSR-1,-2 and AATSR have these channels Blue: Only ATSR-2 and AATSR have these channels

7. 7 Data Products from AATSR  Operational Brightness temperatures and reflectances Sea Surface Temperature (SST) Land Surface Temperature (LST)  New product for AATSR NDVI  Under development Cloud parameters Aerosol optical properties

8. 8 Both blackbodies viewed every scan. AATSR On-board Calibration System

9. 9 Blackbody Crossover Test  Test performed over 17 th -19 th May All commands executed successfully Data to be analysed -XBB Hot BB +XBB Cold BB 11µm BB counts BB temperatures

10. 10 Scan Mechanism Trends

11. 11 NE  T Trend

12. 12 Cooler performance (1)

13. 13 Cooler Performance (2)

14. 14 FPA Temperatures

15. 15 Visible Channel Signals

16. 16 Contamination

17. 17 Dynamic Range and Digitisation  Periodically (nominally every 6 Months) data are processed for one orbit.  Plots produced showing: Max, mins and means for each scan over the orbit to evaluate dynamic range Histograms of nadir view pixel counts to check for any missing/preferred states

18. 18 Dynamic Range – IR Channels DaytimeNight-time

19. 19 Dynamic Range – Visible Channels Daytime Night-time

20. 20 Digitisation States – IR channels Rounding off at 1024, 2048, 3072

21. 21 Digitisation States – Visible Channels Rounding off at multiples of 1024

22. 22  IR Gain Offset Loop maintaining dynamic range of IR channels as expected  No saturation in visible channels – visible gains updated to maintain dynamic range.  Slight rounding off at 1024, 2048, 3072 counts – less than 1bit error (<20mK) Dynamic Range & Digitisation Summary

23. 23 Example Validation Results  ATS_NR__2P (SST & LST) Gridded 1km by 1km global product  Against in-situ radiometric measurements  ATS_AR__2P (SST only) Spatially averaged products at various resolutions (30´; 10´; 50 km; 17 km)  Against in-situ buoy measurements  Further talks on data quality throughout the workshop

24. 24 M-AERI and ISAR (Dual SST) M-AERI ResultsISAR Results NBiasSt. Dev.% ±0.3NBiasSt. Dev.% ±0.3 All match-ups Day 87+0.250.5845.9887+0.490.4437.93 All match-ups Night 261+0.180.3762.45223+0.180.3549.76 ‘Normal’ D-N Day 75+0.150.5353.3384+0.440.3639.29 ‘Normal’ D-N Night 229+0.110.3168.55204+0.140.3253.92 ‘High’ D-N Day 12+0.900.500.003+2.191.320.00 ‘High’ D-N Night 30+0.600.3520.0018+0.700.235.55 From: Lizzie Noyes (University of Leicester), Werenfrid Wimmer (NOCS)

25. 25 AATSR Compared to Buoy SST From: Anne O’Carroll (Met Office) Sat “bulk” SST Sat “skin” SST

26. 26 Buoy Results 04/2003-03/2005 (Dual SST) Match Up Skin resultsBulk results NBiasSt. Dev.% ±0.3NBiasSt. Dev.% ±0.3 All match-ups Day 15011-0.020.32N/A13440+0.150.3363.96 All match-ups Night 16124+0.050.26N/A14527+0.210.2564.02 ‘Normal’ D-N Day 14230-0.030.31N/A12862+0.140.3165.23 ‘Normal’ D-N Night 15593+0.040.25N/A14402+0.210.2464.38 ‘High’ D-N Day741+0.190.55N/A549+0.350.6137.52 ‘High’ D-N Night511+0.310.33N/A115+0.440.4623.48 From: Anne O’Carroll (Met Office)

27. 27 Summary of LST Validation Results BiomeSiteCampaignBias ± StDev 4FinlandDiscrete-0.1 ± 1.0 K 6ValenciaDiscrete+ 2.7 ± 0.8 K (1) 7UardryAutonomous-0.2 ± 0.9 K 8ThangooAutonomous-4.1 ± 3.3 K (2) 11AmburlaAutonomous-1.1 ± 1.5 K 12MoroccoDiscrete0.61 ± 2.7 K 14Lake TahoeAutonomous-0.07 ± 0.22 K From: Cesar Coll (University of Valencia), Jose Sobrino (University of Valencia), Fred Prata (CSIRO), Simon Hook (JPL) (1) Vegetation cover not accounted for properly in the algorithm (2) Actually a sea pixel to which LST retrieval has been applied in error

28. 28 Summary and Conclusions  AATSR is the third in a series of sensors providing a long- term data set of global SST since 1991. Visible channel data available from 1995 LST algorithm can be applied to data from 1991  The sensor is performing extremely well  Geophysical validation results provide evidence of excellent data quality from both the SST and LST operational algorithms Minor algorithm improvements are currently being assessed

29. 29 Acknowledgements  Co-authors Gary Corlett and Dave Smith for all their material  Defra, the UK Department of Environment, Food and Rural Affairs, who funded AATSR to support their programme of climate prediction and research, which in turn provides inputs to their policy-making processes  Funding agencies in Australia who made significant contributions  The European Space Agency