A Fundamental Climate Data Record for the AVHRR Jonathan Mittaz Manik Bali & Andrew Harris CICS/ESSIC University of Maryland

Cooperative Institute for Climate and Satellites University of Maryland 5825 University Research Court, (Suite 4001) College Park, MD Tel: (301) Fax: (301) Institute Director: Dr. Phillip Arkin Assistant Director: Andrew Negri  Funded project through NCDC for 3 years (part of NOAA Climate Data Record Program)  Goal  To provide recalibrated AVHRR Level 1B radiances for the thermal IR channels (3.7, 11 and 12 μ m channels) which are as accurate and bias free as possible and where the uncertainty on the radiances are better understood.  Source Data  NOAA AVHRR Level 1B data  Deliverables – not yet fully defined by likely to be one or more of  Code to calculate new radiances from current AVHRR Level 1B files  Recalibrated Level 1B data files (all AVHRRs in KLM format)  NCDC specific format (netCDF for example)  Part of SW/IR Imager FCDR Team – Team Lead : Bob Evans AVHRR IR CDR Project

Cooperative Institute for Climate and Satellites University of Maryland 5825 University Research Court, (Suite 4001) College Park, MD Tel: (301) Fax: (301) Institute Director: Dr. Phillip Arkin Assistant Director: Andrew Negri Use a physically meaningful calibration algorithm (current operational calibration (Walton et al. 1998) is not) Apply a uniform calibration methodology to the complete AVHRR data record –Current AVHRR Level1B data have a changing calibration methodology over time. Walton et al. calibration is available for NOAA-7,9,10,11,12,14 and all AVHRR/3s but is significantly biased. Reanalyze AVHRR pre-launch data to obtain instrument non-linearity Calibration Algorithm

Cooperative Institute for Climate and Satellites University of Maryland 5825 University Research Court, (Suite 4001) College Park, MD Tel: (301) Fax: (301) Institute Director: Dr. Phillip Arkin Assistant Director: Andrew Negri Calibration Targets - ECT (180->320K) & Space 70K No thermal shielding – very simple test chamber. Future pre-launch tests should be done better Run at 5 instrument temperatures of 10, 15, 20, 25, 30°C Pre-launch Data Calibration Test Chamber

Cooperative Institute for Climate and Satellites University of Maryland 5825 University Research Court, (Suite 4001) College Park, MD Tel: (301) Fax: (301) Institute Director: Dr. Phillip Arkin Assistant Director: Andrew Negri Example of pre-launch problems (Mittaz, Harris & Sullivan) Application of the Walton et al. calibration on the pre-launch data from which it was derived shows large biases – sign of severe problems with the pre-launch data and methodology Can be fixed by the use of a physically based methodology – means that all pre-launch data has to be re-analyzed Some pre-launch calibration parameters will still be corrupted Pre-launch Data (2)

Cooperative Institute for Climate and Satellites University of Maryland 5825 University Research Court, (Suite 4001) College Park, MD Tel: (301) Fax: (301) Institute Director: Dr. Phillip Arkin Assistant Director: Andrew Negri Use Physically based calibration equation (pre-launch and TOA) Use Top Of Atmosphere calibration sources (e.g. (A)ATSR, IASI etc.) when available to correct parameters contaminated during pre- launch testing (underlined in red) Use model of instrument to obtain calibration when contamination exists (solar contamination) when possible Remove periods of bad calibration from record Monitor calibration as a function of time and correct when necessary Calibration Approach (TOA)

Cooperative Institute for Climate and Satellites University of Maryland 5825 University Research Court, (Suite 4001) College Park, MD Tel: (301) Fax: (301) Institute Director: Dr. Phillip Arkin Assistant Director: Andrew Negri AVHRR calibrated by operational scheme – shows large temperature dependent biases Combination of incorrect algorithm and pre- launch contamination Correct by fitting corrupted calibration parameters to a TOA calibration radiance source (in this case IASI) Operational and New Calibration comparisons (IASI)

Cooperative Institute for Climate and Satellites University of Maryland 5825 University Research Court, (Suite 4001) College Park, MD Tel: (301) Fax: (301) Institute Director: Dr. Phillip Arkin Assistant Director: Andrew Negri Assessment of AVHRR/3 stability over 6 months - stable (<0.1K) Even operational calibration has constant biases to 0.05K New calibration shows small trends at the < 0.08K level (note change in scale wrt previous plot by ~ factor 10) K K MetOp-A AVHRR Stability

Cooperative Institute for Climate and Satellites University of Maryland 5825 University Research Court, (Suite 4001) College Park, MD Tel: (301) Fax: (301) Institute Director: Dr. Phillip Arkin Assistant Director: Andrew Negri Now done longer term study – MetOp-A AVHRR stable over 3+ years. Close to climate change requirements (Ohring et al. 2004) Accuracy = 0.1K Stability (per decade) = 0.04K MetOp-A AVHRR stable over 3+years SST Data (>270K) 11 µm Bias = 0.03K Gradient = K/decade 12 µm Bias = 0.03K Gradient = K/decade

Cooperative Institute for Climate and Satellites University of Maryland 5825 University Research Court, (Suite 4001) College Park, MD Tel: (301) Fax: (301) Institute Director: Dr. Phillip Arkin Assistant Director: Andrew Negri MetOp-A AVHRR Thermal Trend Small drift in average orbital temperature (0.2K in 4 years) with clear seasonal variability Constancy of temperature may in part explain stability of AVHRR calibration 0.2K

Cooperative Institute for Climate and Satellites University of Maryland 5825 University Research Court, (Suite 4001) College Park, MD Tel: (301) Fax: (301) Institute Director: Dr. Phillip Arkin Assistant Director: Andrew Negri Baseline instrument for re-calibration is the (A)ATSR series –Designed to be climate ready –Accurate and stable to < 0.05K (apart from the AATSR 12µm channel see later) –Data available from 1991 to present day (covers the AVHRR/2 AVHRR/3 instruments) Data available via FTP –One months worth of data ~130Gbytes – takes ~ 3 days to download AVHRR data matched with (A)ATSR data (first attempt parameters) –Match individual AVHRR GAC ‘pixels’ –Take into account true AVHRR GAC footprint –Both AVHRR and (A)ATSR data should be spatially coherent (current limit σ<1K over ~12x12km area) –Satellite ZA agree to < 1° –Data limited to close to nadir (current limit < 10°) –For daytime 3.7µm channel keep relative azimuth angle to < 30° –Maximum time difference between AVHRR and (A)ATSR data < 10 minutes –Correct (A)ATSR data for differences in spectral response functions Use of the AATSR as a TOA Calibration Source

Cooperative Institute for Climate and Satellites University of Maryland 5825 University Research Court, (Suite 4001) College Park, MD Tel: (301) Fax: (301) Institute Director: Dr. Phillip Arkin Assistant Director: Andrew Negri Compare 11 and 12 µm channel AVHRR data calibrated using the parameters derived from IASI matches - 11µm good agreement, 12 µm not Comparison of MetOp-A AVHRR with AATSR (IASI parameters) Good agreement with a slight (-0.05K) bias – small tweak can make the data match Strong trend to -0.5K at cold temperatures – highlights issues with AATSR 12µm channel (AATSR Cal Team informed)

Cooperative Institute for Climate and Satellites University of Maryland 5825 University Research Court, (Suite 4001) College Park, MD Tel: (301) Fax: (301) Institute Director: Dr. Phillip Arkin Assistant Director: Andrew Negri In Operation since March 2001 – thought to currently have a bad calibration (e.g. ‘out of family’ from NOAA MICROS pages).- test case for AVHRR near terminator/problem checking AATSR/NOAA-16 AVHRR Comparison (11µm) Using calibration from MetOp-A gives a trend and bias (but smaller trends than current calibration) (Data from Feb 2003) Recalibration removes trend/bias

Cooperative Institute for Climate and Satellites University of Maryland 5825 University Research Court, (Suite 4001) College Park, MD Tel: (301) Fax: (301) Institute Director: Dr. Phillip Arkin Assistant Director: Andrew Negri 7 years after previous calibration now close to terminator –Shows a distinct change in the calibration – time dependent effect NOAA-16 data taken Feb 2010 Data is biased and shows a trend relative to Feb 2003 calibration Bias parameters (α,α’) have larger values than in 2003 – impact of change in thermal state

Cooperative Institute for Climate and Satellites University of Maryland 5825 University Research Court, (Suite 4001) College Park, MD Tel: (301) Fax: (301) Institute Director: Dr. Phillip Arkin Assistant Director: Andrew Negri Average Instrument Temperature (NOAA-16) Unlike MetOp-A (0.2K in 4 years), NOAA-16 shows large temperature variations – becomes extreme from ~ A change in the thermal environment may explain the change in the 2010 calibration biases relative to Scan motor problems

Cooperative Institute for Climate and Satellites University of Maryland 5825 University Research Court, (Suite 4001) College Park, MD Tel: (301) Fax: (301) Institute Director: Dr. Phillip Arkin Assistant Director: Andrew Negri Misses some contamination Uses a simple constant to fill Better detection of events Modeled gain including uncertainty estimate Have much better detection of times of contamination – users can be more certain they are not including bad or corrupted data Also have a model for the gain for contaminated times including an uncertainty estimate Again better detection of events Misses some contamination Detection and correction of bad data - solar contamination (3.7μm) NOAA-14

Cooperative Institute for Climate and Satellites University of Maryland 5825 University Research Court, (Suite 4001) College Park, MD Tel: (301) Fax: (301) Institute Director: Dr. Phillip Arkin Assistant Director: Andrew Negri Nighttime Daytime Strong correlation of nighttime gain with Earth scene radiance Note predictive capability of new calibration (also can be used for solar contamination) Up to 0.25K error in daytime 295K Detection and correction of bad data – Earthshine 3.7 µm contaminated by Earthshine (light from Earth scattering via Blackbody in calibration) – fix with model of Self emission

Cooperative Institute for Climate and Satellites University of Maryland 5825 University Research Court, (Suite 4001) College Park, MD Tel: (301) Fax: (301) Institute Director: Dr. Phillip Arkin Assistant Director: Andrew Negri Contamination of the Space clamp view (e.g. by the Moon) will make the true instrument gain be unknowable – so these events are removed Detection and correction of bad data – Space Count contamination To have an accurate FCDR you need to accurately remove/flag all bad data

Cooperative Institute for Climate and Satellites University of Maryland 5825 University Research Court, (Suite 4001) College Park, MD Tel: (301) Fax: (301) Institute Director: Dr. Phillip Arkin Assistant Director: Andrew Negri For future missions - good pre-launch testing is critical and needs to be done properly In orbit comparisons against TOA reference sources is also critical to remove biases –Most of the tools are in place to recalibrate AVHRR/3 series AVHRR/2 waiting on pre-launch analysis AVHRR has the capability of being used for accurate climate studies –MetOp-A is currently accurate and stable Requirement for time/temperature dependence for the calibration –Clear in NOAA-16 (calibration very different in 2010 compared to 2003 –Constant instrument temperature -> constant calibration? (MetOp-A) Need to remove accurately remove/estimate bad data from record –Tools are in place Remaining issues –SRF shift needs to be included for (A)ATSR data –3.7 µm channel Automatic implementation of Earthshine correction –AATSR 12 µm channel needs to be fixed –Look into using RTM data/AVHRR overlap periods when accurate TOA sources not available (pre-1991) CONCLUSION