8 November 2010 SST Science Team Meeting 1 Towards Community Consensus SSTs and Clear-Sky Radiances from AVHRR SST Science Team Meeting 8-10 November 2010, Seattle WA Sasha Ignatov NOAA/NESDIS Prasanjit Dash, Xingming Liang, Feng Xu NOAA/NESDIS and CSU/CIRA
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Towards Community Consensus SSTs and Clear-Sky Radiances from AVHRR
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8 November 2010 SST Science Team Meeting 1
Towards Community ConsensusSSTs and Clear-Sky Radiances
from AVHRR
SST Science Team Meeting8-10 November 2010, Seattle WA
Sasha Ignatov
NOAA/NESDIS
Prasanjit Dash, Xingming Liang, Feng Xu
NOAA/NESDIS and CSU/CIRA
8 November 2010 SST Science Team Meeting 2
Contributions
AVHRR Level 2/3 SST products - J. Sapper, Y. Kihai, B. Petrenko, J. Stroup: ACSPO (GAC: 5 platforms, FRAC: MetOp-A)
- P. LeBorgne: O&SI SAF MetOp-A FRAC
- D. May, B. McKenzie: NAVO SEATEMP
- K. Casey, T. Brandon, R. Evans, J. Vazquez, E. Armstrong: PathFinder v5.0
Level 4 SST products (additional L4 SSTs are being tested)- R. Grumbine, Xu Li, B. Katz: RTG (Low-Res & Hi-Res), GSI
- R. Reynolds: OISST (AVHRR & AVHRR+AMSRE)
- M. Martin: OSTIA foundation, GHRSST Median Product Ensemble
- D. May, B. McKenzie: NAVO K10
- E. Autret, J.-F. Piollé: ODYSSEA
- E. Maturi, A. Harris, W. Meng: POES-GOES blended
- B. Brasnett: Canadian Met. Centre, 0.2 foundation
AVHRR Radiances- C. Cao, X. Wu, J. Mittaz, A. Harris, A. Heidinger, L. Wang: AVHRR Cal
- C. Cao, T. Hewison, M. König: GSICS (Global Space-based Inter-Cal System)
- Y. Han, M. Liu, Y. Chen, P. Van Delst, D. Groff, F. Weng: CRTM
8 November 2010 SST Science Team Meeting 3
SST data come from various sources, sensors, and processing algorithms
Reynolds OISST (AVHRR)Reynolds OISST (+ AMSR-E)Real Time Global high resolutionRTG low resolutionBlended POES and GOESOperational SST and Sea ice analysisCanadian Met. Centre 0.2 degreeNAVOCEANO 1/10 degreeMERSEA IFREMER/CERSATGHRSST Median Ensemble Product
IR: AVHRR, AATSRMW: AMSR-E, & in situ & CMC sea/ice
-0.02 0.15 0.31
ODYSSEASubskin, 0.1°
IR: AATSR, AVHRR, VISSR, SEVIRI, MW: AMSR-E, TMI
-0.03 0.29 0.40
8 November 2010 27SST Science Team Meeting*robust parameters are resistant to outliers, may hide local issues. Should be used with additional diagnostics
8 November 2010 SST Science Team Meeting 28
Conclusion to L4 vs. L4 Comparisons
Currently, nine L4 daily products are continuously monitored in
SQUAM, wrt. each other.
Foundation SST products (OSTIA, CMC) appear more stable in
time, less noisy in space, and more consistent with satellite data.
G1SST is being evaluated (G1SST). RSS MW is in pipeline.
Future plans…
Validate all L4 SSTs against independently QCed in situ data (iQUAM).
Explore DV model. This should reduce cross-platform biases and spurious
noise in “L2-L4”, and will help to globally validate the DV model.
Cooperate with L4 producers to add missing L4s
Radiances
Monitoring Clear-Sky Radiances
298 November 2010 SST Science Team Meeting
8 November 2010 SST Science Team Meeting 30
Monitoring of IR Clear-sky Radiances over Oceans for SST (MICROS)
Web-Based NRT tool to monitor M-O bias- M (Model) = Community Radiative Transfer Model (CRTM) used in
ACSPO to simulate TOA Brightness Temperatures.
- O (Observation) = AVHRR Clear-Sky BTs in Ch3B, 4 & 5.
Key objectives- Fully understand and reconcile CRTM and AVHRR BTs
- Minimize cross-platform biases -
Users/Applications- Test and improve ACSPO products
- Validate and improve CRTM performance
- Contribute to sensor characterization and inter-calibration within Global Space-based Inter-Calibration System (GSICS)
8 November 2010 SST Science Team Meeting 31
MICROS Overview
www.star.nesdis.noaa.gov/sod/sst/MICROS/
MICROS is end-to-end system
8 November 2010 SST Science Team Meeting 32
M-O Biasesand Double-Differences
Warm M-O biases are due to a combined effect of incomplete model (aerosols not included; bulk SST used instead of skin; daily mean Reynolds SST is used to represent nighttime SST) and biased satellite sensor radiances (residual cloud).
Double differences (DDs) cancel out many possible systematic errors in CRTM and its input (SST and GFS, missing aerosol, etc).
Non-zero DDs are mainly due to errors in sensor calibration and spectral response functions. Largest systematic errors are in N18 (Ch4) and N19 (all bands).
NOAA-16 is unstable in whole monitoring period.
8 November 2010 SST Science Team Meeting 33
The effect of CRTM input on M-O bias (Reynolds SST used as CRTM input)
μ and σ: median and RSD over time
Spurious variations found when Reynolds SST used as CRTM input.
8 November 2010 SST Science Team Meeting 34
The effect of reference SST on M-O bias (OSTIA SST used as CRTM input)
Spurious time variability reduced when OSTIA used as CRTM input.The Std Deviations are also dramatically reduced.
8 November 2010 SST Science Team Meeting 35
Conclusion to Monitoring Radiances
SST is an unresolved combination of 2-3 sensor bands. Monitoring
individual bands is needed to unscramble SST anomalies.
Web-based near-real time Monitoring of IR Clear-sky Radiances
over Oceans for SST (MICROS) established
http://www.star.nesdis.noaa.gov/sod/sst/micros/
Currently, three users groups actively use MICROS
- ACSPO SST developers
- CRTM developers
- Sensor calibration scientists
Future plans…
Minimize M-O biases through: Adding aerosol in CRTM; Improving