SST Reprocessing 2019.0


The R2019.0 processing of MODIS Sea Surface Temperature (SST) data by the OBPG incorporates a revised cloud classification scheme based on the theory of Alternating Decision Trees (ADtree) developed by Freund and Mason 1999 and modified by Pfahringer et. al. 2000. This methodology has been in use for the VIIRS-SNPP SST product since R2016.0 Additionally, a correction for atmospheric dust aerosol contaminated nighttime data based on the work of Luo et al., (2019) has been implemented.

Summary of Changes

  • Change SST minimum value to -1.8 (previously -2.0)
  • Add new AQUA and TERRA "tree sums" for the ADtree classifier
  • Use the GHRSST Level 4 CMC (Canadian Meterological Centre) Global Foundation Sea Surface Temperature product as the reference SST value in place of The NOAA 1/4° daily Optimum Interpolation Sea Surface Temperature product
  • No longer use the AQUA detector zero channel 23 BT40 (brightness temperature at 4um) in homogeneity tests
  • Minor bug fixes
  • Implement a new file naming convention


A presentation of the r2019.0 validation of SST products was presented in June 2019 by the GHSST group. Download the poster here.


Freund,Y. and Mason L., (1999) "The alternating decision tree learning algorithm", Proceedings of the 16th International Conference on Machine Learning, Bled, Slovenia , pp. 124-133

Pfahringer B., Holmes G., Kirkby R. (2001) "Optimizing the Induction of Alternating Decision Trees", In: Cheung D., Williams G.J., Li Q. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2001. Lecture Notes in Computer Science, vol 2035. Springer, Berlin, Heidelberg

Luo, B., Minnett, P. J., Gentemann, C. and Szczodrak, G., (2019) "Improving satellite retrieved night-time infrared sea surface temperatures in aerosol contaminated regions", Remote Sensing of Environment,Vol. 223,

Kilpatrick, K.A., G. Podestá, E. Williams, S. Walsh, and P.J. Minnett, 2019: Alternating Decision Trees for Cloud Masking in MODIS and VIIRS NASA Sea Surface Temperature Products. J. Atmos. Oceanic Technol., 36, 387–407, doi: 10.1175/JTECH-D-18-0103.1