SST Reprocessing 2016.0

SST Reprocessing 2016.0


The R2016.0 processing of VIIRS 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. A full description of parameters, training, and validation of the ADtree cloud mask can be found in Kilpatrick et. al. 2019.

Summary of Changes

R2016.1 update

This is a minor update that includes:

R2016.2 update

This is a minor update that includes:


Y. Freund, L. Mason, "The alternating decision tree learning algorithm", Proceedings of the 16th International Conference on Machine Learning, Bled, Slovenia (1999), 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, doi: 10.1007/3-540-45357-1_50

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