Global derived datasets for use in k-NN machine learning prediction of global seafloor total organic carbon

• Main Authors: Lee, Taylor R., Wood, Warren T., Phrampus, Benjamin J.
• Format: Other/Unknown Material
• Language: English
• Published: Zenodo 2018
• Subjects: globaldatasets; machinelearning; globalprediction; Antarctic; Southern Ocean; Antarc*
• Online Access: https://doi.org/10.5281/zenodo.1471639

Thisdataset includes 663 predictor grids used for k-NN global prediction of seafloor total organic carbon. 663 predictor grids available in netCDF4 HDF5 file format. Grids are cell-centered sized 4320 x 2160. File names adhere to the naming conventions discussed below. The naming structure is partioned by underscores and periods in the following order: interface to which the gridded values refer to, quantity of values contained within the grid, units and reference values/units (e.g. meters below sea level), data source, statistic calculated (if applicable), grid pitch, and file extension. Possible interfaces from the top – down: SS – Sea surface – atmosphere interface (may also be average of the entire water column) SF – Seafloor – water interface (may also be denoted by GL) GL – Ground level (e.g. bottom of pure liquid, top of dirt) SC – Sediment – crust interface (e.g. sediment above, igneous/metamorphic below) CM – Crust – mantle interface (e.g. Mohorovicic discontinuity) Appropriate reference naming marker (bold), original data source, and date of last access: Becker Becker, J. J., Wood, W. T., & Martin, K. M. (2014). Global crustal heat flow using random decision forest prediction , Abstract NG31A-3788 presented at 2014 Fall Meeting, AGU, San Francisco, California, U.S.A. Last access: 06/23/2015. CRUST1 Pasyanos, M.E., Masters, G., Laske, G. & Ma, Z. (2012). LITHO1.0 - An Updated Crust and Lithospheric Model of the Earth Developed Using Multiple Data Constraints , Abstract T11D-09 presented at 2012 Fall Meeting, AGU, San Francisco, California, U.S.A. Last access: 07/01/2014. CRUST1_NOAA As the NOAA sediment thickness database is globally not complete, data gaps in the NOAA grid with this have been supplemented by the CRUST1 sediment thickness (see above citation). Whittaker, J., Goncharov, A., Williams, S., Müller, R. D., & Leitchenkov, G. (2013) Global sediment thickness dataset updated for the Australian-Antarctic Southern Ocean, Geochemistry, Geophysics, Geosystems. ...