Files associated with Christopher Holder and Anand Gnanadesikan, How well do Earth System Models capture apparent relationships between phytoplankton biomass and environmental variables? [Version 1]

1. process_cmip_rf.m is a matlab script that reads a single file, generates a random forest using the parameters in the associated paper and computes permutation importance and sensitivities. Note- in order to get process_cmip_rf.m to work as written you must have the Statistics and Machine Learning toolbox installed on Matlab and download the table_modis.asc file below. Files 2-16 are tabular filew containing all datapoints used in Random Forest analysis for the NCAR CESM2 model. Columns are 1. Index of point, enabling a mapping back to the model grid if the resolution is known. 2. Longitude 3. Latitude 4. Month 5. Iron in mol/m3. 6. Mixed layer in m. 7. Ammonia in mol/m3 8. Nitrate in mol/m3. 9. Phytoplankton carbon in mol/m3. 10. Phosphate in mol/m3. 11. Shortwave radiation (net solar radiation at ocean surface in W/m2). 12. Silicate in mol/m3. 13. Salinity in PSU 14. Temperature in C. 15. Upwelling velocity in m/s. If variable is not included in the dataset, the column will be filled with zeros. 2.table_cesm2.asc: Data created from Danabasoglu, G., 2019, NCAR CESM model output prepared for CMIP6 CMIP esm-pi-control http://doi.org/10.22033/ESGF/CMIP6.7579. Grid is 360x180x12 3.table_cems2_fv2.asc: Data created from Danabasoglu, G., 2019, NCAR CESM-FV2 model output prepared for CMIP6 CMIP pi-control http://doi.org/10.22033/ESGF/CMIP6.11301. Grid is 360x180x12 4. table_cesm2_waccm.asc: Data created from Danabasoglu, G., 2019, NCAR CESM2-WACCM model output prepared for CMIP6 CMIP piControl http://doi.org/10.22033/ESGF/CMIP6.10094. Grid is 360x180x12 5. table_cesm2_waccm_fv2.asc: Data created from Danabasoglu, G., 2019, NCAR CESM-WACCM-FV2 model output prepared for CMIP CMIP piControl, http://doi.org/10.22033/ESGF/CMIP6.11302. Grid is 360x180x12 6. table_gfdl_cm4.asc: Data created from Guo, Huan; John, Jasmin G; Blanton, Chris et al,2018, NOAA-GFDL GFDL-CM4 model output piControl, http://doi.org/10.22033/ESGF/CMIP6.8666. Grid is 360x180x12 7.table_gfdl_esm4.asc Data created from Krasting, John P.; John, Jasmin G; Blanton, Chris et al., 2018, NOAA-GFDL GFDL-ESM4 model output prepared for CMIP6 CMIP piControl, http://doi.org/10.22033/ESGF/CMIP6.8669. Grid 360x180x12 8. table_ipsl_cm5a2_inca.asc: Data created from Boucher, Olivier; Denvil, Sébastien; Levavasseur, Guillaume et al.: 2021, IPSL IPSL-CM5A2-INCA model output prepared for CMIP6 CMIP piControl http://doi.org/10.22033/ESGF/CMIP6.13683. Grid is 182x149x12 9. table_ipsl_cm6a_lr.asc: Data created from Boucher, Olivier; Denvil, Sébastien; Levavasseur, Guillaume et al., 2018:, IPSL IPSL-CM6A-LR model output prepared for CMIP6 CMIP piControl, http://doi.org/10.22033/ESGF/CMIP6.5251. Grid is 362x332x12. 10. table_mpi_esm1-2-ham.asc: Neubauer, David; Ferrachat, Sylvaine; Siegenthaler-Le Drian, Colombe et al., 2019: HAMMOZ-Consortium MPI-ESM1.2-HAM model output prepared for CMIP6 CMIP piControl, http://doi.org/10.22033/ESGF/CMIP6.5037. Grid is 256x220x12. 11. table_mpi_esm1-2-hr.asc: Data created from Jungclaus, Johann; Bittner, Matthias; Wieners, Karl-Hermann et al., 2019: MPI-M MPI-ESM1.2-HR model output prepared for CMIP6 CMIP piControl http://doi.org/10.22033/ESGF/CMIP6.6674. Grid is 802x404x12. 12. table_mpi_esm1-2-lr.asc: Data created from Wieners, Karl-Hermann; Giorgetta, Marco; Jungclaus, Johann et al. 2019:MPI-M MPI-ESM1.2-LR model output prepared for CMIP6 CMIP piControl http://doi.org/10.22033/ESGF/CMIP6.6675. Grid is 256x220x12. 13. table_noresm2-lm.asc: Seland, Øyvind; Bentsen, Mats; Oliviè, Dirk Jan Leo et al.,2019 NCC NorESM2-LM model output prepared for CMIP6 CMIP piControl, http://doi.org/10.22033/ESGF/CMIP6.8217. Grid is 360x385x12 14. table_noresm2-mm.asc: Data created from Bentsen, Mats; Oliviè, Dirk Jan Leo; Seland, Øyvind et al.,2019 : NCC NorESM2-MM model output prepared for CMIP6 CMIP piControl, http://doi.org/10.22033/ESGF/CMIP6.8221. Grid is 360x385x12. 15-16. table_kostadinov.asc, table_modis.asc Data is a merger of observational products and model output Observational climatologies for temperature, salinity, mixed layer depth, silicate, phosphate, and nitrate were downloaded from the World Ocean Atlas (WOA) 2018 (Garcia et al., 2019; Locarnini et al., 2019; Zweng et al., 2019). MODIS-POC was downloaded from oceancolor.nasa.gov. Kostadinov POC is taken from https://doi.org/10.1594/PANGAEA.859005 Grid is 360x180x12.

Related Organizations

Johns Hopkins University
United States

Keywords

machine learning, phytoplankton, earth system modeling, random forest, CMIP6

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