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Sea-ice induced Southern Ocean subsurface warming and surface cooling in a warming climate: ROMS model data
<p><strong>Abstract:</strong></p> <p>This data set contains model output data from the regional ocean modelling system (ROMS) that was set up for the Southern Ocean (south of 24 °S; Haumann, 2016) to analyze the effects of changing surface freshwater and momentum fluxes on Southern Ocean water-mass changes over the period 1980 to 2011. All data is provided in NetCDF format. The data set contains 3 sets 40-year long model spin-up, control, and 3 perturbation simulations each. The sets differ by their model mean state to assess the effect of surface salinity biases on the results. One set of simulations are reference simulations where salinity is restored to the observed surface salinity during model spin-up, and the other two sets are simulations in which the restoring surface salinity has been altered by plus and minus 0.1 PSU, respectively. The control and perturbation simulations are 40-year extensions of the respective model spin-up simulations. In the perturbation simulations either the surface freshwater fluxes or momentum fluxes are instantaneously perturbed after the spin-up simulation to reflect the observation-derived changes in these surface fluxes and then held constant (at the perturbed level) for 40 years. They consist of sea-ice freshwater flux, glacial meltwater flux, and atmosphere-ocean momentum flux changes. Details on the model setup, forcing, and simulations can be obtained from the related research article by Haumann et al. (2020; https://doi.org/10.1029/2019AV000132).</p> <p><br> <strong>Contacts:</strong></p> <p>F. Alexander Haumann, ORCID: 0000-0002-8218-977X. Email: alexander.haumann@gmail.com</p> <p><br> <strong>License:</strong></p> <p>When using this data users must cite the original research article by Haumann et al. (2020) published in AGU Advances (https://doi.org/10.1029/2019AV000132). This model output data set is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p> <p><br> <strong>Citations:</strong></p> <p>Haumann, F. A., Gruber, N., Münnich, M. (2020): Sea-ice Induced Southern Ocean Subsurface Warming and Surface Cooling in a Warming Climate. AGU Advances, 1, e2019AV000132. https://doi.org/10.1029/2019AV000132</p> <p>Haumann, F. A., Gruber, N., Münnich, M. (2020): Sea-ice induced Southern Ocean subsurface warming and surface cooling in a warming climate: ROMS model data. (Version 1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3709154</p> <p><br> <strong>Data processing:</strong></p> <p>The model data provided here has been processed for analysis and, due to storage constraints, only variables and averages used in the related research article (Haumann et al., 2020) are published here. Years refer to model years since initiation, i.e. the start of the spin-up simulation, and reach a maximum of 80 at the end of the control and perturbation experiments. Averages are either annual means over an indicated period ('yearly'), overall means over an indicated period ('mean'), or monthly climatologies over an indicated period ('clim'). 'Yearly' and 'Clim' values are provided either for surface fields or vertically integrated fields ('surf'). 'Mean' values are provided on the native vertical model grid as 3D fields. 'Yearly' zonal mean ('zonalmean') values have been first interpolated to from the native vertical model grid to a regular vertical z-level grid and then zonally averaged. All data has been stored in NetCDF format and compressed using level 1 deflation (https://www.unidata.ucar.edu/blogs/developer/entry/netcdf_compression). Full monthly mean model output from these simulations and the forcing fields can be obtained from the corresponding author upon request (alexander.haumann@gmail.com).</p> <p><br> <strong>Standards:</strong></p> <p>Data files have been formatted as Network Common Data Form (NetCDF; https://www.unidata.ucar.edu/software/netcdf/) in Hierarchical Data Format, version 5 (https://portal.hdfgroup.org/display/knowledge/HDF5+Documentation)</p> <p><br> <strong>Contents:</strong></p> <p><em>Data</em><br> - ROMS_SO_d025_grd.nc, ROMS grid file (Note: one row of ghost points on either side of the grid), compressed netcdf-file<br> - ROMS_SO_d025_ref_spinup, ROMS output from reference spin-up simulation, 4 netcdf-files:<br> -- ROMS_SO_d025_ref_spinup_clim.31-40.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 31 to 40, netcdf-file<br> -- ROMS_SO_d025_ref_spinup_mean.31-40.nc, 3D averaged fields for years 31 to 40, netcdf-file<br> -- ROMS_SO_d025_ref_spinup_yearly.31-40.surf.nc, 2D surface or vertically integrated annual mean fields for years 31 to 40, netcdf-file<br> -- ROMS_SO_d025_ref_spinup_yearly.zlev.zonalmean.31-40.nc, vertically interpolated (z-level) and zonally averaged annual mean fields for years 31 to 40, netcdf-file<br> - ROMS_SO_d025_minus01_spinup, ROMS output from minus 0.1 PSU sensitivity spin-up simulation, 4 netcdf-files:<br> -- ROMS_SO_d025_minus01_spinup_clim.31-40.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 31 to 40, netcdf-file<br> -- ROMS_SO_d025_minus01_spinup_mean.31-40.nc, 3D averaged fields for years 31 to 40, netcdf-file<br> -- ROMS_SO_d025_minus01_spinup_yearly.31-40.surf.nc, 2D surface or vertically integrated annual mean fields for years 31 to 40, netcdf-file<br> -- ROMS_SO_d025_minus01_spinup_yearly.zlev.zonalmean.31-40.nc, vertically interpolated (z-level) and zonally averaged annual mean fields for years 31 to 40, netcdf-file<br> - ROMS_SO_d025_plus01_spinup, ROMS output from plus 0.1 PSU sensitivity spin-up simulation, 4 netcdf-files:<br> -- ROMS_SO_d025_plus01_spinup_clim.31-40.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 31 to 40, netcdf-file<br> -- ROMS_SO_d025_plus01_spinup_mean.31-40.nc, 3D averaged fields for years 31 to 40, netcdf-file<br> -- ROMS_SO_d025_plus01_spinup_yearly.31-40.surf.nc, 2D surface or vertically integrated annual mean fields for years 31 to 40, netcdf-file<br> -- ROMS_SO_d025_plus01_spinup_yearly.zlev.zonalmean.31-40.nc, vertically interpolated (z-level) and zonally averaged annual mean fields for years 31 to 40, netcdf-file<br> - ROMS_SO_d025_ref_ctrl, ROMS output from reference control simulation, 4 netcdf-files:<br> -- ROMS_SO_d025_ref_ctrl_clim.46-55.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_ref_ctrl_clim.61-80.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_ref_ctrl_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_ref_ctrl_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_ref_ctrl_yearly.41-80.surf.nc, 2D surface or vertically integrated annual mean fields for years 41 to 80, netcdf-file<br> -- ROMS_SO_d025_ref_ctrl_yearly.zlev.zonalmean.41-80.nc, vertically interpolated (z-level) and zonally averaged annual mean fields for years 41 to 80, netcdf-file<br> - ROMS_SO_d025_minus01_ctrl, ROMS output from minus 0.1 PSU sensitivity control simulation, 4 netcdf-files:<br> -- ROMS_SO_d025_minus01_ctrl_clim.46-55.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_minus01_ctrl_clim.61-80.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_minus01_ctrl_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_minus01_ctrl_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_minus01_ctrl_yearly.41-80.surf.nc, 2D surface or vertically integrated annual mean fields for years 41 to 80, netcdf-file<br> -- ROMS_SO_d025_minus01_ctrl_yearly.zlev.zonalmean.41-80.nc, vertically interpolated (z-level) and zonally averaged annual mean fields for years 41 to 80, netcdf-file<br> - ROMS_SO_d025_plus01_ctrl, ROMS output from plus 0.1 PSU sensitivity control simulation, 4 netcdf-files:<br> -- ROMS_SO_d025_plus01_ctrl_clim.46-55.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_plus01_ctrl_clim.61-80.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_plus01_ctrl_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_plus01_ctrl_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_plus01_ctrl_yearly.41-80.surf.nc, 2D surface or vertically integrated annual mean fields for years 41 to 80, netcdf-file<br> -- ROMS_SO_d025_plus01_ctrl_yearly.zlev.zonalmean.41-80.nc, vertically interpolated (z-level) and zonally averaged annual mean fields for years 41 to 80, netcdf-file<br> - ROMS_SO_d025_ref_seaice, ROMS output from reference sea-ice freshwater flux perturbation simulation, 4 netcdf-files:<br> -- ROMS_SO_d025_ref_seaice_clim.46-55.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_ref_seaice_clim.61-80.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_ref_seaice_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_ref_seaice_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_ref_seaice_yearly.41-80.surf.nc, 2D surface or vertically integrated annual mean fields for years 41 to 80, netcdf-file<br> -- ROMS_SO_d025_ref_seaice_yearly.zlev.zonalmean.41-80.nc, vertically interpolated (z-level) and zonally averaged annual mean fields for years 41 to 80, netcdf-file<br> - ROMS_SO_d025_minus01_seaice, ROMS output from minus 0.1 PSU sensitivity sea-ice freshwater flux perturbation simulation, 4 netcdf-files:<br> -- ROMS_SO_d025_minus01_seaice_clim.46-55.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_minus01_seaice_clim.61-80.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_minus01_seaice_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_minus01_seaice_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_minus01_seaice_yearly.41-80.surf.nc, 2D surface or vertically integrated annual mean fields for years 41 to 80, netcdf-file<br> -- ROMS_SO_d025_minus01_seaice_yearly.zlev.zonalmean.41-80.nc, vertically interpolated (z-level) and zonally averaged annual mean fields for years 41 to 80, netcdf-file<br> - ROMS_SO_d025_plus01_seaice, ROMS output from plus 0.1 PSU sensitivity sea-ice freshwater flux perturbation simulation, 4 netcdf-files:<br> -- ROMS_SO_d025_plus01_seaice_clim.46-55.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_plus01_seaice_clim.61-80.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_plus01_seaice_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_plus01_seaice_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_plus01_seaice_yearly.41-80.surf.nc, 2D surface or vertically integrated annual mean fields for years 41 to 80, netcdf-file<br> -- ROMS_SO_d025_plus01_seaice_yearly.zlev.zonalmean.41-80.nc, vertically interpolated (z-level) and zonally averaged annual mean fields for years 41 to 80, netcdf-file<br> - ROMS_SO_d025_ref_glacial, ROMS output from reference glacial meltwater flux perturbation simulation, 4 netcdf-files:<br> -- ROMS_SO_d025_ref_glacial_clim.46-55.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_ref_glacial_clim.61-80.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_ref_glacial_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_ref_glacial_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_ref_glacial_yearly.41-80.surf.nc, 2D surface or vertically integrated annual mean fields for years 41 to 80, netcdf-file<br> -- ROMS_SO_d025_ref_glacial_yearly.zlev.zonalmean.41-80.nc, vertically interpolated (z-level) and zonally averaged annual mean fields for years 41 to 80, netcdf-file<br> - ROMS_SO_d025_minus01_glacial, ROMS output from minus 0.1 PSU sensitivity glacial meltwater flux perturbation simulation, 4 netcdf-files:<br> -- ROMS_SO_d025_minus01_glacial_clim.46-55.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_minus01_glacial_clim.61-80.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_minus01_glacial_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_minus01_glacial_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_minus01_glacial_yearly.41-80.surf.nc, 2D surface or vertically integrated annual mean fields for years 41 to 80, netcdf-file<br> -- ROMS_SO_d025_minus01_glacial_yearly.zlev.zonalmean.41-80.nc, vertically interpolated (z-level) and zonally averaged annual mean fields for years 41 to 80, netcdf-file<br> - ROMS_SO_d025_plus01_glacial, ROMS output from plus 0.1 PSU sensitivity glacial meltwater flux perturbation simulation, 4 netcdf-files:<br> -- ROMS_SO_d025_plus01_glacial_clim.46-55.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_plus01_glacial_clim.61-80.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_plus01_glacial_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_plus01_glacial_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_plus01_glacial_yearly.41-80.surf.nc, 2D surface or vertically integrated annual mean fields for years 41 to 80, netcdf-file<br> -- ROMS_SO_d025_plus01_glacial_yearly.zlev.zonalmean.41-80.nc, vertically interpolated (z-level) and zonally averaged annual mean fields for years 41 to 80, netcdf-file<br> - ROMS_SO_d025_ref_momentum, ROMS output from reference atmopshere-ocean momentum flux perturbation simulation, 4 netcdf-files:<br> -- ROMS_SO_d025_ref_momentum_clim.46-55.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_ref_momentum_clim.61-80.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_ref_momentum_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_ref_momentum_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_ref_momentum_yearly.41-80.surf.nc, 2D surface or vertically integrated annual mean fields for years 41 to 80, netcdf-file<br> -- ROMS_SO_d025_ref_momentum_yearly.zlev.zonalmean.41-80.nc, vertically interpolated (z-level) and zonally averaged annual mean fields for years 41 to 80, netcdf-file<br> - ROMS_SO_d025_minus01_momentum, ROMS output from minus 0.1 PSU sensitivity atmopshere-ocean momentum flux perturbation simulation, 4 netcdf-files:<br> -- ROMS_SO_d025_minus01_momentum_clim.46-55.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_minus01_momentum_clim.61-80.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_minus01_momentum_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_minus01_momentum_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_minus01_momentum_yearly.41-80.surf.nc, 2D surface or vertically integrated annual mean fields for years 41 to 80, netcdf-file<br> -- ROMS_SO_d025_minus01_momentum_yearly.zlev.zonalmean.41-80.nc, vertically interpolated (z-level) and zonally averaged annual mean fields for years 41 to 80, netcdf-file<br> - ROMS_SO_d025_plus01_momentum, ROMS output from plus 0.1 PSU sensitivity atmopshere-ocean momentum flux perturbation simulation, 4 netcdf-files:<br> -- ROMS_SO_d025_plus01_momentum_clim.46-55.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_plus01_momentum_clim.61-80.surf.nc, 2D surface or vertically integrated climatological monthly mean fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_plus01_momentum_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file<br> -- ROMS_SO_d025_plus01_momentum_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file<br> -- ROMS_SO_d025_plus01_momentum_yearly.41-80.surf.nc, 2D surface or vertically integrated annual mean fields for years 41 to 80, netcdf-file<br> -- ROMS_SO_d025_plus01_momentum_yearly.zlev.zonalmean.41-80.nc, vertically interpolated (z-level) and zonally averaged annual mean fields for years 41 to 80, netcdf-file<br> <br> <em>File headers</em><br> - ROMS_SO_d025_grd:<br> angle [radians]: angle between xi axis and east<br> f [second-1]: Coriolis parameter at RHO-points<br> h [meter]: Final bathymetry at RHO-points<br> hraw [meter]: Working bathymetry at RHO-points<br> lat_rho [degree_north]: latitude of RHO-points<br> lat_psi [degree_north]: latitude of PSI-points<br> lat_u [degree_north]: latitude of U-points<br> lat_v [degree_north]: latitude of V-points<br> lon_rho [degree_east]: longitude of RHO-points<br> lon_psi [degree_east]: longitude of PSI-points<br> lon_u [degree_east]: longitude of U-points<br> lon_v [degree_east]: longitude of V-points<br> mask_rho [-]: mask on RHO-points<br> mask_u [-]: mask on U-points<br> mask_v [-]: mask on V-points<br> pm [meter-1]: curvilinear coordinate metric in XI<br> pn [meter-1]: curvilinear coordinate metric in ETA<br> spherical [char]: Grid type logical switch<br> - ROMS_SO_d025_*_clim.*.surf.nc, ROMS_SO_d025_*_yearly.*.surf.nc:<br> time [days since 0000-01-01 00:00:00]: time<br> lon [degree_east]: longitude<br> lat [degree_north]: latitude<br> zeta [meter]: averaged free-surface elevation<br> temp [degree_celsius]: averaged potential temperature<br> salt [psu]: averaged salinity<br> rho [kilogram meter-3]: averaged density anomaly from model reference density of 1027 kilogram meter-3<br> mld [meter]: averaged mixed layer depth<br> n2 [seconds-2]: averaged buoyancy frequency (upper 100 m)<br> n2temp [seconds-2]: averaged buoyancy frequency due to temperature (upper 100 m)<br> n2salt [seconds-2]: averaged buoyancy frequency due to salinity (upper 100 m)<br> heat_100 [10^18 J]: averaged ocean heat content (upper 100 m)<br> heat_100_2000 [10^18 J]: averaged ocean heat content (between 100 m and 2000 m)" ;<br> - ROMS_SO_d025_*_mean.*.nc:<br> time [days since 0000-01-01 00:00:00]: time<br> lon [degree_east]: longitude<br> lat [degree_north]: latitude<br> zeta [meter]: averaged free-surface elevation<br> temp [degree_celsius]: averaged potential temperature<br> salt [psu]: averaged salinity<br> rho [kilogram meter-3]: averaged density anomaly from model reference density of 1027 kilogram meter-3<br> - ROMS_SO_d025_*_yearly.zlev.zonalmean.*.nc:<br> time [days since 0000-01-01 00:00:00]: time<br> lat [degree_north]: latitude of RHO-points<br> lat_v [degree_north]: latitude of V-points<br> depth [meter]: depth of levels<br> temp [degree_celsius]: averaged potential temperature<br> salt [psu]: averaged salinity<br> rho [kilogram meter-3]: averaged density anomaly from model reference density of 1027 kilogram meter-3<br> moc [10^6 meter^3 second^-1]: averaged meridional overturning circulation on V-points<br> Missing values: missing values are filled as '-9.99e+20'.</p> <p><em>Metadata</em><br> - README.txt, metadata, text format</p> <p><br> <strong>References:</strong></p> <p>Haumann, F. A. (2016): Southern Ocean response to recent changes in surface freshwater fluxes. Doctoral Thesis. ETH Zurich. doi:10.3929/ethz-b-000166276.</p> <p><br> <strong>Acknowledgments:</strong></p> <p>This work was supported by ETH Research Grant CH2-01 11-1 and by the SNSF grant numbers P2EZP2_175162 and P400P2_186681, as well as NSF’s SOCCOM Project under NSF Award No. PLR-1425989.</p>
Dataset supporting publication: "A novel ROM methodology to support the estimation of the energy savings under the Measurement and Verification protocol."
<p>DATASET suporting: "A novel ROM methodology to support the estimation of the energy savings under the Measurement and Verification protocol."</p> <p>Piccinini, Alessandro; Hajdukiewicz, Magdalena; D'Angelo, Letizia; Blanes, Luis Miguel; Keane, Marcus M.</p> <p>This paper presents a novel Reduced Order grey box Model (ROM) methodology, based on a ResistorCapacitor (RC) network, which supports the creation of the baseline energy consumption and the estimation of energy savings due to Energy Conservation Measures (ECMs) under the Measurement and Verification protocol. Within this scope, a description of the RC network, including a calculation of the parameters’ needed to execute the ROM, are presented. This ROM methodology is demonstrated on an educational building located in Sant Cugat, Spain as part of the H2020 GEOFIT project. The results presented in this paper demonstrate that the ROM is sufficiently accurate for the creation of the baseline energy consumption and for estimating the energy savings of different ECMs.</p>
Annual and monthly time series of estimated kelp spore dispersal times among ROMS cells in southern California, 1996 – 2006
These data describe the estimated dispersal duration of spores of giant kelp, Macrocystis pyrifera, among connectivity cells in a high-resolution, three-dimensional, spatiotemporally-explicit ocean circulation model (Regional Oceanic Modeling System, ROMS) in southern California, USA, for an 11-year period from the beginning of 1996 to the end of 2006. Asymmetrical and dynamic estimates of giant kelp spore dispersal durations connecting source and destination ROMS cells were estimated on monthly and annual timescales using minimum mean transit times.
A 3-km model configuration of the southern Benguela Current upwelling system: ROMS model data and Pyticles Lagrangian data
<p>This dataset contains model output data from the Regional Ocean Modelling System (ROMS) configuration of the southern Benguela upwelling system (SBUS) to study the interannual variability of Lagrangian transport in the SBUS. This is a 3-km model resolution that ran for 22 years from 1989-2011 period with the first 3 years considered as spin-up. The model outputs were archived at a daily frequency. The 3-km model was nested in a 7.5 km model resolution described by Ragoasha et.al., 2019.</p> <p>The model output data provided here is a monthly climatology (1995-2011) NetCDF file of the surface temperature, salinity, the velocity fields (<em>u,v & w</em>), and sea surface height (SSH). The file that contains the model grid is also provided.</p> <p>An eddy detection and tracking algorithm were also performed on the daily 3-km SSH model outputs to study mean eddy characteristics of the region for the 1992-2011 period. The file contains identifications of the Eddies detected and tracked in out model domain, their position (longitude and latitude), vorticity, amplitude, propagation and rotational speed.</p> <p> </p> <p>An example of a Pyticles (Gula et al., 2014; Ragoasha et.al., 2019) Lagrangian output subset for 3000 Lagrangian drifters tracked for 60 days. The drifters were released in the upper 100 m depth at an across-shore transect off Cape Point (34<sup>o</sup>S). A Matlab file is also provided for monthly (1992-2011) percentage of drifters that reach St Helena Bay (32<sup>o</sup>S) from Cape Point. </p> <p> </p> <p> </p> <p><strong>Dataset provided:</strong></p> <p>Monthly climatology file: “<em>roms_avg_Y1995M1-Y2011M12.nc”</em></p> <p>Model grid file: “<em>grid_roms_avg_r3km.nc”</em></p> <p>Eddy tracking file: “<em>TRA02_SEL01_DET02_eddies_r3km_1992M1_2011M12.nc”</em></p> <p>Pyticles Lagrangian experiment output example file: “<em>Pyticles_Y2010M10.nc”</em></p> <p>Monthly transport success Matlab file: <em>"R3km_monthly_transport_1992_2011.mat"</em></p> <p> </p> <p> </p> <p><strong>Citations:</strong></p> <p> </p> <p><strong>Ragoasha, N</strong>., Herbette, S., Cambon, G., Reason, C., Roy, C., 2019. Lagrangian pathways in the southern Benguela upwelling system. <em>Journal of Marine Systems</em>, 195: 50-66.</p> <p> </p> <p>Gula, J., Molemaker, M. J., & McWilliams, J. C., 2014. Submesoscale Cold Filaments in the Gulf Stream. <em>Journal of Physical Oceanography.,</em> 44 (10), 2617–2643. DOI: 10.1175/JPO-D-14-0029.1</p> <p> </p> <p><strong>Corresponding author:</strong></p> <p>M.N. Ragoasha, ORCID identifier: 0000-0002-1500-6259. Email: moagaboragoasha@gmail.com</p> <p> </p> <p><strong>Acknowledgements:</strong></p> <p>The authors acknowledge the funding of N. Ragoasha’s PhD by the South-Africa’s National Research Foundation (NRF, South Africa) and the French Institute for Research and Sustainable Development (IRD, France). This work was also supported by the French National Program LEFE/INSU under the project’s name Benguela Upwelling Innershelf</p> <p>647 Circulation (BUIC). This work was granted access to the HPC resources of [TGCC/CINES/IDRIS] under the allocation 2017- [DARI n<sup>◦</sup>A0020107443] attributed by GENCI (Grand Equipement National de Calcul Intensif).</p>
FIGURE 3. ROM 43608 in A faunivorous early sphenacodontian synapsid with a diastema
FIGURE 3. ROM 43608, holotype of Kenomagnathus scottae, gen. et sp. nov., close-up of anterior maxilla in medial aspect, from latero-ventral (above) and lateral (below). Scale bars equal 2 cm.
FIGURE 10. Chancelloria eros Walcott, 1920. ROM 62534 in Chancelloriids of the Cambrian Burgess Shale
FIGURE 10. Chancelloria eros Walcott, 1920. ROM 62534, RT. 1. Wet. 2. Detail of 1 (position marked by frame), wet. Note the common presence of 3+0 Allonnia-type sclerites (arrows) in a scleritome dominated by 5–7+1 Chancelloria- type sclerites.
FIGURE 9. Chancelloria eros Walcott, 1920. 1–3. ROM 57604 in Chancelloriids of the Cambrian Burgess Shale
FIGURE 9. Chancelloria eros Walcott, 1920. 1–3. ROM 57604, BW -130. Specimens of the lingulate brachiopod Acrothyra gregaria appear to be attached to the spines of the Chancelloria. The brachiopods are concentrated to what is interpreted as the apical part of the chancelloriid body. 1. Wet. 2. Detail of 1 (position marked by frame), dry. 3. Detail of 2 (position marked by frame), dry. 4. ROM 63055, ST, dry.
FIGURE 11. Chancelloria eros Walcott, 1920. ROM 49599A in Chancelloriids of the Cambrian Burgess Shale
FIGURE 11. Chancelloria eros Walcott, 1920. ROM 49599A, RQ 8.0. Arrows point to examples of 3+0 sclerites. 1. Dry. 2. Detail of 1 (position marked by frame), dry.
FIGURE 8. Chancelloria eros Walcott, 1920. 1, 2. ROM 49580 in Chancelloriids of the Cambrian Burgess Shale
FIGURE 8. Chancelloria eros Walcott, 1920. 1, 2. ROM 49580, ST. 1. Dry. 2. Detail of 1 (position marked by frame), dry. 3. ROM 62590, ST, dry.
FIGURE 7. Chancelloria eros Walcott, 1920. ROM 62588B in Chancelloriids of the Cambrian Burgess Shale
FIGURE 7. Chancelloria eros Walcott, 1920. ROM 62588B, BW -320. 1. Dry. 2. Detail of 1 (position marked by frame), dry. 3. Detail of 1 (position marked by frame), wet.
FIGURE 5. Chancelloria eros Walcott, 1920. 1. ROM 62538 in Chancelloriids of the Cambrian Burgess Shale
FIGURE 5. Chancelloria eros Walcott, 1920. 1. ROM 62538, ST talus, wet. Arrow points to empty area that may represent an apical orifice. 2. Detail of 1 (position marked by frame), wet. 3. ROM 62535A, BW -300, dry.
FIGURE 6. Chancelloria eros Walcott, 1920. ROM 62539 in Chancelloriids of the Cambrian Burgess Shale
FIGURE 6. Chancelloria eros Walcott, 1920. ROM 62539, BW -320. 1. Dry. 2. Detail of 1 (position marked by frame), wet.
Fig. 14. Cratokalotermes santanensis Bechly, photomicrographs. A. ROM 1764. B. Holotype, SMNS 66195 in The Species of Isoptera (Insecta) from the Early Cretaceous Crato Formation: A Revision
Fig. 14. Cratokalotermes santanensis Bechly, photomicrographs. A. ROM 1764. B. Holotype, SMNS 66195.
Fig. 5. Cratomastotermes wolfschwenningeri Bechly, photomicrographs. A. ROM 1746. B. AMNHSaI-1. C in The Species of Isoptera (Insecta) from the Early Cretaceous Crato Formation: A Revision
Fig. 5. Cratomastotermes wolfschwenningeri Bechly, photomicrographs. A. ROM 1746. B. AMNHSaI-1. C. Detail of wing apex, AMNHSaI-1. D. Detail of hind tarsus, AMNHSaI-1. E. Holotype, SMNS 66186.
Fig. 9. Hemibrycon huambonicus, ROM 55406 in A review of the Cis-Andean species of Hemibrycon Günther (Teleostei: Characiformes: Characidae: Stevardiinae), with description of two new species
Fig. 9. Hemibrycon huambonicus, ROM 55406, male, 70.0 mm SL. Scanning electron micrograph of right side upper and lower jaws. Scale bar = 1 mm.
Representation of submesoscale baroclinic instabilities in ROMS and MPAS-O
<h2>Idealized Model Outputs</h2> <p>This dataset archive contains a subset of the model outputs that are necessary for reproducing the analyses presented in the accompanying manuscript. The datasets correspond to either the MPAS-O or ROMS ocean models at resolutions ranging from 10 km to 100 m. Velocity and corresponding invariant (vorticity/divergence) variables and tracer variables are saved here with only their surface values. Additionally, all variables except those required to compute kinetic energy time series over the simulation period are only saved for a time window that corresponds to the shaded region in Figure 4 of the accompanying manuscript. Some grid metric variables necessary for MPAS-O calculations are also included within "MPAS-O_Initial_*.nc" files. There are two zipped tar directories (mpaso_winds.tar.gz and roms_winds.tar.gz) containing the outputs of all wind stress sensitivity tests needed to recreate the results shown in Figure 2. All datasets are saved in NetCDF format.</p>
SBC LTER: Regional Oceanic Modeling System (ROMS) Setup Files, Code, and Lagrangian Model Setup Files
This data contains all the necessary code, grid, forcing, initial, and boundary condition files for running the UCLA version of the Regional Oceanic Modeling System (ROMS) for the Santa Barbara Channel nested solution set that is analyzed in Dauhajre and McWilliams (2019): Nearshore Lagrangian Connectivity: Resolution Sensitivity and Submesoscale Influence. Along with this abstract and separate methods, a brief readme file (README_ROMS) contains other relevant details for running the simulations. The ROMS files in this data correspond to a one-way grid-nesting with the following horizontal resolutions: dx=1km, 300m, 100m, 36m that correspond to R1km, R300m, R100m, and R36m in the publication. In the data directories here, these grids have the following prefixes for all relevant files (grids, forcing, initial condition, and boundary conditions): “usw1” (dx=1km), “usw2” (dx=300m), “usw3” (dx=100m), and “usw4sbc” (dx=36m). The ROMS code is in fortran and requires compilation, with compilation instructions in the directory /src_ROMS_UCLA_2018 in the file “compile.sh”. All grid, forcing, initial, and boundary condition files are in netcdf form. The grid files are in the directory “grids”. Note that the R1km grid has 2 files: usw1_grd.nc and usw1_grd_samp.nc. The latter is a smaller version of the grid that focuses on the Santa Barbara Channel that can be used for the offline Lagrangian model for faster computation (which requires an analogous sub-sampling of the ROMS output). For running ROMS, usw1_grd.nc needs to be used as it corresponds to the entire domain. The atmospheric forcing, derived from a Weather Research and Forecasting model at dx=6km resolution is given in the directory “forcing_files”; all atmospheric forcing files are interpolated to the relevant ROMS grid and formatted to be used as inputs in ROMS. Each grid contains a file corresponding to precipitation (e.g., usw1_prec.nc), radiation (e.g., usw1_rad.nc), atmospheric temperature and specific humidity (
FIGURE 1. ROM 43608 in A faunivorous early sphenacodontian synapsid with a diastema
FIGURE 1. ROM 43608, holotype of Kenomagnathus scottae, gen. et sp. nov. Scale bar equals 2 cm.
Data rom: Stiffness anisotropy coordinates supracellular contractility driving long-range myotube-ECM alignment
<p>The ability of cells to organize into tissues with proper structure and function requires the effective coordination of proliferation, migration, polarization, and differentiation across length scales. Skeletal muscle is innately anisotropic; however, few biomaterials can emulate mechanical anisotropy to determine its influence on tissue patterning without introducing confounding topography. Here, we demonstrate that substrate stiffness anisotropy coordinates contractility-driven collective cellular dynamics resulting in C2C12 myotube alignment over millimeter-scale distances. When cultured on mechanically anisotropic liquid crystalline polymer networks (LCNs) lacking topography, C2C12 myoblasts collectively polarize in the stiffest direction. Cellular coordination is amplified through reciprocal cell-ECM dynamics that emerge during fusion, driving global myotube-ECM ordering. Conversely, myotube alignment was restricted to small local domains with no directional preference on mechanically isotropic LCNs of the same chemical formulation. These findings provide valuable insights for designing biomaterials that mimic anisotropic microenvironments and underscore the significance of stiffness anisotropy in orchestrating tissue morphogenesis.</p>
ROM model data for North Western Mediterranean Deep Water Formation
<p>ROM model data for North Western Mediterranean Deep Water Formation</p>
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