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2,837 results for “climate data”

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edi60/100

Climate data for saddle catchment sensor network, 2017 - ongoing.

Spatial and temporal variability characterizes virtually all ecosystems, with resource supply changing over the course of growing season and across years due to climate variation. To better understand spatial heterogeneity in ecological response across landscape positions, we established a 16-node sensor array within a 45 hectare catchment landscape that measures temporal variability of important biogeochemical and hydrological controls on ecosystem processes. The array was established at the Niwot Saddle catchment in order to accompany long term water quality and discharge records taken at the top and bottom of this catchment. The region forms an important ecological linkage between the the terrestrial areas of the Niwot Ridge LTER and the aquatic component in the Green Lakes Valley.

openCC (other)Apr 2025View details →

edi60/100

Climate data for C1 data loggers (CR23X and CR1000), 2000 - ongoing, daily.

Climatological data were collected from the C1 climate station on Niwot Ridge (3018 m elevation) throughout the year. From 2000-06-24 to 2013-03-25, data were recorded using a Campbell Instruments CR23X data logger. Starting 2013-03-27, data were recorded using a Campbell Instruments CR1000 data logger. Maximum and minimum values were recorded instantaneously, with a sampling interval of 5 seconds. Daily means and totals were calculated from 17,280 individual measurements. The CR23X logger was programmed to generate both hourly and daily output. The CR1000 logger generated daily, hourly, and minute data until 2014-09-10, when these time periods were discontinued and only 10 minute raw data were collected.

openCC (other)Mar 2025View details →

edi60/100

Climate data for saddle data loggers (CR23X and CR1000), 2000 - ongoing, daily.

Climatological data were collected from the saddle climate station on Niwot Ridge (3525 m elevation) throughout the year. From 2000-06-24 to 2012-03-24, data were recorded using a Campbell Instruments CR23X data logger. Subsequently, data were recorded using a Campbell Instruments CR1000 data logger. Maximum and minimum values were recorded instantaneously, with a sampling interval of 5 seconds. Daily means and totals were calculated from 17,280 individual measurements. The CR23X logger was programmed to generate both hourly and daily output. The CR1000 logger generated daily, hourly, and minute data until September 2014, and 10 minute and minute data thereafter.

openCC (other)Mar 2025View details →

zenodo56/100

Sea-ice induced Southern Ocean subsurface warming and surface cooling in a warming climate: ROMS model data

Abstract: 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). Contacts: F. Alexander Haumann, ORCID: 0000-0002-8218-977X. Email: alexander.haumann@gmail.com License: 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/ Citations: 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 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 Data processing: 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). Standards: 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) Contents: Data - ROMS_SO_d025_grd.nc, ROMS grid file (Note: one row of ghost points on either side of the grid), compressed netcdf-file - ROMS_SO_d025_ref_spinup, ROMS output from reference spin-up simulation, 4 netcdf-files:   -- 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   -- ROMS_SO_d025_ref_spinup_mean.31-40.nc, 3D averaged fields for years 31 to 40, netcdf-file   -- 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   -- 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 - ROMS_SO_d025_minus01_spinup, ROMS output from minus 0.1 PSU sensitivity spin-up simulation, 4 netcdf-files:   -- 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   -- ROMS_SO_d025_minus01_spinup_mean.31-40.nc, 3D averaged fields for years 31 to 40, netcdf-file   -- 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   -- 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 - ROMS_SO_d025_plus01_spinup, ROMS output from plus 0.1 PSU sensitivity spin-up simulation, 4 netcdf-files:   -- 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   -- ROMS_SO_d025_plus01_spinup_mean.31-40.nc, 3D averaged fields for years 31 to 40, netcdf-file   -- 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   -- 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 - ROMS_SO_d025_ref_ctrl, ROMS output from reference control simulation, 4 netcdf-files:   -- 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   -- 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   -- ROMS_SO_d025_ref_ctrl_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file   -- ROMS_SO_d025_ref_ctrl_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file   -- 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   -- 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 - ROMS_SO_d025_minus01_ctrl, ROMS output from minus 0.1 PSU sensitivity control simulation, 4 netcdf-files:   -- 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   -- 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   -- ROMS_SO_d025_minus01_ctrl_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file   -- ROMS_SO_d025_minus01_ctrl_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file   -- 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   -- 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 - ROMS_SO_d025_plus01_ctrl, ROMS output from plus 0.1 PSU sensitivity control simulation, 4 netcdf-files:   -- 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   -- 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   -- ROMS_SO_d025_plus01_ctrl_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file   -- ROMS_SO_d025_plus01_ctrl_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file   -- 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   -- 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 - ROMS_SO_d025_ref_seaice, ROMS output from reference sea-ice freshwater flux perturbation simulation, 4 netcdf-files:   -- 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   -- 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   -- ROMS_SO_d025_ref_seaice_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file   -- ROMS_SO_d025_ref_seaice_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file   -- 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   -- 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 - ROMS_SO_d025_minus01_seaice, ROMS output from minus 0.1 PSU sensitivity sea-ice freshwater flux perturbation simulation, 4 netcdf-files:   -- 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   -- 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   -- ROMS_SO_d025_minus01_seaice_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file   -- ROMS_SO_d025_minus01_seaice_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file   -- 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   -- 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 - ROMS_SO_d025_plus01_seaice, ROMS output from plus 0.1 PSU sensitivity sea-ice freshwater flux perturbation simulation, 4 netcdf-files:   -- 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   -- 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   -- ROMS_SO_d025_plus01_seaice_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file   -- ROMS_SO_d025_plus01_seaice_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file   -- 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   -- 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 - ROMS_SO_d025_ref_glacial, ROMS output from reference glacial meltwater flux perturbation simulation, 4 netcdf-files:   -- 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   -- 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   -- ROMS_SO_d025_ref_glacial_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file   -- ROMS_SO_d025_ref_glacial_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file   -- 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   -- 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 - ROMS_SO_d025_minus01_glacial, ROMS output from minus 0.1 PSU sensitivity glacial meltwater flux perturbation simulation, 4 netcdf-files:   -- 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   -- 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   -- ROMS_SO_d025_minus01_glacial_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file   -- ROMS_SO_d025_minus01_glacial_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file   -- 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   -- 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 - ROMS_SO_d025_plus01_glacial, ROMS output from plus 0.1 PSU sensitivity glacial meltwater flux perturbation simulation, 4 netcdf-files:   -- 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   -- 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   -- ROMS_SO_d025_plus01_glacial_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file   -- ROMS_SO_d025_plus01_glacial_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file   -- 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   -- 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 - ROMS_SO_d025_ref_momentum, ROMS output from reference atmopshere-ocean momentum flux perturbation simulation, 4 netcdf-files:   -- 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   -- 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   -- ROMS_SO_d025_ref_momentum_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file   -- ROMS_SO_d025_ref_momentum_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file   -- 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   -- 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 - ROMS_SO_d025_minus01_momentum, ROMS output from minus 0.1 PSU sensitivity atmopshere-ocean momentum flux perturbation simulation, 4 netcdf-files:   -- 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   -- 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   -- ROMS_SO_d025_minus01_momentum_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file   -- ROMS_SO_d025_minus01_momentum_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file   -- 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   -- 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 - ROMS_SO_d025_plus01_momentum, ROMS output from plus 0.1 PSU sensitivity atmopshere-ocean momentum flux perturbation simulation, 4 netcdf-files:   -- 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   -- 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   -- ROMS_SO_d025_plus01_momentum_mean.46-55.nc, 3D averaged fields for years 46 to 55, netcdf-file   -- ROMS_SO_d025_plus01_momentum_mean.61-80.nc, 3D averaged fields for years 61 to 80, netcdf-file   -- 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   -- 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   File headers - ROMS_SO_d025_grd:     angle [radians]: angle between xi axis and east     f [second-1]: Coriolis parameter at RHO-points     h [meter]: Final bathymetry at RHO-points     hraw [meter]: Working bathymetry at RHO-points     lat_rho [degree_north]: latitude of RHO-points     lat_psi [degree_north]: latitude of PSI-points     lat_u [degree_north]: latitude of U-points     lat_v [degree_north]: latitude of V-points     lon_rho [degree_east]: longitude of RHO-points     lon_psi [degree_east]: longitude of PSI-points     lon_u [degree_east]: longitude of U-points     lon_v [degree_east]: longitude of V-points     mask_rho [-]: mask on RHO-points     mask_u [-]: mask on U-points     mask_v [-]: mask on V-points     pm [meter-1]: curvilinear coordinate metric in XI     pn [meter-1]: curvilinear coordinate metric in ETA     spherical [char]: Grid type logical switch - ROMS_SO_d025_*_clim.*.surf.nc, ROMS_SO_d025_*_yearly.*.surf.nc:     time [days since 0000-01-01 00:00:00]: time     lon [degree_east]: longitude     lat [degree_north]: latitude     zeta [meter]: averaged free-surface elevation     temp [degree_celsius]: averaged potential temperature     salt [psu]: averaged salinity     rho [kilogram meter-3]: averaged density anomaly from model reference density of 1027 kilogram meter-3     mld [meter]: averaged mixed layer depth     n2 [seconds-2]: averaged buoyancy frequency (upper 100 m)     n2temp [seconds-2]: averaged buoyancy frequency due to temperature (upper 100 m)     n2salt [seconds-2]: averaged buoyancy frequency due to salinity (upper 100 m)     heat_100 [10^18 J]: averaged ocean heat content (upper 100 m)     heat_100_2000 [10^18 J]: averaged ocean heat content (between 100 m and 2000 m)" ; - ROMS_SO_d025_*_mean.*.nc:     time [days since 0000-01-01 00:00:00]: time     lon [degree_east]: longitude     lat [degree_north]: latitude     zeta [meter]: averaged free-surface elevation     temp [degree_celsius]: averaged potential temperature     salt [psu]: averaged salinity     rho [kilogram meter-3]: averaged density anomaly from model reference density of 1027 kilogram meter-3 - ROMS_SO_d025_*_yearly.zlev.zonalmean.*.nc:     time [days since 0000-01-01 00:00:00]: time     lat [degree_north]: latitude of RHO-points     lat_v [degree_north]: latitude of V-points     depth [meter]: depth of levels     temp [degree_celsius]: averaged potential temperature     salt [psu]: averaged salinity     rho [kilogram meter-3]: averaged density anomaly from model reference density of 1027 kilogram meter-3     moc [10^6 meter^3 second^-1]: averaged meridional overturning circulation on V-points Missing values: missing values are filled as '-9.99e+20'. Metadata - README.txt, metadata, text format References: Haumann, F. A. (2016): Southern Ocean response to recent changes in surface freshwater fluxes. Doctoral Thesis. ETH Zurich. doi:10.3929/ethz-b-000166276. Acknowledgments: 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.

opencc-by-4.0Dec 2019View details →

edi56/100

Supporting data for “Climate Intervention through Stratospheric Aerosol Injection may partially mitigate marine heatwaves"

Although climate intervention aims to lower the global average temperature, the potential impact of Stratospheric Aerosol Injection on marine heatwaves (MHW) has not been thoroughly examined. This spatial dataset provides global and regional MHW metrics—such as frequency, maximum intensity, and duration—from the Community Earth System Model, version 2 (CESM2), using the baseline scenario SSP2-4.5, referred to as a no climate intervention scenario, and the ARISE-SAI ensemble. The ARISE-SAI model uses the SSP2-4.5 scenario, introducing stratospheric aerosol injection at approximately 21 km in 2035, aiming to keep global mean surface air temperature near 1.5°C for ARISE-SAI-1.5 and near 1.0°C for ARISE-SAI-1.0 above pre-industrial levels. The dataset includes global MHW properties for the historical period (1990-2009), the current period under SSP2-4.5 emission scenario (2015-2034), and future scenarios under SSP2-4.5, ARISE-SAI-1.5, and ARISE-SAI-1.5 for 2050-2059 and 2060-2069.

openCC (other)Nov 2025View details →

edi56/100

Harvard Forest Climate Data since 1964

This dataset provides daily minimum, maximum, and mean air temperature and 24-hour precipitation data from Harvard Forest for long-term climate studies. It combines measurements from the original manual weather station (Shaler Met Station, 1964-2002, 42.53167 N, 72.18937 W, dataset HF000) with measurements from the current automated weather station (Fisher Met Station, since 2001, 42.53311 N, 72.18968 W, dataset HF001). Gaps in the Shaler data were filled using data from nearby stations. Data from a 12-month period when both stations were operational were used to adjust the Shaler data to account for differences in microclimate at the two sites. This dataset is updated annually.

openCC0Feb 2026View details →

zenodo52/100

JasonAlongTrack: A reformatted version of the Integrated Multi-Mission Ocean Altimeter Data for Climate Research Version 5.1

JasonAlongTrack contains geo-registered along-track sea surface height anomalies with respect to the DTU15 mean sea surface at 1-second intervals from Jason-class altimeters, reformatted for convenience into a 3D array with dimensions of along-track direction by geographically sorted track number by cycle.This is a reformatted version of Beckley et al.'s Integrated Multi-Mission Ocean Altimeter Data for Climate Research complete time series Version 5.1 dataset, available from <a href="https://podaac.jpl.nasa.gov/dataset/MERGED_TP_J1_OSTM_OST_ALL_V51">https://podaac.jpl.nasa.gov/dataset/MERGED_TP_J1_OSTM_OST_ALL_V51</a>.   The changes are as follows. Altimeter passes are sorted according to their initial longitude, then split into descending and ascending potions with all descending tracks preceding all ascending tracks. Descending tracks are then flipped so that latitude increases in the alongtrack direction for all tracks. This leads to a 3373 x 254 matrix of observational locations, with the first dimension being the along-track location and the second dimension being the track index. Sea surface height anomaly, time, and flag values are then placed into their correct locations within this matrix, such that these three variables are all of size 3373 x 254 x K where K is the number of cycles, currently 1087. A very good approximation to the time at each of the 3373 x 254 x K observation points is constructed with a length K array of cycles times together with a 3373 x 254 array of time offsets. A median-based editing criterion in introduced to identify a small number of suspect data points.  These are set to a value of NaN in sla, but their positions and values are recorded in rejected_index and rejected_values, respectively.  The DTU15 mean dynamic topography (mdt) is included, in addition to the mean sea surface field already provided, interpolated onto the track locations using bicubic interpolation.  Finally, an estimate of the small-scale noise level, sigma, is produced using a wavelet transform filter.

opencc-by-4.0Nov 2023View details →

zenodo52/100

Survey data on climate policy in three countries (Peru, Ghana, Philippines) within the project "Sustainable Middle Classes in Middle Income Countries: Transforming Carbon Consumption Patterns (SMMICC)"

The unprecedented growth of the new middle classes in middle income developing countries implies a strong growth in both consumption and carbon emissions. The research project Sustainable Middle Classes in Middle Income Countries (SMMICC) investigates the drivers of carbon consumption choices of the new middle classes and policy options to decrease their carbon footprints, including the implementation of carbon taxes The research of the authors generated quantitative data on the acceptability of carbon taxes in three countries (Peru, Ghana, Philippines).   The data is provided in the following formats: - 2024-07-26_malerba_10.5281/zenodo.12662722_ghana.csv - 2024-07-26_malerba_10.5281/zenodo.12662722_peru.csv - 2024-07-26_malerba_10.5281/zenodo.12662722_philippines.csv - 2024-07-26_malerba_10.5281/zenodo.12662722_ghana.dta - 2024-07-26_malerba_10.5281/zenodo.12662722_peru.dta - 2024-07-26_malerba_10.5281/zenodo.12662722_philippines.dta Additionally, the codebooks on variables of questionnaire and political parties in each country are attached in a csv format.

opencc-by-4.0Jul 2024View details →

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Decadal BIOCLIM estimates based on ISIMIP3b climatic forcing data for the European continent

This dataset contains BIOCLIM variables (plus huss, sfcwind, rsds) which have been prepared and calculated from the original ISIMIP3b bias-adjusted climate forcing data from 5 GCM models (obtained on 2023-08-07). For more information on the original data and its properties, please see the ISIMIP3b modelling protocol and here specifically the climate forcing section <a href="https://protocol.isimip.org/#/ISIMIP3b/31-forcing-data" target="_blank" rel="noopener">https://protocol.isimip.org/#/ISIMIP3b/31-forcing-data</a> and <a href="https://doi.org/10.5194/gmd-17-1-2024">Frieler et al. (2024)</a>. The original climate forcing data (global extent, daily temporal grain) were cropped to the European extent and spatial-temporally aggregated. Here 10 year (decadal) steps were chosen as target climatology. For each time slot (e.g. 10 years) and scenario (historical or ssps) the following 22 variables were calculated: bioclim01 = Annual Mean Temperature bioclim02 = Mean Diurnal Range (Mean of monthly (max temp - min temp)) bioclim03 = Isothermality (BIO2/BIO7) (×100) bioclim04 = Temperature Seasonality (standard deviation ×100) bioclim05 = Max Temperature of Warmest Month bioclim06 = Min Temperature of Coldest Month bioclim07 = Temperature Annual Range (BIO5-BIO6) bioclim08 = Mean Temperature of Wettest Quarter bioclim09 = Mean Temperature of Driest Quarter bioclim10 = Mean Temperature of Warmest Quarter bioclim11 = Mean Temperature of Coldest Quarter bioclim12 = Annual Precipitation bioclim13 = Precipitation of Wettest Month bioclim14 = Precipitation of Driest Month bioclim15 = Precipitation Seasonality (Coefficient of Variation) bioclim16 = Precipitation of Wettest Quarter bioclim17 = Precipitation of Driest Quarter bioclim18 = Precipitation of Warmest Quarter bioclim19 = Precipitation of Coldest Quarter huss = Average (arithmetric mean) specific humidity rsds = Average (arithmetric mean) Surface downwelling shortwave radiation sfcwind = Average near-surface wind speed (arithmetric mean) --- Data properties: <table> <tbody> <tr> <td>Shared Socioeconomic Pathways (SSP)</td> <td>SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5</td> </tr> <tr> <td>General circulation models (GCMs)</td> <td>GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1-2-HR, MRI-ESM2-0, UKESM1-0-LL</td> </tr> <tr> <td>Spatial grain</td> <td>0.5 degree (~50km²)</td> </tr> <tr> <td>Geographic projection</td> <td>WGS 84</td> </tr> <tr> <td>Temporal grain</td> <td>10 year steps</td> </tr> <tr> <td>Spatial extent</td> <td>Continental Europe including Turkey (see screenshot)</td> </tr> <tr> <td>Temporal extent</td> <td>1850 to 2010 (Historical), 2010 - 2100 (Future)</td> </tr> <tr> <td>Number of variables</td> <td>22</td> </tr> </tbody> </table> All files are provided in netCDF (nc) format. The preprocessed datasets are provided as it and the author takes no responsibility for errors or misuse.

opencc-by-4.0Aug 2024View details →

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Rainfall data from WRF simulations for the Atacama Desert for present and mid-Pliocene climate

We provide model output for rainfall from WRF experiments for the present-day and mid-Pliocene climate. These are netCDF files that contain processed data shown in figures of Reyers et al. (accepted). Details on the files and content are listed in the primary data information Reyers_et_al_primary_data_information.pdf Refer to Reyers et al. (2022) for the full information on the data production and interpretation. This work used resources of the Deutsches Klimarechenzentrum (DKRZ) granted by its Scientific Steering Committee (WLA) under project ID bb1198. The research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Projektnummer 268236062 – SFB1211 "Earth-evolution at the dry limit" (https://sfb1211.uni-koeln.de/). Reference Reyers, M., Fiedler, S., Ludwig, P., Böhm, C., Wennrich, V., and Shao, Y.: On the importance of moisture conveyor belts from the tropical East Pacific for wetter conditions in the Atacama Desert during the Mid-Pliocene, Clim. Past Discuss. [preprint], https://doi.org/10.5194/cp-2022-72, 2022, accepted.

opencc-by-4.0Feb 2023View details →

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Climate data from the former Arctic LTER Toolik Inlet Wet Sedge Flux site, Toolik Field Station, Alaska 2017 to 2025.

One-minute averages of air temperature and relative humidity, soil temperature and moisture, and solar radiation from 2017 to 2025 for the former Arctic LTER Toolik wet sedge eddy covariance flux site. This site was originally set up for seasonal eddy covariance flux measurements during the summers of 2010–2015 and partially during winters starting in 2014, until 15 June 2016. Flux data are reported in Eugster et al.(2020)(doi:10.5194/amt-2019-402). IMPORTANT NOTE: The data has only been checked for obvious outliers. Use with caution since most of the data has not been carefully checked. It was decided to release this version instead of waiting until there were resources for a complete check.

openCC (other)Jan 2026View details →

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Climate data from the SINERR/GCE/UGAMI weather station at Marsh Landing on Sapelo Island, Georgia, from 01-Jan-2015 to 31-Dec-2015

Air temperature, relative humidity, barometric pressure, precipitation, photosynthetically-available and total solar radiation, and wind speed and direction were measured using an automated Campbell Scientific Instruments climate station installed at Marsh Landing on Sapelo Island, Georgia. Observations were logged at 15 minute intervals throughout the study period. The sensors were mounted on a 10m aluminum tower, with wind sensors mounted at the top, light sensors at approximately 5m, and other sensors at 2-3m to minimize interference from the surrounding landscape. This climate station was jointly operated by the Sapelo Island National Estuarine Research Reserve, the Georgia Coastal Ecosystems LTER Project, and University of Georgia Marine Institute.

openCustomJan 2020View details →

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Climate data from the SINERR/GCE/UGAMI weather station at Marsh Landing on Sapelo Island, Georgia, from 01-Jan-2016 to 31-Dec-2016

openCustomJan 2020View details →

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Long-term Climate data from the SINERR/GCE/UGAMI weather station at Marsh Landing on Sapelo Island, Georgia, from 03-Jan-2003 to 31-Dec-2019

Air temperature, relative humidity, barometric pressure, precipitation, photosynthetically-available and total solar radiation, and wind speed and direction were measured using an automated Campbell Scientific Instruments climate station installed at Marsh Landing on Sapelo Island, Georgia. Observations were logged at 15 minute intervals throughout the study period. The sensors were mounted on a 10m aluminum tower, with wind sensors mounted at the top, light sensors at approximately 5m, and other sensors at 2-3m to minimize interference from the surrounding landscape. Annual data sets from 2003 to 2019 were then synthesized and standardized to create a long-term, monotonic time series data set that will be updated annually. This climate station was jointly operated by the Sapelo Island National Estuarine Research Reserve, the Georgia Coastal Ecosystems LTER Project, and University of Georgia Marine Institute.

openCC (other)Oct 2020View details →

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Climate data from the SINERR/GCE/UGAMI weather station at Marsh Landing on Sapelo Island, Georgia, from 01-Jan-2017 to 31-Dec-2017

openCC (other)Jan 2020View details →

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Long-term climate indices (SPEI and scPDSI) derived from monthly meteorology data collected at USHCN stations in the northern Chihuahuan Desert of the United States, 1911-2021

Drought indices — Standardized Precipitation Evapotranspiration Index (SPEI) and the self-calibrating Palmer Drought Severity Index (scPDSI) —where derived from 9 United States Historical Climate Network (USHCN) stations on the Chihuahuan Desert in North America for this dataset. USHCN is a subset of the NOAA Cooperative Observer Program (COOP) Network, which consists of selected sites based on spatial coverages and completeness of data. Monthly precipitation depths, minimum, maximum and mean temperature were pulled from the dataset. These drought indices were derived using the SPEI package and scPDSI packages in R. Potential evapotranspiration was also calculated in R using the Thornthwaite method. All 9 sites are within the bounds of the Chihuahuan Desert in the state of New Mexico, with a single site (EL PASO) in the state of Texas.

openCC0Oct 2022View details →

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Data for: Climate warming and drought effects on volatile organic compound emissions from Solidago altissima

Volatile organic compounds (VOCs) were collected from Solidago altissima in drought and warming treatments in the KBS-LTER Rain Exclusion Experiment (REX). This sampling took place in July 2022 when the plants had been experiencing warming (via open-top chambers) for 20 months, and drought (via rainout shelters) for 3 weeks. The data presented here are the final data files used for analysis, and contain VOC abundance values per plant across the four climate treatments: ambient, warmed, drought, and warmed + drought. Code is available at: https://github.com/dobsonk2/REX_VOCs (https://doi.org/10.5281/zenodo.15169943)

openCC (other)Apr 2025View details →

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Climate data for C1 data logger (CR1000), 2015 - ongoing, 10 minute.

Climatological data are collected from the C1 climate station on Niwot Ridge (3018 m elevation) throughout the year. Starting 2015-01-01, the CR1000 logger was programmed to collect raw data at a 10 minute resolution. Maximum and minimum values were recorded instantaneously, with a sampling interval of 5 seconds. These data represent the native (ten minute) resolution data from that point onward, with quality flags applied but no data removed.

openCC (other)May 2025View details →

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Climate data for D1 data logger (CR1000), 2014 - ongoing, 10 minute.

Climatological data are collected from the D1 climate station on Niwot Ridge (3738 m elevation) throughout the year. Data were recorded using a Campbell Instruments CR1000 data logger. Maximum and minimum values are recorded instantaneously, with a sampling interval of 5 seconds and programmed to generate 10 minute output. These data represent the native resolution (10 minute) data from 2014 onward, with quality flags applied but no data removed.

openCC (other)May 2025View details →

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Climate data for saddle data logger (CR1000), 2014 - ongoing, 10 minute.

Climatological data were collected from the saddle climate station on Niwot Ridge (3525 m elevation) throughout the year. Data were recorded using a Campbell Instruments CR1000 data logger. Maximum and minimum values are recorded instantaneously, with a sampling interval of 5 seconds. This instrument was programmed to generate 10 minute output starting in September 2014. These data represent the native (10-minute) resolution data from that point from onward, with quality flags applied but no data removed.

openCC (other)May 2025View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record