Find research datasets worth reusing

opencc-by-4.0Oct 2017View details →

Biases of STRUCTURE software when exploring introduction routes: Datasets, STRUCTURE outputs, simulation and analysis pipeline

This archive is associated with the article “Biases of STRUCTURE software when exploring introduction routes of invasive species”. Authors: Eric Lombaert, Thomas Guillemaud & Emeline Deleury. The file contains the 22,500 simulated datasets, the corresponding 900,000 STRUCTURE outputs and the summary statistics files. It also contains SIM_STRUCT which is a home-made pipeline developed for the purpose of carrying out analyzes as described in the manuscript. It can be used to simulate and summarize datasets, and to perform STRUCTURE analyses in batch on those simulated datasets. It is currently based on several softwares such as DIYABC, ARLSUMSTAT and STRUCTURE, as well as on some home-made PERL scripts. A tutorial is included. See the Readme file for details.

opencc-by-4.0Jan 2018View details →

Glacial ice sheet extent effects on tidal mixing and the global overturning circulation - Model Output

This dataset contains the output from the tide model and climate model simulations from the publication Wilmes et al. (2018) "Glacial ice sheet extent effects on tidal mixing and the global overturning circulation" submitted to Paleoceanography. The user is referred to the paper for details on the methodology. Dissipation files: Files beginning with "diss" contain tidal dissipation files calculated from the OTIS tide model output at 1/8th deg using the direct method. Files with the M2 constituent only are in .mat format and extend from 86deg S to 89deg N whereas the files containing all constituents (M2, S2, K1 and O1) are in netcdf format and extend from 90deg S to 90deg N. These files regridded and are used as the climate model tidal forcing. Dissipation file list: diss_dir_ze_1_8_rtp_21kyrBP_i6g_-I1.5_-t_8299008.nc Dissipation for LGM ICE-6G ZE ITdrag 1/8th deg diss_dir_ze_1_8_rtp_21kyrBP_i5g_-I1.5_-t_8299031.nc Dissipation for LGM ICE-5G ZE ITdrag 1/8th deg diss_dir_ze_1_8_rtp_00kyrBP_-I1.5_pdsal_8299034.nc Dissipation for PD ZE ITdrag 1/8th deg diss_dir_js_1_8_rtop_21kyrBP_i6g_-t_-I6.0_7673000.nc Dissipation for LGM ICE-6G JS ITdrag 1/8th deg diss_dir_js_1_8_rtop_21kyrBP_i5g_-t_-I6.0_7672999.nc Dissipation for LGM ICE-5G JS ITdrag 1/8th deg diss_dir_js_1_8_rtop_00kyrBP_-I6.0_7672998.nc  Dissipation for PD JS ITdrag 1/8th deg diss_dir_ze_m2_1_8_rtp_21kyrBP_i5g_blk5_NH_lmsk_-I1.5_8299652.mat  M2 dissipation for LGM ICE-5G blk1 + NH ICE-6G land mask ZE ITdrag 1/8th deg diss_dir_ze_m2_1_8_rtp_21kyrBP_i5g_blk5_-I1.5_8299534.mat  M2 dissipation for LGM ICE-5G blk5 ZE ITdrag 1/8th deg diss_dir_ze_m2_1_8_rtp_21kyrBP_i5g_blk4_-I1.5_8299533.mat  M2 dissipation for LGM ICE-5G blk4 ZE ITdrag 1/8th deg diss_dir_ze_m2_1_8_rtp_21kyrBP_i5g_blk3_-I1.5_8299531.mat  M2 dissipation for LGM ICE-5G blk3 ZE ITdrag 1/8th deg diss_dir_ze_m2_1_8_rtp_21kyrBP_i5g_blk2_-I1.5_8299530.mat M2 dissipation for LGM ICE-5G blk2 ZE ITdrag 1/8th deg diss_dir_ze_m2_1_8_rtp_21kyrBP_i5g_blk1_-I1.5_8299529.mat  M2 dissipation for LGM ICE-5G blk1 ZE ITdrag 1/8th deg diss_dir_ze_m2_1_8_rtp_21kyrBP_140mSLD_i6g_lmsk_-I1.5_8299543.mat M2 dissipation for PD 140mSLD ICE-6G land mask ZE ITdrag 1/8th deg diss_dir_ze_m2_1_8_rtp_21kyrBP_140mSLD_i5g_lmsk_-I1.5_8299542.mat M2 dissipation for PD 140mSLD ICE-5G land mask ZE ITdrag 1/8th deg diss_dir_ze_m2_1_8_rtp_21kyrBP_130mSLD_i6g_lmsk_-I1.5_8299544.mat M2 dissipation for PD 130mSLD ICE-6G land mask ZE ITdrag 1/8th deg diss_dir_ze_m2_1_8_rtp_21kyrBP_130mSLD_i5g_lmsk_-I1.5_8299541.mat M2 dissipation for PD 130mSLD ICE-5G land mask ZE ITdrag 1/8th deg diss_dir_ze_m2_1_8_rtp_21kyrBP_120mSLD_i6g_lmsk_-I1.5_8299545.mat M2 dissipation for PD 120mSLD ICE-6G land mask ZE ITdrag 1/8th deg diss_dir_ze_m2_1_8_rtp_21kyrBP_120mSLD_i5g_lmsk_-I1.5_8299540.mat M2 dissipation for PD 120mSLD ICE-5G land mask ZE ITdrag 1/8th deg diss_dir_ze_m2_1_8_rtp_21kyrBP_110mSLD_i6g_lmsk_-I1.5_8299546.mat M2 dissipation for PD 110mSLD ICE-6G land mask ZE ITdrag 1/8th deg diss_dir_ze_m2_1_8_rtp_21kyrBP_110mSLD_i5g_lmsk_-I1.5_8299539.mat M2 dissipation for PD 110mSLD ICE-5G land mask ZE ITdrag 1/8th deg diss_dir_ze_m2_1_8_rtp_21kyrBP_100mSLD_i6g_lmsk_-I1.5_8299547.mat M2 dissipation for PD 100mSLD ICE-6G land mask ZE ITdrag 1/8th deg diss_dir_ze_m2_1_8_rtp_21kyrBP_100mSLD_i5g_lmsk_-I1.5_8299538.mat M2 dissipation for PD 100mSLD ICE-5G land mask ZE ITdrag 1/8th deg diss_dir_ze_m2_1_8_rtp_21kyrBP_120mSLD_-I1.5_8299537.mat M2 dissipation for PD 120mSLD JS ITdrag 1/8th deg   Climate model output: UVic climate model output for all simulations in the paper has been compressed using tar and zip. Each folder contains the output yearly averages (tavg.xxx.nc) which have been used in the results section of the paper. The model input files are located in /data. The tidal input file is in /data/O_tideenrg_green.nc. Furthermore included are restart files (rest.xxx.nc), model code in /code, and the model exectuables. Climate mode output list: preind_tidal_ze_00kyr_rtop_-1.5_8299034_dir.tgz  Output from PIC lgm_tidal_ze_21kyr_i6g_rtop_-1.5_8299008_dir_tau_lgm.tgz Output from LGM_i6gT_lgmW lgm_tidal_ze_21kyr_i6g_rtop_-1.5_8299008_dir.tgz Output from LGM_i6gT_pdW lgm_tidal_ze_21kyr_i5g_rtop_-1.5_8299031_dir_tau_lgm.tgz Output from LGM_i5gT_lgmW lgm_tidal_ze_21kyr_i5g_rtop_-1.5_8299031_dir.tgz Output from LGM_i5gT_pdW lgm_tidal_ze_00kyr_rtop_-1.5_8299034_dir_tau_lgm.tgz Output from LGM_pdT_lgmW lgm_tidal_ze_00kyr_rtop_-1.5_8299034_dir.tgz Output from LGM_pdT_pdW preind_tidal_js_1_2_rtp_00kyrBP_-I1.0_7881173.tgz Output from PIC_1_2_rtp82 preind_js_1_2_SandS8.2_00kyrBP_82SNcb_-I1.0_8317333_dir.tgz Output from PIC_1_2_SS82 lgm_tidal_js_1_2_SandS8.2_00kyrBP_120mSLD_82SNcb_-t_-I1.0_8317331_dir.tgz Output from LGM_1_2_SS82_sldT lgm_tidal_js_1_2_SandS8.2_00kyrBP_82SNcb_-I1.0_8317333_dir.tgz Output from LGM_1_2_SS82_pdT lgm_tidal_js_1_2_rtop_00kyrBP_120mSLD_82SN_-t_-I1.0_8315693.tgz Output from LGM_1_2_rtp82_sldT lgm_tidal_js_1_2_rtop_00kyrBP_82SN_pdsal_-I1.0_8315702.tgz Output from LGM_1_2_rtp82_pdT

3. MC T0TEM output-UJV-material JRQ

<div>Fractesus project. Fracture test mini-CT. Master curve output JRQ. UJV.                                                                                       </div> <div> <div>   </div> </div>

3. MC T0TEM output_CIEMAT_A508Cl3_KJc_018TCT

<div>Fractesus project. Fracture test mini-CT. Master curve output SA508 Cl.3. CIEMAT.            </div>

3. MC T0TEM output-UJV-73W

<div>Fractesus project. Fracture test mini-CT. Master curve output 73W Irradiated. UJV.           </div>

opencc-by-4.0Nov 2023View details →

Model output: CICE6-WIM Antarctic sea ice data (2010--2019)

CICE6 model with waves-in-ice module (WIM) output analysed with k-means clustering to identify the Antarctic marginal ice zone. Daily data at a 1-degree horizontal resolution of the variables used to inform k-means and the physical processes which drive the Antarctic marginal ice zone are included. The model was spun-up over 2005–2009 and outputs were analysed over 2010–2019.   For further details, see  Day, N. S., Bennetts. L. G., O'Farrell, S. P., Alberello, A., & Montiel, F. (2023) Analysis of the Antarctic Marginal Ice Zone Based on Unsupervised Classification of Standalone Sea Ice Model Data.   Data files: <ul> <li><code>iceh_{year}.nc</code>: gridded NetCDF files containing the training variables for k-mean clustering and the fitted clusters.</li> <li><code>forcing_variables_2010_2019.csv</code>: flat file containing variables of CICE6-WIM forcing and sea ice dynamics.</li> <li><code>fsd_processes_2010_2019.csv</code>: flat file containing each term of the prognostic floe size distribution model in CICE6.</li> </ul>   Scripts: <ul> <li><code>ice_in</code>: CICE namelist</li> <li>Waves-in-Ice Module: <ul> <li><code>ice_floe.F90</code>: Appends the WIM to CICE6</li> <li><code>m_prams_waveice.F90</code>: wave-ice parameters</li> <li><code>m_waveattn.F90</code>: wave attenuation from sea ice</li> <li><code>m_fzero.F90</code>: useful mathematical functions and solvers</li> <li><code>m_waveice.F90</code>: wave-ice physics</li> </ul> </li> </ul> To implement the WIM into CICE6, subroutines within ice_floe.F90 should be called prior calling the floe size distribution subroutines in ice_step_mod.F90. For further details/assistance in implementing the WIM please contact Noah Day (<code>noah.day@adelaide.edu.au</code>).

B. FRAMATOME_MC T0TEM output ANP_4

<div>Fractesus project. Fracture test mini-CT. Master curve output ANP-4. Framatome.           </div>

Erebor LDC2A Hidden Dataset Output Catalogs

The catalogs output from our LISA global fit pipeline called Erebor. These datasets can be read in and analyzed with <a href="https://github.com/tlittenberg/lisacattools">lisacattools</a>. This catalog corresponds to the hidden dataset from the LISA Data Challenges 2A dataset (Sangria). The zip file downlaod is ~2.9 GB. The unzipped data files amount to ~15 GB of data.

Erebor LDC2A Training Dataset Output Catalogs

The catalogs output from our LISA global fit pipeline called Erebor. These datasets can be read in and analyzed with <a href="https://github.com/tlittenberg/lisacattools">lisacattools</a>. This catalog corresponds to the training dataset from the LISA Data Challenges 2A dataset (Sangria). The zip file downlaod is ~2.9 GB. The unzipped data files amount to ~15 GB of data.

openAug 2023View details →

Model output derived from SWE pacemaker experiments using MIROC6-AGCM

This data set is model output derived from numerical simulations using MIROC6-AGCM (Onuma et al., 2024, Journal of Climate). The contents are as below. - python: Python scripts for the visualization - figure: PNG files created by the Python scripts - data: model output data for the Python scripts. The data directory includes the below contents. -- LMIP: Output data simulated using MATSIRO6 with GSWP3 reanalysis data (LMIP experiment) are included. Monthly time-series data and regional averages for 1901-2010 derived from LMIP experiment (netCDF and csv files, respectively). -- AMIP: Output data simulated using MIROC6 with prescribed sea surface temperature and sea ice concentration (AMIP experiment) are included. Monthly time-series data and regional averages for 1901-2010 derived from AMIP ensemble experiments (netCDF and csv files, respectively). -- AMIP+SWE: Output data simulated using MIROC6 with prescribed sea surface temperature, sea ice concentration and snow water equivalent (AMIP+SWE experiment) are included. Monthly time-series data and regional averages for 1901-2010 derived from AMIP+SWE ensemble experiments (netCDF and csv files, respectively). Difference in a surface energy budget between AMIP+SWE and AMIP is also included (feedback_*.csv). -- AS-A: Statistical results analyzed from output data in AMIP+SWE and AMIP experiments (csv files). R_a (R_b) means the correlation coefficients of the outputs in AMIP+SWE (AMIP) for inter-annual change from 1901 to 2010 with those in LMIP. P means p-value.  RMSD_a (RMSD_b) means the root mean square difference of the outputs in AMIP+SWE (AMIP) for inter-annual change from 1901 to 2010 with those in LMIP. Tr_a (Tr_b, Tr_ref) means the inter-annual trends from 1901 to 2010 in AMIP+SWE (AMIP, LMIP). -- else: CMIP6 amip multi-models output, GlobSnow3 observation data and mask files for the regional averages. CMIP6 and GlobSnow3 data have been processed for analysis. *Regarding AMIP and AMIP+SWE data, the uploaded data are limited to ensemble mean data and run01 data due to data size that can be uploaded. If you need model outputs from run02 to run10, please contact Yukihiko Onuma (yonuma613@gmail.com).  The abbreviations of the output files are below. alb: land surface albedo clt: total cloud cover fraction ebflx: soil evaporation gdt: surface air temperature (GSWP3) hfls: latent heat flux hfss: sensible heat flux mrsos: surface soil moisture pr: total precipitation rlds: downward longwave radiation at the surface rldscs: clear-sky downward longwave radiation at the surface rls: net longwave radiation at the surface rlus: upward longwave radiation at the surface rsds: downward shortwave radiation at the surface rsdscs: clear-sky downward shortwave radiation at the surface rss: net shortwave radiation at the surface rsus: upward shortwave radiation at the surface snc: snow cover fraction snow: snow water equivalent T2: surface air temperature tsl_z0: surface soil temperature (top 0.05 m) tsl_z1: sub-surface soil temperature (top 0.05-0.25 m)

opencc-by-4.0Oct 2023View details →

Open access GIS database using T2 outputs

Open access GIS database using the ouputs from BRIDGE Task 2 (Innovation Laboratory - InnoLab).  This GIS dataset is composed by several shape files and pdf files with the inputs and results from the participatory mapping process.  For more information on the BRIDGE InnoLab Participatory Mapping process please look for the project deliverables and papers available in the BRIDGE Zenodo community (https://zenodo.org/communities/bridge_community/records?q=&l=list&p=1&s=10&sort=newest) or in the BRIDGE website (https://bridgecomunidade.pt/recursos/).

opencc-by-4.0May 2024View details →

Dam Break Videos and Outputs of the Paper "Increasing flood awareness through dam-break serious games"

This is the repository of the Dam-Break output results of the dams simulated in the paper "Increasing flood awareness through dam-break serious games".   This repository contains .csv of modeling results of the dams simulated in the paper. In addition, it contains videos showing the evolution of the simulated states (e.g., flood depths, velocities, and forces) for all dams.    For the Brumadinho analysis, we show the cross-section data used to simulate the dam.   If you have any questions, please reach em out in marcusnobrega.engcivil@gmail.com.

opencc-by-4.0Jan 2024View details →

Raw web API output related to Figure 3 from https://arxiv.org/abs/2309.09893

Raw web API output related to Figure 3 from https://arxiv.org/abs/2309.09893.   Can also be found here https://github.com/CQCL/One_Bit_Addition_Raw_Data

opencc-by-4.0May 2024View details →

diagnostic file output from MPAS-A(tmospheric) mode

diagnostic file output from MPAS-A(tmospheric) component which is in an unstructured grid

opencc-by-4.0Mar 2024View details →

Data, models, and outputs for an agent-based hydro-economic modeling study in an intensively irrigated region of the U.S. High Plains

In this dataset, we include all the models developed for the study "An integrated modeling approach to simulate human-crop-groundwater interactions in intensively irrigated regions", which is published in Environmental Modelling & Software (<a href="https://doi.org/10.1016/j.envsoft.2024.106120">https://doi.org/10.1016/j.envsoft.2024.106120</a>). Additionally, we provide all the data used in this study. Below, you will find a description of the contents of each file: <ul> <li>abm_modflow.zip: This file includes the agent-based hydro-economic model (ABM-MODFLOW), including model inputs and outputs, Python post-processing scripts, and the Windows batch script for the integration process.</li> <li>modflow.zip: This file contains the standalone MODFLOW model files. Each folder includes files for individual simulation periods, starting with a steady-state model for the predevelopment period, followed by seven transient models.</li> <li>modflow_rs.zip: This file contains the MODFLOW-RS model files. Given that remote sensing data is provided for years from 1984 onwards, only models for the post-1980 simulation periods are included. For model files corresponding to years prior to 1980, refer to modflow.zip.</li> <li>Figurers.zip: This file includes all data and Python scripts used to produce the figures in the main text.</li> <li>Tables.zip: This file contains all tables and the associated data included in the main text.</li> <li>Supporting_Info_Figures: This file includes all data and Python scripts used to produce the figures in the Supporting Information.</li> <li>Supporting_Info_Tables: This file contains all tables and the associated data included in the Supporting Information.</li> <li>Supporting_Info_Videos: This file stores Videos S1 and S2 of the Supporting Information, displaying the historical development of irrigation wells and groundwater-fed irrigated lands in the study area from 1946 to 2018.</li> </ul>

Assessing exchange-correlation functionals for heterogeneous catalysis of nitrogen species: VASP input and output

This contains all VASP data used in the paper titled "Assessing exchange-correlation functionals for heterogeneous catalysis of nitrogen species". Please read README.md file for the description of each file. Author list: Honghui Kim, Neung-Kyung Yu, Nianhan Tian, and Andrew J. Medford* arxiv:<a href="https://arxiv.org/abs/2403.14482"> https://arxiv.org/abs/2403.14482</a>

opencc-zeroJun 2024View details →

dryad36/100

Coupled PPE model output - land parameter impacts on the mean climate state

Terrestrial processes influence the atmosphere by controlling land-to-atmosphere fluxes of energy, water, and carbon. Prior research has demonstrated that parameter uncertainty drives uncertainty in land surface fluxes. However, the influence of land process uncertainty on the climate system remains underexplored. Here, we quantify how assumptions about land processes impact climate using a perturbed parameter ensemble for 18 land parameters in the Community Earth System Model (CESM2) under preindustrial conditions. We find that an observationally-informed range of land parameters generate biogeophysical feedbacks that significantly influence the mean climate state, largely by modifying evapotranspiration. Global mean land surface temperature ranges by 2.2°C across our ensemble (standard deviation = 0.5°C) and precipitation changes were significant and spatially variable. Our analysis demonstrates that the impacts of land parameter uncertainty on surface fluxes propagates to the entire Earth system, and provides insights into where and how land process uncertainty influences climate.

SI3 sea-ice hourly output for SI3-BBM and SI3-default Pan-Arctic simulations (Brodeau et al., 2024, final version)

These netCDF files contain the simulated SI3 sea-ice hourly output for experiments SI3-BBM and SI3-EVP that are discussed in the following paper: Implementation of a brittle sea-ice rheology in an Eulerian, finite-difference, C-grid modeling framework:        Impact on the simulated deformation of sea-ice in the Arctic by Laurent Brodeau, Pierre Rampal, Einar Ólason and Véronique Dansereau, in Geoscientific Model Development (GMD), 2024.   More specifically, they contain: <ul> <li>hourly sea-ice velocity (u,v) vector (m/s)</li> <li>hourly sea-ice concentration</li> <li>hourly  sea-ice volume per area (m)</li> <li>hourly sea-ice damage</li> <li> </li> </ul> File <code>NANUK4_ICE-BBM2412_1h_19961201_19970420_icemod.nc4</code> contains data for experiment "SI3-BBM" File <code>NANUK4_ICE-EVP2403_1h_19961201_19970420_icemod.nc4</code> contains data for experiment "SI3-default" File <code>mesh_mask_NANUK4_L31_4.2_1stLev.nc</code> contains the metrics of the horizontal grid of the model (NEMO regional Arctic configuration named NANUK4).

Output data for: Flammable Futures – Storylines of climatic impacts on wildfire events and palm oil plantations in Indonesia

This repository contains the output data associated with the publication "Flammable Futures – Storylines of climatic impacts on wildfire events and palm oil plantations in Indonesia". It contains the FLAM modeled burned area and the GLOBIOM output, as well as the a downscaling grid. Descriptions of the results can be found in the publication (DOI will follow).

A regional high-resolution (1/12 degree) coupled ocean-ecosystem model (INCOIS-BIO-ROMS) output for Indian Ocean

The dataset contains sea-surface temperature, sea-surface salinity, sea-surface dissolved inorganic carbon, sea-surface total alkalinity, sea-surface pH, and sea-surface partial pressure of CO2 for the Indian Ocean region. The data is available from 1980 to 2019 on a monthly time scale. Each of these data has a spatial resolution of 1/12º.