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Dataset results
18 results for “Force Feedback”
Supplementary data for "Effect of Uncertainty in Water Vapor Continuum Absorption on CO2 Forcing, Longwave Feedback, and Climate Sensitivity"
<h3>This dataset is supplementary to the article "Effect of Uncertainty in Water Vapor Continuum Absorption on CO2 Forcing, Longwave Feedback, and Climate Sensitivity".</h3> <h3>spectral_olr.nc</h3> <p>This file contains the spectral outgoing longwave radiation (OLR) calculated using the line-by-line radiative transfer model ARTS and the radiative-convective equilibrium model konrad. It contains spectral OLR for surface temperatures from 270K to 330K for different strengths of the water vapor continuum absorption.</p> <h3>opacity_emission_level.py</h3> <p>This file also contains the spectrally resolved optical depth and the emission level of outgoing longwave radiation for the considered absorption species (H2O lines, H2O continuum, H2O self continuum, H2O foreign continuum, CO2, N2, and O2).</p> <h3>continuum_reference_conditions.nc</h3> <p>This file contains the reference continuum absorption coefficients that were used to calculate the adjustment to the foreign continuum for the single-constraint experiment.</p> <h3>continuum_all_profiles.nc</h3> <p>This file contains the reference continuum absorption coefficients that were used to calculate the adjustment to the foreign continuum for the general-constraint experiment.</p> <h3>modified_continuum_input_files_single_constraint.zip and modified_continuum_input_files_general_constraint.zip</h3> <p>These files contain the modified continuum data files used for the implementation of the MT_CKD continuum model in the line-by-line model ARTS for the single-constraint and general-constraint experiments, respectively.</p> <h3>tau_column.nc and tau_profile.nc</h3> <p>These files contain separately for each absorption species the vertically integrated opacity spectra, and the opacity profiles at two selected wavenumbers.</p> <p> </p>
Maintenance of Convectively Coupled Kelvin waves: Relative Importance of Internal Thermodynamic Feedback and External Momentum Forcing (Code and Data)
<p>This is the dataset and code for generating all figures for the journal article named "Maintenance of Convectively Coupled Kelvin Waves: Relative Importance of Internal Thermodynamic Feedback and External Momentum Forcing," The article was written by Mu-Ting Chien and Daehyun Kim and submitted to Geophysical Research Letters in 2024.</p>
Last Glacial Maximum (LGM) climate forcing and ocean dynamical feedback and their implications for estimating climate sensitivity
<p><strong>Citation:</strong> Zhu, J., & Poulsen, C. J. (2021). Last Glacial Maximum (LGM) climate forcing and ocean dynamical feedback and their implications for estimating climate sensitivity. <em>Clim. Past</em>, <em>17</em>(1), 253–267. <a href="https://doi.org/10.5194/cp-17-253-2021">https://doi.org/10.5194/cp-17-253-2021</a></p> <p>Casename:</p> <ul> <li>FCM_PI: b.e12.B1850C5.f19_g16.iPI.01</li> <li>FCM_LGM: b.e12.B1850C5.f19_g16.i21ka.03</li> <li>SOM_PI: e.e12.E1850C5.f19_g16.PI.02</li> <li>SOM_GHG: e.e12.E1850C5.f19_g16.PI.21kaGHG.02</li> <li>SOM_ICE: e.e12.E1850C5.f19_g16.PI.21kaICE.02</li> <li>SOM_2CO2: e.e12.E1850C5.f19_g16.PIx2.02</li> <li>ATM_PI: f.e12.F1850C5.f19_g16.iPI.01</li> <li>ATM_GHG: f.e12.F1850C5.f19_g16.iPI.21kaGHG_ERF</li> <li>ATM_ICE: f.e12.F1850C5.f19_g16.iPI.21kaICE_ERF</li> <li>ATM_2CO2: f.e12.F1850C5.f19_g16.iPI.01.x2</li> </ul> <p><strong>Boundary condition files and the restart files are also provided as .zip files (bc.zip & rest.zip).</strong></p> <p><strong>Check out the Github repository for the setup of the LGM simulation</strong> (i.e., the entire CESM case folder): <a href="https://github.com/jiang-zhu/icesm1.2_lgm_cheyenne">https://github.com/jiang-zhu/icesm1.2_lgm_cheyenne</a></p> <p><strong>[NEW IN V3] More monthly data for PMIP4 (cmorized) are provided (files starting with `PMIP4.NCAR.CESM1.2-FV2`).</strong></p>
Data supporting: "Bayesian diagnosis of climate feedback evolution and forced temperature response"
<p><strong>This data set supports the paper:<br> Calafat, F. M., & Cael, B. B. (2023). Bayesian diagnosis of climate feedback evolution and forced temperature response, Geophysical Research Letters, submitted.</strong></p> <p>Please cite this paper when using this data set.</p> <p><em>Data description:</em></p> <ul> <li><strong>EBM_estimates.nc:</strong> this file contains Bayesian estimates from the energy balance model, including estimates of the climate feedback parameter and forced global average temperature change.</li> <li><strong>EBM_input_data.nc:</strong> this file contains all of the data used as input to the Bayesian energy balance model.</li> </ul>
Data that are used to Explain the Forcing Efficacy with Pattern Effect and Feedback Nonlinearity"
<p> This dataset is for the draft "Explaining the Forcing Efficacy with Pattern Effect and Feedback Nonlinearity".</p> <p> The netcdf file "last150yravg_picontrol.nc" represents the time-average fields for the last 150 years of PI-control experiment. Netcdf files beginning with "last20yravg" represent the time-average fields for the last 20 years (Year131-150) of abrupt forcing experiments. Note that "0p5co2" in the file name denotes 0.5xCO2, "4psolar" denotes +4% solar radiation, and "m2psolar" denotes -2% solar radiation.</p> <p> The netcdf files beginning with "fixedsst" represent the time-average fields for fixed-SST experiments, where the file "fixedsst_control.nc" denotes the fixed SST control experiment.</p> <p> The netcdf files beginning with "uni" represent the time-average fields for uniform warming/cooling experiments, where the magnitude of SST change is indicated by the file names (m2K denotes -2K).</p> <p> The text file "GFA_partialR_over_partial_SST" denote the value of partial_R over partial_SST for each grid, and its grid (96x144) is same as other netcdf files in this datasets .</p> <p> </p>
Feedback from task force members on the format, frequency and duration of workshop
<p>This dataset gathers the feedback from task force members, gathered through an online questionnaire, on the format, frequency and duration of workshops roganised by DOWEL in view of elaboration White Papers on topics related to smart buildings.</p>
Forcing, cloud feedbacks, cloud masking, and internal variability in the cloud radiative effect satellite record (Data)
<p>README file for ERA5-PRP datasets used in:</p> <p>Raghuraman et al., 2023, Journal of Climate,<br> "Forcing, cloud feedbacks, cloud masking, and internal variability in the cloud radiative effect satellite record"</p> <p>Point of Contact: Shiv Priyam Raghuraman, shivr@alumni.princeton.edu</p> <p>30 ERA5-PRP files:</p> <p>2 files: '2000_2020-allsky_small.nc' and '2000_2020-clearsky_small.nc'</p> <ul> <li>all input quantities varying</li> </ul> <p>2 files: 'clim-allsky-clim-var-all.nc' and 'clim-clearsky-clim-var-all.nc'</p> <ul> <li>all input quantities at climatology</li> </ul> <p>13 files: 'clim-var'</p> <ul> <li>Input quantity X at climatology, rest varying</li> <li>X = clouds, q, fal, skt, t, ghg, or o3. Fluxes computed in clear-sky and all-sky, apart from clouds which will only have all-sky.</li> </ul> <p>13 files: 'clim-except-var'</p> <ul> <li>Input quantity X varying, rest at climatology</li> <li>X = clouds, q, fal, skt, t, ghg, or o3. Fluxes computed in clear-sky and all-sky, apart from clouds which will only have all-sky.</li> </ul> <p>Other datasets:</p> <p>GFDL AM4 AMIP and Control<br> https://doi.org/10.5281/zenodo.4784726</p> <p>CMIP6 Control, Historical, RFMIP<br> Downloaded from ESGF</p>
Simulations for manuscript Unravelling the forcing and feedbacks contributing to Pliocene Arctic warming in EC-Earth simulations
<p>Nine PlioMIP2 experiments were conducted to investigate the mid-Pliocene Arctic climate. These experiments considered three CO2 levels (280, 400 and 560 ppm), modern or Pliocene ice sheet conditions in Greenland and Antarctica and either prescribed or dynamic vegetation. Simulations were performed by the EC-Earth3-LR Veg climate model with a horizontal resolution of ~1.125°. The dataset contains selected output data from the simulations. Simulations were run for 1000 years. The last 200 years were used for analysis after the model reached an equilibrium as measured by global surface air temperature trend less than 0.05 K per century. </p> <p>The dataset contains Earth system model results from EC-Earth3 presented in the study by Power et al. (2023).</p>
Data from: Tuning of feedforward control enables stable muscle force-length dynamics after loss of autogenic proprioceptive feedback
Open the record for dataset details and reuse information.
Analysis code in support of "The Interaction Between Climate Forcing and Feedbacks"
<p>Analysis code in support of Manuscript "The Interaction Between Climate Forcing and Feedbacks"</p> <p>Data is already available through DOI: https://doi.org/10.26024/bzne-yf09</p> <p>read_ppe2map.ipynb will create data files from the PPE output (if the files at the DOI do not work), and then the different codes herein are used to create figures in the manuscript.</p>
Data for "Snow albedo feedbacks enhance snow impurity-induced radiative forcing in the Sierra Nevada"
<p>This is the data prepared for submission of "<strong>Snow albedo feedbacks enhance snow impurity-induced radiative forcing in the Sierra Nevada</strong>". Three folders are included: 1) The model output with aerosol deposition in snow (aero); 2) The model output without aerosol deposition in snow (noaero) 3) processed observations used to validate the model results (SPIReS)</p>
Greenhouse gas forcing and climate feedback signatures identified in hyperspectral infrared satellite observations (Data)
<p>README file for LBL-ERA5, LBL-GCM, and band datasets used in:<br> Raghuraman et al., 2023, Geophysical Research Letters,<br> "Greenhouse gas forcing and climate feedback signatures identified in hyperspectral infrared satellite observations "</p> <p>Point of Contact: Shiv Priyam Raghuraman, shivr@alumni.princeton.edu</p> <p> </p> <p>LBL-ERA5</p> <p>6 files (3 experiments with olr and olr_clr output separately):</p> <p>2003-2021.GFDL.all-2010-o3_*.nc - varying WMGHG,Ts,T,q,clouds, fixed o3</p> <p>2003-2021.GFDL.fo3_*.nc - varying WMGHG and fixed Ts,T,q,clouds,surface albedo,o3</p> <p>2003-2021.GFDL.ff_*.nc - fixed Ts,T,q,clouds,surface albedo, varying o3</p> <p> </p> <p>LBL-GCM (clear-sky only)</p> <p>4 AM4 files:</p> <p>AM4piclim-control.nc (for ERF)</p> <p>AM4piclim-4xCO2_1xCO2IRF.nc (for ERF)</p> <p>AM4piclim-control_STRAT.nc (for SARF)</p> <p>AM4piclim-4xCO2_1xCO2IRF_STRAT.nc (for SARF)</p> <p>4 CM3/AM3 files:</p> <p>CTLAM3CM3_P1_APR_allctm_E1_RFM_1CM_A2_WN3_1xCO2N.nc (for \lambda)</p> <p>EXPAM3CM3_P1_APR_allctm_E1_RFM_1CM_A2_WN3_1xCO2N.nc (for \lambda)</p> <p>CTLAM3CM3_P1_2003C.nc (for IRF)</p> <p>CTLAM3CM3_P1_2021C.nc (for IRF)</p> <p> </p> <p>Band-AM4/MERRA-Total: GFDL AM4 with prescribed SSTs and sea-ice (AMIP) and nudged with MERRA winds</p> <p>2 files:</p> <p>atmos.200001-202112.olr.nc - all-sky OLR</p> <p>atmos.200001-202112.olr_clr.nc - clear-sky OLR</p> <p> </p> <p>Observational and reanalysis files used in paper (AIRS, CERES EBAF and SSF, GISTEMP, ERA5 input data) can be downloaded from their respective websites (see paper's "Open Research" section).</p> <p> </p>
Combination of Force Control Training and Mirror Visual Feedback Device on Stroke Patients on Brain Activation and Hand Function
ClinicalTrials.gov study NCT07150325. IPD Sharing: Not stated. Countries: 1. Publications: 89.
Effect of Task-oriented Training Assisted by Force Feedback Hand Rehabilitation Robot on Finger Function in Stroke Patients With Hemiplegia
ClinicalTrials.gov study NCT05841108. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The Impact of Force Feedback in the dV5 Robotic Surgical System on Learning Curve and Safety in Robot-Assisted Radical Prostatectomy - A Prospective, Single-Center, Investigator-Initiated Clinical Tri
ClinicalTrials.gov study NCT07247175. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Force Feedback Joystick in Upper Limb Rehabilitation Following Stroke
ClinicalTrials.gov study NCT00758147. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Assessing Force Feedback With the SoftHand Pro
ClinicalTrials.gov study NCT03412656. IPD Sharing: NO. Countries: 1. Publications: 0.
A Study to Understand the Utility of the Force Feedback Instruments in Robotic Procedures Using da Vinci 5 Robot
ClinicalTrials.gov study NCT06879912. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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