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81 results for “response surface”
Evaluation of a wind tunnel designed to investigate the response of evaporation to changes in the incoming longwave radiation at a water surface
<p>Experimental Record of a Longwave-Evaporation experiment. The record to be referenced in a forthcoming scientific paper.</p>
Dataset for: Wood et al Role of sea surface temperature patterns for the Southern hemisphere jet stream response to CO2 forcing
<p>This is a dataset of output from version 4 of the Reading Intermediate Global Circulation Model (IGCM4) that was used in the article Wood et al (2020) 'Role of sea surface temperature patterns for the Southern hemisphere jet stream response to CO2 forcing' published in Environmental Research Letters (<a href="https://doi.org/10.1088/1748-9326/abce27">https://doi.org/10.1088/1748-9326/abce27</a>).</p> <p>To isolate the role of sea surface temperature (SST) patterns for the Southern Hemisphere circulation response in the abrupt-4xCO2 experiments in CMIP5 and CMIP6, we perform experiments using IGCM4.</p> <p>Five 120-year long simulations were performed following a 5-year spin-up period. In the control simulation (CTRL) we prescribe an annually repeating cycle of climatological monthly mean SSTs using the multi-model mean (MMM) of the ‘ts’ field for the first 200 years of the CMIP5 piControl simulations. Following the CMIP6 protocol (Eyring et al., 2016), greenhouse gas (CO<sub>2</sub>, CH<sub>4</sub>, and N<sub>2</sub>O) concentrations are set at preindustrial (year 1850) values and ozone is prescribed as a zonally averaged monthly mean preindustrial climatology.</p> <p>In two perturbation simulations (4xCO2-FULL<sub>CMIP5</sub> and 4xCO2-FULL<sub>CMIP6</sub>) the same boundary conditions are used as in CTRL, but with an annually repeating cycle of climatological monthly mean SST anomalies added using the MMM ‘ts’ field for either the CMIP5 or CMIP6 FAST (years 4-10) responses. In both the 4xCO2-FULL<sub>CMIP5</sub> and 4xCO2-FULL<sub>CMIP6</sub> simulations CO<sub>2</sub> is quadrupled from its preindustrial concentration. This enables a like-for-like comparison with the CMIP5 and CMIP6 abrupt-4xCO2 simulations. Two further perturbation simulations (SHET-only<sub>CMIP5</sub> and SHET-only<sub>CMIP6</sub>) are used to isolate the effect of differences in SH extratropical SST patterns alone. In both simulations CO<sub>2</sub> is kept at preindustrial values, and CTRL SSTs are used with the SST anomalies from either 4xCO2-FULL<sub>CMIP5</sub> or 4xCO2-FULL<sub>CMIP6</sub> added poleward of 18°S. Similarly to McCrystall et al. (2020), the SST anomalies are smoothed between 18°S and 29°S using a cosine squared weighting function with weights of 0 at 18°S and 1 at 29°S. This minimizes sharp gradients in SST across the tropical-extratropical boundary.</p> <p>To enable a clean determination of the effects of SST patterns alone, in all perturbation simulations we keep sea ice fixed at preindustrial values by only adding SST anomalies where the MMM sea ice concentration in the CMIP5 piControl simulations is less than 15% (i.e., equatorward of the sea ice edge). Furthermore, to remove the effect of differences in the change in global mean SST, the SST anomalies in each CMIP model are normalised by the respective global mean SST anomaly and then scaled to a global mean value of 2.2 K (the pooled MMM of CMIP5 and CMIP6). The CMIP6 FAST SST anomalies are added to the CMIP5 preindustrial control SSTs, so as to isolate the effect of differences in the fast SST responses between CMIP5 and CMIP6, and not the effect of differences in the base state.</p>
Fifty-year changes of the world ocean's surface layer in response to climate change
<p>This object includes two files. One (GlobalML_Trend_1970_2018.mat) contains the 1970-2018 trends of mixed-layer depth, 0-200 stratification, and pycnocline stratification, as described in: Sallée, J.B., Pellichero, V., Akhoudas, C., Pauthenet, E., Vignes, L., Schmidtko, S., Naveira Garabato, A., Sutherland, P., Kuusela, M., 2020, Fifty-year changes of the world ocean’s surface layer in response to climate change, 591, 592–598, https://doi.org/10.1038/s41586-021-03303-x. The second one (<a href="https://zenodo.org/api/files/15c80d5f-a6f9-4b7b-bde1-12de43732195/GlobalML_Climato_1970_2018.mat">GlobalML_Climato_1970_2018.mat</a>) contains a climatology of mixed-layer depth based on the same methodology as in Sallée et al., 2021 (nature; doi:https://doi.org/10.1038/s41586-021-03303-x) but without regressing a trend. The climatological field is therefore different than in the paper; more robust in region where trends are unphysical (e.g. winter high latitude)</p>
Revisiting Interior Water Mass Responses to Surface Forcing Changes and the Subsequent Effects on Overturning in the Southern Ocean
<p>This dataset contains processed model data used in</p> <p>Tesdal, J.-E., A. MacGilchrist, G., Beadling, R. L., Griffies, S. M., Krasting, J. P., & Durack, P. J. (2023). Revisiting interior water mass responses to surface forcing changes and the subsequent effects on overturning in the Southern Ocean. Journal of Geophysical Research: Oceans, 128, e2022JC019105. <a href="https://doi.org/10.1029/2022JC019105">https://doi.org/10.1029/2022JC019105</a>.</p> <p>The above publication uses two coupled climate models (AOGCMs), GFDL-CM4 and GFDL-ESM4, to assess the impact of perturbations in wind stress and Antarctic ice sheet melting on the Southern Ocean meridional overturning circulation (SO MOC) and associated water mass transformations (WMT).</p> <p>The attached archive includes netCDF files to recreate all figures and tables in <a href="https://doi.org/10.1029/2022JC019105">Tesdal et al. (2023)</a>, including overturning streamfunction (moc), volume storage change (dVdt), surface water mass transformation (swmt), meridional volume transports (mvt) zonal mean potential density referenced to 2000 dbar (sigma2) and mixed layer depth (mld). These variables are derived from preindustrial control (piControl) and idealized perturbation runs of Antarctic melting (Antwater), wind stress (Stress), as well as the combination (Antwater-Stress) using the Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP) protocol.</p> <p>The FAFMIP protocol (<a href="https://doi.org/10.5194/gmd-9-3993-2016">Gregory et al., 2016</a>) involves adding perturbations to the surface fluxes that are computed within the atmosphere-ocean general circulation model (AOGCM) from the state of the system (<a href="https://doi.org/10.1029/2005JC003421">Lowe and Gregory, 2006</a>; <a href="https://doi.org/10.1088/1748-9326/9/3/034004">Bouttes and Gregory, 2014</a>). The perturbations in this dataset were technically added as a flux adjustment similar to that formerly used in AOGCMs (<a href="https://doi.org/10.1007/BF01053472">Sausen et al., 1988</a>).</p> <p>The data files contain processed model output and do not include any raw model output. Model data from the piControl runs of CM4 and ESM4 are available at the Earth System Grid Federation archive (<a href="https://esgf-node.llnl.gov/projects/cmip6">https://esgf-node.llnl.gov/projects/cmip6</a>). The forcing fields (perturbations) used in the perturbation experiments can be found at <a href="https://github.com/becki-beadling/Beadling_et_al_2022_JGROceans">https://github.com/becki-beadling/Beadling_et_al_2022_JGROceans</a>. Python scripts and Jupyter notebooks to reproduce the tables and figures can be accessed at <a href="https://github.com/jetesdal/Tesdal_et_al_2023_JGROceans">https://github.com/jetesdal/Tesdal_et_al_2023_JGROceans</a>.</p> <p><strong>Contents</strong>:</p> <ul> <li>Overturning streamfunction (moc)</li> <li>Volume storage change (dVdt)</li> <li>Surface water mass transformation (swmt)</li> <li>Meridional volume transports (mvt) </li> <li>Zonal-mean potential density referenced to 2000 dbar (sigma2)</li> <li>Mixed layer depth (mld) </li> <li>Antarctic shelf mask</li> <li>Static grid files</li> </ul> <p><strong>Models</strong>:</p> <ul> <li>GFDL-CM4</li> <li>GFDL-ESM4</li> </ul> <p><strong>Simulations</strong>:</p> <ul> <li>Preindustrial control (piControl)</li> <li>Experiment with a 0.1 Sv freshwater perturbation entering at the Antarctic coast (Antwater)</li> <li>Experiment with zonal and meridional wind stress perturbations (Stress)</li> <li>Experiment with combined perturbation of both Antarctic melting and wind stress (Antwater-Stress)</li> </ul> <p><strong>NetCDF file name structure</strong>:<br> <model>_<simulation>_<member_id>_<domain>_<time_period>_<variable>.nc</p> <ul> <li>model: CM4, ESM4</li> <li>simulation: control, antwater, stress, antwaterstress</li> <li>member_id (only for antwater, stress, antwaterstress): 251, 290, 332 (CM4), 101, 151, 201 (ESM4)</li> <li>domain: global, so</li> <li>time_period: yyyy-yyyy (first year to last year)</li> <li>variable: e.g., moc_rho2_online_lores, dVdt_rho2_online_lores, swmt_sigma2_005, sigma2_jmd95_zmean</li> </ul>
Simulation dataset and plotting scripts used for journal article "Impact of acidity and surface modulated acid dissociation on cloud response to organic aerosol" by Sengupta et al. (2024)
<p>Simulation data underlying all figures presented in "Impact of acidity and surface modulated acid dissociation on cloud response to organic aerosol" by Sengupta et al. (2024). DOI: 10.5194/acp-24-1467-2024</p> <p>The data for each figure and the plotting scripts are included in a zip file labelled by the figure number as presented in the paper and accompanying supplement.</p>
Response of convectively coupled Kelvin waves to surface temperature forcing in aquaplanet simulations: data and code
<p>This is the data and code used for a journal paper entitled "Response of convectively coupled Kelvin waves to surface temperature forcing in aquaplanet simulations", written by Mu-Ting Chien and Daehyun Kim in 2024. This paper is in minor revision in the Journal of Advances in Modeling Earth System. The submitted paper is here: (https://essopenarchive.org/doi/full/10.22541/essoar.171322728.86206700/v1).</p>
MITgcm simulations of sea level response to freshwater injected at the surface and at depth in southern high latitudes: Model output and analysis code
<p>Model output (netcdf) and python code (included in both py and ipynb formats) to create the figures in Eisenman et al. (2024).</p> <div> <p>See https://eisenman-group.github.io for further details.</p> </div>
Probing temperature-responsivity of microgels and its interplay with a solid surface by superresolution microscopy and numerical simulations
<p>This dataset supports the publication ' Probing temperature-responsivity of microgels and its interplay with a solid surface by super resolution microscopy and numerical simulations' published on ACS Nano. DOI: https://doi.org/10.1021/acsnano.2c07569</p>
GF4ACE -- Data from: Reanalysis-based global radiative response to sea surface temperature patterns: Evaluating the Ai2 climate emulator
Open the record for dataset details and reuse information.
Data supplementing the article: Schultz, N.M., Lawrence P.J, Lee X., Global satellite data highlights the diurnal asymmetry of the surface temperature response to deforestation. Journal of Geophysical Research - Biogeosciences
<p>These data supplement the article: Schultz, N.M., Lawrence P.J, Lee X. Global satellite data highlights the diurnal asymmetry of the surface temperature response to deforestation, under review at the Journal of Geophysical Research - Biogeosciences.</p> <p>contact: Natalie M. Schultz, natalie.schultz@yale.edu</p> <p>Below are descriptions of the data files included here:</p> <p><br> (1) Global LST data: globalLST_Forest_Open.YYYY.nc [2003-2013]</p> <p>- DayLST1/NightLST1 and DayLST2/NightLST2 are the final (after the DEM correction) LST values for forest, and open land cover classes, respectively.<br> - Count variables show the number of pixels of each land cover class in each 0.5 degree grid<br> - The average elevation of each class is given by the DEM1 and DEM2 vars<br> - The DEM correction is the dLSTdDEM vars</p> <p>(2) Global fluxes data: globalFluxes_Forest_Open.YYYY.nc [2003-2013]<br> - Again, forest class = var1, open class = var2<br> - SWRABS is absorbed solar radiation<br> - LE is the latent heat flux<br> - HP is the heating potential term, as defined in the manuscript<br> - As described for the LST data, class pixel counts and DEM data are included</p> <p>(3) climzones3.nc<br> - The delineation of the three climate zones defined in this paper</p> <p>(4) MERRA inversion data: MERRA_11yr_TS_T10M.mat [2003-2013]<br> - 11 years of daily 1am local data averaged over 8-day intervals for 2003-2013<br> - TS = surface temperature<br> - T10M = 10M air temperature (above d)</p> <p> </p> <p> </p>
The role of bottom friction in mediating the response of the Weddell Gyre circulation to changes in surface stress and buoyancy fluxes
<p>This repository contains code to reproduce the figures in the paper titled "The role of bottom friction in mediating the response of the Weddell Gyre circulation to changes in surface stress and buoyancy fluxes" published in the Journal of Physical Oceanography (DOI: <a href="https://doi.org/10.1175/JPO-D-23-0165.1">https://doi.org/10.1175/JPO-D-23-0165.1</a>), as well as the barotropic vorticity budget terms for each of simulation in the paper.</p>
Response to Sea Surface Temperature and Primary Productivity to change in Earth's Orbit Eccentricity - Simulations
<p>This dataset contains ocean and ocean biogeochemistry outputs from modeling experiments with present-day geography and various Earth's orbit confiurations. The set of simulation targets the role of Eccentricity on the tropical ocean sea surface temperature and primary productivity (Beaufort & Sarr, 2024) . The simulations have been run using the IPSL-CM5A2 General Circulation Model (Sepulchre et al. 2020 - IPSL-CM5A2 – an Earth system model designed formulti-millennial climate simulations, GMD) and offline version of PISCESv2 model (Aumont et al., 2015 - PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, GMD). It includes 4 simulations. Data are monthly averages over the last 100 years of the simulations.</p> <p>Complementary outputs (4 simulations) can be found at https://www.seanoe.org/data/00728/84031/ (Beaufort et al., 2022)</p>
Dataset of the paper "Response of Sea Surface Temperature to Atmospheric Rivers"
<p>Dataset of the paper "Response of Sea Surface Temperature to Atmospheric Rivers", whose manuscript will be submitted by 10/25/2023</p> <p><br>The dataset contains the necessary data to generate the figures in the paper with the code in the link <a href="https://doi.org/10.5281/zenodo.10958491">https://doi.org/10.5281/zenodo.10958491</a> whose Github reference is <a href="https://github.com/meteorologytoday/paperfigures-2023-AR-SST-response">https://github.com/meteorologytoday/paperfigures-2024-AR-SST-response</a></p> <p> </p>
Boreal Winter Hadley Cell Contraction in Response to the Incorporation of a Comprehensive Ocean Surface Albedo in CESM2
<p>Simulated output for: Boreal Winter Hadley Cell Contraction in Response to the Incorporation of a Comprehensive Ocean Surface Albedo in CESM2</p>
Finding Efficient Trade-offs in Multi-Fidelity Response Surface Modeling: Generated data files and figures
<p>All data files and figures generated for the paper "Finding Efficient Trade-offs in Multi-Fidelity Response Surface Modeling".</p> <p>The code used to generate this is archived at <a href="https://doi.org/10.5281/zenodo.6123254">zenodo.org/record/6123254</a></p>
Model output of: Excitation of an MJO event in response to a transient sea surface warming in Super-Parameterized CAM
<p>Recent studies have suggested that the Madden-Julian Oscillation (MJO) could be generated in the atmospheric adjustment to equatorial heating anomalies in models properly resolving moist convection. Here we use Super-Parameterized CAM to simulate atmospheric response to transient sea surface warming in the equatorial Indian Ocean, which leads to the excitation of an MJO event, robust across different ensemble members, in addition to the much-expected equatorial Rossby and Kelvin waves. A moist static energy (MSE) budget analysis suggests that longwave and surface turbulent latent heat flux anomalies are predominantly responsible for the MJO excitation; however, these terms oppose its eastward propagation. In contrast, advection of MSE generally weakens the MJO amplitude, but contributes to its eastward propagation. These results highlight the role of the MJO in the moist atmospheric adjustment to equatorial heating, with implications for the MJO mechanisms and prediction.</p>
Response of surface temperature to afforestation in the Kubuqi Desert, Inner Mongolia
<p>This is the data used in “Response of surface temperature to afforestation in the Kubuqi Desert, Inner Mongolia” by Wang et al, for Journal of Geophysical Research - Atmospheres [MS#2017JD027522].</p>
Contrasting Responses of Surface Heat Fluxes to Tropical Deforestation
<p>2D_GSWP3*.nc are the CLM simulation outputs with GSWP3 as input forcings.</p> <p>2D_*_piControl.nc and 2D_*_deforest-globe.nc are the CMIP6 model outputs.</p> <p>Offline.m and LUMIP.m are matlab code files to reproduce figures in the article.</p> <p>nc_*.py are python code files to generate netCDF files for producing figures.</p>
Contrasting Responses of Surface Heat Fluxes to Tropical Deforestation
<p>2D_*_piControl.nc and *.nc are the analyzed CMIP6 piControl experiments.</p> <p>2D_*_deforest-globe.nc are the analyzed LUMIP deforestation experiments.</p> <p>2D_GSWP3_*.nc are the analyzed CLM simulation output forced with modified GSWP3 forcings.</p> <p>Offline.m and LUMIP.m are to obtain the changes in surface heat fluxes under deforestation and plot figures.</p>
Response mechanism of residual strength to meso-structure of shear surface in gravelly slip zone of ancient landslide
<p>Response mechanism of residual strength to meso-structure of shear surface in gravelly slip zone of ancient landslide-Original data</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.
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.
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.
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.
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.