Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
748
datasets available to search
ShareScore release 0.9.0
Dataset results
748 results for “surface temperature”
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>
GR6901 wintertime North American daily anomalous surface temperature data
<p>20 years of wintertime (December-February) North American daily anomalous surface temperature from a model simulation. The daily data has had a 7-day low-pass filter applied, and has been weighted for this analysis.</p>
Four organic sea surface temperature proxies (UK'37, TEXH86, RI-OH' and LDI) in the westernmost Mediterranean for the last 35 kyr
<p>We present a high-resolution paleotemperature reconstruction from a marine sediment core (GP04PC) recovered in the westernmost Mediterranean, the Alboran Sea basin, over the last 35 kyr using for the first time in pararell four independent organic sea surface temperature (SST) proxies (U<sup>K'</sup><sub>37</sub>,<sup> </sup>TEX<sup>H</sup><sub>86</sub>,RI-OH' and LDI). We also present the δ<sup>18</sup>O of planktonic foraminifera <em>G. bulloides</em> record together with records of bulk parameters (total organic carbon content, δ<sup>13</sup>C<sub>org</sub>) and the accumulation rates of different biomarkers, providing insights in terrestrial input and primary productivity variations. </p> <p>We have also examined the Bayesian calibrations BAYSPLINE for U<sup>K'</sup><sub>37 </sub>and BAYSPAR for TEX<sub>86</sub>, although the non-Bayesian calibrations are used in this study.</p> <p> </p> <p> </p>
[Dataset] Polar and Topographic Amplifications of Inter-model Spread of Surface Temperature in Climate Models
<p>All the raw CMIP5 and CMIP6 model data used in this work are available at <a href="https://data.ceda.ac.uk/badc/cmip5/data/cmip5/output1">https://data.ceda.ac.uk/badc/cmip5/data/cmip5/output1</a> and <a href="https://esgf-node.llnl.gov/search/cmip6/">https://esgf-node.llnl.gov/search/cmip6/</a> respectively.</p> <p>The data uploaded here is the processed data that support and lead to the described results in the manuscript entitled "Polar and Topographic Amplifications of Inter-model Spread of Surface Temperature in Climate Models"</p> <p>Figure numbers shown in brackets are associated figures in the manuscript.</p> <p><br> cmip5_sdev.nc (the first row of figure 1 )<br> cmip6_sdev.nc (the second row figure 1 )</p> <p>cmip6_np_decompose.nc (figure 2 and figure 6)<br> cmip6_sp_decompose.nc (figure 3 and figure 7)<br> cmip6_tp_decompose.nc (figure 4 and figure 8)<br> cmip6_clt.nc (figure 5)<br> cmip6_np_energy_transport.nc (the first column of figure 9)<br> cmip6_sp_energy_transport.nc (the second column of figure 9)<br> cmip6_tp_energy_transport.nc (the third column of figure 9)</p> <p><br> cmip5_np_decompose.nc (figure 10 and figure 14 in appendix)<br> cmip5_sp_decompose.nc (figure 11 and figure 15 in appendix)<br> cmip5_tp_decompose.nc (figure 12 and figure 16 in appendix)<br> cmip5_clt.nc (figure 13 in appendix)<br> cmip5_np_energy_transport.nc (the first column of figure 17 in appendix)<br> cmip5_sp_energy_transport.nc (the second column of figure 17 in appendix)<br> cmip5_tp_energy_transport.nc (the third column of figure 17 in appendix)<br> </p>
Assessment of the sea surface temperature diurnal cycle in CNRM-CM6-1 based on its 1D coupled configuration - model outputs
<p>These tar file are associated with an article submitted to Geoscientific Model Development under identification number gmd-2021-413 (https://www.geoscientific-model-development.net): Assessment of the sea surface temperature diurnal cycle in CNRM-CM6-1 based on its 1D coupled configuration<br> By A. Voldoire, R. Roehrig, H. Giordani, R. Waldman, Y. Zhang, S. Xie, MN Bouin</p> <p>3 files correspond to code components that can be distributed freely</p> <p>- surfex.tgz for the surfex v8.0 distributed under a Cecill-C License</p> <p>- oasis-mct-3.0.tgz for oasis-mct3.0 distributed under a GNU General Public License</p> <p>- nemo_v3.6.tgz for the nemo, distibuted under a Cecill-C License</p> <p>These three components are mainly fortran codes.</p> <p>The last file "<a href="https://zenodo.org/api/files/e94922e7-22eb-445b-acc3-03e11ca1af6b/CNRM-CM6-1D_published_experiments.tgz?versionId=2460ec63-89f5-415f-9613-1954f048b238">CNRM-CM6-1D_published_experiments.tgz </a>" contains all model outputs that have been used in this article. These model outputs are in netcdf format and organized by experiment.</p>
Data for "Multiple Equilibria in Weak Temperature Gradient Simulations over a Moist Land-Like Surface"
<p>Codes, simulation input files, and simulation output data supporting “Multiple Equilibria in Weak Temperature Gradient Simulations over a Moist Land-Like Surface”, submitted to GRL. README files in GRLWTGEquilibria.zip provide detailed descriptions of the archive contents.</p>
Data used in JAMES paper "Sensitivity of the Horizontal Scale of Convective Self‐Aggregation to Sea Surface Temperature in Radiative Convective Equilibrium Experiments Using a Global Nonhydrostatic Model"
<p>Data used in JAMES paper "Sensitivity of the Horizontal Scale of Convective Self‐Aggregation to Sea Surface Temperature in Radiative Convective Equilibrium Experiments Using a Global Nonhydrostatic Model" by Shuhei Matsugishi and Masaki Satoh doi: 10.1029/2021MS002636</p>
Land Surface Temperature for the city of Berlin
<p>Daily daytime and nighttime Land Surface Temperature products of 100 m x 100 m spatial resolution covering 2018 - 2019 over a large area in Berlin, derived from MODIS satellite thermal acquisitions using downscaling techniques.</p>
Datasets and code of the manuscript 'Insights into the Aerodynamic versus Radiometric Surface Temperature Debate in Thermal-based Evaporation Modeling'
<p>This contains the datasets and codes that were used to generate the results and discussions in the manuscript</p>
Relative importance of meridional and zonal sea surface temperature gradients for the onset of the ice ages and Pliocene-Pleistocene climate evolution
<p>Climatologies from the 3 different model simulations performed for the paper published in Paleoceanography (2010, v25, issue 2, <a href="https://doi.org/10.1029/2009PA001809">https://doi.org/10.1029/2009PA001809</a>). This table shows how the names of the simulations provided here relate to the names in the paper:</p> <table align="center"> <caption>Simulation names for cross-referencing</caption> <thead> <tr> <th scope="col">Name of Files</th> <th scope="col">Name in Article</th> </tr> </thead> <tbody> <tr> <td>EPSST_T_85.*.nc</td> <td>Early Pliocene Simulation</td> </tr> <tr> <td>New_MZSST_T_85.*.nc</td> <td>Modern Zonal Simulation</td> </tr> <tr> <td>ctl_85_Kerry.*.nc</td> <td>Modern Control Simulation</td> </tr> </tbody> </table> <p>Additionally the NCL script originally used to create all the figures is included. It is called paleoc_onsetNHG_rev.ncl. The abstract of the paper is below:</p> <p>"During the early Pliocene (roughly 4 Myr ago), the ocean warm water pool extended over most of the tropics. Subsequently, the warm pool gradually contracted toward the equator, while midlatitudes and subpolar regions cooled, establishing a meridional sea surface temperature (SST) gradient comparable to the modern about 2 Myr ago (as estimated on the eastern side of the Pacific). The zonal SST gradient along the equator, virtually nonexistent in the early Pliocene, reached modern values between 1 and 2 Myr ago. Here, we use an atmospheric general circulation model to investigate the relative roles of the changes in the meridional and zonal temperature gradients for the onset of glacial cycles and for Pliocene-Pleistocene climate evolution in general. We show that the increase in the meridional SST gradient reduces air temperature and increases snowfall over most of North America, both factors favorable to ice sheet inception. The impacts of changes in the zonal gradient, while also important over North America, are somewhat weaker than those caused by meridional temperature variations. The establishment of the modern meridional and zonal SST distributions leads to roughly 3.2°C and 0.6°C decreases in global mean temperature, respectively. Changes in the two gradients also have large regional consequences, including aridification of Africa (both gradients) and strengthening of the Indian monsoon (zonal gradient). Ultimately, this study suggests that the growth of Northern Hemisphere ice sheets is a result of the global cooling of Earth's climate since 4 Myr rather than its initial cause. Thus, reproducing the correct changes in the SST distribution is critical for a model to simulate the transition from the warm early Pliocene to a colder Pleistocene climate."</p> <p> </p>
CESM2 data for "Ocean complexity shapes sea surface temperature variability in a CESM2 coupled model hierarchy" - submitted to JCLI
<p><strong>CESM2 Experiment names:</strong></p> <ul> <li>FC = fully coupled model, CESM2 (variables freely available on https://esgf-node.llnl.gov/search/cmip6/)</li> <li>MD = mechanically decoupled model, CESM2</li> <li>SOM = slab ocean model, CESM2</li> </ul> <p>All datasets are for pre-industrial forcing (e.g., piControl), nominal 1-degree horizontal resolution </p> <p>---</p> <p>Decoding the files names:</p> <ul> <li><strong>climatology_monthly </strong>= 12 month climatology </li> <li><strong>climatology_annual</strong> = time mean climatology</li> <li><strong>variance</strong> = anomaly variance computed over time</li> </ul> <p>---</p> <p>Variables:</p> <ul> <li><strong>PRECL</strong> = large-scale convective precipitation</li> <li><strong>PRECC</strong> = convective precipitation</li> <li><strong>total precipitation (not provided but can be calculated)</strong> = PRECC + PRECL</li> <li><strong>HMXL</strong> = mixed layer depth</li> <li><strong>SST</strong> = sea surface temperature </li> </ul> <p><strong>Files for the CESM2 MD piControl run:</strong></p> <ol> <li>forcing_coupled.F90: POP2 (ocean) source code changes for cesm2.1.4-rc08 (search for "slarson" throughout code to find our changes</li> <li>cesm2.1.4-exp03-CTRL_B1850_f09_g17_hourlyclim_TAUX.nc: 6 hourly climatology for TAUX, from a FC run of CESM2. This file and the TAUY climatology are opened and read in the "rotate wind stress" subroutine in forcing_coupled.F90. This file is named "x2oavg_Foxx_taux_6hourly.nc" in forcing_coupled (we wanted a shorter file name in the code)</li> <li>cesm2.1.4-exp03-CTRL_B1850_f09_g17_hourlyclim_TAUY.nc: 6 hourly climatology for TAUY. This file is named "x2oavg_Foxx_tauy_6hourly.nc" in forcing_coupled (we wanted a shorter file name in the code) </li> </ol> <p> </p>
From performance curves to performance surfaces: Interactive effects of temperature and oxygen availability on aerobic and anaerobic performance in the common wall lizard
<p>1. Accurately predicting the responses of organisms to novel or changing environments requires the development of ecologically-appropriate experimental methodology and process-based models.</p> <p>2. For ectotherms, thermal performance curves (TPCs) have provided a useful framework to describe how organismal performance is dependent on temperature. However, this approach often lacks a mechanistic underpinning, which limits our ability to use thermal performance curves predictively. Further, thermal dependence varies across traits, and performance is also limited by additional abiotic factors, such as oxygen availability.</p> <p>3. We test a central prediction of our recent Hierarchical Mechanisms of Thermal Limitation (HMTL) Hypothesis which proposes that natural hypoxia exposure will reduce maximal performance and cause the thermal performance curve for whole-organism performance to become more symmetrical.</p> <p>4. We quantified thermal performance curves for two traits often used as fitness proxies, sprint speed and aerobic scope, in lizards under conditions of normoxia and high-elevation hypoxia.</p> <p>5. In line with the predictions of HMTL, anaerobically-fueled sprint speed was unaffected by acute hypoxia while the TPC for aerobic scope became shorter and more symmetrical. This change in TPC shape resulted from both the maximum aerobic scope and the optimal temperature for aerobic scope being reduced in hypoxia as predicted.</p> <p>6. Following these results, we present a mathematical framework, which we call Temperature-Oxygen Performance Surfaces (TOPS), to quantify the interactive effects of temperature and oxygen on whole-organism performance in line with the HMTL hypothesis. This framework is transferrable across traits and levels of organization to allow predictions for how ectotherms will respond to novel combinations of temperature and other abiotic factors, providing a useful tool in a time of rapidly changing environmental conditions.</p>
A global historical twice-daily (daytime and nighttime) land surface temperature dataset produced by AVHRR observations from 1981 to 2021 (1981–2000)
<ul> <li>Land surface temperature (LST) is a key variable for monitoring and evaluating global long-term climate change. However, existing satellite-based twice-daily LST products only date back to 2000, which makes it difficult to obtain robust long-term temperature variations. We developed the first global historical twice-daily LST dataset (GT-LST), with a spatial resolution of 0.05°, using Advanced Very High Resolution Radiometer Level-1b Global Area Coverage data from 1981 to 2021.</li> <li>Validation with in situ measurements from Surface Radiation Budget sites showed that the overall root-mean-square errors of GT-LST varied from 2.0 K to 3.9 K. Inter-comparison with a common LST product (i.e., MYD11A1) revealed that the overall root-mean-square-difference was approximately 3.2 K.</li> <li>More details of this dataset can be seen in <em>readme.pdf.</em></li> <li>This dataset provides GT-LST product from 1981 to 2000.</li> </ul>
A global historical twice-daily (daytime and nighttime) land surface temperature dataset produced by AVHRR observations from 1981 to 2021 (2001–2005)
<ul> <li>Land surface temperature (LST) is a key variable for monitoring and evaluating global long-term climate change. However, existing satellite-based twice-daily LST products only date back to 2000, which makes it difficult to obtain robust long-term temperature variations. We developed the first global historical twice-daily LST dataset (GT-LST), with a spatial resolution of 0.05°, using Advanced Very High Resolution Radiometer Level-1b Global Area Coverage data from 1981 to 2021.</li> <li>Validation with in situ measurements from Surface Radiation Budget sites showed that the overall root-mean-square errors of GT-LST varied from 2.0 K to 3.9 K. Inter-comparison with a common LST product (i.e., MYD11A1) revealed that the overall root-mean-square-difference was approximately 3.2 K.</li> <li>More details of this dataset can be seen in <em>readme.pdf.</em></li> <li>This dataset provides GT-LST product from 2001 to 2005.</li> </ul>
Dataset for model input of WRF model for the paper:Modulation of Extratropical Cyclones by Previous Cyclones via the Sea Surface Temperature Anomaly over the Sea of Japan in Winter
<p>This is the dataset and code for generating the lower boundary condition which used in our study submitted to the JGR-Atmospheres. The meteorological data for the initial condition are available on NCEP-FNL ftp database.</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>
Impact of persistently high sea surface temperatures on the rhizobiomes of Zostera marina in a Baltic Sea benthocosms
Open the record for dataset details and reuse information.
LANDSAT Land Surface Temperature
<p>LANDSAT Land Surface Temperature for 2016 (Jan, Jul, Aug, Dec), calculated from USGS LANDSAT C02-O2 band B10.</p> <p>Lon Lat files are available</p>
Ground surface temperature measurements at grazed and ungrazed plots in Central Mongolia
<p>Ground surface temperature measurements from two sites with different topographic aspect in Central Mongolia. The dataset includes both grazed and ungrazed plots, and covers ca. 14 months from May 2022 to August 2023.</p>
Fig. 1 in Retrieving climate change dependent Sea Surface Temperature (SST) in Southern Turkey by using Landsat thermal imagery
Fig. 1 — Map of the study area, Bay of Goköva
ScienceDex guides
Understand access before you commit
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.