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294 results for “sea surface temperature”
Data from: Sea-surface temperature pattern effects have slowed global warming and biased warming-based constraints on climate sensitivity
<p>The observed rate of global warming since the 1970s has been proposed as a strong constraint on equilibrium climate sensitivity (ECS) and transient climate response (TCR) – key metrics of the global climate response to greenhouse-gas forcing. Using CMIP5/6 models, we show that the inter-model relationship between warming and these climate sensitivity metrics (the basis for the constraint) arises from a similarity in transient and equilibrium warming patterns within the models, producing an effective climate sensitivity (EffCS) governing recent warming that is comparable to the value of ECS governing long-term warming under CO<sub>2</sub> forcing. However, CMIP5/6 historical simulations do not reproduce observed warming patterns. When driven by observed patterns, even high ECS models produce low EffCS values consistent with the observed global warming rate. The inability of CMIP5/6 models to reproduce observed warming patterns thus results in a bias in the modeled relationship between recent global warming and climate sensitivity. Correcting for this bias means that observed warming is consistent with wide ranges of ECS and TCR extending to higher values than previously recognized. These findings are corroborated by energy balance model simulations and coupled model (CESM1-CAM5) simulations that better replicate observed patterns via tropospheric wind nudging or Antarctic meltwater fluxes. Because CMIP5/6 models fail to simulate observed warming patterns, proposed warming-based constraints on ECS, TCR, and projected global warming are biased low. The results reinforce recent findings that the unique pattern of observed warming has slowed global-mean warming over recent decades, and that how the pattern will evolve in the future represents a major source of uncertainty in climate projections.</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>
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>
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 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>
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>
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>
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.
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
Fig. 4 in Retrieving climate change dependent Sea Surface Temperature (SST) in Southern Turkey by using Landsat thermal imagery
Fig. 4 — Average annual temperature in Gökova Bay
Figure 1 in Climate Changes of the Temperature of the Surface and Level of the Black Sea by the Data of Remote Sensing at the Coast of the Krasnodar Krai and the Republic of Abkhazia
Figure 1. The Black Sea coast of the Krasnodar Krai and the Republic of Abkhazia.
Figure 1 in Assessment of the accuracy of determining the Caspian Sea surface temperature by Landsat-5, -7 satellites based on the measurements of drifters
Figure 1. Drifter device [Lagrangian drifter laboratory, 2024]
CRITER 1.0: Sea Surface Temperature Evaluation Datasets
<p>Training and evaluation datasets used in CRITER 1.0: A coarse reconstruction with iterative refinement network for sparse spatio-temporal satellite data .</p>
Planktonic foraminifera faunal data and derived sea-surface temperatures for the Marine Isotope Stage (MIS) 18 to MIS 28 interval of IODP Site U1387, Gulf of Cadiz
<p>Planktonic foraminifera faunal data and sea-surface temperature reconstructions for the early-middle Pleistocene interval between 750 and 1006 kilo years from IODP Site U1387 in the Gulf of Cadiz (southern Portuguese margin). This data was used to reconstruct the paleoecological and paleoclimatical changes at the southern Portuguese margin in Mega et al. (2025), The Early–Middle Pleistocene Transition in the Gulf of Cadiz (NE Atlantic) – an interplay between subtropical gyre and extremely cold surface waters. Clim. Past 21, 919-939, doi: 10.5194/cp-21-919-2025.</p> <p>The data is also available from the world data center Pangaea as a bundled data set:</p> <p>Voelker, Antje H L; Mega, Aline; Rodrigues, Teresa (2025): Planktonic foraminifera faunal data and sea-surface temperatures for the Marine Isotope Stage (MIS) 18 to MIS 28 interval of IODP Site 339-U1387, Gulf of Cadiz [dataset bundled publication]. PANGAEA, <a href="https://doi.org/10.1594/PANGAEA.974451" target="_blank" rel="nofollow noopener">https://doi.org/10.1594/PANGAEA.974451</a></p>
PhanSST - A global database of Phanerozoic sea surface temperature proxy data
<p>Beta pre-publication release of the PhanSST database of globally distributed Phanerozoic paleo-sea surface temperature proxy data. The database is currently accepted at Scientific Data.</p>
Data for "Clouds increasingly influence Arctic sea surface temperatures as CO2 rises" part 1
<p>Data for "Clouds increasingly influence Arctic sea surface temperatures as CO2 rises" submitted to Geophysical Research Letters.</p> <p>Data are included from three fully-coupled CESM2 simulations with variable CO2 concentrations: pre-industrial climate ('control'), 424 ppm CO2 ('yr40'), and 1139 ppm CO2 ('yr140'). Data in all files are restricted to 40-90<sup>o</sup>N. Variables include surface temperature (TS), sea ice concentration (ICEFRAC), CALIPSO total cloud fraction (CLDTOT_CAL), total grid cell cloud liquid water path (TGCLDLWP), sea surface temperature (SST), surface downwelling shortwave radiation (FSDS), surface downwelling longwave radiation (FLDS), surface net shortwave radiation (FSNS), clear-sky surface net shortwave radiation (FSNSC), and clear-sky surface downwelling longwave radiation (FLDSC).</p>
Daily surface temperature and current from a 10 members ensemble simulation of June-September 2018 over the South China Sea
<p>This file contains the outputs from an ensemble of 10 members of simulation performed over the South China Sea for summer 2018.</p> <p>Members are numbered from 09 to 18.</p> <p>member_11_daily_surface_tem_u_v_JJAS.nc contains the surface daily temperature and current simulated by member 11</p> <p>grid.nc contains all information about the Arakawa C grid (longitude, latitude, mask, mesh size etc).</p> <p>wstress_surf_2018_JJAS_daily.nc contains the daily wind stress for summer 2018</p>
Sea Surface Temperature Graphs from ERA5
<p>The sea surface temperature graphs were generated from the ERA5 reanalysis product and used in the paper: Graph-Based Deep Learning for Sea Surface Temperature Forecasts, which was accepted at the Tackling Climate Change with Machine Learning Workshop at ICLR 2023.</p>
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OpenNeuro
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