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11 results for “sea-surface temperature”
SBC LTER: Reference: Sea-surface water temperature, Santa Barbara Harbor, Santa Barbara, CA, USA, 1955 to present, ongoing
The SBC-LTER has access to data on seawater temperature collected at Santa Barbara Harbor, Santa Barbara, CA, USA through the Scripps Institution of Oceanography Manual Shore Stations program. The SIO Manual Shore Stations program provides data and information about this shore station. For further information, please visit the SIO Manual Shore Stations website at https://library.ucsd.edu/dc/object/bb07606686. Please note: manual shore station data is updated periodically, not continuously. Funding for the Shore Stations Program provided by the California Department of Parks and Recreation, Natural Resources Division, Award# C22820005. Contact shorestation@ucsd.edu if you have questions
sea-surface temperature proxy data (TEX86 and UK'37) from Ocean Drilling Program Site 1168
<p>These 2 data files contain the TEX86 and UK'37 sea surface temperature proxy data from Ocean Drilling Program Site 1168, covering the Eocene to recent (35–0 Ma). These were updated compared to previous versions, wherein some alkenone data was omitted.</p>
North Atlantic average sea-surface temperature in a CMIP6 multi-model ensemble of historical and ssp585/ssp245 simulations
<p>This dataset contains North Atlantic average sea-surface temperatures and derived indices calculated for a multi-model ensemble of historical and future scenario (ssp585, ssp245) simulations contributing to the Coupled Model Intercomparison Project phase 6. A detailed description of the dataset is provided by Zanchettin, D., and Rubino, A., Accelerated North Atlantic surface warming reshapes the Atlantic Multidecadal Variability, Communications Earth & Environment, 2024, doi:10.1038/s43247-024-01804-x.</p> <p><br>The data are provided as netcdf files.</p> <p>The name of each file is structured as {model}_r{realization}_historical_{scenario}.nc where {model} is the model name, {realization} is a number corresponding to the historical realization, and {scenario} is either of the two scenarios considered (ssp585 and ssp245).</p> <p>Each file contains data for the following one dimensional variables:</p> <ul> <li>year: the sequence of years for which the data are provided</li> <li>NASST: annual-average spatially averaged North Atlantic sea-surface temperature</li> <li>state: slowly variable component of NASST obtained from a dlm decomposition of NASST</li> <li>strend: stochastic trend of NASST obtained from a dlm decomposition of NASST</li> <li>AMV: Atlantic Multidecadal Varibility index obtained as difference between NASST and state</li> </ul> <p> </p>
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>
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>
Data from: Sea-surface temperature pattern effects have slowed global warming and biased warming-based constraints on climate sensitivity
Open the record for dataset details and reuse information.
Sea-surface temperature anomalies mediate changes in fish richness and abundance in Western North Atlantic and Gulf of Mexico estuaries
<p class="MsoNormal"><strong><span>Aim: </span></strong><span>Anthropogenic-driven warming of marine systems has resulted in a series of biological and physiological responses that are fundamentally altering ecosystem structure. Because estuaries exist at the land-ocean interface, they are particularly vulnerable to the effects of ocean warming as they can undergo rapid biogeochemical and hydrological shifts due to climate and land-use change. We explored how fish diversity structures—turnover, richness and abundance—have changed in the western North Atlantic and Gulf of Mexico estuaries through space and time and the drivers of change. </span></p> <p class="MsoNormal"><span><strong>Location:</strong> North Atlantic and Northern Gulf of Mexico</span></p> <p class="MsoNormal"><strong><span>Taxa</span></strong><span>: Fish</span></p> <p class="MsoNormal"><strong><span>Results:</span></strong><span> We found that species richness and abundance, turnover have increased in North Atlantic and northern Gulf of Mexico estuaries in the last 3 decades. These changes were mediated largely by sea-surface temperature anomalies, especially in more northern estuaries where warming has been relatively pronounced. </span><span>There is also an indication that urbanization, perhaps through habitat fragmentation and/or fisheries activities may be contributing to the increase in fish richness in many of these estuaries. </span></p> <p class="MsoNormal"><strong><span>Main Conclusion: </span></strong><span>The increasing trajectory of turnover in many of the estuaries suggests that the fish communities have changed fundamentally from the baselines. A fundamental change in community composition can lead to an irreversible trophic imbalance or alternative stable states among other outcomes. Thus, predicting how shifting community structures might influence food webs, ecosystem stability and human resource use remains a pertinent task.</span></p>
Sea-surface temperature anomalies mediate changes in fish richness and abundance in Western North Atlantic and Gulf of Mexico estuaries
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Daily sea-surface temperature measurements, collected and provided by the Shore Stations Program, La Jolla CA, 1916 - May 2019
Personnel from the Stephen Birch Aquarium-Museum at Scripps take daily temperature and salinity samples from the end of the Scripps Pier at the sea surface and a depth of about 5 meters. The proximity of Scripps Pier to the deep waters at the head of La Jolla submarine canyon results in data quite representative of oceanic conditions. Scripps Pier is a total of 1084 ft. long (330.4 M) and 22.5 ft. wide for most of it's length. However it is 46.0 ft. wide at the end where the lab/pump house structure is situated with the west wall standing 88.0 ft. from the end of the pier (=996 ft. from the shore). The orientation is 277 / 97 degrees magnetic, 14 degrees East variation. The deck of the pier is 33.5 ft. above Mean Low Low Water (MLLW). Data provided by Shore Stations Program with current funding provided by the "California Department of Parks and Recreation, Division of Boating and Waterways, Award# DPR-C1370020". Data are collected by staff aquarists and volunteers with the Birch Aquarium at Scripps. Contact shorestation@ucsd.edu if you have questions
Data for "Antarctic ice-sheet meltwater reduces transient warming and climate sensitivity through the sea-surface temperature pattern effect"
<p>Data of the Historical Hosing simulations presented in "Antarctic ice-sheet meltwater reduces transient warming and climate sensitivity through the sea-surface temperature pattern effect" submitted to Geophysical Research Letters</p> <p>Authors: Yue Dong, Andrew G. Pauling, Shaina Sadai, Kyle C. Armour </p> <p>Abstract:</p> <p>Coupled global climate models (GCMs) generally fail to reproduce the observed sea-surface temperature (SST) trend pattern since the 1980s. The model-observation discrepancies may arise in part from the lack of realistic Antarctic ice-sheet meltwater imbalance in GCMs. Here we employ two sets of CESM1-CAM5 simulations forced by anomalous Antarctic meltwater fluxes over 1980--2013 and into the 21st century. Both show a reduced global warming rate and an SST trend pattern that better resembles observations. The meltwater drives surface cooling in the Southern Ocean and the tropical southeast Pacific, in turn increasing low-cloud cover and driving radiative feedbacks to become more stabilizing (corresponding to a lower effective climate sensitivity). These feedback changes contribute more than ocean heat uptake efficiency changes in reducing the global warming rate. Accurately projecting historical and future warming thus requires improved representation of Antarctic meltwater and its impacts in models. </p>
Sensitivity of atmospheric river vapor transport and precipitation to uniform sea-surface temperature increases
<p>This is the companion data for the manuscript of the same title, originally submitted to JGR: Atmospheres on 02/08/2020 and resubmitted on 06/30/2020. Specifically, this dataset corresponds to the resubmitted version. Note that the only change is the addition of code example to generate kernel density estimates of Hadley cell edge, subtropical jet, and eddy-driven jet positions. </p> <p><strong>modelParameters: </strong>this folder contains the scripts I ran on NERSC Cori in 2019 to initialize the CESM2.0/CAM5 model runs. </p> <ul> <li>qobs_script_newcase.sh: creates all cases, for the Baseline as well as the +xK SST runs</li> <li>docn_comp_mod.F90: original CAM5 aquaplanet SST distributions; "QOBS" is used for my "Baseline" experiments</li> <li>plusxK_docn_comp_mod.F90: modified SST distributions, for x=(2,4,6); these are simply uniform additions to the QOBS SST distributions</li> <li>Macros.make & env_mach_specific.xml: configuration files to run CESM2.0 on Cori at the time</li> <li>user_nl_cam: namelist for CAM5; specifies some model run parameters as well as output variables.</li> </ul> <p><strong>detectionParameters: </strong>this folder contains the scripts I ran on NERSC Cori in 2019 to detect tropical cyclones and atmospheric rivers. Use this code for reference purposes only (i.e., to see which parameters were used to detect ARs or TCs). It will not run as-is.</p> <p><strong>All other subfolders </strong>provide working examples of code used to generate figures (all in Jupyter notebooks) for the manuscript; folder names are descriptive. </p> <p>Unfortunately, model output was large (~12 TB). Hence, I only provide mean data, used directly to generate figures, in this repository. All model output are archived on tape at NERSC. </p> <p>For more details, refer to the manuscript, or contact me (eelliott@ucdavis.edu). </p>
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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