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617 results for “Climate models”
Supporting model data for Paleogeographic controls on the evolution of Late Cretaceous ocean circulation by Ladant, J.-B., et al. in Climate of the Past, doi:10.5194/cp-2019-157.
<p>The dataset is comprised of CCSM4 model variables required to reproduce the figures shown in the following manuscript:</p> <p>Ladant, J.-B., C. J. Poulsen, F. Fluteau, C. R. Tabor, K. G. MacLeod, E. E. Martin, S. J. Haynes and M. A. Rostami, Paleogeographic controls on the evolution of Late Cretaceous ocean circulation, Climate of the Past, doi:10.5194/cp-2019-157.</p>
Dataset for "Comparison of climate response to ocean albedo modification and marine cloud brightening: A model study"
<p>Reproducible dataset for "Comparison of climate response to ocean albedo modification and marine cloud brightening: A model study"</p>
The Resilience of Habitable Climates Around Circumbinary Stars: 3D climate model data Part 2
<p>Climate modeling outputs used in the paper, "The Resilience of Habitable Climates Around Circumbinary Stars", to be published JGR-Planets Special Edition on Exoplanets. Files contain 4 Earth years of hourly time cadence outputs of basic climate fields. Hourly time-cadence is needed in order to grasp the temporal variations of circumbinaries. </p>
Model output for: Attributing causes of future climate change in the California Current System with multi-model downscaling
<p>Regional Ocean Modeling System outputs from dynamic downscaling of Coupled Model Intercomparison Project climate forcings in the California Current system, including projections with full climate forcings, as well as attribution experiments with only changes in wind, heat fluxes and other properties changing stratification, and boundary biogeochemical forcings. Output variables include euphotic zone integrated net primary productivity, and incident photosytnehtically available radiation, and ocean temperature, salinity, vertical velocity, and dissolved oxygen and nitrate concentrations at select depths.</p>
Data from: Modelling the potential impacts of climate change on the distribution of ichthyoplankton in the Yangtze Estuary, China
<p><span><a name="_Hlk10553342"><b>Aim: </b></a>Species distribution models (SDMs) are an effective tool to explore the potential distribution of terrestrial, freshwater, and marine organisms; however, SDMs have been seldom used to model ichthyoplankton distributions and thus our understanding of how larval stages of fishes will respond to climate change is still limited. Here, we developed SDMs to explore potential impacts of climate change on habitat suitability of ichthyoplankton.</span></p> <p><span><b>Location: </b>Yangtze Estuary, China</span></p> <p><span><b>Methods: </b>Using long-term ichthyoplankton survey data and a large set of marine predictor variables, we developed ensemble SDMs for five abundant ichthyoplankton species in the Yangtze Estuary (<i>Coilia mystus</i>, <i>Hypoatherina valenciennei</i>, <i>Larimichthys polyactis</i>, <i>Salanx ariakensis</i>, and <i>Chelidonichthys spinosus</i>). Then, we projected their habitat suitability under present and future climate conditions.</span></p> <p><span><b>Results: </b>The ensemble SDMs had good predictive performance and were successful in estimating the known distributions of the five species. Model projections highlighted two contrasting patterns of response to future climates: while <i>C. mystus</i> will likely expand its range, the ranges of the other four species will likely contract and shift northward.</span></p> <p><span><b>Main conclusions: </b><a name="_Hlk15635552">According to our SDM projections, the five ichthyoplankton species that we tested in the Yangtze Estuary are likely to respond differently to future climate changes. These projected different responses seemingly reflect the differential functional attributes and life history strategies of these species. </a>To the extent that climate change emerges as a critical driver of the future distribution of these species, our findings provide an important roadmap for designing future conservation strategies for ichthyoplankton in this region.</span></p>
Dataset supporting - On the Problem of Modeling the Boat Wake Climate; the Florida Intracoastal Waterway - by Forlini et al., submitted to JGR-Ocean
<p>This dataset comprises of 9 .txt file containing water levels data (m) necessary to reconstruct the wakes observations for all the instruments (Acoustic Doppler Velocimeter) deployed during the field experiment.</p> <p> </p>
Data for GMD article: "Towards an improved treatment of cloud-radiation interaction in weather and climate models: exploring the potential of the Tripleclouds method for various cloud types using libRadtran 2.0.4"
<p>Dataset for the publication by Nina Črnivec and Bernhard Mayer: "Towards an improved treatment of cloud-radiation interaction in weather and climate models: exploring the potential of the Tripleclouds method for various cloud types using libRadtran 2.0.4" submitted to Geoscientific Model Development in 2020.</p> <p>The repository contains data for stratocumulus, cirrus and cumulonimbus cloud case studies. It also contains MYSTIC benchmark radiation data (including atmosphering heating rate and net surface flux) for the aforementioned cloud cases. See README for additional information and description of data files.</p>
Data from: Climate limitation at the cold edge – contrasting perspectives from species distribution modelling and a transplant experiment
<p>The role of climate in determining range margins is often studied using species distribution models (SDMs), which are easily applied but have well-known limitations, e.g. due to their correlative nature and colonization and extinction time lags. Transplant experiments can give more direct information on environmental effects, but often cover small spatial and temporal scales. We simultaneously applied an SDM using high-resolution spatial predictors and an integral projection (demographic) model based on a transplant experiment at 58 sites to examine the effects of microclimate, light and soil conditions on the distribution and performance of a forest herb, <i>Lathyrus vernus</i>, at its cold range margin in central Sweden. In the SDM, occurrences were strongly associated with warmer climates. In contrast, only weak effects of climate were detected in the transplant experiment, whereas effects of soil conditions and light dominated. The higher contribution of climate in the SDM is likely a result from its correlation with soil quality, forest type, and potentially historic land use, which were unaccounted for in the model. Predicted habitat suitability and population growth rate, yielded by the two approaches, were not correlated across the transplant sites. We argue that the ranking of site habitat suitability is probably more reliable in the transplant experiment than in the SDM because predictors in the former better describe understory conditions, but that ranking might vary among years, e.g. due to differences in climate. Our results suggest that <i>L. vernus</i> is limited by soil and light rather than directly by climate at its northern range edge, where conifers dominate forests and create suboptimal conditions of soil and canopy-penetrating light. A general implication of our study is that to better understand how climate change influences range dynamics, we should not only strive to improve existing approaches but also to use multiple approaches in concert.</p>
A climate database with varying drought-heat signatures for climate impact modelling
<p>To allow for impact modelling for a wide range of sectors, we provide six scenarios with differing drought-heat signatures. Each scenario is 100 years long and we provide temperature variables (mean, minimum, maximum), precipitation, radiation (short- and longwave downward radiation and shortwave net radiation) and wind (zonal and meridional) at daily timescales. All variables are available at a regular 1◦×1◦grid over land, except Antarctica and large parts of Greenland. Leap days were removed, so there are 365×100 time steps for each scenario.</p>
Quality-quantity tradeoffs drive functional trait evolution in a model microalgal "climate change winner"
<p>Phytoplankton are the unicellular photosynthetic microbes that form the base of aquatic ecosystems, and their responses to global change will impact everything from food web dynamics to global nutrient cycles. Some taxa respond to environmental change by increasing population growth rates in the short-term, and are projected to increase in frequency over decades. To gain insight into how these projected "climate change winners" evolve, we grew populations of microalgae in ameliorated environments for several hundred generations. Most populations evolved to allocate a smaller proportion of carbon to growth while increasing their ability to tolerate and metabolise reactive oxygen species (ROS). This tradeoff drives the evolution of traits that underlie the ecological and biogeochemical roles of phytoplankton. This offers evolutionary and a metabolic frameworks for understanding trait evolution in projected "climate change winners", and suggests that short-term population booms have the potential to be dampened or reversed when environmental amelioration persists.</p>
Data from: Phylogeography, population genetics, and distribution modeling reveal vulnerability of Scirpus longii (Cyperaceae) and the Atlantic Coastal Plain Flora to climate change.
A proactive approach to conservation must be predictive, anticipating how habitats will change and which species are likely to decline or prosper. We use composite species distribution modeling to identify suitable habitats for 18 members of the North American Atlantic Coastal Plain Flora (ACPF) since the Last Glacial Maximum and project these into the future. We then use Scirpus longii (Cyperaceae), a globally imperiled ACPF sedge with many of the characteristics of extinction vulnerability, as a case study. We integrate phylogeographic and population genetic analyses and species distribution modeling to develop a broad view of its current condition and prognosis for conservation. We use genotyping-by-sequencing to characterize the genomes of 142 S. longii individuals from twenty populations distributed throughout its range (New Jersey to Nova Scotia). We measure the distribution of genetic diversity in the species and reconstruct its phylogeographic history using SNAPP and RASE. Extant populations of S. longii originated from a single refugium south of the Laurentide ice sheet around 25 thousand years ago. The genetic diversity of S. longii is exceedingly low, populations exhibit little genetic structure, and the species is slightly inbred. Projected climate scenarios indicate that nearly half of extant populations of S. longii will be exposed to unsuitable climate by 2070. Similar changes in suitable habitat will occur for many other northern ACPF species – centers of diversity will shift northward and Nova Scotia may become the last refuges for those species not extinguished.
Data from: Climate-mediated hybrid zone movement revealed with genomics, museum collection and simulation modeling
Climate-mediated changes in hybridization will dramatically alter the genetic diversity, adaptive capacity and evolutionary trajectory of interbreeding species. Our ability to predict the consequences of such changes will be key to future conservation and management decisions. Here we tested through simulations how recent warming (over a 32-year period) is affecting the geographic extent of a climate-mediated developmental threshold implicated in maintaining a butterfly hybrid zone (Papilio glaucus and Papilio canadensis; Lepidoptera: Papilionidae). These simulations predict a 68 km shift of this hybrid zone. To empirically test this prediction, we assessed genetic and phenotypic changes using contemporary and museum collections and document a 40 km northward shift of this hybrid zone. Interactions between the two species appear relatively unchanged during hybrid zone movement. We found no change in the frequency of hybridization and regions of the genome that experience little to no introgression moved largely in concert with the shifting hybrid zone. Model predictions based on climate scenarios predict this hybrid zone will continue to move northward, but with substantial spatial heterogeneity in the velocity (55-144 km/1°C), shape, and contiguity of movement. Our findings suggest that the presence of non-climatic barriers (e.g., genetic incompatibilities) and/or non-linear responses to climatic gradients may preserve species boundaries as the species shift. Further, we show that variation in the "geography" of hybrid zone movement could result in evolutionary responses that differ for geographically distinct populations spanning hybrid zones and thus have implications for the conservation and management of genetic diversity.
Impact of increased resolution on long-standing biases in HighResMIP-PRIMAVERA climate models
<p>This contains the data and plot scripts to reproduce the figures of the manuscript: <em>Impact of increased resolution on long-standing biases in HighResMIP-PRIMAVERA climate models</em>.</p> <p><strong>Authors:</strong></p> <p>Eduardo Moreno-Chamarro<sup>1*</sup>, Louis-Philippe Caron<sup>1,2</sup>, Saskia Loosveldt Tomas<sup>1</sup>, Oliver Gutjahr<sup>3,4</sup> , Marie-Pierre Moine<sup>5</sup>, Dian Putrasahan<sup>3</sup> , Christopher D. Roberts<sup>6</sup>, Malcolm J. Roberts<sup>7</sup>, Retish Senan<sup>6</sup>, Laurent Terray<sup>5</sup>, Etienne Tourigny<sup>1</sup>, Pier Luigi Vidale<sup>8</sup></p> <p><br> <sup>1 Barcelona Supercomputing Center (BSC), Barcelona, Spain.</sup></p> <p><sup>2 Ouranos, Montreal, H3A 1B9, Canada.</sup></p> <p><sup>3 Max Planck Institute for Meteorology. Hamburg, Germany.</sup></p> <p><sup>4 Now at Institut für Meereskunde, Universität Hamburg, Hamburg, Germany.</sup></p> <p><sup>5 CECI, Université de Toulouse, CERFACS/CNRS, Toulouse, France.</sup></p> <p><sup>6 ECMWF European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom.</sup></p> <p><sup>7 Met Office, Exeter EX1 3PB, United Kingdom.</sup></p> <p><sup>8 NCAS-Climate, Department of Meteorology, University of Reading, Reading, United Kingdom.</sup></p> <p><sup>Correspondence to: Eduardo Moreno-Chamarro (eduardo.moreno@bsc.es)</sup></p> <p><strong>Abstract. </strong>We examine the impacts of increased resolution on four long-standing biases using five different climate models developed within the PRIMAVERA project. Atmospheric resolution is increased from ~100–200 km to ~25–50 km, and ocean resolution is increased from ~1° (i.e., eddy-parametrized) to ~0.25° (i.e., eddy-present). For one model, ocean resolution is also increased to 1/12° (i.e., eddy-rich). Fully-coupled general circulation models and their atmosphere-only versions are compared with observations and reanalysis of near-surface temperature, precipitation, cloud cover, net cloud radiative effect, and zonal wind over the period 1980–2014. Both the ensemble mean and the individual models are analyzed. Increased resolution especially in the atmosphere helps reduce the surface warm bias over the tropical upwelling regions in the coupled models, with further improvements in the cloud cover and precipitation biases over the tropical Atlantic particularly. Related to this and to the improvement in the precipitation distribution over the western tropical Pacific, the double ITCZ bias also weakens with resolution. Overall, increased ocean resolution from 1° to 0.25° offers limited improvements or even bias degradation in some models, although an eddy-rich ocean resolution seems beneficial to reduce the North Atlantic cold bias and the Gulf Stream path. Despite the improvements, however, large biases in precipitation and cloud cover persist over the whole tropics as well as in the upper-troposphere zonal winds at mid-latitudes in both coupled and atmosphere-only models at higher resolutions. The SO warm bias also worsens or persists in some coupled models. And a new warm bias emerges in the Labrador Sea in all the high-resolution coupled models. The analysis of the PRIMAVERA models therefore suggests that, to reduce biases, i) increased atmosphere resolution up to ~25–50 km alone might not be sufficient and ii) an eddy-rich ocean resolution might be needed. The study thus adds to evidence that further improved model physics and tuning might be necessary in addition to increased resolution to mitigate biases.</p>
Data from: Impacts of rainfall extremes predicted by climate-change models on major trophic groups in the leaf-litter arthropod community
1. Arthropods in the leaf-litter layer of forest soils influence ecosystem processes such as decomposition. Climate-change models predict both increases and decreases in average rainfall. Increased drought may have greater impacts on the litter arthropod community. In addition to affecting survival or behavior of desiccation-sensitive species, lower rainfall may indirectly lower abundances of consumers that graze drought-stressed fungi, with repercussions for higher trophic levels. 2. We tested the hypothesis that trophic structure will differ between the two rainfall scenarios. In particular, we hypothesized that densities of several broadly defined trophic groupings of arthropods would be lower under reduced rainfall. 3. To test this hypothesis we used sprinklers to impose two rainfall treatments during three growing seasons in roofed, fenced 14-m2 plots; and documented changes in abundance from initial, pre-treatment densities of 39 arthropod taxa. Experimental plots were subjected to either LOW (fortnightly) or HIGH (weekly) average rainfall based upon climate models and the previous 100 years of regional weekly averages. Unroofed open plots, our reference treatment (REF), experienced higher-than-average rainfall during the experiment. 4. The two rainfall extremes produced clear negative effects of lowered rainfall on major trophic groups. Broad categories of fungivores, detritivores and predators were more abundant in HIGH than LOW plots by the final year. Springtails (Collembola), which graze fungal hyphae, were 3x more abundant in the HIGH-rainfall treatment. Taxa of larger-bodied fungivores and detritivores, spiders (Araneae), and non-spider predators were 2x more abundant under HIGH rainfall. Densities of mites (Acari), which include fungivores, detritivores and predators, were 1.5x greater in HIGH rainfall plots. Abundances and community structure of arthropods were similar in REF and experimental plots, showing that effects of rainfall uncovered in the experiment are applicable to nature. 5. This pattern suggests that changes in rainfall will alter bottom-up control processes in a critical detritus-based food web of deciduous forests. Our results, in conjunction with other findings on the impact of desiccation on arthropods and fungal growth, suggest that drier conditions will depress densities of fungal consumers, causing declines in higher trophic levels, with possible impacts on soil processes and the larger forest food web.
Spin-up time and internal variability analysis for overlapping time slices in a regional climate model
<p>In order to increase computational efficiency, several long-term regional climate simulations were split into overlappings time slices. These overlappings slices were used to explore the relative role of spin-up time and internal variability in the discontinuities that are produced once the slices are joined.</p> <p>This dataset was generated using the Weather Research and Forecasting (WRF) model and includes two sets of time slices for the periods 2002-2006 and 2006-2010 over the CORDEX South American domain at 0.44º horizontal resolution (SAM-44), regular on a rotated latitude-longitude projection. The data was forced by the scenario RCP 8.5 and driven by the Canadian Earth System model (CanESM2). The model configuration files are also attached.</p>
Data Release for Retreat and Regrowth of the Greenland Ice Sheet During the Last Interglacial as Simulated by the CESM2-CISM2 Coupled Climate–Ice Sheet Model
<p>CESM2 and CISM2 data files for figures in "Retreat and Regrowth of the Greenland Ice Sheet During the Last Interglacial as Simulated by the CESM2-CISM2 Coupled Climate–Ice Sheet Model" (Sommers et al., 2021, Paleoceanography and Paleoclimatology)</p>
Main output data used in "Coupling the regional climate MAR model with the ice sheet model PISM mitigates the melt-elevation positive feedback" (Delhasse et al., 2024)
<p>Outputs used in:</p> <p><em>Delhasse, A., Beckmann, J., Kittel, C., and Fettweis, X.: Coupling MAR (Modèle Atmosphérique Régional) with PISM (Parallel Ice Sheet Model) mitigates the positive melt–elevation feedback, The Cryosphere, 18, 633–651, https://doi.org/10.5194/tc-18-633-2024, 2024.</em></p> <p>MAR-PISM coupling experiments outputs over 1991-2200. The main experiments are:</p> <ul> <li>MAPI-2w: 2-way coupling, consideration <em>online</em> of the melt-elevation feedback (evolving topography in MAR).</li> <li>MAPI-1w: 1-way coupling, consideration of the melt-elevation feedback only with the <em>offline</em> correction (Franco <em>et al.</em>, 2012) of the MAR outputs (fixed topography in MAR).</li> <li>MAPI-0w: 0-way coupling, no consideration of the melt-elevation feedback (fixed topography in MAR and no correction during interpolation).</li> </ul> <p>MAR files contain yearly SMB (surface mass balance) and ST (surface temperature) interpolated (with correction) on the PISM-4.5km grid. Gradients used for the correction of the melt-elevation feedback are also given for both variables. SMB and ST are the two required MAR fields to couple MAR with PISM. </p> <p>PISM files contain yearly ice thickness (THK) and ice mask (MASK) as simulated by PISM for each of the three experiments. </p> <p>The MAR code used in this dataset is tagged as v3.11.3 on https://gitlab.com/Mar-Group/MARv3# (last access: 23 January 2024) (MARTeam, 2024). The PISM code used is tagged as PISMv1.2.2 on <a href="https://github.com/pism/pism/releases/tag/v1.2.2" target="_blank" rel="noopener noreferrer">https://github.com/pism/pism/releases/tag/v1.2.2</a> (last access: 23 January 2024). Other coupling scripts are also available upon request by email (<a href="mailto:alison.delhasse@uliege.be" target="_blank" rel="noopener noreferrer">alison.delhasse@uliege.be</a>).</p> <p>If you need other variables from MAR or PISM, send us an email (alison.delhasse@uliege.be, johanna.beckmann@monash.edu) and we will be glad to help you. We will also be happy to share the scripts we have developed to analyse the outputs and make the figures in this paper if needed. Please cite the paper if you use these MAR-PISM outputs.<br><br>Data usage notice:</p> <p>If you use any of these results, please acknowledge the work of the people involved in producing them. Acknowledgments should be similar to the one below that contains information related to MAR and PISM. To document MAR scientific impact and enable ongoing support of the model, users are likely encouraged to contact me to add their works to the list of MAR-related publications. </p> <p>"We thank A. Delhasse and J. Beckmann, as well as the MAR and PISM teams which make available the model outputs. We also thank agencies (F.R.S - FNRS, CÉCI, and the Walloon Region) that provided computational resources for MAR-PISM simulations. "</p> <p>You should also refer to and cite the following paper in its latest version:</p> <p><em>Delhasse, A., Beckmann, J., Kittel, C., and Fettweis, X.: Coupling MAR (Modèle Atmosphérique Régional) with PISM (Parallel Ice Sheet Model) mitigates the positive melt–elevation feedback, The Cryosphere, 18, 633–651, https://doi.org/10.5194/tc-18-633-2024, 2024.</em></p> <p>Reference</p> <p><em>Franco, B., Fettweis, X., Lang, C., and Erpicum, M.: Impact of spatial resolution on the modelling of the Greenland ice sheet surface mass balance between 1990–2010, using the regional climate model MAR, The Cryosphere, 6, 695–711, https://doi.org/10.5194/tc-6-695-2012, 2012.</em></p> <p><em>MARTeam: MARv3.11, GitLab [data set], <a href="https://gitlab.com/Mar-Group/MARv3" target="_blank" rel="noopener">https://gitlab.com/Mar-Group/MARv3#</a> (last access: 28 May 2022), 2021.</em></p>
Application of a Comprehensive Hygroscopicity Framework for Simulating Aerosol Water Uptake in a Large-scale Climate Model
<p>This dataset was generated from 18-month simulations of the NCAR Community Atmosphere Model (CAM); the atmospheric component of the Community Earth System Model version 2 (CESM2). The dataset can be used to reproduce the analysis and figures presented in the upcoming JGR publication.</p>
Data for the publication "Developing a climatological simplification of aerosols to enter the cloud microphysics of a global climate model" - part 2
<p>The data is split into two datasets, for each to be smaller than 50 GB.</p>
Evaluating Effects of Climate Change, Restoration Scenarios, and Hatchery Effects on Chinook Salmon in the Stillaguamish River Basin with the HARP Model
<p>Model code (R) to accompany the 2023 NOAA report "<strong>Evaluating Effects of Climate Change, Restoration Scenarios, and Hatchery Effects on Chinook Salmon in the Stillaguamish River Basin with the HARP Model</strong>"</p>
ScienceDex guides
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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.