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2,837 results for “Climate Data”
Data for: Climate and forest attributes influence aboveground biomass of deciduous broadleaf forests in China
<p>Forests provide a huge carbon pool, a substantial portion of which is stored in aboveground biomass (AGB). Deciduous broadleaf forests in China are an essential component of global deciduous broadleaf forests, yet the impacts of climate and forest attributes on their AGB are not well understood.</p> <p>Using a comprehensive forest inventory database available from 772 plots distributed across the temperate and subtropical deciduous broadleaf forests in China (23.51°-42.53° N and 104.24°-128.27° E), we applied variance partitioning analysis, model selection analysis and structural equation models to explore how AGB was associated with climate and forest attributes (species diversity, community-level functional traits, and stand structures) in different climatic regions (semi-arid forests, semi-humid forests and humid forests).</p> <p>Community-level functional traits and stand structures together explained a great portion of the variance in AGB. The effect of community-level functional traits was greater than that of stand structures in semi-arid forests and semi-humid forests, but smaller in humid forests. Further analyses showed that community-level maximum tree height, stem density and tree size inequality were the best explanatory variables. Although climate and species diversity had only minor effects, the direct positive effect of mean annual precipitation (MAP) was still important, especially in semi-arid forests.</p> <p><em><strong>Synthesis.</strong></em> Community-level functional traits but not species diversity were key drivers of AGB, indicating that tree species diversity loss may not impair AGB substantially in deciduous broadleaf forests in China. Moreover, stand structures had also strong effects on AGB in both semi-arid forests and humid forests, highlighting the importance of structural complexity. In addition, MAP had a direct positive effect on AGB in semi-arid forests and semi-humid forests, and a future predicted increase in drought might potentially reduce carbon storage in these forests.</p>
Data for The missing risks of climate change
<p>This repository contains the data behind the quantitative figures (figures 1, 3, and 4) in Rising, James, et al. "The missing risks of climate change." <em>Nature</em> 610.7933 (2022): 643-651. https://www.nature.com/articles/s41586-022-05243-6.</p> <p>The figures directory contains the figures (in their accepted paper form). The data directory contains CSV files with the associated data. The rows and columns are defined as follows:</p> <p> - fig1-mc.csv: Rows describe Monte Carlo draws describing the uncertainty for each scenario (SSP1-2.6 and SSP3-7.0) and outcome variable (in the "variable" column). The "run" column describes the basis for each draw of the uncertainty (e.g., model used). The "unit" column provides the units for the "value" column. The "compound" column is TRUE if the rows report compounded uncertainty, and false if the uncertainty is only from the individual analysis stage.</p> <p> - fig3-zscores.csv: Each row is a grid cell across the globe, reporting z-scores for various hazards and the population from GPW v4.0 (https://sedac.ciesin.columbia.edu/data/collection/gpw-v4). The z-scores are calculated compared to the recent history (1980-2010) from either longer historical data from CRU TS, with the column prefix "hist.", or from SSP3-7.0 estimates from WorldClim bioclimatic variables for 2050, with the column prefix "ssp370.". Column suffixes describe various hazards: "wet" is average precipitation in the wettest month, "dry" is annual precipitation, "logwet" is as "wet" but evaluated in logs, "logdry" is as "dry" but evaluated in logs, "pcv" is precipitation seasonality (coefficient of variation), "hot" is the maximum temperature of the warmest month, and "cld" is the minimum temperature of the coldest month. "topcol" reports the column with the most extreme z-score (with the z-score in "topscore" and a label in "toplabel").</p> <p> - fig4-dmgfunc.csv: Monte Carlo draws of the uncertainty in number of people affected across 16 impacts, reported in "affected" as a fraction of the global population, for each temperature change from preindustrial, reported in "temp".</p> <p> - fig4-pdfs.csv: Monte Carlo draws of the uncertainty in the number of people affected for each of 16 impacts and four aggregates. The fraction of the global population affected in reported in "affected" for the temperature change from preindustrial reported in "temp". The impact is labeled in "name" and the aggregate category is reported in "rname".</p> <p>Additional details on the generation of these data are included in the SI of the paper.</p>
Intermediate data belonging to "Process-based climate change assessment for European winds using EURO-CORDEX and global models"
<p>This dataset contains the intermediate results of Wohland (2022) that are needed to redo the analysis und produce the figures. It allows to bypass those steps that rely on access to the supercomputers at the German Climate Computing Centre (DKRZ). When using this data in academic work, please reference</p> <blockquote> <p>Jan Wohland, Process-based climate change assessment for European winds using EURO-CORDEX and global models, Environmental Research Letters (provisionally accepted on 28/11/2022), 2022</p> </blockquote> <p><strong>Using this data to reproduce results</strong></p> <p>The data can be used together with the code provided in https://github.com/jwohland/kliwist_modelchain</p> <p>In the above mentioned github repository, there is a `run_all.py` script that repeats the analysis presented in Wohland (2022). After downloading and extracting this data, you can ignore the steps under "calculations", and begin with "plots".</p> <p><strong>Underlying data</strong></p> <p>The dataset draws on output from the CMIP5, CMIP6 and EURO-CORDEX initiatives. I thank the climate modeling groups for making their data openly available. In particular, I acknowledge the World Climate Research Programme’s Working Group on Regional Climate, and the Working Group on Coupled Modelling, former coordinating body of CORDEX and responsible panel for CMIP5. I also acknowledge the Earth System Grid Federation infrastructure an international effort led by the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison, the European Network for Earth System Modelling and other partners in the Global Organisation for Earth System Science Portals (GO-ESSP). I also acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP5 and CMIP6.</p> <p><strong>Funding</strong></p> <p>This work is part of the project "The influence of climate change on wind energy site assessments – KliWiSt" funded by the German Federal Ministry for Economic Affairs and Climate Action (BMWK).</p> <p><strong>References to raw data journal articles</strong></p> <blockquote> <p>Jacob, D. <em>et al.</em> EURO-CORDEX: new high-resolution climate change projections for European impact research. <em>Reg Environ Change</em> <strong>14</strong>, 563–578 (2014).</p> </blockquote> <blockquote> <p>Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An Overview of CMIP5 and the Experiment Design. <em>Bull. Amer. Meteor. Soc.</em> <strong>93</strong>, 485–498 (2012).</p> </blockquote> <blockquote> <p>Hurtt, G. C. <em>et al.</em> Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands. <em>Climatic Change</em> <strong>109</strong>, 117–161 (2011).</p> </blockquote>
Data from: Microclimate-based species distribution models in complex terrain indicate widespread cryptic refugia under climate change
<p class="MsoNoSpacing"><i>Aim: </i>Species' climatic niches may be poorly predicted by regional climate estimates used in species distribution models (SDMs) due to microclimatic buffering of local conditions. Here, we compare SDMs generated using a locally validated below-canopy microclimate model to those based on interpolated weather station data at two spatial scales to determine the effects of scale, topography, and forest cover on potential future ground-level warming and species distributions.</p> <p class="MsoNoSpacing"><i>Location:</i> Great Smoky Mountains National Park (2090 km<sup>2</sup>; NC, TN, USA)</p> <p class="MsoNoSpacing"><i>Time period: </i>1970 – 2006</p> <p class="MsoNoSpacing"><i>Major taxa:</i> Vascular plant species of the Southern Appalachians</p> <p class="MsoNoSpacing"><i>Methods:</i> We compared the fit and predictions of SDMs generated using a database of plant occurrences and three climate models: macroclimate (1 km, WorldClim), fine-scale (30 m) interpolation of macroclimate with elevation, and fine-scale below-canopy microclimate from a ground-level sensor network.</p> <p class="MsoNoSpacing"><i>Results: </i>We found that, although SDM fit was similar across models, microclimate-derived SDMs predicted substantially greater species persistence with 4 °C of regional warming, with a difference of 50% of the species pool in some areas. Microclimate SDMs predicted higher stability of mid-elevation species, particularly in thermally buffered areas near streams, and critically, less change in species composition at high elevation. In contrast, predictions of macroclimate and interpolation models were similar despite improved resolution.</p> <p class="MsoNoSpacing"><i>Main conclusions:</i> Our results demonstrate that careful selection of climate drivers, including local near-ground validation rather than interpolation, is critical for projecting distributions. They also suggest that some species at risk from climate change might persist, even with 4 °C of macroclimate warming, in cryptic refugia buffered by microclimate, pointing to the roles of forest cover and topography in explaining slower-than-expected changes in understory communities. However, certain species, such as those currently occurring on low-elevation ridges that are sensitive to atmospheric changes, may be at more risk than macroclimate or interpolated SDMs suggest.</p> <p class="MsoNoSpacing"> </p>
Copernicus Climate Change Service data for the pypsa-entsoe Github repository
<p>Files needed for the https://github.com/matteodefelice/pypsa-entsoe repository.</p>
Data from: Evolutionary constraints mediate extinction risk under climate change
<p>Mounting evidence suggests that rapid evolutionary adaptation may rescue some organisms from the impacts of climate change. However, evolutionary constraints might hinder this process, especially when different aspects of environmental change generate antagonistic selection on genetically correlated traits. Here, we use individual-based simulations to explore how genetic correlations underlying the thermal physiology of ectotherms might influence their responses to the two major components of climate change—increases in mean temperature and thermal variability. We found that genetic correlations can influence population dynamics under climate change, with declines in population size varying three-fold depending on the type of correlation present. Surprisingly, populations whose thermal performance curves were constrained by genetic correlations often declined less rapidly than unconstrained populations. Our results suggest that accurate forecasts of the impact of climate change on ectotherms will require an understanding of the genetic architecture of the traits under selection.</p>
Supplementary materials and data: Climate change in the Arctic: testing the poleward expansion of ticks and tick-borne diseases
<p>This accompanies the article "Climate change in the Arctic: testing the poleward expansion of ticks and tick-borne diseases" that has been accepted for publication in Global Change Biology. The file contains the supplementary materials for the article including the raw microsatellite genotype data and a link to the files containing the serological data and analyses.</p>
Data for "Nitrogen availability mediates soil carbon cycling response to climate warming: a meta-analysis"
<p>This dataset was used to make tables and figures for the study entitled "Nitrogen availability mediates soil carbon cycling response to climate warming: a meta-analysis", which was submitted to Global Change Biology in October 2022. It contains a meta-analysis database focusing on the effects of warming on soil C storage, root biomass and soil respiration.</p>
Data for: Spring emergence and canopy development strategies in miscanthus hybrids in Mediterranean, continental and temperate European climates
<p class="MsoNormal"><span>Due to its versatility and storability, biomass is an important resource for renewable materials and energy. Miscanthus hybrids combine high yield potential, low input demand, tolerance of certain marginal land types and several ecosystem benefits. To date, miscanthus breeding has focussed on increasing yield potential by maximising radiation interception through: 1) selection for early emergence, 2) increasing the growth rate to reach canopy closure fastest possible, and 3) delayed flowering and senescence. The objective of this paper is to compare early season re-growth in miscanthus hybrids cultivated at across Europe. Determination of differences in early canopy development on end-of-year yield traits are required to provide information for breeding decisions to improve future crop performance. Therefore, a trial was planted with four miscanthus hybrids (two novel seed-based hybrids <em>M. sinensis×sinensis</em> (<em>M sin×sin</em>) and <em>M. sacchariflorus×sinensis </em>(<em>M sac×sin</em>), a novel rhizome-based <em>M sac×sin</em> and a standard <em>Miscanthus</em>×<em>giganteus </em>(<em>M</em>×<em>g</em>) clone) in the UK, Germany, Croatia and Italy and was monitored in the third and fourth growing season. We determined differences in base temperature, frost sensitivity and emergence strategy between the hybrids. <em>M×g</em> and <em>M sac×sin</em> mainly emerged from belowground plant organs, producing fewer but thicker shoots at the beginning of the growing season, but these shoots were susceptible to air frosts (as determined by recording 0°C at 2 m above ground surface). By contrast, <em>M sin×sin</em> emerged 10 days earlier avoiding damage by late spring frosts with a high number of thinner shoots from aboveground shoots. Therefore we recommend cultivating <em>M sac×sin</em> at locations with low risk and <em>M sin×sin</em> at locations with higher risk of late spring frosts. Selecting miscanthus hybrids producing shoots throughout the vegetation period is an effective strategy to limit the risk of late frost damages and avoid a reduction in yield due to a shortened growing season. </span></p>
Data and GrADS scripts for "Changes in March mean snow water equivalent since the mid-twentieth century and the contributing factors in reanalyses and CMIP6 climate models", submitted to The Cryosphere
<p>Data and GrADS (Grid Analysis and Display System) scripts for reproducing the figures and numerical results included in the manuscript "Changes in March mean snow water equivalent since the mid-twentieth century and the contributing factors in reanalyses and CMIP6 climate models". Revised for The Cryosphere in March 2023.</p> <p>In addition to the README file, there are two zipped archives:</p> <p>swe_trends.zip (2.3 GB) includes both the data (mostly as GrADS binaries), the GrADS data descriptor files and the scripts.</p> <p>swe_trends_no_data.zip (74 kB) includes just the scripts and the data descriptor files.</p> <p>Please see the README file for further details on the content and use of the archives.</p>
Data for "Energy Surplus and Atmosphere – Land-Surface "Tug of War" Induced by Climate Change Control Future Evapotranspiration"
<p>USGS gauges used in manuscript "<strong>Energy Surplus and An Atmosphere-Land-Surface “Tug of War” Control Future Evapotranspiration"</strong>. USGS_CTL15_Gage.mat contains the USGS gauge ID, and one can use retrieve_daily_streamflow.m to download the corresponding streamflow time series. </p>
Data for: Coral adaptive capacity insufficient to halt global transition of coral reefs into net erosion under climate change
<p>Projecting the effects of climate change on net reef calcium carbonate production is critical to understanding the future impacts on ecosystem function, but prior estimates have not included corals' natural adaptive capacity to such change. Here we estimate how the ability of symbionts to evolve tolerance to heat stress, or for coral hosts to shuffle to favourable symbionts, and their combination, may influence responses to the combined impacts of ocean warming and acidification under three representative concentration pathway emissions scenarios (RCP2.6, RCP4.5, RCP8.5). We show that symbiont evolution and shuffling both individually and when combined favours persistent positive net reef calcium carbonate production. However, our projections of future net calcium carbonate production under climate change vary both spatially and by RCP. For example, 19–35% of modelled coral reefs are still projected to have net positive net calcium carbonate production by 2050 if symbionts can evolve increased thermal tolerance, depending on the RCP. Without <span>symbiont adaptive capacity,</span> the number of coral reefs with positive net calcium carbonate production drops to 9–13% by 2050. Accounting for both symbiont evolution and shuffling, we project median positive net calcium carbonate production of coral reefs will still occur under low greenhouse emissions (RCP2.6) in the Indian Ocean, and even under moderate emissions (RCP4.5) in the Pacific Ocean. However, adaptive capacity will be insufficient to halt the transition of coral reefs globally into erosion by 2050 under severe emissions scenarios (RCP8.5).</p>
Supporting data for: Emissions background, climate, and season determine the impacts of past and future pandemic lockdowns on atmospheric composition and climate
<p>COVID-19 pandemic responses affected atmospheric composition and climate. These effects are historically contingent, depending on the background emissions, climate, and season in which they occur. We used the GISS ModelE Earth System Model to evaluate how atmospheric and climate impacts depend on the decade and season in which lockdowns occurred. Data underlying the figures and analysis are provided as Python numpy arrays as a courtesy for peer reviewers. These data are annual means of diagnostic variables from ModelE.</p>
Climate data, burned areas and active fires predited in Guinea-Savannah and Forest-savannah mosaic zones in Ghana
<p>Climate data, burned areas and active fires predited in Guinea-Savannah zone and Forest-savannah mosaic zone in Ghana</p>
Data for Spaulding-Astudillo and Mitchell (2023), "Effects of varying saturation vapor pressure on climate, clouds, and convection"
<p>Data for Spaulding-Astudillo and Mitchell (2023), "Effects of varying saturation vapor pressure on climate, clouds, and convection"</p> <p>The main directories have a common nomenclature: e.g., TEST_1360_FSC_288K_1p0, where 1360 is the insolation, FSC indicates that it is a full-sky radiation run, 288 K is the initial surface temperature, and the multiplicative factor on the saturation vapor pressure of water is 1p0, meaning 1.0. </p> <p>In every directory, each .nc file contains 5 years of model output. There are 5 types of .nc files, which correspond to different output streams of ECHAM6. The main output stream is ..._echam.nc.</p>
Bayesian spatiotemporal modelling of wildfire occurrences and sizes for projections under climate change (Data)
<p>This repository contains the data necessary to reproduce the study developed in Legrand et al. (2023) "Bayesian spatiotemporal modelling of wildfire occurrences and sizes for projections under climate change"</p>
"The main message is that sustainability would help" – Reflections on takeaway messages of climate change data visualizations.
<p>As part of a larger project investigating expert opinions on public climate change communication and the role of data visualizations1, we conducted semi-structured interviews with 17 experts in the fields of climate change, science communication, or data visualization. We also interviewed six members of the general public with no professional background in either of these areas, who we refer to as lay participants. In the following, lay participants are identified as L-1 to L-6 and expert participants as E-1 to E-17.</p> <p>We used two example visualizations from online news sources (if preferred, translated to German) as a discussion basis and asked participants about the main takeaway message the visualization author wanted to convey. Example visualization 1 was also shown to 17 experts, resulting in a total of 23 formulated takeaway messages. Example visualization 2 was shown to all six lay participants and to seven experts, resulting in a total of 13 messages. For both example visualizations and an overall count of 36 formulated takeaway messages for thematic analysis, we have observed variations in the included contents and the length/abstraction of messages, as well as in the sensemaking process itself among the two participant groups, but also between lay and expert participants. This document provides an overview of those 36 takeaway messages formulated by the study participants.</p>
Data for: Phenotypic outcomes of predator-prey coevolution are predicted by landscape variation in climate and community composition
<ol> <li>Landscape patterns of phenotypic coevolution are determined by variation in the outcome of predator-prey interactions. These outcomes may depend not only on the functional phenotypes that mediate species interactions but also on aspects of the environment that enable encounters between coevolutionary partners.</li> <li>Exploring the relationship between coevolutionary traits and the environment requires extensive sampling across the range of the interaction to determine the relationship between local ecological variation and coevolution.</li> <li>In this study, we synthesized >30 years of data on predator-prey interactions between toxic newts (<em>Taricha</em> <em>granulosa</em>) and their snake predators (<em>Thamnophis</em> <em>sirtalis</em>) to explore the environmental predictors of arms race escalation.</li> <li>We found that geographic variation in phenotypes at the interface of coevolution was best predicted by a combination of community and climatic variation. Coevolutionary phenotypes were greatest in environments with climate favorable for newt-snake overlap. We found prey toxicity was elevated in regions with more predator species, and predator resistance was higher in regions with more prey species.</li> <li>Our results suggest specific environmental conditions reinforce the process of coevolution, signifying the phenotypic outcomes of coevolutionary arms races are sensitive to local ecological contexts that vary across the landscape. </li> </ol>
data for the paper "Seasonal Prediction of Regional Arctic Sea Ice Using the High-Resolution Climate Prediction System CMA-CPSv3"
<p>CMA-CPSv3 data for the paper "Seasonal Prediction of Regional Arctic Sea Ice Using the High-Resolution Climate Prediction System CMA-CPSv3"</p>
Data and code: High-resolution CMIP6 climate projections for Ethiopia using the gridded statistical downscaling method
<p>Data and code supporting the research article:High-resolution CMIP6 climate projections for Ethiopia using the gridded statistical downscaling method - <br> Fasil M. Rettie, Sebastian Gayler, Tobias KD Weber, Kindie Tesfaye, Thilo Streck. Please, find detail description of the codes and datasets in readme file.</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.