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214 results for “Climatic variables”
Data for "Millennial modulation of Atlantic Multidecadal Variability in a climate model"
<p>Processed data and Jupyter notebooks for manuscript "Millennial modulation of Atlantic Multidecadal Variability in a climate model" by Joakim Kjellsson and Wonsun Park</p>
Predicting time series of vegetation leaf area index across North America based on climate variables for land surface modeling using attention-enhanced LSTM
<p>We developed an attention-enhanced long and short memory (AELSTM) model for predicting vegetation LAI time series based on climatic data. The developed AELSTM model establishes the relationships between the time series of vegetation LAI and climatic variables. </p>
Model data - Impact of Ural blocking on early-winter climate variability under different Barents-Kara sea ice conditions
<p>Model data for JGR paper : Impact of Ural blocking on early-winter climate variability under different Barents-Kara sea ice conditions</p>
Data from Climate adaptability in hydrological models: variable storage capacity to improve performance under contrasting climates.
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Data associated with "The importance of terrain and climate for predicting soil organic carbon is highly variable across local to continental scales"
<p>The zipped folder contains the processed soil datasets including covariates, soil depths, and SOC concentrations for training the deep learning models described in the paper "The importance of terrain and climate for predicting soil organic carbon is highly variable across local to continental scales". </p> <p>"soil_profile/" contains a table including the geolocations of all the soil profiles in this study. "patch_data/" and "point_data/" contain the covariates to feed the models with patch input and point input respectively. "depth/" contains the upper and lower depths of the soil samples. "y/" contains the target variable - SOC concentration of the soil samples. The data files with suffix "_1" is a small subset of their counterparts without "_1" (10 % in sample size) used for model hyperparameters tuning.</p>
Raw Data for Publication "Earth observations reveal impacts of climate variability on maize cropping systems in Sub-Saharan Africa"
<p>Phenological metrics extracted for all agricultural fields used in the study. Data also includes the coordinates of the fields.</p>
Datasets for "Insights into Atlantic multidecadal variability using the Last Millennium Reanalysis framework" (Climate of the Past, Feb 2018)
<p>Reanalysis data used for figures and calculations in manuscript. </p>
Data for "The influence of internal variability on Earth's energy balance framework and implications for estimating climate sensitivity"
<p>This archive contains processed model output necessary for reproducing the figures in Dessler, Maurtisen, Stevens, ACP, 2018</p> <p>historicalEnsemble.nc contains data from the 100-member MPI historical ensemble</p> <p>forcing_aed_ensemble.nc contains the forcing for the historical runs</p> <p>model0001.nc is the control run of the MPI model<br> model0003.nc is an abrupt 4xCO2 run of the MPI model</p> <p>cmip5 contains data from individual CMIP5 models </p> <p>the folder "fig 5" contains zonal average fields necessary for that figure</p>
FIGURE 7. Sample sites and climatic suitability for all Alpinobombus species combined estimated using Maxent from climate variables for the year 2000 in The arctic and alpine bumblebees of the subgenus Alpinobombus revised from integrative assessment of species' gene coalescents and morphology (Hymenoptera, Apidae, Bombus)
FIGURE 7. Sample sites and climatic suitability for all Alpinobombus species combined estimated using Maxent from climate variables for the year 2000. Bright yellow and brown areas show where the logistic prediction of occurrence is p> 0.5 (the outlier records with exceptionally low probabilities of suitability were excluded in step-wise iterations); brown spots show all consistent Alpinobombus site records; '?' shows the five records that are in climatically outlying sites. Polar projection, North Pole (starred) at the centre of the map, international boundaries and the Arctic Circle shown as narrow grey lines.
Climate-induced interannual variability and projected change of two harmful algal bloom taxa in Chesapeake Bay, USA
<p>This dataset include the input files for the hindcast simulation of ROMS-RCA in Chesapeake Bay during 2002-2011.</p> <p>ROMS (Regional Ocean Modeling System) model used in this study is version 3.4.</p> <p>RCA (Row-Column AESOP) water quality model used in this study is improved by UMCES, coupling with ROMS output.</p>
Equilibrium in plant functional trait responses to warming is stronger under higher climate variability during the Holocene
Aim.The functional trait composition of plant communities is thought to be largely determined by climate, but relationships between contemporary trait distributions and climate are often weak. Spatial mismatches between trait and climatic conditions are commonly thought to arise from disequilibrium responses to past environmental changes. We here investigated whether current trait-climate disequilibrium were likely to emerge during plant functional responses to Holocene climate warming. Location.North America Time period.14-0Kya Major taxa studied. Terrestrial plants Methods. We joined global trait data with paleoecological time-series and climate simulations on 425 sites. We estimated plant community functional composition for three leaf traits involved in resource use. We then quantified disequilibrium in plant trait temporal responses to climate change during two contrasted periods : a period of high climate variability (14-7 Kya), and a period low climate variability (7-0 Kya). Results. Functional trait composition showed consistent deviation from climatic equilibrium during both periods. The temporal dynamics of trait composition tends to be positively correlated to climate equilibrium expectations during Holocene climate warming (14-7 Kya), but not during a following period of low climate variability (7-0 Kya). Main conclusions.Long-term functional responses of plants to climate change showed mixed evidence for both equilibrium and disequilibrium responses. Temporal trait dynamics were closer to spatial dynamics expectations under high climate variability, indicating that relevance of space-for-time substitution might be partially dependent on climate variability. Our results further suggest that current mismatches between trait and climatic conditions may arise due to a divergence of factors influencing trait dynamics during low climate variability periods. These findings provide a counterpoint to the common assumption that contemporary trait-climate mismatches result from lagged responses to past climate warming. Our study also demonstrates the need for a deeper investigation of the potential influence of non-climatic factors on functional plant community dynamics.
Data for the manuscript entitled "AMOC variability and watermass transformations in the AWI climate model" by Sidorenko et al. 2021, submitted to JAMES
<p>Data is stored in a SHELVE persistent storage as produced in Python 3.7.4. The visualisation example is provided in a Jupyter Python Notebook.</p>
Changes in microbial community structure and functioning with elevation are linked to local soil characteristics as well as climatic variables
<p>Mountain forests are important carbon stocks but are threatened by increased insect outbreaks and climate driven forest conversion. Soil microorganisms play an eminent role in nutrient cycling in forests and form the basis of soil food webs. Uncovering the driving factors shaping microbial communities and functioning at mountainsides worldwide is of importance to better understand their dynamics at local and global scales. We investigated microbial communities and their drivers along an elevational gradient of primary forests at Changbai Mountain, China. We analysed substrate-induced respiration and phospholipid fatty acids (PLFA) in litter and two soil layers at seven sites. In the litter layer the increase in microbial biomass (Cmic) as well as in stress indicator ratios with elevation were negatively correlated with Ca concentrations indicating increased nutritional stress in high microbial biomass communities at sites with lower Ca availability. PLFA profiles in litter separated low and high elevations, this was less pronounced in soil, suggesting that leaflitter functions as buffer for soil microbial communities. Annual variations in temperature correlated with PLFA profiles in all layers, while annual variations in precipitation correlated with PLFA profiles in upper soil only. Furthermore, the availability of resources, soil moisture, Ca concentrations and pH structured the microbial communities. Pronounced changes in Cmic and stress indicator ratios in the litter layer between pine dominated (800 – 1100 m) and spruce dominated (1250 – 1700 m) forests indicated a shift in the structure and functioning of microbial communities between forest types. The study highlights strong changes in microbial community structure and functioning along elevational gradients, but also shows that these changes and their driving factors vary between layers. Besides annual variations in temperature and precipitation, carbon accumulation and nitrogen acquisition shape changes in microbial communities with elevation at Changbai Mountain.</p>
Impact of Ural blocking on early-winter climate variability under different Barents-Kara sea ice conditions
<p>Model data from "Impact of Ural blocking on early-winter climate variability under different Barents-Kara sea ice conditions".</p>
CP_OdU (Climate Projections for Odesa, Ukraine): Climate indices and daily meteorological variables for Odesa (Ukraine) in 2021-2050 by different RCM simulations from Euro-CORDEX
<ol> <li>ODS-UA_RCM_outputs_day_20210101-20501231.zip file contains outputs from Euro-CORDEX RCM’s simulation for a land-located point closest to the Odesa meteorological site (46.44N, 30.77E).</li> <li>The RCM grids define the coordinates for this point (the gridpoint is mostly located in the city center (Kateryninska^Troitska) or near the 7-km market.</li> <li>The nomenclature of files and variables in these files are defined in http://is-enes-data.github.io/cordex_archive_specifications.pdf.</li> <li>Other files contain the so-called climate indices as described in <a href="https://knmi-ecad-assets-prd.s3.amazonaws.com/documents/atbd.pdf">https://knmi-ecad-assets-prd.s3.amazonaws.com/documents/atbd.pdf</a> and table in 0readme.pdf.</li> </ol>
Output data for the article "Climate variability in 2030 European power systems"
<p>Model outputs for the paper "Climate variability on Fit for 55 European power systems"</p>
A New GFSv15 based Climate Model Large Ensemble and Its Application to Understanding Climate Variability, and Predictability
<p>Data and analysis scripts for figures of Journal article (A New GFSv15 based Climate Model Large Ensemble and Its Application to Understanding Climate Variability, and Predictability)</p>
Data from: Variable effects of a changing climate on lay dates and productivity across the range of the Red-cockaded Woodpecker
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Data from: The effect of competition on responses to drought and interannual climate variability of a dominant conifer tree of western North America
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Data from: Explaining European fungal fruiting phenology with climate variability
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.