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354 results for “Budget”
An ensemble of 48 physically perturbed model estimates of the 1/8° terrestrial water budget over the conterminous United States, 1980–2015
<p>This dataset contains the 1980–2015 monthly terrestrial water budget simulated by a 48-member perturbed-physics ensemble configured from the Noah LSM with multi-physics options (Noah‑MP v3.6). Simulation outputs include total evapotranspiration and its constituents (canopy evaporation, soil evaporation, and transpiration), runoff (the surface and subsurface components), as well as terrestrial water storage (snow water equivalent, four-layer soil water content from the surface down to 2 m, and the groundwater storage anomaly). The file name has four parts: the abbreviation for "terrestrial water budget", the used parameterization, the time scale, and the suffix.</p> <p>The 48 physics configurations are generated by combining four runoff parameterizations (run1: SIMGM, run2: SIMTOP, run3: NOAHR, run4: BATS), two parameterizations of stomatal conductance (can1: Ball–Berry, can2: Jarvis), three parameterizations of soil moisture stress factor (btr1:NOAHB, btr2: CLM, btr3: SSiB), and two parameterizations of near-surface atmospheric turbulence (tub1: M-O, tub2: Chen97).</p> <p>The simulation domain covers the all of conterminous United States (25°–53°N, 125°–67°W), which is also called the NLDAS-2 testbed (Xia et al., 2012a, b). The simulations were performed at a spatial resolution of 0.125°, which is the same as for NLDAS-2 models. Details of the simulation settings and spin-up run can be found in Section 2.3 of Zheng et al. (2019) and Section 2.2 of Fei et al. (2021).</p>
Supplementary Materials of "Elementary mathematics helps to shed light on the transpiration budget under water stress"
<p>This directory contains the Jupyter notebook used to do complete analysis from our paper "Elementary mathematics sheds light on the transpiration budget under water stress" submitted to the Ecohydrology Journal at the Special Issues "ECOHYDROLOGY OF INLAND AND COASTAL WATERS in honor of Ignacio Rodriguez-Iturbe".</p> <p>These materials are referenced in the main text and supplemental text of the publication. The purpose of this repository is to facilitate replication of our analysis by any interested parties. </p> <p>Specifically, this directory contains ten files:</p> <ul> <li>From 0 to 5, Jupyter Notebook prepared and used for the analysis (please execute the notebooks in numerical sequence). </li> <li>"Table_S1.xlsx" Data From: Kröber, W., H. Heklau, and H. Bruelheide. 2015. “Leaf Morphology of 40 Evergreen and Deciduous Broadleaved Subtropical Tree Species and Relationships to Functional Ecophysiological Traits.” Plant Biology 17 (2): 373–83. <a href="https://doi.org/10.1111/plb.12250"><span>https://doi.org/10.1111/plb.12250</span></a>.</li> <li>"Richards_VG.csv" contains Van Genuchten Parameters for various soils.</li> <li>"The_Rosetta_Stone_of_the_Darcy_Buckingham_law.pdf" addresses the challenge of converting water flux units between Darcy-like soil and plant descriptions, where hydrologists use "head" units (meters) and plant physiologists use pressure potential (MPa). The aim is to clarify and perform the necessary unit conversions, with detailed explanations available in the relevant section on <a href="https://abouthydrology.blogspot.com/2022/10/my-water-management-in-agricolture.html"><span>this webpage</span></a>.</li> </ul>
Plains zebra time budgets, social behavior, and communication during the 2021-2022 Laikipia-Samburu ecosystem drought
<p>Anthropogenically induced climate change has significantly increased the frequency of acute weather events, such as drought. As human activities amplify environmental stresses, animals may be forced to prioritize survival over behaviors less crucial to immediate fitness, such as socializing. Yet, social bonds may also buffer organisms from the deleterious effects of environmental conditions. We investigated how the highly social plains zebra (<em>Equus quagga</em>) modify their activity budgets, social networks, and multimodal communication during a drought. This dataset contains a) activity budget, b) steps per minute as a proxy for foraging effort, c) nearest neighbor association data, d) interaction rate, e) juvenile social interaction partner data, and f) multimodal communication data.</p>
Fig. 5 in New insight in the determination of thermodynamic equilibrium thickness using heat budget over Barents Sea
Fig. 5 — Retrieved Thermodynamic Equilibrium Thickness (TET) over Barents Sea during (a) November, (b) December, (c) January, (d) February, (e) March, and (f) April for the span of 2002 – 2020
Fig. 2 in New insight in the determination of thermodynamic equilibrium thickness using heat budget over Barents Sea
Fig. 2 — Climatology of Sea Ice Area (SIA) and Oceanic Energy (OE) over Barents Sea for the span 2002 – 2020
Fig. 4 in New insight in the determination of thermodynamic equilibrium thickness using heat budget over Barents Sea
Fig. 4 — Histogram representing percentage contribution of Barents Sea Ice Thickness (SIT) over Arctic Sea Ice Thickness (SIT) during (a) November, (b) December, (c) January, (d) February, (e) March, and (f) April for the span of 2002 – 2020
Dataset: Avis Budget Group, Inc. (CAR) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Data for: Contrasting response of precipitation to aerosol perturbation in the tropics and extra-tropics explained by energy budget considerations. Dagan et al., 2019 GRL
<p>Data available form the simulation conducted with ICON.</p> <p>The data include the different terms of the energy budget from all the different simulations presented in the paper.</p> <p>ARC is the atmospheric radiative cooling, l is the precipitation, Qsh is the sensiblel heat flux and R is the residual (or the divergent term).</p> <p>ref is for the reference simulation while the rest of the files denote the location of the plume, its size (in degree) and the SSA. for example:</p> <p>p_40N_25_9_5.nc</p> <p>continue the precipitation for the simulation with a plume located at 40N, the size of the plume is 25 degrees and the SSA=9.5.</p> <p> </p> <p>The 3D varblees of temperature and winds are given is the files :</p> <p>monmean_atm_trop_2_4aod_10deg_8ssa_3D_atm_3d_ml.nc</p> <p>and:</p> <p>monmean_atm_40N_2_4aod_10deg_8ssa_3D_atm_3d_ml.nc</p> <p> </p> <p>for two different simulations with the same plume size and SSA but different plume locations (this data is used in Figs. 3 and 4 in the paper).</p> <p> </p> <p> </p>
Assessing Negative Carbon Dioxide Emissions from the Perspective of a National 'Fair Share' of the Remaining Global Carbon Budget: Supplementary Material
<p>Detailed calculations supporting the results in the published paper, <em>Assessing Negative Carbon Dioxide Emissions from the Perspective of a National 'Fair Share' of the Remaining Global Carbon Budget</em>, <a href="https://link.springer.com/journal/11027">Mitigation and Adaptation Strategies for Global Change</a>, DOI: <a href="https://doi.org/10.1007/s11027-019-09881-6">10.1007/s11027-019-09881-6</a>.</p> <ul> <li><strong>IE-CO2-Quota-2015.ods</strong>: Spreadsheet/workbook in <a href="http://opendocumentformat.org/">Open Document</a> format. Includes table and charts as presented in the paper. Prepared using <a href="http://www.libreoffice.org">LibreOffice</a> (v 5.0+). Should also be accessible also in Microsoft Excel, but some formatting or functionality may be lost.</li> <li><strong>IE-CO2-Quota-2015.ipynb</strong>: Mathematical background and cross-check of detailed calculations in interactive <a href="https://jupyter.org/">Jupyter notebook</a> format (coding in <a href="https://www.python.org/">python</a>).</li> <li><strong>IE-CO2-Quota-2015-ipynb.html</strong>: Static HTML version of the <strong>IE-CO2-Quota-2015.ipynb</strong> suitable for simple viewing/printing.</li> <li><strong>IE-CO2-Quota-2015-ipynb.pdf</strong>: Static version of the <strong>IE-CO2-Quota-2015.ipynb</strong> suitable for simple viewing/printing.</li> </ul>
Figure 2 in Time-activity budgets of wintering Ferruginous Duck, Aythya nyroca, at Gajoldoba wetland, Jalpaiguri, India
Figure 2. Mean percentage of nocturnal time spent in various activities by the Ferruginous Duck in different time blocks, with standard error bars.
Figure 1 in Time-activity budgets of wintering Ferruginous Duck, Aythya nyroca, at Gajoldoba wetland, Jalpaiguri, India
Figure 1. Percentage of time allocated to different activities by Ferruginous Duck at different parts of winter season.
Figure 2 in Diurnal time-activity budget and foraging techniques of red-crested pochards (Netta rufina) wintering at the wetlands of West Bengal, India
Figure 2. Canonical correspondence analysis (CCA with 95% ellipses) ordination diagram showing the scatter plot for the month-wise and site-wise density of the wintering RCPs together with the selected environmental variables. Vector lines represent the relationship of significant environmental variables to the ordination axes; their length is proportional to their relative significance.
Figure 1 in Diurnal time-activity budget and foraging techniques of red-crested pochards (Netta rufina) wintering at the wetlands of West Bengal, India
Figure 1. Study site (Adra saheb bandh,Purulia saheb bandh, Kadamdeuli Dam, and Gangdoa Dam) locations inWest Bengal, India (India and West Bengal maps not in scale).
Figure 4 in Diurnal time-activity budget and foraging techniques of red-crested pochards (Netta rufina) wintering at the wetlands of West Bengal, India
Figure 4. Comparison of the aggregated proportional time budget (values in percentages of the time spent) of the diurnal foraging activities of male and female RCPs in January and December; deep water conditions prevailed in both December and January at Sites 1, 2, and 4, while shallow water conditions prevailed at Site 3 in January.
Hybrid iterating-averaging low photon budget Gabor holographic microscopy - dataset
<p>Dataset (Matlab files) containing holograms employed in:<br><br>M. Rogalski, P. Arcab, E. Wdowiak, J. Á. Picazo-Bueno, V. Micó, M. Józwik, and M. Trusiak, “Hybrid iterating-averaging low photon budget Gabor holographic microscopy,” Submitted 2024<br><br>This dataset should be used together with the codes present at:<br><a href="https://github.com/MRogalski96/IGA" target="_blank" rel="noopener">https://github.com/MRogalski96/IGA</a></p>
Zurich Participatory Budgeting Digital Voting Experiment
<p>This release contains the dataset from the study Designing Digital Voting Systems for Citizens: Achieving Fairness and Legitimacy in Participatory Budgeting. The experiment, conducted in March 2023 with 180 participants from ETH Zurich and the University of Zurich, explores how different voting input formats and aggregation methods (Greedy and MES) affect citizens' perceptions of fairness and trustworthiness in Participatory Budgeting (PB).</p> <p>The dataset includes:</p> <ul> <li>Voting data across six formats (A-F).</li> <li>Participants' perceptions of fairness and voting ease.</li> <li>Responses to simulated voting outcomes.</li> </ul> <p>This research is part of a Swiss National Science Foundation (SNSF) project (NRP 77 Digital Transformation, project no. 187249). </p> <h4>Citation:</h4> <p>If you use the data, please cite the study as follows:</p> <p>Joshua C. Yang, Carina I. Hausladen, Dominik Peters, Evangelos Pournaras, Regula Hänggli Fricker, and Dirk Helbing. 2024. Designing Digital Voting Systems for Citizens: Achieving Fairness and Legitimacy in Participatory Budgeting. ACM Digital Government: Research and Practice. <a href="https://doi.org/10.1145/3665332" target="_new" rel="noopener">https://doi.org/10.1145/3665332</a></p>
Canadian fossil fuel production, greenhouse gas emissions, emissions targets and carbon budgets
<p>This spreadsheet shows the amounts of coal, oil and natural gas produced in Canada from 2010 to 2020 using governmental sources. It includes calculations of the corresponding emissions according to a life-cycle analysis. The total greenhouse gas emissions from fossil fuels extracted annually in Canada (including those burned abroad) are computed. McGlade and Ekins (2015) proposed budgets for the production of each type of fossil fuel in order to provide a 67% chance to limit warming to 2.0 °C by 2100. The proportion of each budget that is already spent is calculated. Emissions targets from 21 scenarios originating from five effort-sharing studies are compared with Canadian 2020 emissions to evaluate the difference. Carbon budgets from 18 scenarios originating from seven studies are compared with Canadian cumulative emissions to evaluate the percentage of the budgets within the period 2010-2050 already emitted.</p>
Fig. 6 in Activity budget, travel distance, sleeping time, height of activity and travel order of wild East Bornean Grey gibbons (Hylobates funereus) in Danum Valley Conservation Area
Fig. 6. Average daily travel distance and average sleeping time of the JACUZZI male for May–June (dry season) and December (wet season) from 2011 to 2013. Travel distance was counted for 13 days in August and for 13 days in December. Sleeping time was counted for 14 days in August and for 15 days in December. Solid line: travel distance. Dotted line: sleeping time.
Fig. 3 in Activity budget, travel distance, sleeping time, height of activity and travel order of wild East Bornean Grey gibbons (Hylobates funereus) in Danum Valley Conservation Area
Fig. 3. Activity budget of the SAPA male in both wet season (December) and dry season (August) from 2005 to 2008.
Fig. 2 in Activity budget, travel distance, sleeping time, height of activity and travel order of wild East Bornean Grey gibbons (Hylobates funereus) in Danum Valley Conservation Area
Fig. 2. Location of the BRL, the territory of the SAPA group and the territory of the JACUZZI group. The grey area represents the territory.
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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.