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135 results for “Urban Model”
Urban Heat: Forward-Looking Climate Modeling for Gaza City
<p>We produced actionable data on heat stress in cities to inform analysis and client dialogue on the part of World Bank teams. We applied an urban-scale climate modeling framework to generate datasets describing modeled heat stress exposure for present-day and future conditions under selected climate scenarios. The study domain focuses on Gaza City.</p> <p>More details about the dataset: </p> <ul> <li>The dataset includes calculations for each indicator across three scenarios (<strong>present, SSP1-1.9, SSP3-7.0</strong>) and three twenty-year periods (<strong>2001-2020, 2021-2040, and 2041-2060</strong>). The present period refers to 2001-2020, while the other two periods correspond to the two SSP scenarios.</li> <li>All indicators are available in both <strong>NetCDF</strong> and <strong>GeoTiff</strong> formats.</li> <li>The indicators are calculated at a resolution of <strong>100 m</strong>, consistent with the UrbClim and WBGT simulations. Additionally, downscaled versions of the indicators are provided at a resolution of <strong>30 m</strong>.</li> <li>The UrbClim and WBGT simulations, as well as the postprocessing, are conducted using the regional projection <strong>E</strong><strong>PSG 32636</strong>. The NetCDF and GeoTiff data also adopt this projection. Furthermore, a GeoTiff data file with <strong>EPSG 4326</strong> projection is included.</li> <li>All indicators are calculated as <strong>yearly averages</strong>. Some indicators also have additional calculations for <strong>seasonal averages</strong>, including Spring (MAM), Summer (JJA), Autumn (SON), and Winter (DJF).</li> <li>Ten representative locations within the study domain have been selected to retrieve the WBGT profile on a chosen date (2017-07-11). The results and the locations are stored in wbgt_profile.xlsx.</li> <li>Images for <strong>quick viewing</strong> <strong>in</strong> <strong>png</strong> format visualizing the results for each indicator. Present denotes the period 2001-2020; 2030 denotes the period 2021-2040; & 2050 denotes the period 2041-2060.</li> <li>The NetCDF and GeoTiff data can be found in the data.zip; The png files for quick viewing can be found in quickview.zip; more information about the dataset, including the methodology, all available data list, contact information, etc. can be found in the Technical_Annex_Gaza.docx</li> </ul>
Associated results of Phase 1 of the Urban-PLUMBER model evaluation project
<p><strong>Archive of: https://urban-plumber.github.io/AU-Preston/plots/</strong></p> <p>Files in this folder are associated with the manuscript:</p> <blockquote> <p>“Evaluation of 30 urban land surface models in the Urban-PLUMBER project: Phase 1 results”</p> </blockquote> <p>Files are an archive of the website https://urban-plumber.github.io/AU-Preston/plots/ as of 2nd December 2022.</p> <p>Use of any data must give credit through citation of the above manuscript, the data repository, and other site references as appropriate. </p> <p>Corresponding author: Mathew Lipson (mathew.lipson@bom.gov.au)</p> <p><strong>Usage</strong></p> <p>Load the "index.html" to navigate through plots and results subpages</p> <p><strong>Description</strong></p> <p>These files include results from Phase 1 of the Urban-PLUMBER model evaluation project for urban areas. </p> <p>Data includes:</p> <p> - individual model results (error metrics) and submission metadata <br> - individual model plots (timeseries, subsets, energy closure, distributions)<br> - collective timeseries for every submitted output in the baseline experiment<br> - collective timeseries for every submitted output in the detailed experiment<br> - supplementary material for the manuscript<br> - variable definitions</p> <p><strong>Authors</strong></p> <p>Mathew Lipson, Sue Grimmond, Martin Best, Gab Abramowitz, Andrew Coutts, Nigel Tapper, <br> Jong-Jin Baik, Meiring Beyers, Lewis Blunn, Souhail Boussetta, Elie Bou-Zeid, <br> Martin G. De Kauwe, Cécile de Munck, Matthias Demuzere, Simone Fatichi, <br> Krzysztof Fortuniak, Beom-Soon Han, Maggie Hendry, Yukihiro Kikegawa, Hiroaki Kondo, <br> Doo-Il Lee, Sang-Hyun Lee, Aude Lemonsu, Tiago Machado, Gabriele Manoli, Alberto Martilli, <br> Valéry Masson, Joe McNorton, Naika Meili, David Meyer, Kerry A. Nice, Keith W. Oleson, <br> Seung-Bu Park32, Michael Roth33, Robert Schoetter34, Andres Simon35, Gert-Jan Steeneveld, <br> Ting Sun, Yuya Takane, Marcus Thatcher, Aristofanis Tsiringakis, Mikhail Varentsov, <br> Chenghao Wang, Zhi-Hua Wang</p>
Modelling of Correlation Between Emergency Department Admissions and Location-specific Air Quality and Weather in the Florence Urban Area
ClinicalTrials.gov study NCT06491290. IPD Sharing: NO. Countries: 1. Publications: 1.
A Comparison of Different Community Models of ART Delivery Amongst Stable HIV+ Patients in Two Urban Settings in Zambia
ClinicalTrials.gov study NCT03025165. IPD Sharing: NO. Countries: 1. Publications: 2.
Plasticine model predation of adult white-lined sphinx moths (Hyles lineata) across time and sites (urban and rural)
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Data from: Evaluating the potential for bird-habitat models to support biodiversity-friendly urban planning
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Data from: Modelling short-rotation coppice and tree planting for urban carbon management – a city-wide analysis
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Data from MECO(n) model simulations on "Urban greenhouse gas emissions from the Berlin area: A case study using airborne CO2 and CH4 in situ observations in summer 2018"
<p>This tar-files contain the results of the MECO(n) model, which are published in</p> <p>T. Klausner, M. Mertens, H. Huntrieser, M. Galkowski, G. Kuhlmann, R. Baumann, A. Fiehn, P. Jöckel, M. Pühl, and A. Roiger: Urban greenhouse gas emissions from the Berlin area: A case study using airborne CO<sub>2</sub> and CH<sub>4</sub> in situ observations in summer 2018, Elementa: Science of the Anthropocene (Ref.: Ms. No. ELEMENTA-D-19-00074R1), 2019.</p>
Model and observational dataset used in Tsiringakis, A. , Holtslag, A.A.M., Grimmond, S. and Steeneveld, G.J. Surface and atmospheric driven variability of the single-layer urban canopy model under clear sky conditions over London, Journal of Geophysical Research: Atmospheres
<p>This dataset contains:</p> <p>- Model output from the single-column version of the Weather Research and Forecasting model v3.8.1.</p> <p>- Observations from the KSSW tower (King's College London, United Kingdom) used for model evaluation.</p> <p>- The Single-column Urban Boundary Layer Inter-comparison Model Experiment (SUBLIME) case study description and external forcing file for the single-column version of Weather Research and Forecasting model.</p> <p>This dataset is used in :</p> <p>~Tsiringakis, A., Holtslag, A.A.M., Grimmond, S. and Steeneveld, G.J. Surface and atmospheric driven variability of the single-layer urban canopy model under clear sky conditions over London. Journal of Geophysical Research: Atmospheres</p>
Supporting data for "Reducing uncertainties in urban drainage models by explicitly accounting for timing errors in objective functions"
<p>Supporting data for "Reducing uncertainties in urban drainage models by explicitly accounting for timing errors in objective functions" submitted to Water Resources Research.</p> <p>Contains:</p> <ul> <li>SWMM template files.</li> <li>Objective function values for all model runs.</li> <li>Jupyter Notebooks used to create figures and tables for the article.</li> <li>Copy of rainfall runoff data available from <a href="https://doi.org/10.5281/zenodo.3931582">https://doi.org/10.5281/zenodo.3931582</a></li> </ul> <p>For python implementations of the Hydrograph Matching Algorithm (Ewen 2011) see <a href="https://doi.org/10.5281/zenodo.3923792">https://doi.org/10.5281/zenodo.3923792</a></p> <p>Ewen, John. “Hydrograph Matching Method for Measuring Model Performance.” <em>Journal of Hydrology</em> 408, no. 1–2 (September 2011): 178–87. <a href="https://doi.org/10.1016/j.jhydrol.2011.07.038">https://doi.org/10.1016/j.jhydrol.2011.07.038</a>.</p>
Data for the parameterization of radiative transfer processes in urban climate models
<p><em>Radiative Transfer</em> <em>Model</em> (RTM) is a key component in microscale building resolving urban climate models (<em>UCM</em>), which are used to simulate the flow within urban area. We use different parameterizations of RTMs in the model system <a href="https://gmd.copernicus.org/articles/13/1335/2020/gmd-13-1335-2020.html">PALM</a> version 6.0 to show how much detail modellers should include in their simulation.</p> <p>We introduce the output PALM model results for two examples: (1) A simplified urban geometry consisting of an urban crossing (UC) and (2) a realistic urban domain located at the town square Ernst-Reuter-Platz in Charlottenburg in Berlin (ER). The netCDF files contain the radiative flux received by each surface in the domains, including the shortwave (direct and diffuse) radiation as well as the longwave radiation. Also, the data set includes the 3D flow variables (<em>u</em>, <em>v</em>, <em>w</em>) and the potential temperature. The model drivers (input data) for both examples are included as well.</p> <p>The data set consists of the following model input/output data:</p> <p>1) Simplified urban domain (UC):</p> <ul> <li>Input driver for the model PALM for UC (UC_model_driver.tar.gz)</li> <li>Radiation fluxes for UC when using RTM_01: radiation for horizontal surfaces (UC_RTM_01.nc)</li> <li>Radiation fluxes for UC when using RTM_02: sky view effect (building shadows) (UC_RTM_02.nc)</li> <li>Radiation fluxes for UC when using RTM_03: vegetation interaction with SW radiation (UC_RTM_03.nc)</li> <li>Radiation fluxes for UC when using RTM_04: receiving radiation from surface emission (UC_RTM_04.nc)</li> <li>Radiation fluxes for UC when using RTM_05: vegetation interaction with LW radiation (UC_RTM_05.nc)</li> <li>Radiation fluxes for UC when using RTM_06: single reflection (UC_RTM_06.nc)</li> <li>Radiation fluxes for UC when using RTM_07: vegetation interaction with reflected radiation (UC_RTM_07.nc)</li> <li>Radiation fluxes for UC when using RTM_08: multiple reflections (UC_RTM_08.nc)</li> <li>3D data for the UC reference case which includes u,v,w,theta</li> </ul> <p>2) Realistic urban domain (ER):</p> <ul> <li>Input driver for the model PALM for ER (ER_model_driver)</li> <li>Radiation fluxes for ER when using RTM_01: radiation for horizontal surfaces (ER_RTM_01.nc)</li> <li>Radiation fluxes for ER when using RTM_02: sky view effect (building shadows) (ER_RTM_02.nc)</li> <li>Radiation fluxes for ER when using RTM_03: vegetation interaction with SW radiation (ER_RTM_03.nc)</li> <li>Radiation fluxes for ER when using RTM_04: receiving radiation from surface emission (ER_RTM_04.nc)</li> <li>Radiation fluxes for ER when using RTM_05: vegetation interaction with LW radiation (ER_RTM_05.nc)</li> <li>Radiation fluxes for ER when using RTM_06: single reflection (ER_RTM_06.nc)</li> <li>Radiation fluxes for ER when using RTM_07: vegetation interaction with reflected radiation (ER_RTM_07.nc)</li> <li>Radiation fluxes for ER when using RTM_08: multiple reflections (ER_RTM_08.nc)</li> <li>3D data for the ER reference case which includes u,v,w,theta</li> </ul> <p>For more information and analysis, please check out the relevant publication in the international journal Geoscientific Model Development: Salim et. al, Importance of radiative transfer processes in urban climate models:A study based on the PALM model system 6.0, submitted to GMD.</p>
WASHTREET - Hydraulic, wash-off and sediment transport experimental data obtained in an urban drainage physical model
<p><strong>WASHTREET</strong><strong> -</strong> <strong>Hydraulic, wash-off and sediment transport experimental data obtained in an urban drainage physical model.</strong></p> <p>This dataset contains the results from the tests carried out at a laboratory physical model in the Hydraulic Laboratory of the Centre for Technological Innovation in Construction and Civil Engineering (CITEEC) at the University of A Coruña (Spain) as part of the <a href="https://zenodo.org/communities/washtreet">WASHTREET project</a>. The objective of the project is to perform a series of high-resolution experiments where urban surface wash-off and sediment transport through gully pots and pipes were accurately measured in laboratory-controlled conditions in a separate drainage system.</p> <p>The experimental facility is a 36 m2 full-scale street section and consists of a rainfall simulator placed over a concrete street surface with two gully pots that drain runoff into an underground pipe system. Further details of the physical model are provided in ‘1_Physical_model_description.pdf’. Two zip files with rain intensity distributions (‘2_Rain_intensity_maps.zip’) and model topographies (‘3_Elevation_data.zip’) complete physical model information as accurately measured inputs for hydraulic, wash-off and sediment transport experiments. ‘4_Hydraulic_tests_description.pdf’ describes experimental procedure, equipment, measuring points, results and data set files of the hydraulic characterization of the experiments. Data regarding these hydraulic tests is included in ‘5_Hydraulic_tests.zip’. In these tests, flow in both gully pots and in the pipe system outlet, and a total of 6 surface and 6 pipe depths were measured by ultrasound distance sensors for the different simulated rains.</p> <p>‘6_Washoff_tests_description.pdf’ includes information of the experimental initial conditions, the different sediment granulometries used, measuring points, experimental procedure and result files regarding wash-off and sediment transport experiments. Data files of a total of 23 tests are included in ‘7_Wash-off_tests.zip’. In these experiments, an initial mass of sediment is distributed over the model surface, and the wash-off and sediment transport processes are measured during a steady and uniform rainfall by total suspended solids (TSS) and particle size distribution (PSD) samples at the entrance of gully pots and at the pipe system outlet. Online turbidity measurements at pipe system outlet, pipe depths and flow at pipe system outlet are also measured during the experiments. Results regarding mass balances, which are performed at the end of the experiment to assess the final distribution of sediments, are also included. At last, some relevant photos and videos taken during the experiments are provided in ‘8_Multimedia.zip’. </p> <p>Flow measurements have been used in Naves et al. (2019) (DOI: <a href="https://doi.org/10.1016/j.jhydrol.2019.05.003">10.1016/j.jhydrol.2019.05.003</a>), together with the related datasets <a href="http://www.doi.org/10.5281/zenodo.3239401">WASHTREET - PIV data</a> and <a href="http://www.doi.org/10.5281/zenodo.3241337">WASHTREET - Structure from Motion data</a>, to calibrate a 2D shallow water model.</p> <p>The WASHTREET project is being developed in the scope of the PhD thesis of the first author, which is in receipt of a Spanish Ministry of Science, Innovation and Universities predoctoral grant [FPU14/01778]. The project also receive funding from the Spanish Ministry of Science, Innovation and Universities under POREDRAIN project RTI2018-094217-B-C33 (MINECO/FEDER-EU)</p> <p> </p> <p>Derived publications:</p> <ul> <li>Naves, J., Anta, J., Suárez, J., & Puertas, J. (2020). Hydraulic, wash-off and sediment transport experiments in a full-scale urban drainage physical model. <em>Scientific Data</em>, <em>7</em>(1), 1-13. <a href="https://doi.org/10.1038/s41597-020-0384-z">https://doi.org/10.1038/s41597-020-0384-z</a></li> <li>Naves, J., Rieckermann, J., Cea, L., Puertas, J., & Anta, J. (2020). Global and local sensitivity analysis to improve the understanding of physically-based urban wash-off models from high-resolution laboratory experiments. <em>Science of The Total Environment</em>, <em>709</em>, 136152. <a href="https://doi.org/10.1016/j.scitotenv.2019.136152">https://doi.org/10.1016/j.scitotenv.2019.136152</a></li> <li>Naves, J., Anta, J., Puertas, J., Regueiro-Picallo, M., & Suárez, J. (2019). Using a 2D shallow water model to assess Large-Scale Particle Image Velocimetry (LSPIV) and Structure from Motion (SfM) techniques in a street-scale urban drainage physical model. <em>Journal of Hydrology</em>, <em>575</em>, 54-65. <a href="https://doi.org/10.1016/j.jhydrol.2019.05.003">https://doi.org/10.1016/j.jhydrol.2019.05.003</a></li> <li>Naves, J., Anta, J., Suárez, J., & Puertas, J. (2020). Development and Calibration of a New Dripper-Based Rainfall Simulator for Large-Scale Sediment Wash-Off Studies. <em>Water</em>, <em>12</em>(1), 152. <a href="https://doi.org/10.3390/w12010152">https://doi.org/10.3390/w12010152</a></li> </ul>
Application of Different Building Representation Techniques in HEC-RAS 2-D for Urban Flood Modeling Using the Toce River Experimental Case
<p>The output of numerical simulation in HEC-RAS 2-D</p>
Urbanization mediates the effects of water quality and climate on a model aerial insectivorous bird
<p>Aerial insectivorous birds have experienced alarming population declines in eastern North America. Meanwhile, urbanization continues to increase rapidly, with urban land use comprising 69.4 million acres, or 3.6% of total land area, in the contiguous United States. Multiple environmental changes are associated with urbanization, including alterations to local climate, changes in habitat structure, and potential shifts in both terrestrial and emergent aquatic flying insects on which aerial insectivorous birds rely. Here, we investigated the linkages between urbanization, water quality, and Tree Swallow (<i>Tachycineta bicolor</i>) reproductive success and body condition at seven river-riparian sites representing urban and protected land use in Columbus, Ohio over five consecutive years (2014-2018). Tree Swallows at urban and protected sites relied on emergent aquatic insects for 37.4 and 30.8% (SD = 28.4 and 24.1%) of their nutritional subsidies, respectively. Despite the loss of environmental quality generally attributed to cities, Tree Swallows exhibited greater reproductive success in urban settings where climate was more amenable to egg and nestling survival, and the breeding season was longer. Urban-nesting Tree Swallows initiated laying 7.9 days earlier and fledged 35% more young per nest than those at protected sites. Multiple characteristics of urban sites appeared to drive these patterns, including differences in mean and extreme air temperatures and measures of water quality (e.g., water temperature, nutrient concentrations, turbidity). However, chronic effects of elevated Hg concentrations – which were 482% greater in adult swallow blood at urban sites than at protected sites where swallows exhibited a 17.4% lower trophic position – may disadvantage individuals in other ways. Further, although Tree Swallows are a good model aerial insectivore bird species, characteristics of urban landscapes that benefit Tree Swallows may not advantage other aerial insectivorous birds owing to differences in life-history and foraging strategies. These findings implicate urbanization, local climate, and water quality as important considerations in the conservation of aerial insectivorous birds.</p>
Caterpillar survival in the city: Attack rates on model lepidopteran larvae along an urban-rural gradient show no increase in predation with increasing urban intensity (Raw Data)
<p><span><span><span><span><span><span><span><span><span><span><span>Growing native plants in urban gardens is often promoted as a possible means of increasing lepidopteran populations. However, the efficacy of such efforts has not been well studied. Lepidopterans vary widely in their ability to survive in cities, and the few previous studies of caterpillar abundance or biomass across an urban-rural gradient have yielded mixed results. We placed clay caterpillar models in native plant gardens to assess whether the attack rate on these models varied with degree of urbanization (percent impervious surface within 1 km radius of each garden), and whether responses differed across predator taxa. We also examined how garden characteristics (plant biovolume density, plant species richness) affected probability of attack. Overall, attack rates on these models decreased with increasing impervious surface, although predator taxa varied in their sometimes complex responses. For parasitoid wasps, which accounted for 47% of all attacks, increasing biovolume density increased attack probability at impervious surface levels below 35%, but decreased the probability of attack at higher levels of impervious surface. In contrast, probabilities of attack by both predatory wasps and vertebrates decreased with increasing percent impervious surface, but did not vary with impervious surface for ants and spiders. Predation on caterpillars in urban gardens may be lower than in rural ones; however, this potential increase in survival may be a result of declines in some predator taxa, such as predatory wasps and insectivorous birds. More studies across an urban gradient are needed to measure factors other than predation that influence caterpillar survival in gardens.</span></span></span></span></span></span></span></span></span></span></span></p>
Data from: A model to identify urban traffic congestion hotspots in complex networks
The rapid growth of population in urban areas is jeopardizing the mobility and air quality worldwide. One of the most notable problems arising is that of traffic congestion. With the advent of technologies able to sense real-time data about cities, and its public distribution for analysis, we are in place to forecast scenarios valuable for improvement and control. Here, we propose an idealized model, based on the critical phenomena arising in complex networks, that allows to analytically predict congestion hotspots in urban environments. Results on real cities' road networks, considering, in some experiments, real- traffic data, show that the proposed model is capable of identifying susceptible junctions that might becomes hotspots if mobility demand increases.
Data from: A model of urban scaling laws based on distance dependent interactions
Socio-economic related properties of a city grow faster than a linear relationship with the population, in a log–log plot, the so-called superlinear scaling. Conversely, the larger a city, the more efficient it is in the use of its infrastructure, leading to a sublinear scaling on these variables. In this work, we addressed a simple explanation for those scaling laws in cities based on the interaction range between the citizens and on the fractal properties of the cities. To this purpose, we introduced a measure of social potential which captured the influence of social interaction on the economic performance and the benefits of amenities in the case of infrastructure offered by the city. We assumed that the population density depends on the fractal dimension and on the distance-dependent interactions between individuals. The model suggests that when the city interacts as a whole, and not just as a set of isolated parts, there is improvement of the socio-economic indicators. Moreover, the bigger the interaction range between citizens and amenities, the bigger the improvement of the socio-economic indicators and the lower the infrastructure costs of the city. We addressed how public policies could take advantage of these properties to improve cities development, minimizing negative effects. Furthermore, the model predicts that the sum of the scaling exponents of social-economic and infrastructure variables are 2, as observed in the literature. Simulations with an agent-based model are confronted with the theoretical approach and they are compatible with the empirical evidences.
U-Surf: a global 1km spatially continuous urban surface property dataset for kilometer-scale urban-resolving Earth system modeling
<p>High-resolution urban climate modeling has faced substantial challenges due to the absence of a globally consistent, spatially continuous, and accurate dataset to represent the spatial heterogeneity of urban surfaces and their biophysical properties. This deficiency has long obstructed the development of urban-resolving Earth System Models (ESMs) and ultra-high-resolution urban climate modeling, particularly at large scales. Here, we present a first-of-its-kind 1km-resolution present-day (circa-2020) global continuous urban surface parameter dataset – U-Surf. Using the urban canopy model (UCM) in the Community Earth System Model as a base model for developing dataset requirements, U-Surf leverages the latest advances in remote sensing, machine learning, and cloud computing to provide the most relevant urban surface biophysical parameters, including radiative, morphological, and thermal properties, for UCMs at the facet- and canopy-level. Our high-resolution U-Surf dataset significantly improves the representation of the urban land heterogeneity both within and across cities globally. U-Surf provides essential, high-fidelity surface biophysical constraints to urban-resolving ESMs, enables detailed city-to-city comparisons across the globe, and supports the next-generation kilometer-resolution Earth system modeling across scales. U-Surf parameters can be easily converted or adapted to various types of UCMs, such as those embedded in weather and regional climate models, as well as air quality models. The fundamental urban surface constraints provided by U-Surf are also relevant as features for machine learning models and can have other broad-scale applications for socioeconomic, public health, and urban planning contexts. We expect U-Surf to promote the research frontier on urban systems science, climate-sensitive urban design, and coupled human-Earth systems in the future.</p> <p>The complete list of parameters is presented in the table below.</p> <table> <tbody> <tr> <td>Category</td> <td>Parameter</td> <td>Notes</td> </tr> <tr> <td>Radiative</td> <td>Roof | Impervious | Pervious canyon floor | Wall emissivity</td> <td> </td> </tr> <tr> <td> </td> <td>Roof | Impervious | Pervious canyon floor | Wall albedo</td> <td> </td> </tr> <tr> <td>Morphological</td> <td>Roof | Pervious fraction</td> <td>Roof fraction is w.r.t. urban horizontal surface, and pervious fraction is w.r.t. canyon floor (i.e. pervious and impervious canyon floor).</td> </tr> <tr> <td> </td> <td>Building height</td> <td>Unit: m; Height of wind in the canyon is simply set as half of the building height in CLMU.</td> </tr> <tr> <td> </td> <td>Canyon height-to-width ratio</td> <td> </td> </tr> <tr> <td> </td> <td>Urban percentage</td> <td> </td> </tr> <tr> <td>Thermal</td> <td>Roof | Wall thickness</td> <td>Unit: m</td> </tr> <tr> <td> </td> <td>Roof | Impervious canyon floor | Wall thermal conductivity</td> <td>Unit: W/m*K</td> </tr> <tr> <td> </td> <td>Roof | Impervious canyon floor | Wall volumetric heat capacity</td> <td>Unit: J/m^3*K</td> </tr> <tr> <td> </td> <td>Number of impervious canyon floor layer</td> <td> </td> </tr> <tr> <td> </td> <td>Minimum | Maximum interior building temperature</td> <td>Unit: K</td> </tr> <tr> <td> </td> <td>Air conditioning adoption rate</td> <td> </td> </tr> </tbody> </table> <p> </p> <p>Radiative and morphological parameters are presented in the format of both .tif and .nc to accommodate different needs for the urban climate modeling community. Thermal parameters adapted from CLMU are available in a single .nc file. A CESM-compatiable surface dataset and a time-variant urban dataset (including P_AC and T_BUILDING_MAX; Li et al., 2024) at standard resolution (0.9375°x1.25°) are included for direct simulation use. Note that the urban percentage used to create the surface dataset comes from the PCT_URBAN parameter calculated in U-Surf, but users can input their own urban extent data to generate a customized surface dataset. The raw 1-km data can be easily aggregated/regridded to other resolution as needed.</p> <p> </p> <p><strong>Version 1.1 updates:</strong></p> <p>1. Fill part of the data gaps in Asia. </p> <p>2. Change the aggregation method of some parameters to be facet-area weighted in the 1deg surfdata.</p>
The TUFI dataset used in research paper "Assessing Large Multimodal Models for Urban Floodwater Depth Estimation"
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The DUFI dataset used in research paper "Assessing Large Multimodal Models for Urban Floodwater Depth Estimation"
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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.