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35 results for “forward model”
Urban Heat: Forward-Looking Climate Modelling for West-Africa: Guinea cities
<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 focuses on two cities in Guinea: Conakry and Kankan.</p> <p>More details about the dataset: </p> <ul> <li>The dataset includes calculations for each indicator across three scenarios (<strong>present, SSP2-4.5, SSP3-7.0</strong>) and three twenty-year periods (<strong>2001-2020, 2031-2050, and 2051-2070</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>(Kankan) and <strong>200 m </strong>(Conakry), 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 32629 </strong>(Kankan) and <strong>EPSG 32628 </strong>(Conakry). 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>. </li> <li>Images for <strong>quick viewing</strong> <strong>in</strong> <strong>png</strong> format visualizing the results for each indicator. </li> <li>The indicators in NetCDF and GeoTiff format as well as the visualized PNG files can be found in the <strong>{city}_indicators.zip</strong>.</li> <li>Three representative locations within the study domain have been selected to retrieve the WBGT profile on a chosen date (a hot day in 2020). The results are stored in WBGT_data.xlsx and visualized as WBGT_{date}.png. The shapefile is named as selected_locations.shp. These data together with the visualization of the land use map is compressed in <strong>{city}_landuse_wbgt.zip</strong>. </li> <li>More information about the dataset, including the methodology, all available data list, contact information, etc. can be found in the <strong>Technical_description_Guinea.docx</strong></li> </ul>
Urban Heat: Forward-Looking Climate Modelling for West-Africa : Corridor Abidjan-Lagos
<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 focuses on five cities at Corridor Abidjan-Lagos: Abidjan, Cotonou, Lome, Accra and Lagos.</p> <p>More details about the dataset: </p> <ul> <li>The dataset includes calculations for each indicator for the reference period <strong>(present: 2001 to 2020</strong>). For city Lome two more future scenarios (<strong>SSP2-4.5, SSP3-7.0</strong>) and with two twenty-year periods (<strong>2031-2050, and 2051-2070</strong>) were applied.</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 to 200 m</strong> (depending on the size of the city), 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. 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>. </li> <li>Images for <strong>quick viewing</strong> <strong>in</strong> <strong>png</strong> format visualizing the results for each indicator. </li> <li>The indicators in NetCDF and GeoTiff format as well as the visualized PNG files can be found in the <strong>{city}_present_indicators.zip </strong>or <strong>{city}_indicators.zip </strong>(for Lome).</li> <li>Three representative locations within the study domain have been selected to retrieve the WBGT profile on a chosen date (a hot day in 2020). The results are stored in WBGT_data.xlsx and visualized as WBGT_{date}.png. The shapefile is named as selected_locations.shp. These data together with the visualization of the land use map is compressed in <strong>{city}_landuse_wbgt.zip</strong>. </li> <li>More information about the dataset, including the methodology, all available data list, contact information, etc. can be found in the <strong>Technical_description_corridor.docx</strong></li> </ul>
Dataset for the paper "CoMAF: Context and Mobility-Aware Forwarding Model For V-NDN"
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Urban Heat: Forward-Looking Climate Modelling for West-Africa: extra indicator
<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. This dataset serves as a supplement to the previous two datasets: https://zenodo.org/doi/10.5281/zenodo.11085333 and https://zenodo.org/doi/10.5281/zenodo.11073297. It contains an extra indicator Heat Index (HI) based on the apparent temperature (AT) for 12 cities in west Africa. </p> <p>More details about the dataset: </p> <ul> <li>The dataset includes calculations for HI across three scenarios (<strong>present, SSP2-4.5, SSP3-7.0</strong>) and three twenty-year periods (<strong>2001-2020, 2031-2050, and 2051-2070</strong>). The present period refers to 2001-2020, while the other two periods correspond to the two SSP scenarios.</li> <li>The indicator is available in both <strong>NetCDF</strong> and <strong>GeoTiff</strong> formats. It is named as HIAT in the file name with extra information such as scenario, resolution, projection, etc. </li> <li>The indicator is calculated at a resolution from <strong>100 m </strong>to <strong>200 m </strong>(depending on the size of the city). Additionally, downscaled versions of the indicator is provided at a resolution of <strong>30 m</strong>.</li> <li>The Heat Index is calculated as the <strong>yearly average number of days when apparent temperature reaches 105 F</strong>. More information regarding the definition and calculation of HI can be found: Rohat, G., Flacke, J., Dosio, A., Dao, H., & Van Maarseveen, M. (2019). Projections of human exposure to dangerous heat in African cities under multiple socioeconomic and climate scenarios. <em>Earth's Future</em>, <em>7</em>(5), 528-546.</li> <li>Images for <strong>quick viewing</strong> <strong>in</strong> <strong>png</strong> format are available. </li> <li>The indicators in NetCDF and GeoTiff format as well as the visualized PNG files can be found in the <strong>{city}_HIAT.zip </strong>(for the cities with future projection) or <strong>{city}</strong><strong>_present_HIAT.zip </strong>(for those cities without future projection).</li> <li>More information about other indicators, including the simulation, methodology, all available data list, contact information, etc. can be found in the other two datasets.</li> </ul>
Optimal Spectral Sampling Forward Model Test Data
<p>Binary and ASCII files for tests of the OSS forward model application.</p>
Conformational ensembles used in "Assessment of forward models for the hydrodynamic radius of intrinsically disordered proteins. Pesce et al. 2022"
<p>Ensemble of intrinsically disordered proteins used in: <em>"Assessment of forward models for the hydrodynamic radius of intrinsically disordered proteins. Pesce et al. 2022"</em>.</p> <p>Ensembles are produced with Flexible-meccano and Langevin simulations with CALVADOS for:</p> <ul> <li>Hst5</li> <li>RS</li> <li>DSS1</li> <li>Sic1</li> <li>ProTa</li> <li>NHE6cmdd</li> <li>A1</li> <li>aSyn</li> <li>ANAC046</li> <li>GHR-ICD</li> <li>Tau</li> </ul>
Forward modelling of Dα camera view in ST40 informed by experimental data (dataset)
<p>Database for reproducing the calculations presented in the publication "Forward modelling of Dα camera view in ST40 informed by experimental data", submitted to <em>Fusion Engineering and Design</em>.</p>
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>
Pay It Forward: Journal Cost Modeling Data
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Integrating univariate niche dynamics in species distribution models: a step forward for marine research on biological invasions
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Data from: Forward modeling the rubber hand: illusion of ownership modifies motor-sensory predictions by the brain
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OCO-3 Level 2 geolocated XCO2 retrievals results, physical model, Forward Processing V11 (OCO3_L2_Standard) at GES DISC
Version 11 is the current version of the data set. Older versions will no longer be available and are superseded by Version 11. The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2. The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data with further analysis performed on OCO-2 simulations. The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.
OCO-3 Level 2 meteorological parameters interpolated from global assimilation model for each sounding, Forward Processing V11 (OCO3_L2_Met) at GES DISC
Version 11 is the current version of the data set. Older versions will no longer be available and are superseded by Version 11. The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2. The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data with further analysis performed on OCO-2 simulations. The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.
OCO-3 Level 2 geolocated XCO2 retrievals results, physical model, Forward Processing V10 (OCO3_L2_Standard) at GES DISC
Version 10 is the current version of the data set. Older versions will no longer be available and are superseded by Version 10. The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2. The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data with further analysis performed on OCO-2 simulations. The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.
OCO-3 Level 2 meteorological parameters interpolated from global assimilation model for each sounding, Forward Processing V10 (OCO3_L2_Met) at GES DISC
Version 10 is the current version of the data set. Older versions will no longer be available and are superseded by Version 10. The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2. The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data with further analysis performed on OCO-2 simulations. The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.
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International Brain Laboratory public data
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OpenNeuro
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