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453 results for “Reanalysis”
Dataset for the research article titled "Evaluation of Reanalysis and Satellite Products against Ground-based Observations in a Desert Environment "
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Sample ERA5 Climate Reanalysis Data for UW Geospatial Data Analysis Course
<p>Used for Module 09: https://uwgda-jupyterbook.readthedocs.io/en/latest/modules/09_NDarrays_xarray_ERA5/</p> <p>Generated using Copernicus Climate Change Service information [2022]<br> Original license: https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf</p>
Environmental (oxygen) conditions on the NW African coast from 3D reanalysis models
<p>This dataset contain hydrodynamic and biogeochemical variables extracted from the CMEMS service (<a href="https://marine.copernicus.eu/">https://marine.copernicus.eu/</a>) covering the NW region of the African coast and the period 1993 to 2019. The environmental dataset include subsurface (100 to 200m) oxygen concentration.</p>
Environmental (biogeochemical) conditions on the NW African coast from 3D reanalysis models
<p>This dataset contain hydrodynamic and biogeochemical variables extracted from the CMEMS service (<a href="https://marine.copernicus.eu/">https://marine.copernicus.eu/</a>) covering the NW region of the African coast and the period 1993 to 2019. The environmental dataset include: nitrate concentration, phosphate concentration and chlorophyll-a concentration.</p>
Data for: Deep Learning of Model- and Reanalysis- Based Precipitation and Pressure Mismatches over Europe
<p>This study focuses on using UNet Convolutional Neural Networks to predict the spatiotemporal mismatches (errors) between TSMP-G2A model-based and COSMO-REA6 reanalysis-based precipitation and surface pressure over Europe.</p> <p>The following data are provided in this dataset:</p> <p>1) The remapped and NetCDF-merged TSMP-G2A and COSMO-REA6 precipitation and surface pressure over the study area (EU-11 EUROCORDEX, ~0.11 degrees) for the years 1995-2017. Files: COSMO-REA6_PREPROCESSED.zip and TSMP_PREPROCESSED.zip</p> <p>2) The actual and predicted spatiotemporal mismatch data for training, validation, and testing periods (1995-2017). Files: MISMATCH_ACTUAL.zip and MISMATCH_PREDICTED.zip<br> </p> <p>References for original TSMP-G2A and COSMO-REA6 data:<br> TSMP-G2A: http://doi.org/10.17616/R31NJMGR<br> COSMO-REA6: doi:10.1002/qj.2486, 2015</p>
Transformed Eulerian mean data from the MERRA-2 reanalysis (daily means)
<p>This dataset provides <strong>daily</strong> and zonal mean variables derived from the MERRA-2 reanalysis, including terms of the transformed Eulerian mean (TEM) momentum budget.</p> <p>All variables (zonal, meridional and vertical wind speed, temperature, zonal wind tendencies from Eliassen-Palm (EP) flux divergence and advection, EP fluxes and the residual streamfunction) are obtained from 6-hourly and native vertical and spatial resolution data of the 'Assimilated' (ASM, M2I3NVASM) collection. Zonal mean wind tendency from gravity wave drag is also provided, obtained from the M2T3NPUDT collection.</p> <p>Data are provided as one .zip file per decade (only partial for the 2020s). <strong>Monthly</strong> means of the same quantities are provided in a companion dataset.</p> <p>The data and related documentation are provided 'as is' and without any warranty of any kind. Users are invited to report any issue or inconsistency they may find. Please cite the reference publication when using this dataset.</p> <p> </p> <p>Known issues:</p> <p>- All TEM terms divided by<em> </em><span>\(cos(\phi)\)</span> diverge at the north and south poles (where <span>\(\phi = \pm \pi/2\)</span>), so they should not be considered. If variables at the poles are needed, values at neighbouring latitudes should be taken.</p>
SACC Files for Stage-III Cosmic Shear Reanalysis with TXPipe
<p>This file contains the SACC (Save All Correlations and Covariances) files from the Stage-III Cosmic Shear Reanalysis using TXPipe. They contain the two-point correlation functions for each of the DES-Y1, HSC-Y1 and KiDS-1000 surveys as computed by TXPipe. They correspond to the paper "A Unified Catalog-level Reanalysis of Stage-III Cosmic Shear Surveys". </p>
Effects of Reanalysis Forcing Fields on Ozone Trends and Age of Air from a Chemical Transport Model
<p>This dataset is based on the global off-line 3-D chenmical transport model (TOMCAT/SLIMCAT) forced with ECMWF reanalyses (ERA-Interim and ERA5) to compare the performance of the stratospheric ozone simulations. Each field is separately saved as NETCDF file. Each field is show on geographic coordinates, which can be longitude, latitude, vertical hybrid-pressure level (for zonal mean fields, such as ozone, temperature and age-of-air).</p> <p>The dimensions in each field are:</p> <p>lat --> latitude</p> <p>lon --> longitude</p> <p>lev --> hydrid pressure level</p> <p>time --> months of the simulation</p> <p>The output of the total column ozone from the TOMCAT/SLIMCAT simulations forced with ERA-Interim and ERA5 for Figures 1-4 and Figure S2 in the supplement are in files:</p> <p>toz_A_ERAI.nc</p> <p>toz_B_ERA5.nc</p> <p>The output of the stratospheric column ozone (SCO) in Figure S1 in the supplement are in the file (levels1-3 are SWOOSH, B_ERA5 and A_ERAI SCO data, respectively):</p> <p>sco_SWOOSH_A_ERAI_B_ERA5.nc</p> <p>The output of zonal mean ozone profiles from the TOMCAT/SLIMCAT simulations forced with ERA-Interim and ERA5 for Figures 5-7, 9 and Figures S3-4 are in files:</p> <p>O3_mm_A_ERAI.nc</p> <p>O3_mm_B_ERA5.nc</p> <p>The output of zonal mean temperature from the TOMCAT/SLIMCAT simulations forced with ERA-Interim and ERA5 for Figure 8 are in files:</p> <p>te_mm_A_ERAI.nc</p> <p>te_mm_B_ERA5.nc</p> <p>The output of zonal mean age-of-air from the TOMCAT/SLIMCAT simulations forced with ERA-Interim and ERA5 for Figures 10-12 are in files:</p> <p>Age_mm_A_ERAI.nc</p> <p>Age_mm_B_ERA5.nc</p> <p>The output of the zonal mean ozone, temperature and age-of-air from the ERA5.1 reanalysis corrected simulations during the period from 2000 to 2006 in all Figures above using ERA5 are in files:</p> <p>ERA5_1_O3_2000_18.nc</p> <p>ERA5_1_te_2000_18.nc</p> <p>ERA5_1_Age_2000_18.nc</p> <p> </p>
Transformed Eulerian mean data from the ERA5 reanalysis (daily means)
<p>This dataset provides <strong>daily</strong> and zonal mean variables derived from the ERA5 reanalysis, including terms of the transformed Eulerian mean (TEM) momentum budget.</p> <p>All variables (zonal, meridional and vertical wind speed, temperature, zonal wind tendencies from Eliassen-Palm (EP) flux divergence and advection, EP fluxes and the residual streamfunction) are obtained from 6-hourly and native vertical and 0.5 degrees spatial resolution data. Zonal mean wind tendency from parameterizations is also provided (from the forecasts). Data are obtained from the MARS archive.</p> <p>Data are provided as one .zip file per decade (only partial for the 2020s and 1950s). <strong>Monthly</strong> means of the same quantities are provided in a companion dataset (10.5281/zenodo.7081721).</p> <p>The data and related documentation are provided 'as is' and without any warranty of any kind. Users are invited to report any issue or inconsistency they may find. Please cite the reference publication when using this dataset.</p> <p> </p> <p>Known issues:</p> <p>- All TEM terms divided by<em> <span>\(\cos(\phi)\)</span></em>, where <span>\(\phi\)</span> is latitude, diverge at the north and south poles (where <span>\(\phi = \pm \pi/2\)</span>), so they should not be considered. If variables at the poles are needed, values at neighbouring latitudes should be taken.</p>
Transformed Eulerian mean data from the ERA5 reanalysis (monthly means)
<p>This dataset provides <strong>monthly</strong> and zonal mean variables derived from the ERA5 reanalysis, including terms of the transformed Eulerian mean (TEM) momentum budget.</p> <p>All variables (zonal, meridional and vertical wind speed, temperature, zonal wind tendencies from Eliassen-Palm (EP) flux divergence and advection, EP fluxes and the residual streamfunction) are obtained from 6-hourly and native vertical and 0.5 degrees spatial resolution data. Zonal mean wind tendency from parameterizations is also provided (from the forecasts). Data are obtained from the MARS archive.</p> <p>Data are provided as one .zip file per decade (only partial for the 2020s and 1950s). <strong>Daily</strong> means of the same quantities are provided in a companion dataset (10.5281/zenodo.7081436).</p> <p>The data and related documentation are provided 'as is' and without any warranty of any kind. Users are invited to report any issue or inconsistency they may find.</p> <p> </p> <p>Known issues:</p> <p>- All TEM terms divided by<em> <span>\(\cos(\phi)\)</span></em>, where <span>\(\phi\)</span> is latitude, diverge at the north and south poles (where <span>\(\phi = \pm \pi/2\)</span>), so they should not be considered. If variables at the poles are needed, values at neighbouring latitudes should be taken.</p>
Evolution of India's PM2.5 Pollution Between 1998 and 2020 Using Global Reanalysis Fields
<p>These datasets are part of Supplementary information for the journal article<br> "<a href="https://doi.org/10.1039/D2EA00027J">Evolution of India’s PM2.5 Pollution Between 1998 and 2020 Using Global Reanalysis Fields Coupled with Satellite Observations and Fuel Consumption Patterns</a>"</p> <p>Fuel consumption patterns linked to the evolution of PM2.5 pollution data is available <a href="https://doi.org/10.5281/zenodo.7156314">here</a><br> <a href="https://doi.org/10.5281/zenodo.7156314">https://doi.org/10.5281/zenodo.7156314</a></p> <p><br> Data period - 1998 to 2020<br> PM2.5 units - micro-gm/m3<br> State and District GIS Shapefiles are available here - <a href="http://projects.datameet.org/maps">https://projects.datameet.org/maps</a></p> <p><strong>List of files available for download</strong></p> <p>india_wustl_extracts_pm25_bygrid_annual.xlsx</p> <ul> <li>PM2.5 concentrations data resolution is 0.1 degrees</li> <li>Covers India and the remaining countries in the domain covering 67E to 99E in longitudes and 7N to 39 N in latitudes (Pakistan, Bangladesh, Nepal and partially Sri Lanka and Afghanistan)</li> </ul> <p>india_wustl_extracts_pm25_bystate.xlsx</p> <ul> <li>PM2.5 concentrations data aggregated at the state level</li> <li>States are as designated under Census 2011 + Telangana</li> <li>Total states = 30</li> <li>Total Union Territories (UT) = 6</li> <li>JK as State includes new UT - Ladakh</li> </ul> <p>india_wustl_extracts_pm25_bydistrict.xlsx</p> <ul> <li>PM2.5 concentrations data aggregated at the district level</li> <li>Districts are as designated under Census 2011</li> <li>Total districts = 640</li> </ul> <p>india_wustl_extracts_pmsa.xlsx</p> <ul> <li>PM2.5 source apportionment concentrations aggregated at state and district level </li> <li>36 states and UTs</li> <li>640 districts</li> <li><a href="https://sites.wustl.edu/acag/datasets/gbd-maps/">GBDMAPS source classification</a> <ul> <li>1. AFCID = Anthropogenic Fugitive, Combustion, and Industrial Dust</li> <li>2. AGR = Agriculture - includes manure management, soil fertilizer emissions, rice cultivation, enteric fermentation, and other agriculture</li> <li>3. ENEcoal = Energy Production (coal combustion only) - Includes electricity and heat production, fuel production and transformation, oil and gas fugitive/flaring, and fossil fuel fires</li> <li>4. ENEother = Energy Production (all non-coal combustion) - Includes electricity and heat production, fuel production and transformation, oil and gas fugitive/flaring, and fossil fuel fires</li> <li>5. GFEDagburn = Agricultural Waste Burning - Includes solid waste disposal, waste incineration, waste-water handling, and other waste handling (from the GFED fires inventory)</li> <li>6. GFEDoburn = Other Open Fires - Includes deforestation, boreal forest, peat, savannah, and temperate forest fires (from the GFED fires inventory)</li> <li>7. INDcoal = Industry (coal combustion only) - Includes Industrial combustion (iron and steel, non-ferrous metals, chemicals, pulp and paper, food and tobacco, non-metallic minerals, construction, transportation equipment, machinery, mining and quarrying, wood products, textile and leather, and other industry combustion) and non-combustion industrial processes and product use (cement production, lime production, other minerals, chemical industry, metal production, food, beverage, wood, pulp, and paper, and other non-combustion industrial emissions)</li> <li>8. INDother = Industry (all non-coal combustion) - Includes Industrial combustion (iron and steel, non-ferrous metals, chemicals, pulp and paper, food and tobacco, non-metallic minerals, construction, transportation equipment, machinery, mining and quarrying, wood products, textile and leather, and other industry combustion) and non-combustion industrial processes and product use (cement production, lime production, other minerals, chemical industry, metal production, food, beverage, wood, pulp, and paper, and other non-combustion industrial emissions)</li> <li>9. NRTR = non-road/ off-road transportation - Includes Rail, Domestic navigation, Other transportation</li> <li>10. OTHER = all remaining sources, including: volcanic SO2, lightning NOx, biogenic soil NO, ocean emissions, biogenic emissions, very short lived iodine and bromine species, decaying plants (misc. inventories)</li> <li>11. RCOC = Commercial Combustion - Includes commercial and institutional combustion</li> <li>12. RCOO = Other Combustion - Includes combustion from agriculture, forestry, and fishing</li> <li>13. RCORbiofuel = Residential combustion (solid biofuel combustion only) - includes residential heating and cooking</li> <li>14. RCORcoal = Residential combustion (coal combustion only) - includes residential heating and cooking</li> <li>15. RCORother = Residential Combustion (all non-coal and non-solid biofuel) - includes residential heating and cooking</li> <li>16. ROAD = Road Transportation - includes cars, motorcycles, heavy and light duty trucks and buses</li> <li>17. SHP = International Shipping - Includes international shipping and tanker loading</li> <li>18. SLV = Solvents - Includes solvents production and application (degreasing and cleaning, paint application, chemical products manufacturing and processing, and other product use)</li> <li>19. WDUST = Windblown Dust - (from the DEAD dust model)</li> <li>20. WST = Waste - Includes solid waste disposal, waste incineration, waste-water handling, and other waste handling</li> </ul> </li> <li>Aggregated Source definitions used in this presentation <ul> <li>1. DUST = Anthropogenic dust = AFCID</li> <li>2. WINDUST = Wind erosion (dust storms) = WDUST</li> <li>3. WASTE = Waste burning = WST</li> <li>4. RESI = All commercial and residential cooking, lighting, and heating = RCOC + RCOO + RCORbiofuel + RCORcoal + RCORother</li> <li>5. TRANS = All transport (excluding aviation) = ROAD + NRTR + SHP</li> <li>6. POWER = Energy generation = ENEcoal + ENEother</li> <li>7. INDUS = All industries and product use = INDcoal + INDother + SLV</li> <li>8. BIOB = Biomass burning, including forest fires and agricultural waste burning = GFEDoburn + GFEDagburn</li> <li>9. AGR = Agricultural activities (excluding agricultural waste burning) = AGR</li> <li>10. OTHER = All others = OTHER</li> </ul> </li> </ul> <p>India_PMSA_APnA_50airsheds_CAMxOutputs.csv</p> <ul> <li> <p>Summary of estimated source contributions to ambient PM2.5 concentrations, including the contribution of sources outside the city airsheds. These results are explained and discussed in journal articles.<br> 1. Air pollution knowledge assessments (APnA) for 20 Indian cities [<a href="https://doi.org/10.1016/j.uclim.2018.11.005">link</a>]<br> 2. National Clean Air Programme (NCAP) for Indian cities: Review and outlook of clean air action plans [<a href="https://doi.org/10.1016/j.aeaoa.2020.100096">link</a>]<br> 3. Also explained here <a href="https://zenodo.org/record/6919069#.YzKHIHZBxPY">https://zenodo.org/record/6919069#.YzKHIHZBxPY</a> </p> </li> </ul> <p> </p> <p>Original data source at 0.01 degree resolution: <a href="https://sites.wustl.edu/acag/datasets/surface-pm2-5">https://sites.wustl.edu/acag/datasets/surface-pm2-5</a><br> </p>
Figures 1-2. Phidippus pacosauritus male, anterior view. Figure 2 in Description of Phidippus pacosauritus sp. nov. (Salticidae: Salticinae: Dendryphantini: Dendryphantina), with a reanalysis of related species in the mystaceus group
Figures 1-2. Phidippus pacosauritus male, anterior view. Figure 2. Arrow pointing at femur I dorsal setal tuft. Photo credits: Colin Hutton.
Figures 24-29. Phidippus mystaceus clade group members, male anterior view. Figure 24. Phidippus mystaceus, Oklahoma. Figure 25. Phidippus toro, Arizona. Figure 26. Phidippus pacosauritus, Sinaloa. Figure 27 in Description of Phidippus pacosauritus sp. nov. (Salticidae: Salticinae: Dendryphantini: Dendryphantina), with a reanalysis of related species in the mystaceus group
Figures 24-29. Phidippus mystaceus clade group members, male anterior view. Figure 24. Phidippus mystaceus, Oklahoma. Figure 25. Phidippus toro, Arizona. Figure 26. Phidippus pacosauritus, Sinaloa. Figure 27. Phidippus arizonensis, central Mexico, state uncertain. Figure 28. Phidippus cruentus, Jalisco. Figure 29. Phidippus adonis, Morelos. Photo credits: Figures 24, 26-29, David Hill.
Figures 42-43. Primary courtship positions for P. pacosauritus. Figure 42. Stationary position. Figure 43 in Description of Phidippus pacosauritus sp. nov. (Salticidae: Salticinae: Dendryphantini: Dendryphantina), with a reanalysis of related species in the mystaceus group
Figures 42-43. Primary courtship positions for P. pacosauritus. Figure 42. Stationary position. Figure 43. Lateral display position. Photo credits: David Hill.
Figure 46 in Description of Phidippus pacosauritus sp. nov. (Salticidae: Salticinae: Dendryphantini: Dendryphantina), with a reanalysis of related species in the mystaceus group
Figure 46. New proposed phylogeny of mystaceus clade with addition of P. pacosauritus. Version resolving behavioral and some morphological homoplasy. One of the two homoplasious carapace modifications (in
Figures 20-23. Phidippus pacosauritus genital structures. Figures 20-21. Male palp. Figure 20. Ventral view. Figure 21. Lateral view. Figures 22-23. Female epigyne. Figure 22. Ventral view. Figure 23 in Description of Phidippus pacosauritus sp. nov. (Salticidae: Salticinae: Dendryphantini: Dendryphantina), with a reanalysis of related species in the mystaceus group
Figures 20-23. Phidippus pacosauritus genital structures. Figures 20-21. Male palp. Figure 20. Ventral view. Figure 21. Lateral view. Figures 22-23. Female epigyne. Figure 22. Ventral view. Figure 23. Dorsal view cleared.
Figure 44 in Description of Phidippus pacosauritus sp. nov. (Salticidae: Salticinae: Dendryphantini: Dendryphantina), with a reanalysis of related species in the mystaceus group
Figure 44. Phidippus phylogeny based only on morphological characters, proposed by Edwards (2004), with mystaceus group in orange box and clade containing P. mystaceus in blue box and enlargement.
Figure 45 in Description of Phidippus pacosauritus sp. nov. (Salticidae: Salticinae: Dendryphantini: Dendryphantina), with a reanalysis of related species in the mystaceus group
Figure 45. New proposed phylogeny of mystaceus clade with addition of P. pacosauritus. Version without leg
Figures 7-10. Phidippus pacosauritus female. Figure 7. Anterior view. Figures 8-10 in Description of Phidippus pacosauritus sp. nov. (Salticidae: Salticinae: Dendryphantini: Dendryphantina), with a reanalysis of related species in the mystaceus group
Figures 7-10. Phidippus pacosauritus female. Figure 7. Anterior view. Figures 8-10. Variation in dorsal abdominal pattern in color and visibility of lateral abdominal bands. Figure 10. Dark integument and scales variant. Photo credits: Figures 7-9, Colin Hutton; Figure 10, David Hill.
Figures 16-19. Preserved Phidippus pacosauritus, ventral view. Figure 16. Male. Figures 17-19 in Description of Phidippus pacosauritus sp. nov. (Salticidae: Salticinae: Dendryphantini: Dendryphantina), with a reanalysis of related species in the mystaceus group
Figures 16-19. Preserved Phidippus pacosauritus, ventral view. Figure 16. Male. Figures 17-19. Female variations.
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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)
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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.