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607 results for “wind data”
Aquarius Official Release Level 3 Wind Speed Standard Mapped Image Ascending Seasonal Climatology Data V5.0
Aquarius Level 3 ocean surface wind speed standard mapped image data contains gridded 1 degree spatial resolution wind speed data averaged over daily, 7 day, monthly, and seasonal time scales. This particular data set isthe seasonal climatology, Ascending wind speed product for version 5.0 of the Aquarius data set, which is the official end of mission public data release from the AQUARIUS/SAC-D mission. Only retrieved values for Ascending passes have been used to create this product. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath.
Aquarius Official Release Level 3 Wind Speed Standard Mapped Image Descending Seasonal Data V5.0
Aquarius Level 3 ocean surface wind speed standard mapped image data contains gridded 1 degree spatial resolution wind speed data averaged over daily, 7 day, monthly, and seasonal time scales. This particular data set is theSeasonal, Descending wind speed product for version 5.0 of the Aquarius data set, which is the official end of mission public data release from the AQUARIUS/SAC-D mission. Only retrieved values for Descending passes have been used to create this product. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath.
Aquarius Official Release Level 3 Wind Speed Standard Mapped Image 7-Day Running Mean Data V5.0
Aquarius Level 3 ocean surface wind speed standard mapped image data contains gridded 1 degree spatial resolution wind speed data averaged over daily, 7 day, monthly, and seasonaltime scales. This particular data set is the 7-Day running mean wind speed product for version 5.0 of the Aquarius data set, which is the official end of mission public data release from the AQUARIUS/SAC-D mission. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath.
Aquarius Official Release Level 3 Wind Speed Standard Mapped Image Descending Monthly Climatology Data V5.0
Aquarius Level 3 ocean surface wind speed standard mapped image data contains gridded 1 degree spatial resolution wind speed data averaged over daily, 7 day, monthly, and seasonal time scales. This particular data set is themonthly climatology, Descending wind speed product for version 5.0 of the Aquarius data set, which is the official end of mission public data release from the AQUARIUS/SAC-D mission. Only retrieved values for Descending passes have been used to create this product. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath.
Aquarius Official Release Level 3 Wind Speed Standard Mapped Image Descending Seasonal Climatology Data V5.0
Aquarius Level 3 ocean surface wind speed standard mapped image data contains gridded 1 degree spatial resolution wind speed data averaged over daily, 7 day, monthly, and seasonal time scales. This particular data set isthe seasonal climatology, Descending wind speed product for version 5.0 of the Aquarius data set, which is the official end of mission public data release from the AQUARIUS/SAC-D mission. Only retrieved values for Descending passes have been used to create this product. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath.
MetOp-A ASCAT Level 2 12.5-km Ocean Surface Wind Vector Climate Data Record Optimized for Coastal Ocean
This dataset represents the first historically reprocessed Level 2 coastal ocean surface wind vector climate data record from the Advanced Scatterometer (ASCAT) on MetOp-A sampled on a 12.5 km grid. This coastal dataset utilizes a spatial box filter to generate a spatial average of the Sigma-0 retrievals from the Level 1B dataset and obtains additional winds near the coast. Since the full resolution L1B Sigma-0 retrievals are used, all non-sea retrievals are discarded prior to the Sigma-0 averaging. Each box average Sigma-0 is then used to compute the vector cell wind using the same CMOD7 geophysical model function as in the operational OSI SAF ASCAT wind vector datasets. With this enhanced coastal retrieval, winds are computed as close to ~15 km from the coast. Each file corresponds to one complete orbit and is provided in netCDF version 3 format. The beginning of the orbit files is defined near the South Pole. ASCAT is a C-band fan beam radar scatterometer, providing two independent swaths of backscatter retrievals, aboard the MetOp-A platform in sun-synchronous polar orbit. It is a product of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSI SAF) provided through the Royal Netherlands Meteorological Institute (KNMI). For more information on the MetOp mission, please visit: https://www.eumetsat.int/our-satellites/metop-series . For access to more contemporaneous and near-real-time MetOp-A ASCAT 12.5km data, please visit: https://podaac.jpl.nasa.gov/dataset/ASCATA-L2-Coastal. For more timely announcements, users are encouraged to register with the KNMI scatterometer email list: scat@knmi.nl. All intellectual property rights of the OSI SAF products belong to EUMETSAT. The use of these products is granted to every interested user, free of charge. If you wish to use these products, EUMETSAT's copyright credit must be shown by displaying the words "copyright (year) EUMETSAT" on each of the products used. Use cases and feedback on the products will be much appreciated and in fact helps to sustain the reprocessing capability.
First ISCCP Regional Experiment (FIRE) Cirrus Phase II Colorado State University (CSU) Wind Profiler Data
The First ISCCP Regional Experiments have been designed to improve data products and cloud/radiation parameterizations used in general circulation models (GCMs). Specifically, the goals of FIRE are (1) to improve basic understanding of the interaction of physical processes in determining life cycles of cirrus and marine stratocumulus systems and the radiative properties of these clouds during their life cycles and (2) to investigate the interrelationships between the ISCCP data, GCM parameterizations, and higher space and time resolution cloud data.To-date, four intensive field-observation periods were planned and executed: a cirrus IFO (October 13-November 2, 1986); a marine stratocumulus IFO off the southwestern coast of California (June 29-July 20, 1987); a second cirrus IFO in southeastern Kansas (November 13-December 7, 1991); and a second marine stratocumulus IFO in the eastern North Atlantic Ocean (June 1-June 28, 1992). Each mission combined coordinated satellite, airborne, and surface observations with modeling studies to investigate the cloud properties and physical processes of the cloud systems.The Colorado State University (CSU) wind profiler data set was produced by the Department of Atmospheric Sciences of CSU as part of the FIRE Phase II Cirrus Intensive Field Observations (IFO) conducted in Coffeyville, Kansas. The CSU wind profiler data were collected during the period from Nov. 12, 1991 to Dec. 7, 1991 at the Parsons KG&E Power Plant, Parsons, Kansas (37 deg. 18 min. N and 95 deg. 07 min. W).
Aquarius Official Release Level 3 Wind Speed Standard Mapped Image Descending Annual Data V5.0
Aquarius Level 3 ocean surface wind speed standard mapped image data contains gridded 1 degree spatial resolution wind speed data averaged over daily, 7 day, monthly, and seasonal time scales. This particular data set is theAnnual, Descending wind speed product for version 5.0 of the Aquarius data set, which is the official end of mission public data release from the AQUARIUS/SAC-D mission. Only retrieved values for Descending passes have been used to create this product. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath.
GOES-16 cloud-motion wind and ASCAT ocean surface wind data for the article "Evolution of an atmospheric Kármán vortex street from high-resolution satellite winds: Guadalupe Island case study"
<p>This repository contains GOES-16 cloud-motion winds and ASCAT ocean surface winds derived for and analysed in the article "Evolution of an atmospheric Kármán vortex street from high-resolution satellite winds: Guadalupe Island case study".</p> <p> </p> <p><strong>GOES-16 Local Cloud-Motion Vectors</strong></p> <p>Data in two ASCII text files: <em>raw5x5g16b2_2018d129_1437z_2232z_north.txt</em> and <em>raw5x5g16b2_2018d129_1437z_2232z_south.txt</em>, with the former containing data for the upper half and the latter for the lower half of the study domain between ~26<sup>o</sup>N and ~29.5<sup>o</sup>N. Both files include 96 records, each record corresponding to a specific 5-minute time interval between 14:37 UTC and 22:32 UTC on 9 May 2018—9 May is day of year 129. The start and end times are given at the beginning of each record in YYYYDDDHHMM format, where Y is year, D is day of year, H is hour, and M is minute. For example, the first record contains data between 14:37 UTC and 14:42 UTC, as indicated by the start and end times of 20181291437 and 20181291442. Then follows the four column headers LAT LON SPD DIR, corresponding to latitude (degree), longitude (degree), wind speed (m/s), and wind direction (meteorological convention, degree north), respectively—note that no cloud-top height/pressure value was calculated for the wind vectors. Each subsequent line is a single GOES-16 local cloud-motion vector, derived from 5x5-pixel band 2 (0.64 micron visible red band) image templates, which represent an area of ~2.5x2.5 km<sup>2</sup> at the subsatellite point.</p> <p> </p> <p><strong>MODIS–GOES-16 3D Cloud-Motion Vectors</strong></p> <p>Data in two netCDF files: <em>MOD.A2018129.1810-75_ABI_CONUS_band_02_goes16.nc</em> and <em>MYD.A2018129.2120-75_ABI_CONUS_band_02_goes16.nc</em>, which correspond to the MODIS Terra and MODIS Aqua overpasses, respectively. These joint MODIS–GOES-16 wind retrievals were derived using ~8x8 km<sup>2</sup> red band image templates sampled every 2 km. The data files are self-explanatory, but the variables "lat", "lon", "V_3D", and "H_3D" provide the latitude (degree), longitude (degree), the [east-west, north-south] wind components (m/s), and the geometric stereo height (m) for each wind retrieval.</p> <p> </p> <p><strong>ASCAT Ocean Surface Wind Vectors</strong></p> <p>Data in two netCDF files: <em>ascat_20180509_030000_metopa_59945_srv_o_063_ovw_new.nc</em> and <em>ascat_20180509_040000_metopb_29259_srv_o_063_ovw_new.nc</em>, which correspond to the MetOp-A and MetOp-B overpasses, respectively. These ASCAT ocean surface retrievals are stress-equivalent winds at 10 m height, given on a 6.25-km grid. The data files are self-explanatory, but the variables "lat", "lon", "wind_speed", and "wind_dir" provide the latitude (degree), longitude (degree), the wind speed (m/s), and the wind direction (oceanographic convention, degree north) for each wind retrieval. <em>Note that wind direction follows the oceanographic convention and refers to the direction towards which the wind blows (equivalent to meteorological wind direction minus 180<sup>o</sup>)!</em></p>
The flow past a flatback airfoil with flow control devices: Benchmarking numerical simulations against wind tunnel data - Animations
<p>As wind turbines grow larger, the use of flatback airfoils has become standard practice for the root region of the blades. Flatback profiles provide higher lift and reduced sensitivity to soiling at significantly higher drag values. A number of flow control devices has been proposed to improve the performance of flatback profiles. In the present study, the flow past a flatback airfoil at a chord Reynolds number of 1.5×10<sup>6 </sup>with and without trailing edge flow control devices is considered. Two different numerical approaches are applied, Unsteady Reynolds Averaged Navier Stokes (RANS) simulations and Detached Eddy Simulations (DES). The computational predictions are compared to wind tunnel measurements to assess the suitability of each method. The effect of each flow control device on the flow is examined based on the DES results on the finer mesh. Results agree well with the experimental findings and show that a newly proposed flap device outperforms traditional solutions for flatback airfoils. In terms of numerical modelling, the more expensive DES approach is more suitable if the wake frequencies are of interest, but the simplest 2D RANS simulations can provide acceptable load predictions.</p> <p>These animations are the DES results on a Fine (25M cells, AR = 1) mesh. Animations include a 3D view of Q = 1.5 isosurfaces and a side view of Q = 100 isosurfaces for each case.</p> <p> </p>
Data in manuscript of "Nebkha alignments and their implications for shadow dune elongation under unimodal wind regime"
<p>All the data were used in manuscript of “Nebkha alignments and their implications for shadow dune elongation under unimodal wind regime”, including the wind tunnel data (data in Figure 7), CFD simulation data (data in Figure 3) and the field observation data (wind regime data in Figure 5 ).</p>
The flow past a flatback airfoil with flow control devices: Benchmarking numerical simulations against wind tunnel data - Animations II
<p>Animations from accepted (06/2020) publication:</p> <p>The flow past a flatback airfoil with flow control devices: Benchmarking numerical simulations against wind tunnel data, Wind Energ. Sci., https://doi.org/10.5194/wes-2020-36</p> <p>These animations are the DES results on a Fine (25M cells, AR = 1) mesh. Animations include a 3D view of Delta = 10^5 isosurfaces coloured by X vorticity and Z vorticity. Two animations are available for each case (Plain airfoil, Flap, Flap + Cavity, Cavity, Splitter). Contour levels are included in separate files.</p> <p> </p>
Resource and Load Compatibility Assessment of Wind Energy Offshore of Humboldt County, California: Data and Software
<p>These files contain the raw data and code used to analyzed wind resource and local load compatibility of offshore wind in Humboldt, California.</p>
Climate model data for "Atmosphere-ocean feedback from wind-driven sea spray aerosol production"
<p>Data from atmosphere-only and coupled climate model simulations performed for "Atmosphere-ocean feedback from wind-driven sea spray aerosol production". Files are in netCDF format.</p>
Raw and Preprocessed BMRA Wind Power Data
<p>Dataset of metered energy generation and Bid Acceptance Volume (i.e., observational dataset) used as input for the probabilistic wind power forecasting tool developed for the paper: <strong>Seamless short- to mid-term probabilistic wind power forecasting</strong>.</p>
Data used for Investigating the role of Amazonian mesoscale wind patterns and strength on the spatial distribution of Martian bedrock exposures
<p>This upload contains four distinct zipped files with several different datasets contained within used for the analysis in publication "Investigating the role of Amazonian mesoscale wind patterns and strength on the spatial distribution of Martian bedrock exposures" by Gary-Bicas et al., 2022 Description for each dataset is below.</p> <p>- External data (Contains data used for thermophysical and morphological analysis).</p> <ul> <li>binary files NBmap2007.bin (Putzig and Mellon, 2007) and nmap2003.bin( Putzig et al., 2005) . These contain global Mars thermal inertia maps using the Thermal Emission Spectrometer (TES) onboard Mars Global Surveyor (MGS) </li> <li>Comma separated files with terminations "...USGS.csv" these are files extracting data for the studies' regions from the Mars global USGS geologic map #3292 (Tanaka et al., 2014) </li> <li>Shape file for bedrock designations (bedrock.[shp,shx,prj,dbf]) created by Cowart et al., 2019 where they mapped locations with bedrock exposures on Mars. We also include comma separated value files of the same maps for locations studied in this analysis (files with termination "...bedrock.csv")</li> <li>Shape file included has the locations of craters identified in all study regions for analysis (craters.point.[shp,shx,prj,dbf] and craters.polygon.[shp,shx,prj,dbf]) paired with the comma separated value intracrat.csv</li> <li>Shape file with study locations for analysis (windo_modeling_locations_revised3.[shp,shx,prj,dbf])</li> </ul> <p>- MRAMS data files.zip</p> <ul> <li>Contains 11 simulated climate states for each of the ten study location in analysis as well as Jezero crater using the Mars Regional Atmospheric Modeling System (MRAMS, Rafkin and Michaels, 2019). For each simulated case there are 4 seasonal time steps equating to 44 simulated cases for each study region in total (484 files) see associated python software publication indicating ingestion and processing of MRAMS datasets</li> </ul> <p>- MRAMS output files.zip</p> <ul> <li>After ingesting the datasets in MARS data files.zip into a python algorithm (see associated software publication) values for Wind Erosion Potential were extracted from the datasets and weighted sums were conducted to get annual values (see manuscript publication and associated python software publication,"MRAMS Data Output.ipynb") data was output into comma separated values for ease of use</li> </ul> <p>-MRAMS elevation and slope files.zip</p> <ul> <li>MRAMS data from output files.zip was further ingested into other algorithms to extract elevation and terrain slope values (see associated python software publication, "MRAMS Data Output.ipynb") that were output into comma separated values for ease of use</li> </ul> <p> </p> <p> </p>
Supporting data_Strong-wind events control barchan dune migration
<p>Supporting data_Strong-wind events control barchan dune migration</p>
Data from Doppler-Wind Lidar (DWL) measurements at Paris – Arboretum (PAARBO) from 2023-07-27 to 2023-09-13 [RAW]
<p>Original data files from DWL measurements at the arboretum de Vallée-aux-Loups (Département 92) in the built-up area in the SW of Greater Paris.</p>
Data from Doppler-Wind Lidar (DWL) measurements at Paris – Chemin Vert Bobigny (PACHEM) from 2023-08-03 to 2024-03-04 [RAW]
<p>Original data files from doppler wind lidar (DWL) measurements at Paris–Chemin Vert Bobigny in the NE of built-up Greater Paris.</p>
Data from Doppler-Wind Lidar (DWL) measurements at Paris – SIRTA Atmospheric Observatory (PASIRT) from 2022-11-10 to 2024-02-02 [RAW]
<p>Original data files from DWL measurements at Paris–SIRTA Atmospheric Observatory in Palaiseau. Due to technical problems with the instrument, this dataset is likely flawed / problematic. Therefore access is restricted. </p>
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