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61 results for “radar observation”
The Observed and Simulated Evolution of a Microburst Using X-Band Phased-Array Radar Data Assimilation with EnKF
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Radar Observations of Convective Processes Associated with Eyewall Formation during the Rapid Intensification of Typhoon Cempaka (2021)
<p>Dataset for Radar Observations of Convective Processes Associated with Eyewall Formation during the Rapid Intensification of Typhoon Cempaka (2021)</p>
Data for 3 Swarm-E Fast Auroral Imager Passes Observing the ICEBEAR Radar Field of View
<p>Files containing data for 3 Swarm-E satellite passes observing the Ionospheric Continuous-wave E-region Bistatic Experimental Auroral Radar (ICEBEAR) field of view during semi-active geomagnetic conditions using the Fast Auroral Imager. The dates and times of the passes are:</p> <p>2018-03-10 05:21:00-05:26:00 UT<br> 2019-10-27 04:03:00-04:13:00 UT<br> 2020-03-19 09:00:00-09:04:00 UT</p>
pywaterinfo dataset for master's dissertation: Updating a conceptual rainfall-runoff model based on radar observation and machine learning
<p>This forcings dataset is the output of the pywaterinfo (https://fluves.github.io/pywaterinfo/) read in of forcing data (rain and potential evapotranspiration).</p> <p>Code related to this dataset can be found here: https://github.com/olivierbonte/master_thesis</p>
OpenEO dataset for master's dissertation: Updating a conceptual rainfall-runoff model based on radar observation and machine learning
<p>This dataset is the output of the <a href="https://openeo.org/">OpenEO</a> processing of satellite data (SAR backscatter and LAI). </p> <p>Code related to this dataset can be found <a href="https://github.com/olivierbonte/master_thesis">here</a></p>
Inferring neutral winds in the ionospheric transition region from AGW-TID observations with the EISCAT VHF radar and the Nordic Meteor Radar Cluster
<p>[Dataset] Inferring neutral winds in the ionospheric transition region from AGW-TID observations with the EISCAT VHF radar and the Nordic Meteor Radar Cluster</p>
Minimal dataset for master's dissertation: Updating a conceptual rainfall-runoff model based on radar observation and machine learning
<p>The minimal dataset needed of data which can not be retrieved from the internet by APIs in the preprocessing. Consists of shape, land use and rivers for the Zwalm catchment. </p> <p>Code related to this dataset can be found here: https://github.com/olivierbonte/master_thesis </p>
Preprocessing output for master's dissertation: Updating a conceptual rainfall-runoff model based on radar observation and machine learning
<p>Outputs of the local preprocessing of the OpenEO data (see <a href="https://doi.org/10.5281/zenodo.7691342">here</a>) and pywaterinfo data (see <a href="https://doi.org/10.5281/zenodo.7689200">here</a>).</p> <p>Code related to this dataset can be found <a href="http://github.com/olivierbonte/master_thesis">here</a></p>
Inverse observation operator parameters/models for master's dissertation: Updating a conceptual rainfall-runoff model based on radar observation and machine learning
<p>Both saved models and results of hyperparameter tuning are given. </p> <p>Code related to this dataset can be found <a href="http://github.com/olivierbonte/master_thesis">here</a></p> <p> </p>
Observational dataset of snowfall events in 20160121 and 20180104 by polarimetric radar and 2-dimensional vedio disdrometer
<p>Observational dataset of snowfall events in 20160121 and 20180104 by polarimetric radar and 2-dimensional vedio disdrometer used for the Manuscript: "Potential of Snowfall Nowcasting Using Polarimetric Radar Data and Its Link to Ice Microphysics: Study of Two Snowstorms in East China". QVP.zip represents the quasi-vertical profiles composited from NUIST CPOL at the 19.5-degree elevation. VAD.zip is the velocity azimuth displays (VADs) estimated from radar volume scans, using the method by Matejka and Srivastava (1991). Traj_ele_1p5.zip is the reflectivity factor at the trajectory final location estimated by VAD winds at the 1.5-degree elevation. Snow_data.zip is the observations of snow particles by NJU 2DVD. The files that end with .pkl can be read by python joblib module. The files that end with .nc are in Netcdf format.</p>
Data from: Resolving the heading-direction ambiguity in vertical-beam radar observations of migrating insects
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A new dataset of rain cell generated from observations of the Tropical Rainfall Measuring Mission (TRMM) precipitation radar and visible and infrared scanner and microwave imager
<p>This new dataset (M.TRMM-1B01-1B11-2A25-PMD-Rain) contains orbit-level data with 5 km spatial resolution and 0.25 km vertical resolution. It is produced by merging TRMM PR, VIRS and TMI measurements at PR pixel resolution combined with rain cell identification. The near-surface rain rate, profiles of rain rate and precipitation reflectivity factor, visible and infrared signals and microwave signals can be obtained in the dataset. The dataset provides new important data for in-depth research on the structural characteristics of rain cells and supports the study of precipitation mechanisms.</p>
Meteor radar wind observations
<p>Daily meteor radar wind observations over Poker Flat region in Alaska</p>
Dataset used in "Unmanned Aerial System (UAS) observations of water surface elevation in a small stream: comparison of radar altimetry, LIDAR and photogrammetry techniques"
<p>Dataset for research paper "Unmanned Aerial System (UAS) observations of water surface elevation in a small stream: comparison of radar altimetry, LIDAR and photogrammetry techniques", published in Remote Sensing of Environment 2019, Elsevier Journal.</p> <p>Dataset includes:</p> <p>-MATLAB_codes.rar: zip file that contains MATLAB codes. MAIN.m is the main code, it refers to external functions that are included in the zip file. MAIN.m plots the figures of the paper in which we compare radar, LIDAR and photogrammetry and computes statistics of table 3 (table of the paper)</p> <p>-zip file WL_observations_Aomose.zip contains LIDAR, radar, and photogrammetry observations to be loaded by MATLAB code MAIN.m</p> <p>-the LIDAR Digital Surface Model (DSM_final.tif) retrieved in the stream Amose Å</p> <p>-the photogrammetry Digital Elevation Model (DEM_nov.tif) and orthomosaic (orthomosaic_nov.tif) </p> <p> </p>
Studying solar storm impact on global neutral wind pattern using WACCM-X numerical simulations and Meteor radar observations
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Prestorm atmospheric dynamic variable profiling dataset in Beijing as observed from the Radar wind profiler mesonet
<p>This dataset contains prestorm atmospheric dynamical variables of 30 minutes before rainfall onset in summer (June ~ August) for the period 2018–2019, which is determined by the measurements from the triangular mesonet of radar wind profile in Beijing. Each data file is stored in CSV format, containing the triangle area averaged divergence, vertical velocity and vorticity at 400、450、500、550, 600, 650, 700, 750, 775, 800, 825, 850, 875 and 900 hPa levels. The name for each data is formatted as RWP_YYYY_NNN hPa_Lead-MM min.csv, where YYYY refers to 2018 and 2019, NNN refers to 400、450、500、550, 600, 650, 700, 750, 775, 800, 825, 850, 875 and 900 hPa, and MM refers to 12, 18, 24, 30, 36 and 42 minutes prior to rainfall onset. </p>
APR-2 Dual-frequency Airborne Radar Observations, Wakasa Bay, Version 1
The Airborne Second Generation Precipitation Radar (APR-2) collected data in the Wakasa Bay AMSR-E validation campaign over the sea of Japan on board a NASA P-3 aircraft. Data were collected on all P-3 flights that encountered precipitation.
Ice-penetrating radar data used in paper "Evaluating and locating a suitable bedrock drilling site near Zhongshan Station with airborne and ground-based observations"
<p>These are the ice-penetrating radar data used in Figure 4 of the paper "Evaluating and locating a suitable bedrock drilling site near Zhongshan Station with airborne and ground-based observations".</p> <p>The"read_image.m" file can be used to re-display Figure 4(a) of the paper, where the "x.mat", "y.mat", and "radar_profile_data.mat" are the x and y coordinates of the survey line, and the return power of the ice-penetrating radar data, respectively.</p> <p>The "Data_of_profile_A-A'(Figure_4b).xlsx" file includes two sheets. One is the "subglacial topography" sheet, which includes information about longitude, latitude, ice thickness, bed elevation, and hydraulic potential along the profile A-A'. The other sheet is the "BRP" sheet, which includes information about bed reflection power along the profile A-A'.</p>
Radar observations of traveling ionospheric disturbances produced by high power HF radio waves and natural sources
<p>The zip-archived data underlying the publication.</p>
Joint observation from aircraft and radar for stratiform precipitation in North China
<p>dataset for the paper https://doi.org/10.1175/JAS-D-21-0248.1</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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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.