This dataset contains the weather radar (WXR) data collected during the High Ice Water Content 2022 (HIWC 2022) project, onboard the NASA DC-8 aircraft, that was based out of Jacksonville, Florida. The radar measurements contained in this dataset have been processed to remove the instrument properties from the airborne radar data and thereby produce scientific measures of the atmosphere and the HIWC conditions and the surrounding meteorological environment. There are 4 different file types (RadProd, bmp, list, and kmz) containing radar measurements with each file type containing all of the flights in one zip file.

The up-to-date weather radar from the FMI radar network is available as Open Data. The data contain both single radar data along with composites over Finland in GeoTIFF and HDF5-formats. Available composite parameters consist of radar reflectivity (DBZ), rainfall intensity (RR), and precipitation accumulation of 1, 12, and 24 hours. Single radar parameters consist of radar reflectivity (DBZ), radial velocity (VRAD), rain classification (HCLASS), and Cloud top height (ETOP 20). Raw volume data from singe radars are also provided in HDF5 format with ODIM 2.3 conventions. Radar data becomes available as soon as it's received from the radar and pre-processed into deliverable formats. Typically the most recent radar data was collected less than 5 minutes ago.

This dataset contains the weather radar (WXR) data collected during the High Altitude Ice Crystals - High Ice Water Content (HAIC-HIWC) project that took place in Darwin, Australia. Some of the data files provide 4D tracks of the aircraft that can be played within Google Earth. The other data files contain the radar data. The data files are arranged by flight and are in zip, kml, and kmz format.

This dataset consists of Level III weather radar products collected from Next-Generation Radar (NEXRAD) stations located in the contiguous United States, Alaska, Hawaii, U.S. territories and at military base sites. NEXRAD is a network of 160 high-resolution Doppler weather radars operated by the NOAA National Weather Service (NWS), the Federal Aviation Administration (FAA), and the U.S. Air Force (USAF). Doppler radars detect atmospheric precipitation and winds, which allow scientists to track and anticipate weather events, such as rain, ice pellets, snow, hail, and tornadoes, as well as some non-weather objects like birds and insects. NEXRAD stations use the Weather Surveillance Radar - 1988, Doppler (WSR-88D) system. This is a 10 cm wavelength (S-Band) radar that operates at a frequency between 2,700 and 3,000 MHz. The radar system operates in two basic modes: a slow-scanning Clear Air Mode (Mode B) for analyzing air movements when there is little or no precipitation activity in the area, and a Precipitation Mode (Mode A) with a faster scan for tracking active weather. The two modes employ nine Volume Coverage Patterns (VCPs) to adequately sample the atmosphere based on weather conditions. A VCP is a series of 360 degree sweeps of the antenna at pre-determined elevation angles and pulse repetition frequencies completed in a specified period of time. The radar scan times 4.5, 5, 6 or 10 minutes depending on the selected VCP. During 2008, the WSR-88D radars were upgraded to produce increased spatial resolution data, called Super Resolution. The earlier Legacy Resolution data provides radar reflectivity at 1.0 degree azimuthal by 1 km range gate resolution to a range of 460 km, and Doppler velocity and spectrum width at 1.0 degree azimuthal by 250 m range gate resolution to a range of 230 km. The upgraded Super Resolution data provides radar reflectivity at 0.5 degree azimuthal by 250 m range gate resolution to a range of 460 km, and Doppler velocity and spectrum width at 0.5 degree azimuthal by 250 m range gate resolution to a range of 300 km. Super resolution makes a compromise of slightly decreased noise reduction for a large gain in resolution. In 2010, the deployment of the Dual Polarization (Dual Pol) capability to NEXRAD sites began with the first operational Dual Pol radar in May 2011. Dual Pol radar capability adds vertical polarization to the previous horizontal radar waves, in order to more accurately discern the return signal. This allows the radar to better distinguish between types of precipitation (e.g., rain, hail and snow), improves rainfall estimates, improves data retrieval in mountainous terrain, and aids in removal of non-weather artifacts. The NEXRAD products are divided in two data processing levels. The lower Level II data are base products at original resolution. Level II data are recorded at all NWS and most USAF and FAA WSR-88D sites. From the Level II quantities, computer processing generates numerous meteorological analysis Level III products. The Level III data consists of reduced resolution, low-bandwidth, base products as well as many derived, post-processed products. Level III products are recorded at most U.S. sites, though non-US sites do not have Level III products. There are over 40 Level III products available from the NCDC. General products for Level III include the base and composite reflectivity, storm relative velocity, vertical integrated liquid, echo tops and VAD wind profile. Precipitation products for Level III include estimated ground accumulated rainfall amounts for one and three hour periods, storm totals, and digital arrays. Estimates are based on reflectivity to rainfall rate (Z-R) relationships. Overlay products for Level III are alphanumeric data that give detailed information on certain parameters for an identified storm cell. These include storm structure, hail index, mesocyclone identification, tornadic vortex signature, and storm tracking information. Radar messages for Level III are sent by the radar site to users in order to know more about the radar status and special product data. NEXRAD data are provided to the NOAA National Climatic Data Center for archiving and dissemination to users. Data coverage varies by station and ranges from May 1992 to 1 day from present. Most stations began observing in the mid-1990s, and most period of records are continuous.

This dataset consists of Level II weather radar data collected from Next-Generation Radar (NEXRAD) stations located in the contiguous United States, Alaska, Hawaii, U.S. territories and at military base sites. NEXRAD is a network of 160 high-resolution Doppler weather radars operated by the NOAA National Weather Service (NWS), the Federal Aviation Administration (FAA), and the U.S. Air Force (USAF). Doppler radars detect atmospheric precipitation and winds, which allow scientists to track and anticipate weather events, such as rain, ice pellets, snow, hail, and tornadoes, as well as some non-weather objects like birds and insects. NEXRAD stations use the Weather Surveillance Radar - 1988, Doppler (WSR-88D) system. This is a 10 cm wavelength (S-Band) radar that operates at a frequency between 2,700 and 3,000 MHz. The radar system operates in two basic modes: a slow-scanning Clear Air Mode (Mode B) for analyzing air movements when there is little or no precipitation activity in the area, and a Precipitation Mode (Mode A) with a faster scan for tracking active weather. The two modes employ nine Volume Coverage Patterns (VCPs) to adequately sample the atmosphere based on weather conditions. A VCP is a series of 360 degree sweeps of the antenna at pre-determined elevation angles and pulse repetition frequencies completed in a specified period of time. The radar scan times 4.5, 5, 6 or 10 minutes depending on the selected VCP. The NEXRAD products are divided into multiple data processing levels. The lower Level II data contain the three meteorological base data quantities at original resolution: reflectivity, mean radial velocity, and spectrum width. With the advent of dual polarization beginning in 2011, additional base products of differential reflectivity, correlation coefficient and differential phase are available. Level II data are recorded at all NWS and most USAF and FAA WSR-88D sites. From the Level II quantities, computer processing generates numerous meteorological analysis Level 3 products. NEXRAD data are acquired by the NOAA National Centers for Environmental Information (NCEI) for archiving and dissemination to users. Data coverage varies by station and ranges from June 1991 to 1 day from present. Most stations began observing in the mid-1990s, and most period of records are continuous.

The data provided in this folder contains the processed Chennai Doppler Weather Radar reflectivity and radial velocity informaton along with its geographic locations in standard Netcdf format. This processed data was used for creation of the figures in the manuscript accepted for publication in the JGR Atmospheres journal entitled: "Significance of 4DVAR Radar data assimilation in Weather Research and Forecast model based Nowcasting system" [Paper #2019JD031369RR].

The processed data used for creating figures are being shared here. The original raw data is shared to us by the Indian Meteorological Department who is the sole authority for the same.

This dataset contains the Level 1 (L1) raw radar event data recorded at Next Generation Radar (NEXRAD) sites and collected by the NOAA National Weather Service (NWS) Radar Operations Center (ROC) for specific radar case studies. It includes only the Level 1 data that has been used for algorithm development and verification by the ROC and its partners. NEXRAD operational sites and test sites are used. The dataset period of record starts in 2008 with new data added approximately every year. The number of case studies per year ranges from 1 to 33, with an average of approximately 10 per year. The data files are in the native compressed file format as Time Series (TS) Archive. The data files have been aggregated by event and by hour for the archive with a total data volume of approximately 20 TB. An event summary file with descriptive information is included for each case study.

Gridded files of radar-derived 5 minute precipitation accumulations, corrected by rain gauge data. Radar data over the Netherlands and surrounding area measured by Dutch, Belgian, and German radars are corrected by available data from automatic rain gauges. Time interval is 5 minutes. See data set nl_rdr_data_rtcor_5m_tar/1.0 for an archive that goes back to 2018. Starting with data from 31 January 2023 - 10.45 UTC onwards, this dataset is created using improved algorithms. This includes correction for signal attenuation, correction for vertical variation of precipitation, correction for fast-moving showers and use of uncertainty information in merging data from multiple radars. Starting with data from 18 November 2024 - 14.40 UTC onwards, this dataset is created using improved methodologies. This includes a) the usage of additional rain gauge data from water authorities and water companies, and b) reducing the quality indication of data of the Herwijnen radar of the lowest two elevations and for a small set of azimuth angles, to mitigate beam blockage due to trees and wind turbines.

Données concernant les quelques 3000 radars automatiques en France. Informe de l'emplacement précis, de la route, de la direction, du type (fixe, feu rouge, tronçon...), de la vitesse contrôlée, de la date d'installation. Vous pouvez en apprendre plus sur une page dédiée sur le site de la sécurité routière. Ce jeu de données utilise comme source le site du Ministère de l'Intérieur https://radars.securite-routiere.gouv.fr. Exemple $ head -n 5 *.csv date_heure_dernier_changement,date_heure_creation,departement,latitude,longitude,id,direction,equipement,date_installation,type,emplacement,route,longueur_troncon_km,vitesse_poids_lourds_kmh,vitesse_vehicules_legers_kmh 2018-06-28T12:18:22Z,2018-06-28T11:02:09Z,80,49.95842,2.85479,10354,PARIS VERS LILLE,MORPHO,2003-11-05T00:00:00Z,Radar fixe,HEM MONACU,A1,,,130 2018-06-28T12:18:22Z,2018-06-28T11:02:09Z,91,48.67029,2.27976,10355,PARIS VERS MONTLHERY,MORPHO,2003-10-31T00:00:00Z,Radar fixe,LA VILLE DU BOIS,RN20,,,70 2018-06-28T12:18:22Z,2018-06-28T11:02:09Z,91,48.63212,2.4065,10356,PARIS VERS CORBEIL ESSONNES,MORPHO,2003-10-31T00:00:00Z,Radar fixe,COURCOURONNES,A6,,,110 2018-06-28T12:18:22Z,2018-06-28T11:02:09Z,78,48.83313,2.08501,10357,TRAPPES VERS PARIS,MORPHO,2003-10-30T00:00:00Z,Radar fixe,BAILLY,A12,,,110 Prévisualisation possible sur GitHub

Climate Policy Radar Open Data

This repo contains the full text data of all of the documents from the Climate Policy Radar database (CPR), which is also available at Climate Change Laws of the World (CCLW). Please note that this replaces the Global Stocktake open dataset: that data, including all NDCs and IPCC reports is now a subset of this dataset.

  What’s in this dataset

This dataset contains two corpus types (groups of the same types or sources of documents) which… See the full description on the dataset page: https://huggingface.co/datasets/ClimatePolicyRadar/all-document-text-data.

This repository contains netCDF data files from the Tropical Cyclone Radar Archive of Doppler Analyses with Re-centering (TC-RADAR) version v3k. For more information on the creation of the database, refer to Fischer et al. (2022; https://doi.org/10.1175/MWR-D-21-0223.1). This repository also contains a readme for additional information on the variables stored in the "swath" and "merged" data files. The bias-corrected reflectivity data file ("tc_radar_v3k_corrected_ref.nc") was created following the methods described in Wadler et al. (2023; https://doi.org/10.1175/MWR-D-23-0048.1) and Fischer et al. (2023; Monthly Weather Review, accepted pending minor revision). The storm-centered infrared brightness temperatures ("tc_radar_swath_mergIR_v3k.nc") were derived from NASA's MergIR data set (https://disc.gsfc.nasa.gov/datasets/GPM_MERGIR_1/summary).

This data set contains the data from the KULM polarimetric S-band Doppler weather radar operated by the University of Louisiana-Monroe near the Monroe Regional Airport during VORTEX-SE 2018 field season operations. Included are radar reflectivity, radial velocity, signal-to-noise ratio, spectrum width, differential reflectivity (ZDR), correlation coefficient (rhohv), and differential propagation phase (phidp). Data are included only for days of VORTEX-SE 2018 operations (10-11 and 28 March and 6-7 and 13-14 April 2018). The data are in CF/Radial compliant NetCDF format.

For detailed information about how the database has been gathered, please see the following paper:

https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/iet-rsn.2019.0307

Context

Nowadays, using radar devices to protect critical infrastructures is an extended worldwide practice. These sensors provide early detection and warning of incoming threats and a high accuracy estimate of their position and dynamics. In many cases, more diverse information about the nature of the target is desired. Also, automatic classification techniques would improve the efficiency of these systems. To build such classifiers, quality labeled data is needed. For this purpose, an extensive controlled trial test campaign has been done, resulting in a novel dataset with more than 17000 samples of drones, cars, and people.

The radar used to capture the data is a ubiquitous or persistent radar system developed by the Microwave and Radar Group from the UPM called RAD-DAR (Digital Array Receiver). The radar uses a frequency-modulated continuous wave (FMCW) on a frequency band centered at 8.75 GHz with a maximum bandwidth of 500 MHz.

More information will be provided soon.

Content

After a digital signal processing chain (more information will be provided about it), a 4092x512 matrix for each scene is obtained, where the rows are the distance cells, the columns are the doppler frequencies, and the values are in dBm. These matrices have been trimmed around the detected object (the detector is based on CFAR techniques), resulting in 11x61 matrices. Examples of each target can be seen in the following figures:

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1412594%2Fc0e5c2512f82d96369c45fe3bffd82d4%2Fcar.png?generation=1567007381846770&alt=media" alt="">

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1412594%2F9c8be206c5ecd076160e5d043d1f122e%2Fdronet0.png?generation=1567007411564753&alt=media" alt="">

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1412594%2F818c9cb008c7c8ae4ea3e46bcffa63fc%2Fperson.png?generation=1567007438458044&alt=media" alt="">

More information will be provided soon.

Acknowledgements

Advanced Radar Technologies [1] have played a vital role in the acquisition of this database, providing support during the field tests and allowing the use of their facilities.

The radar system used is a ubiquitous radar system developed by the Microwave and Radar Group from the UPM called RAD-DAR (Radar with a Digital Array Receiver).

Inspiration

In progress

[1] https://www.advancedradartechnologies.com/

This repository contains the data acquired from the MESEWI weather radar at the Delft University of Technology for Doppler processing. It contains MATLAB code for estimating the raindrop size distribution (DSD) parameters (sub-optimal estimates) and the radial mean wind and turbulence parameters. In addition to the DSD estimates, this code can generate the Plan Position Indicator (PPI) plots for terminal fall velocity and median diameter as a function of range and azimuth. This novel estimator can make use of these incoherent radar fast scans to estimate the parameters.

The MESEWI radar is an X-band azimuthally scanning radar at TU Delft, Netherlands. The data folder contains the data for several azimuthal radar scans at an elevation of 30 degrees from the ground level. The code files are in the folder Production4TURD. Details of the code repository can be found in the README.pdf file.

This dataset is applied in the manuscript 'An Automatic Framework of Region-of-interest Detection and Classification for Networked X-band Weather Radar System'. The compressed file contains reflectivity data from the networked X-band radar located in Chengdu, China in 38 days of the rainy seasons during 2017~2019. Each raw data is the composed reflectivity from three radars.

U.S. Geological Survey researchers conducted time-series ground-penetrating radar (GPR) surveys with a Sensors and Software 500-MHz Pulse Ekko Pro system. This data release contains ground-based (ski and snowmobile) as well as airborne common-offset profiles. All profiles are linked to coincident GPS observations. Additionally, common-midpoint data was collected at specific glacier locations. Coincident in-situ data may provide calibration information, and may be composed of any of the following: snow pits and/or snow-pit/snow-core combinations, probe profiles, and ablation stake data. This supplemental information provides estimates of snow properties which may be used to calibrate radar velocity.

This service contains the locations used for 3RWW's Gauge-Adjusted Radar Rainfall Data (GARRD) services.

GARRD is also referred to as Calibrated Radar Rainfall Data.Note: this layer doesn't contain any rainfall data; it only provides the locations for which gauge adjusted radard rainfall data is produced.More information is available on http://www.3riverswetweather.org/municipalities/calibrated-radar-rainfall-data

Overview This dataset coincides with a selected atmospheric case from the 200-m meteorological tower data. Data Details These data have been provided by Texas Tech University, from their boundary layer radar profiler. Data Quality These data have been acquired in 20-minute logs from a Vaisala LAP-3000 radar profiler.

This data set contains the gridded radar data from the National Oceanic and Atmospheric Administration (NOAA) P-3 aircraft tail Doppler radar and sweep file data from the lower fuselage radar for flights into the tropical systems of interest to the Tropical Cyclone Intensity (TCI) field project. The storms included are Erika from the 2015 Atlantic region, Patricia from the 2015 Eastern Pacific region, and Matthew from the 2016 Atlantic region. These data are in a binary format.

This dataset constitutes the as-recorded echo data from the MARFA radar system. The data was recorded by a National Instruments acquisition system, simultaneously with GPS, magnetics, laser range data, outside air temperature and IMU data. The data was acquired using the Environment for Linked Serial Acquisition (ELSA).

The data is provided in two forms: • Flight based and as recorded on the aircraft in raw packets • Transect based, reorganized into transects corresponding to the survey design, and demultiplexed into text tables and flat binary files.