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61 results for “radar observation”
Ka, W and G-band radar observations of clouds and light precipitation during the EPCAPE campaign in March and April 2023
<p>The files contained in the data sets include Ka, W and G-band radar observations of clouds and light precipitation for several days from March 23 to April 27, 2023, during the EPCAPE campaign in La Jolla, CA, USA. <br>The YYYYMMDD_HHMMSS file naming convention corresponds to the starting measurement time of the data set in UTC.<br>The CloudCube_EPCAPE_Gband_Spectra.zip folder contains G-band radar Doppler spectra in the form of calibrated reflectivity as a function of Doppler velocity and range, where the noise has been masked out. The CloudCube_EPCAPE_Gband_Spectra_Noise.zip folder contains G-band radar Doppler spectra, including noise and SNR. The CloudCube_EPCAPE_Gband_Moments.zip folder contains G-band radar Doppler spectra moments, i.e. calibrated reflectivity, mean Doppler velocity and Doppler spectrum width. The CloudCube_EPCAPE_Multifrequency.zip folder includes Ka, W and G-band calibrated reflectivity and dual-frequency reflectivity ratios. <br>These data were obtained from CloudCube, a Ka, W and G-band atmospheric profiling radar, to demonstrate synergies between multifrequency retrievals.<br>For more details about the data processing and description, please refer to: Socuellamos, J. M., Rodriguez Monje, R., Lebsock, M. D., Cooper, K. B., Beauchamp, R. M., and Umeyama, A.: Multifrequency radar observations of marine clouds during the EPCAPE campaign, Earth Syst. Sci. Data. https://doi.org/10.5194/essd-2023-454, 2024. </p>
A Test of Energetic Particle Precipitation Models Using Simultaneous Incoherent Scatter Radar and Van Allen Probes Observations
<p>BERI modeling reuslts for "A Test of Energetic Particle Precipitation Models Using Simultaneous Incoherent Scatter Radar and Van Allen Probes Observations"</p>
SMART Radar and WSR-88D Data Associated with "Mobile Radar Observations of Hurricanes at Landfall. Part II: Convectively Coupled Vortex Rossby Waves"
<p>The data contained in this archive are associated with "Mobile Radar Observations of Hurricanes at Landfall. Part II: Convectively Coupled Vortex Rossby Waves" in review in the <em>Journal of the Atmospheric Sciences</em>. Two sets of data associated with Hurricanes Isabel (2003) and Matthew (2016) are contained. Each subset of data contains the raw radar files that contribute to the manuscript in cfradial netCDF format.</p> <p>A readme file in included that describes the variables and format of the radar volume files. Questions about the dataset may be directed to addisonalford@ou.edu, drdoppler@ou.edu, or gordon.carrie-1@ou.edu.</p>
Data for "Hunting for gravity waves in non-orographic winter storms using 3+ years of regional surface air pressure networks and radar observations"
<p>These data are shown in the figures included with the article "Hunting for gravity waves in non-orographic winter storms using 3+ years of regional surface air pressure networks and radar observations," submitted to Atmospheric Chemistry and Physics.</p>
Dataset used in Kittel et al., 2017 (https://doi.org/10.5194/hess-2017-549), including model files and processed remote sensing observations (CryoSat-2 radar altimetry and GRACE total water storage)
<p>Dataset used in</p> <p>Kittel, C. M. M., Nielsen, K., Tøttrup, C., Bauer-Gottwein, P., 2017.Informing a hydrological model of the Ogooué with multi-mission remote sensing data. Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-549</p> <p>The dataset contains</p> <p>Model files:</p> <ul> <li>River delineation of the Ogooué river based on the SRTM 3 arc-second DEM </li> <li>Climate input data for the Ogooué model subbasins (TRMM and FEWS-RFE precipitation and ECMWF temperature)</li> <li>Parameter files</li> </ul> <p>Processed remote sensing data:</p> <ul> <li>CryoSat-2 satellite altimetry data over the Ogooué River from July 2010 to February 2015</li> <li><strong> </strong>Water mask derived from Sentinel-1 SAR, used to filter CryoSat-2 data</li> <li>GRACE TWS time series for the Ogooué basin</li> </ul> <p>The data is provided in a .zip file with a README.txt file providing additional information and details on the data, including where to obtain similar/original datasets.</p> <p>(c) Author(s) and Technical University of Denmark (DTU) 2018</p>
SMART-R2 Ground based C-band mobile radar observations of Hurricane Harvey landfall 2017
<p>This dataset contains radar scans collected by Shared Mobile Atmospheric Research and Teaching Radar #2 (SMART-R2) near Woodsboro, Texas during Hurricane Harvey landfall, 25-26 August 2017.</p> <p>Extract the data on a Unix system with the command "tar zxf hurricane_harvey.smart-r2.tar.gz"</p> <p>Directory harvey/SR2/iris_data/product_raw contains the data. The files are in Sigmet raw product format, documented at:<br> ftp://ftp.sigmet.com/outgoing/manuals/IRIS_Programmers_Manual.pdf</p> <p>Directory hurricane_harvey.smart-r2/SR2/log/ contains the radar operator's log.</p> <p>The deployment was funded by RAPID grant AGS-1759479 from the National Science Foundation, funds from the School of Meteorology at the University of Oklahoma, and a NASA Earth and Space Science Fellowship Program grant 17-EARTH17R-72.</p> <p>For more information, please contact:<br> M. I. Biggerstaff drdoppler@ou.edu<br> G. D. Carrie gordon.carrie-1@ou.edu</p> <p> </p>
Data set for "Multi-frequency SuperDARN HF radar observations of the ionospheric response to the October 2023 annular solar eclipse"
<p>This data set contains rawACF and sounding mode data files from the Christmas Valley East (CVE) SuperDARN radar and manually scaled ionogram parameters from the Boulder (BC840) Digisonde used in the paper "Multi-frequency SuperDARN HF radar observations of the ionospheric response to the October 2023 annular solar eclipse" submitted to Geophysical Research Letters.</p>
radar observations and WRF simulations of Typhoon Yagi (2024)
<p>This data set contains radar observations and WRF modal simulations (with Thompson and WDM6 microphysics schemes) of super Typhoon Yagi (2024).</p>
Triple-frequency (Ka-, W- and G-band) radar observations of a light precipitation event
<p>Triple-frequency (Ka-, W- and G-band) radar observations of a light precipitation event. Data is either in raw IQ form or processed spectral data.</p>
Level 2 base data in Lekima (2019) observed by Wenzhou S-band radar
<p>Level 2 base data in Lekima (2019) observed by Wenzhou S-band radar</p>
Simulation details for: Radar signatures and surface observations of elevated convection associated with damaging surface winds
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2007-2016 Surface Circulation over the Mid Atlantic Bight Continental Shelf derived from a Decade of High Frequency Radar Observations
<p>A decade (2007-2016) of hourly 6 km resolution maps of the surface currents across the Mid Atlantic Bight (MAB) generated by a regional-scale High Frequency Radar network are used to reveal new insights into the spatial patterns of the long term annual and seasonal mean surface flows. Across the 10 year time series, temporal means, inter- and intra-annual variability are used to quantify the variability of spatial surface current patterns from season to season and year to year. The 10-year annual mean surface flows are weaker and mostly cross shelf near the coast, increasing in speed and rotating to more alongshore directions near the shelf break, and increasing in speed and rotating to flow off-shelf in the southern MAB. The annual mean surface current pattern is relatively stable year to year compared to the hourly variations within a year. The ten-year seasonal means exhibit similar current patterns, with winter and summer more cross-shore while spring and fall transitions are more alongshore. Fall and winter mean current speeds are larger and correspond to a time when the mean winds are stronger and cross-shore. Summer mean currents are weakest and correspond to a time when the mean wind opposes the alongshore flow. Again, intra-annual variability is much greater than interannual, with the fall season exhibiting the most interannual variability in the surface current patterns. The extreme fall seasons of 2009 and 2011 are related to extremes in the wind and river discharge events caused by different persistent synoptic meteorological conditions, resulting in more or less rapid fall transitions from stratified summer to well-mixed winter conditions.</p>
Radar observations of an active subglacial lake system in the David Glacier catchment, Antarctica
<p>Unfocused radar observations of David Glacier, Antarctica. Collected in December 2016 to Februrary 2017 by Korea Polar Research Institute and University of Texas -- Institute for Geophysics.</p> <p>Full documentation can be found within the netCDF files.</p>
Data from: Resolving the heading-direction ambiguity in vertical-beam radar observations of migrating insects
1. Each year, massive numbers of insects fly across the continents at heights of hundreds of metres, carried by the wind, bringing both environmental benefits and serious economic and social costs. To investigate the insects' flight behaviour and their response to winds, entomological radar has proved to be a particularly valuable tool; however, its observations of insect orientation are ambiguous with regard to the head/tail direction and this greatly hinders interpretation of the migrants' flight behaviour. 2. We have developed two related methods of using wind data to resolve the head/tail ambiguity and we have compared their outputs with those from simply assigning the heading direction to be that which is closer to the track direction. We applied all three methods to observations of Australian Plague Locust migrations made with an Insect Monitoring Radar. 3. For the study dataset, some of the headings selected by the simpler method are shown to be clearly incorrect. The two new methods generally agree and reveal a significantly different, and presumably more accurate, relationship of heading direction to track direction. However, use of these methods leads to quite a large proportion of the sample being lost because the wind values, which derive from a regional-scale numerical model, are shown to be incompatible with the radar observations. This exploratory study has moreover demonstrated that locusts are frequently oriented at a large angle to their track, and that quite often their movement is at least slightly tail-first. 4. Both new methods appear to be a significant improvement on the simpler method. As well as providing an accurate representation of migratory flight behaviour, they allow occasions when the model wind values are unreliable to be eliminated from the data sample.
Calibration Bias Evaluation and Correction of S-Band Ground-Based Radar Reflectivity Using Ku-Band Space-Borne Radar Observations Along the East Coast of India
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Specular Meteor Radar Observations of the Semidiurnal Tide in Northern Scandinavia and Northern Germany
<p>The dataset contains specular meteor radar observations of the atmospheric semidiurnal tide in the mesosphere and lower thermosphere. The observations are from specular meteor radars located in Northern Scandinavia (Andenes, Kiruna, and Tromso) and Northern Germany (Collm and Juliusruh). The radar observations in Northern Scandinavia cover the years 1999, 2000, 2001, 2002, 2010, 2012, 2013, 2015, and 2019. Observations in Northern Germany cover the years 2010, 2012, 2013, 2015, and 2019. These data are in support of the publication "Migrating Semidiurnal Tide during the September Equinox Transition in the Northern Hemisphere."</p>
Observation of Electrical Alignment Signatures in An Isolated Thunderstorm by Dual-Polarized Phased Array Weather Radar and the Relationship with Intracloud Lightning Flash Rate
<div> <p>The data of the Dual-polarized Phased Array Weather Radar (DP-PAWR), from 2019-08-20 16:10:15 to16:41:04 on August 20, 2019. </p> <p> </p> </div>
Dataset for "On the quantification of thermodynamic phases of raining clouds: insights from multi-year CloudSat and ground-based radar observations over Longmen, Southern China"
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Bistatic HF Observations of CODAR Radars from CARL and MSR sites
<p>03-09-2022: More to written with a description of the data. </p>
The study of daytime ionospheric E-region radar echoes simultaneously observed by Qujing VHF radar and multi-ionosondes
<p>Qujing VHF coherent backscatter radar observed from 05:00 - 08:00 UT (13:00-16:00 LT) on 20 June, 2020;</p> <p>Ionosonde data observed on 19, 20, and 21 June 2020 at Huize and Qujing;</p> <p>Fengyun-4A (FY-4A) satellite data observed from 0230 UT to 0730 UT on 20 June, 2020.</p>
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OpenNeuro
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