Dataset DOI: 10.5061/dryad.5dv41nshp

Description of the data and file structure

This dataset was produced in support of Leghart et al. 2025 (in review, Monthly Weather Review), which investigates shear and turbulence within winter storms by identifying and characterizing spectrum width layers (SWLs)—coherent horizontal features associated with turbulent or shear-driven processes in the cloud. This dataset contains Ka-band radar observations collected by the Ka-Band Scanning Polarimetric Radar (KASPR), located at Stony Brook University (40.899°N, 73.127°W) on Long Island, NY, during cool-season precipitation events between 2017 and 2021. KASPR is a dual-polarization, Doppler radar designed to observe fine-scale cloud and precipitation structures with high spatial and temporal resolution. Technical details and performance characteristics of the radar are described in Kumjian et al. (2020, J. Appl. Meteor. Climatol., https://doi.org/10.1175/JAMC-D-20-0054.1) and Kollias et al. (2020, Geophys. Res. Lett., https://doi.org/10.1029/2020GL088440). KASPR was one of the ground-based radars participating in the NASA Investigation of Microphysics and Precipitation of Atlantic Coast-Threatening Snowstorms (IMPACTS) field experiment (McMurdie et al. 2022, https://doi.org/10.1175/BAMS-D-20-0246.1).

Each KASPR_XXX_SWL_moments file (XXX is PPI or VPT) corresponds to a single radar scan. For plan position indicator (PPI) scans, the file time indicates the start time of the scan; for vertically pointing (VPT) profiles, the file time represents the beginning of the time–height profile. Only radar moments used for SWL detection are included in these files: range, elevation, altitude, spectrum width (SW), reflectivity, and supporting metadata. KASPR SWL files are in NetCDF (.nc) format. The .nc files are stored by winter season (Dec - March) within .zip files. These data provide a high-resolution record of sub-kilometer-scale dynamical features in coastal winter storms and are intended to support further research on turbulent processes and microphysical variability in stratiform cloud systems. 

The SWL identification methodology relies on a convolution-based algorithm designed to detect linear enhancements in the spectrum width field. Multiple two-dimensional convolution kernels with vertical dimensions corresponding to layer thicknesses of 100, 250, and 500 meters are used to ensure sensitivity to both thin, transient features and broader structures. The kernels act as filters to quantify relative increases in SW by comparing the local SW to its surrounding environment. A binary mask is created from the convolution output by applying a threshold (0.20 m/s for VPT profiles and 0.25 m/s for PPI scans), and connected components within the binary field are labeled as individual SWLs. The resulting dataset provides a high-resolution record of sub-kilometer-scale dynamical features within coastal winter storms and is intended to support future research on turbulent processes and microphysical variability in stratiform cloud systems. The PPI SWL dataset (PPI SWL Climatology csv) and VPT SWL dataset (VPT SWL Climatology csv), which result from the KASPR SWL files, are .csv files. 

A supporting .csv file, "kaspr_dates.csv", contain information about the storm number, storm dates, and storm types. For more information, see Leghart et al. 2025 (in review, Monthly Weather Review).

Description of variables

KASPR PPI SWL moments

• timeh: Time in hours since 00:00:00 on the day of the radar scan. Useful for referencing local scan time relative to midnight.
• times: Unix time (seconds since 00:00:00 UTC on 1 January 1970) indicating the time of observation for each radar pulse.
• ref: Horizontal co-polar reflectivity, measured in decibels of reflectivity (dBZ). Reflects hydrometeor concentration and size.
• spw: Doppler spectrum width, in meters per second (m/s). Represents the spread of radial velocities within a radar volume, used to infer turbulence and shear (in PPI).
• snr: Signal-to-noise ratio, in decibels (dB). Represents the strength of the radar signal relative to background noise. Data with SNR < 6 dB were filtered out as part of quality control.
• rangekm: Slant range from the radar to each gate, in kilometers (km).
• xkm: East–west horizontal distance from the radar, in kilometers (km). Positive values are east of KASPR.
• ykm: North–south horizontal distance from the radar, in kilometers (km). Positive values are north of KASPR.
• zkm: Beam height above the surface, in kilometers (km), accounting for Earth curvature and refraction.
• elev_deg: Radar elevation angle of the beam in degrees above the horizon.
• az_deg: Azimuth angle in degrees clockwise from true north, indicating the pointing direction of the radar beam.
• file_duration_s: Duration of the PPI scan (in seconds) from the beginning to the end of the radar volume.

KASPR VPT SWL moments

• timeh: Time in hours since 00:00:00 on the day of the radar scan. Useful for referencing local scan time relative to midnight.
• times: Unix time (seconds since 00:00:00 UTC on 1 January 1970) indicating the time of observation for each radar pulse.
• ref: Horizontal co-polar reflectivity, measured in decibels of reflectivity (dBZ). Reflects hydrometeor concentration and size.
• spw: Doppler spectrum width, in meters per second (m/s). Represents the spread of radial velocities within a radar volume, used to infer turbulence (in VPT).
• snr: Signal-to-noise ratio, in decibels (dB). Represents the strength of the radar signal relative to background noise. Data with SNR < -10 dB were filtered out as part of quality control.
• rangekm: Slant range from the radar to each gate, in kilometers (km), corresponding to altitude above the radar.
• elev: Elevation angle of the beam (in degrees). For vertically pointing profiles, this angle is 90°, indicating a zenith-pointing beam.

XXX (PPI or VPT) SWL Climatology

• profileDateTime: YYYYMMDD-HHmmss of beginning of KASPR PPI scan or VPT profile (PPI or VPT).
• stormDate: YYYYMMDD of KASPR PPI scan or VPT profile (PPI or VPT).
• stormNum: storm ID number given in kaspr dates .csv file (PPI or VPT).
• layerHeight_km: altitude of SWL (km) given as the median altitude of the SWL (PPI or VPT).
• layerThickness_m: vertical depth or thickness of SWL (m) given as the difference between the top range gate and bottom range gate of the SWL (PPI or VPT).
• layerMagnitude: the mean SW value (m/s) of all SW observations contained within the SWL (PPI or VPT).
• layerAzimuth_deg: total azimuthal span of a PPI SWL given as the difference between the highest azimuthal and lowest azimuthal range gate (PPI).
• scanDuration_s: total observational time of the KASPR PPI file the PPI SWL was identified within (PPI).
• layerDuration_s: total observed duration of the VPT SWL  (VPT).
• profile_duration_s: total observational time of the KASPR VPT file the VPT SWL was identified within (VPT).

Code/software

The analysis and spectrum width layer (SWL) detection algorithm described in the associated paper were developed and run in MATLAB R2023a. The SWL detection algorithm was implemented in MATLAB and uses the function "conv2" to identify coherent enhancements in the spectrum width field using 2D convolution. Binary labeling of identified features was performed using MATLAB’s "bwlabel". MATLAB's "Regionprops" with descriptor "BoundingBox" from the Image Processing Toolbox is used to create the spatial and temporal characteristics of SWLs. The XXX_SWL_Climatology.csv (XXX being PPI or VPT) files contain the SWL datasets which are generated using matlab code found at https://github.com/erinleghart/SWL_Detection.

Access information

Other publicly accessible locations of the data:

• KASPR data from 2020 can be obtained from the Global Hydrology Resource Center Distributed Active Archive Center at http://dx.doi.org/10.5067/IMPACTS and McMurdie et al. (2019).