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1. Northeast US Regional NEXRAD radar mosaics of winter storms from 1996-2023, part 2

   https://doi.org/10.5061/dryad.rbnzs7hj9  

   Tomkins, Laura; Yuter, Sandra; Miller, Matthew; Corbin, Nicole; Hoban, Nicole (January 2023, Dryad)

   This dataset contains over 14,000 hours of regional radar mosaics over the northeast US from 600+ winter storm days between 1996-2023. Winter storm days are defined when at least 2 out of 15 surface stations in the northeast US (see attached map) produced at least 1 inch of snow over the 24 hour period. Sequences of these mosaics aid in analyzing the precipitation area and the structures within winter storms. Radar reflectivity data is combined from the first, lowest (0.5 degree) elevation angle from 12 NEXRAD WSR-88D radars in the northeast US (see attached). The scans occur every 5-10 minutes from each radar depending on the radar scan settings.  The time label of the regional map is based on the scan time central radar, KOKX (Upton, NY). Scans from other radars in the region are used for that time as long as they are within 8 minutes of the KOKX scan. The polar radar data from each radar is interpolated to a regional 1202 km x 1202 km Cartesian grid with 2 km grid spacing covering 35.73-46.8 degN and 66.36-81.85 degW. Where the radar domains overlap, we take the highest reflectivity value. For dates after dual-polarization integration (2012 onwards), files contain the correlation coefficient (RHO_HV) field and a binary field  that can be used to “image mute” the reflectivity which reduces the visual prominence of melting and mixed precipitation commonly mistaken for heavy snow. Image muting is applied where radar reflectivity is ≥ 20 dBZ and RHO_HV is ≤ 0.97. This product is different from other widely used radar mosaics such as the MRMS produced by NOAA since it does not interpolate to a constant altitude and thus preserves the finer scale details in the reflectivity field. Because the data used to create these mosaics are not interpolated to a constant altitude, the altitude varies over the region (altitudes of radar scan used at each grid point are provided as a field for each data file). This data set is specifically designed to analyze fine-scale structures in winter storms. Part 1 contains files pre-dual polarization integration (1996-2012)Part 2 contains files post-dual polarization integration (2012-2023) 

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2. High-Resolution Spatial Distribution of Bird Movements Estimated from a Weather Radar Network

   https://doi.org/10.3390/rs12040635  

   Kranstauber, Bart; Bouten, Willem; Leijnse, Hidde; Wijers, Berend-Christiaan; Verlinden, Liesbeth; Shamoun-Baranes, Judy; Dokter, Adriaan M. (February 2020, Remote Sensing)

   Weather radars provide detailed information on aerial movements of organisms. However, interpreting fine-scale radar imagery remains challenging because of changes in aerial sampling altitude with distance from the radar. Fine-scale radar imagery has primarily been used to assess mass exodus at sunset to study stopover habitat associations. Here, we present a method that enables a more intuitive integration of information across elevation scans projected in a two-dimensional spatial image of fine-scale radar reflectivity. We applied this method on nights of intense bird migration to demonstrate how the spatial distribution of migrants can be explored at finer spatial scales and across multiple radars during the higher flying en-route phase of migration. The resulting reflectivity maps enable explorative analysis of factors influencing their regional and fine-scale distribution. We illustrate the method’s application by generating time-series of composites of up to 20 radars, achieving a nearly complete spatial coverage of a large part of Northwest Europe. These visualizations are highly useful in interpreting regional-scale migration patterns and provide detailed information on bird movements in the landscape and aerial environment. 

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3. Image muting of mixed precipitation to improve identification of regions of heavy snow in radar data

   https://doi.org/10.5194/amt-15-5515-2022  

   Tomkins, Laura M.; Yuter, Sandra E.; Miller, Matthew A.; Allen, Luke R. (January 2022, Atmospheric Measurement Techniques)

   Abstract. In winter storms, enhanced radar reflectivity is often associated with heavy snow. However, some higher reflectivities are the result of mixed precipitation including melting snow. The correlation coefficient (a dual-polarization radar variable) can identify regions of mixed precipitation, but this information is usually presented separately from reflectivity. Especially under time pressure, radar data users can mistake regions of mixed precipitation for heavy snow because of the high cognitive load associated with comparing data in two fields while simultaneously attempting to discount a portion of the high reflectivity values. We developed an image muting method for regional radar maps that visually de-emphasizes the high reflectivity values associated with mixed precipitation. These image muted depictions of winter storm precipitation structures are useful for analyzing regions of heavy snow and monitoring real-time weather conditions. 

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4. Rapid Sampling and Polarimetric Statistics of Lightning With a Phased Array Radar

   https://doi.org/10.1029/2024GL112193  

   Goede, Vitor; Schvartzman, David; Bodine, David; Chmielewski, Vanna_C; Yu, Tian‐You; Bruning, Eric; Tzeng, Min‐Duan; Stock, Michael (January 2025, Geophysical Research Letters)

   Abstract Previous studies of lightning detection by radar mostly consisted of observations with reflector‐antenna systems yielding slow volume scan times. Phased array radars offer much faster scan times that are likely to capture echoes from propagating lightning channels. Rapidly updated range‐height indicator scans were used to observe severe storms that occurred in central Oklahoma with the fully digital S‐band Horus PAR to examine echoes from lightning plasma. Numerous lightning echoes were observed during the sampling period in good spatial and temporal agreement with lightning mapping array detections of very high frequency radiation sources. Statistically, they result in increased horizontal reflectivity factor, deviations in radial velocity and spectrum width, highly variable differential reflectivity and differential phase, and decreases in correlation coefficient. Results presented also highlight the capability of phased array radars to better observe lightning compared to current radars, and aid in the study of storm electrification and lightning physics. 

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5. Comparing Reflectivity from Space-Based and Ground-Based Radars During Detection of Rainbands in Two Tropical Cyclones

   https://doi.org/10.3390/atmos16030307  

   Matyas, Corene J; Zick, Stephanie E; Wood, Kimberly M (March 2025, Atmosphere)

   With varying tangential winds and combinations of stratiform and convective clouds, tropical cyclones (TCs) can be difficult to accurately portray when mosaicking data from ground-based radars. This study utilizes the Dual-frequency Precipitation Radar (DPR) from the Global Precipitation Measurement Mission (GPM) satellite to evaluate reflectivity obtained using four sampling methods of Weather Surveillance Radar 1988-Doppler data, including ground radars (GRs) in the GPM ground validation network and three mosaics, specifically the Multi-Radar/Multi-Sensor System plus two we created by retaining the maximum value in each grid cell (MAX) and using a distance-weighted function (DW). We analyzed Hurricane Laura (2020), with a strong gradient in tangential winds, and Tropical Storm Isaias (2020), where more stratiform precipitation was present. Differences between DPR and GR reflectivity were larger compared to previous studies that did not focus on TCs. Retaining the maximum value produced higher values than other sampling methods, and these values were closest to DPR. However, some MAX values were too high when DPR time offsets were greater than 120 s. The MAX method produces a more consistent match to DPR than the other mosaics when reflectivity is <35 dBZ. However, even MAX values are 3–4 dBZ lower than DPR in higher-reflectivity regions where gradients are stronger and features change quickly. The DW and MRMS mosaics produced values that were similar to one another but lower than DPR and MAX values. 

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