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Abstract The potential of millimeter-wavelength radar-based ice water content (IWC) estimation is demonstrated using a Ka-band Scanning Polarimetric Radar (KASPR) for the U.S. northeast coast winter storms. Two IWC relations for Ka-band polarimetric radar measurements are proposed: one that uses a combination of the radar reflectivityZand the estimated total number concentration of snow particlesN_tand the other based on the joint use ofZ, specific differential phaseK_DP, and the degree of rimingf_rim. A key element of the algorithms is to obtain the “Rayleigh-equivalent” value ofZmeasured at the Ka band, i.e., the correspondingZat a longer radar wavelength for which Rayleigh scattering takes place. This is achieved via polarimetric retrieval of the mean volume diameterD_mand incorporating the relationship between the dual-wavelength ratio DWR_S/KaandD_m. Those techniques allow for retrievals from single millimeter-wavelength radar measurements and do not necessarily require the dual-wavelength ratio (DWR) measurements, if the DWR–D_mrelation and Rayleigh assumption for Ka-bandK_DPare valid. Comparison between the quasivertical profile product obtained from KASPR and the columnar vertical profile product generated from the nearby WSR-88D S-band radar measurements demonstrates that the DWR_S/Kacan be estimated from the two close radars without the need for collocated radar beams and synchronized antenna scanning and can be used for determining the Rayleigh-equivalent value ofZ. The performance of the suggested techniques is evaluated for seven winter storms using surface disdrometer and snow accumulation measurements. Significance StatementIce water content (IWC) estimation using millimeter-wavelength radar measurements has been challenging for decades, because of the complexity of snow particle properties and size, which can cause complex scattering at the shorter radar wavelengths. The suggested polarimetric techniques overcome this difficulty via utilizing specific differential phaseK_DPwhich is higher at millimeter wavelengths than at centimeter wavelengths. This study proposes new IWC relationships for Ka-band polarimetric radar measurements and evaluates them using a Ka-band Scanning Polarimetric Radar (KASPR) and a nearby NEXRAD (S-band) polarimetric radar for the U.S. northeast coast winter storms. The proposed techniques can be applied to other millimeter-wavelength radars and shed light on the millimeter-wavelength polarimetric radar IWC estimation. 

Abstract The Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) field project deployed two aircraft and ground-based assets in the vicinity of Houston, TX, between 27 May 2022 and 2 July 2022, examining how meteorological conditions, dynamics, and aerosols control the initiation, early growth stage, and evolution of coastal convective clouds. To ensure that airborne and ground-based assets were deployed appropriately, a Forecasting and Nowcasting Team was formed. Daily forecasts guided real-time decision making by assessing synoptic weather conditions, environmental aerosol, and a variety of atmospheric modeling data to assign a probability for meeting specific ESCAPE campaign objectives. During the research flights, a small team of forecasters provided “nowcasting” support by analyzing radar, satellite, and new model data in real time. The nowcasting team proved invaluable to the campaign operation, as sometimes changing environmental conditions affected, for example, the timing of convective initiation. In addition to the success of the forecasting and nowcasting teams, the ESCAPE campaign offered a unique “testbed” opportunity where in-person and virtual support both contributed to campaign objectives. The forecasting and nowcasting teams were each composed of new and experienced forecasters alike, where new forecasters were given invaluable experience that would otherwise be difficult to attain. Both teams received training on forecast models, map analysis, HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) modeling and thermodynamic sounding analysis before the beginning of the campaign. In this article, the ESCAPE forecasting and nowcasting teams reflects on these experiences, providing potentially useful advice for future field campaigns requiring forecasting and nowcasting support in a hybrid virtual/in-person framework. 

Abstract. A large convection–cloud chamber has the potential to produce drizzle-sized droplets, thus offering a new opportunity to investigate aerosol–cloud–drizzle interactions at a fundamental level under controlled environmental conditions. One key measurement requirement is the development of methods to detect the low-concentration drizzle drops in such a large cloud chamber. In particular, remote sensing methods may overcome some limitations of in situ methods. Here, the potential of an ultrahigh-resolution radar to detect the radar return signal of a small drizzle droplet against the cloud droplet background signal is investigated. It is found that using a small sampling volume is critical to drizzle detection in a cloud chamber to allow a drizzle drop in the radar sampling volume to dominate over the background cloud droplet signal. For instance, a radar volume of 1 cubic centimeter (cm3) would enable the detection of drizzle embryos with diameter larger than 40 µm. However, the probability of drizzle sampling also decreases as the sample volume reduces, leading to a longer observation time. Thus, the selection of radar volume should consider both the signal power and the drizzle occurrence probability. Finally, observations from the Pi Convection–Cloud Chamber are used to demonstrate the single-drizzle-particle detection concept using small radar volume. The results presented in this study also suggest new applications of ultrahigh-resolution cloud radar for atmospheric sensing. 

Abstract Clouds, crucial for understanding climate, begin with droplet formation from aerosols, but observations of this fleeting activation step are lacking in the atmosphere. Here we use a time-gated time-correlated single-photon counting lidar to observe cloud base structures at decimeter scales. Results show that the air–cloud interface is not a perfect boundary but rather a transition zone where the transformation of aerosol particles into cloud droplets occurs. The observed distributions of first-arriving photons within the transition zone reflect vertical development of a cloud, including droplet activation and condensational growth. Further, the highly resolved vertical profile of backscattered photons above the cloud base enables remote estimation of droplet concentration, an elusive but critical property to understanding aerosol–cloud interactions. Our results show the feasibility of remotely monitoring cloud properties at submeter scales, thus providing much-needed insights into the impacts of atmospheric pollution on clouds and aerosol-cloud interactions that influence climate. 

Abstract National Aeronautics and Space Administration's Investigations of Convective Updrafts (INCUS) mission aims to document convective mass flux through changes in the radar reflectivity (ΔZ) in convective cores captured by a constellation of three Ka‐band radars sampling the same convective cells over intervals of 30, 90, and 120 s. Here, high spatiotemporal resolution observations of convective cores from surface‐based radars that use agile sampling techniques are used to evaluate aspects of the INCUS measurement approach using real observations. Analysis of several convective cells confirms that large coherent ΔZstructure with measurable signal (>5 dB) can occur in less than 30 s and are correlated with underlying convective motions. The analysis indicates that the INCUS mission radar footprint and along track sampling are adequate to capture most of the desirable ΔZsignals. This unique demonstration of reflectivity time‐lapse provides the framework for estimating convective mass flux independent from Doppler techniques with future radar observations. 

Abstract The discovery of a polarimetric radar signature indicative of hydrometeor refreezing has shown promise in its utility to identify periods of ice pellet production. Uniquely characterized well below the melting layer by locally enhanced values of differential reflectivity ( Z DR ) within a layer of decreasing radar reflectivity factor at horizontal polarization ( Z H ), the signature has been documented in cases where hydrometeors were completely melted prior to refreezing. However, polarimetric radar features associated with the refreezing of partially melted hydrometeors have not been examined as rigorously in either an observational or microphysical modeling framework. Here, polarimetric radar data—including vertically pointing Doppler spectral data from the Ka-band Scanning Polarimetric Radar (KASPR)—are analyzed for an ice pellets and rain mixture event where the ice pellets formed via the refreezing of partially melted hydrometeors. Observations show that no such distinct localized Z DR enhancement is present, and that values instead decrease directly beneath enhanced values associated with melting. A simplified, explicit bin microphysical model is then developed to simulate the refreezing of partially melted hydrometeors, and coupled to a polarimetric radar forward operator to examine the impacts of such refreezing on simulated radar variables. Simulated vertical profiles of polarimetric radar variables and Doppler spectra have similar features to observations, and confirm that a Z DR enhancement is not produced. This suggests the possibility of two distinct polarimetric features of hydrometeor refreezing: ones associated with refreezing of completely melted hydrometeors, and those associated with refreezing of partially melted hydrometeors. Significance Statement There exist two pathways for the formation of ice pellets: refreezing of fully melted hydrometeors, and refreezing of partially melted hydrometeors. A polarimetric radar signature indicative of fully melted hydrometeor refreezing has been extensively documented in the past, yet no study has documented the refreezing of partially melted hydrometeors. Here, observations and idealized modeling simulations are presented to show different polarimetric radar features associated with partially melted hydrometeor refreezing. The distinction in polarimetric features may be beneficial to identifying layers of supercooled liquid drops within transitional winter storms. 

One of the challenges of analyzing convective cell properties is quick evolution of the individual convective cells.  While the operational radar data provide great a data set to analyze the evolution of radar observables of convective precipitation clouds statistically, previous studies also suggested that, because of the quick evolution of cell life cycle, conventional radar volume scan strategies taking ~5-7 minutes might not capture the detailed evolution. The TRACER campaign deployed CSAPR2, which performed frequent update of RHI and sector PPI scans to track convective cells every < 2 minutes guided by a new cell-tracking framework, Multisensor Agile Adaptive Sampling (MAAS; Kollias et al. 2020). This allows for capturing fast-evolving radar observables. The submitted data files are CSAPR2 data in CfRadial format collected during the TRACER field campaign from June to September 2020. The data files include processed radar variables including: noise-masked reflectivity and differential reflectivity corrected for rain attenuation and systematic biases, noise-masked dealiased radial velocity, specific differential phase, locations of target cells (latitude, longitude, radar range), and radar-echo classification.   

Abstract Quasi-linear convective systems (QLCSs) are responsible for approximately a quarter of all tornado events in the U.S., but no field campaigns have focused specifically on collecting data to understand QLCS tornadogenesis. The Propagation, Evolution, and Rotation in Linear System (PERiLS) project was the first observational study of tornadoes associated with QLCSs ever undertaken. Participants were drawn from more than 10 universities, laboratories, and institutes, with over 100 students participating in field activities. The PERiLS field phases spanned two years, late winters and early springs of 2022 and 2023, to increase the probability of intercepting significant tornadic QLCS events in a range of large-scale and local environments. The field phases of PERiLS collected data in nine tornadic and nontornadic QLCSs with unprecedented detail and diversity of measurements. The design and execution of the PERiLS field phase and preliminary data and ongoing analyses are shown.