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The analysis and forecast of precipitation characteristics is a key task for national meteorological services for providing high-quality weather forecasts and warnings. Beside the precipitation amount, the precipitation type is essential to describe and evaluate the recent, ongoing, and future weather situations. This paper introduces a new surface-based hybrid hydrometeor classification algorithm. The presented method combines polarimetric radar observations at radar beam height from the C-band dual-polarization weather radar network of the German Weather Service [Deutscher Wetterdienst (DWD)] with corrected thermodynamical profiles of numerical weather prediction (NWP) model output and extrapolates the hydrometeor classes at radar beam height to a height of 2 m above ground level (AGL). The implemented technique parameterizes the microphysical processes in the lower troposphere based on the appropriate thermodynamical profile that the hydrometeors have to pass along their way from the radar beam height to the surface. Due to errors in NWP output, the NWP vertical profiles of temperature and humidity are adjusted by using several types of surface stations with high spatial and temporal resolution. Verification results show considerable improvements in the hydrometeor classification near the ground compared to the radar sweep height. After an additional positive in-house evaluation, the presented method is integrated into DWD's operational environment. The topic of this paper is to describe the processing steps for the computation of the near-surface precipitation type. In addition, example cases and a verification study complement the explanations. Significance Statement: For a national weather service and its customers, the separation of precipitation types into solid and liquid is a key issue for improving weather forecasts and warnings. We combined measurements from weather radars and weather stations together with output of numerical weather prediction models and developed a method of estimating the precipitation type at a height of 2 m. Previous studies of the hydrometeor classification field concentrate on warm season weather conditions using "radar observations only" or apply a hybrid combination of radar observations with model information. The uniqueness of our work is the additional introduction of surface observations with high temporal and spatial resolution for a better estimation of the thermodynamical profiles to improve the "all season alignment." [ABSTRACT FROM AUTHOR]

Doppler spectra measured by vertically pointing radars are inherently linked to raindrop size distributions (DSDs). But accurate estimation of DSDs remains challenging because raindrop spectra are broadened by atmospheric turbulence and shifted by vertical air motions. This paper presents a novel method to estimate vertical air motions in which there is no need to assume a model for DSD at each range gate. The theory of the new method is that the spectral difference between the adjacent range gates is contributed by vertical air motions and the variability of DSDs. The contribution of the change of DSDs is estimated by looking up the prepared tables [lookup tables (LUTs)] of raindrop velocity difference and shape function difference. Then the vertical air motions can be estimated by minimizing the cost function of the two spectra between the adjacent range gates. The retrieval algorithm is applied to three cases including a stratiform case and two convective cases observed by a C-band vertically pointing radar in Longmen, Guangdong Province, China, in June 2016. Before that, the spectrum broadening effect is removed by the traditional deconvolution method with a wind profiler. The vertical profiles of precipitation parameters are also retrieved to investigate the microphysical process. The precipitation parameters retrieved near the surface are compared with the ground data collected by a two-dimensional video disdrometer (2DVD), and the results show good agreement. Significance Statement: Estimating vertical air motions and raindrop size distributions are of great help to improve precipitation forecasts and weather modification. This study developed a new method to estimate the vertical air motions using Doppler spectra measured by a vertically pointing radar. The advantage of the new method is that there is no need to assume models for raindrop size distributions. We applied the new method to a stratiform case and two convective cases, and the vertical profiles of precipitation parameters are retrieved. The results show that both the dynamic and microphysical processes in convective cases have larger variability than those in the stratiform case. In the future, the characteristics of more types of precipitation clouds will be investigated. [ABSTRACT FROM AUTHOR]

Since the dual-polarization upgrade of the Weather Surveillance Radar-1988 Doppler (WSR-88D), the polarimetric variables have become a fundamental tool for better interpretation and forecasting of hazardous weather events. Thus, improving their quality has been an important long-standing effort. In this paper, we introduce the hybrid-scan estimators (HSE), which use the available data in split cuts of operational volume coverage patterns (VCP) to provide better estimates of differential reflectivity, differential phase, and correlation coefficient. The HSE are designed to choose between the data provided by either one of the two scans in split cuts based on their expected statistical performance, resulting in the same or better data quality compared to the conventional estimators. The performance improvement realized with the HSE is characterized with simulations and illustrated with data from WSR-88D. While relatively simple, an operational implementation of the HSE could bring improvements to forecasters' data interpretation and algorithm performance, both of which rely on dual-polarization radar data. [ABSTRACT FROM AUTHOR]

This paper investigates the ability of the Weather Research and Forecasting (WRF) Model in simulating multiple small-scale precipitation bands (multibands) within the extratropical cyclone comma head using four winter storm cases from 2014 to 2017. Using the model output, some physical processes are explored to investigate band prediction. A 40-member WRF ensemble was constructed down to 2-km grid spacing over the Northeast United States using different physics, stochastic physics perturbations, different initial/boundary conditions from the first five perturbed members of the Global Forecast System (GFS) Ensemble Reforecast (GEFSR), and a stochastic kinetic energy backscatter scheme (SKEBS). It was found that 2-km grid spacing is adequate to resolve most snowbands. A feature-based verification is applied to hourly WRF reflectivity fields from each ensemble member and the WSR-88D radar reflectivity at 2-km height above sea level. The Method for Object-Based Diagnostic Evaluation (MODE) tool is used for identifying multibands, which are defined as two or more bands that are 5–20 km in width and that also exhibit a >2:1 aspect ratio. The WRF underpredicts the number of multibands and has a slight eastward position bias. There is no significant difference in frontogenetical forcing, vertical stability, moisture, and vertical shear between the banded versus nonbanded members. Underpredicted band members tend to have slightly stronger frontogenesis than observed, which may be consolidating the bands, but overall there is no clear linkage in ambient condition errors and band errors, thus leaving the source for the band underprediction motivation for future work. [ABSTRACT FROM AUTHOR]

Information about the characteristics of ice particles in clouds is necessary for improving our understanding of the states, processes, and subsequent modeling of clouds and precipitation for numerical weather prediction and climate analysis. Two NASA passive microwave radiometers, the satellite-borne Global Precipitation Measurement (GPM) Microwave Imager (GMI) and the aircraft-borne Conical Scanning Millimeter-Wave Imaging Radiometer (CoSMIR), measure vertically and horizontally polarized microwaves emitted by clouds (including precipitating particles) and Earth's surface below. In this paper, GMI (or CoSMIR) data are analyzed with CloudSat (or aircraft-borne radar) data to find polarized difference (PD) signals not affected by the surface, thereby obtaining the information on ice particles. Statistical analysis of 4 years of GMI and CloudSat data, for the first time, reveals that optically thick clouds contribute positively to GMI PD at 166 GHz over all the latitudes and their positive magnitude of 166-GHz GMI PD varies little with latitude. This result suggests that horizontally oriented ice crystals in thick clouds are common from the tropics to high latitudes, which contrasts the result of Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) that horizontally oriented ice crystals are rare in optically thin ice clouds. [ABSTRACT FROM AUTHOR]

The stability and accuracy of weather radar reflectivity calibration are imperative for quantitative applications, such as rainfall estimation, severe weather monitoring and nowcasting, and assimilation in numerical weather prediction models. Various radar calibration and monitoring techniques have been developed, but only recently have integrated approaches been proposed, that is, using different calibration techniques in combination. In this paper the following three techniques are used: 1) ground clutter monitoring, 2) comparisons with spaceborne radars, and 3) the self-consistency of polarimetric variables. These techniques are applied to a C-band polarimetric radar (CPOL) located in the Australian tropics since 1998. The ground clutter monitoring technique is applied to each radar volumetric scan and provides a means to reliably detect changes in calibration, relative to a baseline. It is remarkably stable to within a standard deviation of 0.1 dB. To obtain an absolute calibration value, CPOL observations are compared to spaceborne radars on board TRMM and GPM using a volume-matching technique. Using an iterative procedure and stable calibration periods identified by the ground echoes technique, we improve the accuracy of this technique to about 1 dB. Finally, we review the self-consistency technique and constrain its assumptions using results from the hybrid TRMM–GPM and ground echo technique. Small changes in the self-consistency parameterization can lead to 5 dB of variation in the reflectivity calibration. We find that the drop-shape model of Brandes et al. with a standard deviation of the canting angle of 12° best matches our dataset. [ABSTRACT FROM AUTHOR]

Accurate and automated dealiasing of radar data is important for data interpretation and downstream applications such as numerical weather prediction (NWP) models. In this paper an improved radial velocity dealiasing scheme is presented and evaluated using observations from several S-band radars under the severe weather conditions of typhoons and hurricanes. This scheme, named Automated Dealiasing for Typhoon and Hurricane (ADTH), is a further development of the China New Generation Doppler Weather Radar (CINRAD) improved dealiasing algorithm (CIDA). The upgraded algorithm ADTH includes three modules designed to select the first radial from which the dealiasing process starts, to conduct a two-way multipass dealiasing, and to perform an error check for a final local dealiasing. The dealiasing algorithm is applied to two typhoon hurricane cases and four typhoon cases observed with radars from CINRAD, NEXRAD of the United States, and the Taiwan radar network for a continuous period of 12 h for each of the selected cases. The results show that ADTH outperforms CIDA for all of the test cases. [ABSTRACT FROM AUTHOR]

Thirty National Weather Service forecasters worked with 1-, 2-, and 5-min phased-array radar (PAR) volumetric updates for a variety of weather events during the 2015 Phased Array Radar Innovative Sensing Experiment. Exposure to each of these temporal resolutions during simulated warning operations meant that these forecasters could provide valuable feedback on how rapidly updating PAR data impacted their warning decision processes. To capture this feedback, forecasters participated in one of six focus groups. A series of open-ended questions guided focus group discussions, and forecasters were encouraged to share their experiences and opinions from the experiment. Transcriptions of focus group discussions were thematically analyzed, and themes belonging to one of two groups were identified: 1) forecasters' use of rapidly updating PAR data during the experiment and 2) how forecasters envision rapidly updating PAR data being integrated into warning operations. Findings from this thematic analysis are presented in this paper, and to illustrate these findings from the forecasters' perspectives, dialogue that captures the essence of their discussions is shared. The identified themes provide motivation to integrate rapidly updating radar data into warning operations and highlight important factors that need to be addressed for the successful integration of these data. [ABSTRACT FROM AUTHOR]

Polarimetric radar signatures have been related to the typical evolution of supercell storms, including through tornado life cycles. Now that polarimetric radar observations are available for a large sample of supercell storms, time series of new radar metrics can be derived. These metrics can be compared with phases of known tornado life cycles in an effort to develop new methods of anticipating tornadoes and to increase understanding of storm-scale structural and microphysical changes through supercell and tornado life cycles. In this paper, radar metrics including measures of differential reflectivity ZDR columns, ZDR arcs, polarimetrically inferred hailfall regions, and mean value of copolar correlation coefficient ρhv in the echo appendage are compared to the tornado life cycle and to storm-maximum tornado intensity in a sample of 35 tornadic supercells. It is shown that these radar metrics may change repeatedly and thus can be used to distinguish tornadic and nontornadic periods in single supercell storms, tornadogenesis from tornado demise times, and modes of storm evolution relative to tornadoes (e.g., if a storm produces one tornado or several). The polarimetric radar metrics are nearly as predictive of tornado intensity as commonly used measures of environmental variability for this sample. [ABSTRACT FROM AUTHOR]

In Doppler weather radars, the presence of unfolding errors or outliers is a well-known quality issue for radial velocity fields estimated using the dual-pulse repetition frequency (PRF) technique. Postprocessing methods have been developed to correct dual-PRF outliers, but these need prior application of a dealiasing algorithm for an adequate correction. This paper presents an alternative procedure based on circular statistics that corrects dual-PRF errors in the presence of extended Nyquist aliasing. The correction potential of the proposed method is quantitatively tested by means of velocity field simulations and is exemplified in the application to real cases, including severe storm events. The comparison with two other existing correction methods indicates an improved performance in the correction of clustered outliers. The technique proposed is well suited for real-time applications requiring high-quality Doppler radar velocity fields, such as wind shear and mesocyclone detection algorithms, or assimilation in numerical weather prediction models. [ABSTRACT FROM AUTHOR]

This paper reports a high-speed volumetric observation of a wet microburst event using X-band phased array weather radar (PAWR) in Japan. On 10 September 2014, PAWR observed the three-dimensional structure of a convection cell, which had a vertical extent of 5-6 km and a horizontal dimension of 2-10 km, moving toward the east-northeast. At 2310 Japan standard time (JST), a precipitation core with a radar reflectivity of >40 dB Z appeared at 3-5 km above ground level. The core then increased in size and intensity and rapidly descended to the ground. During this time, a reflectivity notch associated with midlevel inflow was initially formed near the top of the precipitation core and, subsequently, at lower altitudes. A strong low-level outflow with a radial divergence of >4 × 10−3 s−1 appeared just below the notch at around 2321 JST. The outflow lasted for approximately 13 min and eventually disappeared after 2333 JST along with dissipation of the causative storm cell. These results suggest that, in addition to hydrometeor loading, evaporative cooling due to the entrainment of midlevel relatively dry air played an additional role in driving a strong downdraft. The preceding signatures including descending precipitation core, reflectivity notch, and midlevel convergence observed by PAWR are useful precursors to forecast the occurrence of low-level wind shear 5-10 min ahead, which is important for safe air traffic operation. [ABSTRACT FROM AUTHOR]

Natural small-scale microphysical and dynamical mechanisms are identified in a winter orographic snowstorm over the Sierra Madre Range of Wyoming during an intensive observational period (IOP) from the AgI Seeding Cloud Impact Investigation (ASCII; January-March 2012). A suite of high-resolution radars, including a ground-based scanning X-band dual-polarization Doppler on Wheels radar, vertically pointing Ka-band Micro Rain Radar (MRR), and airborne W-band Wyoming Cloud Radar (WCR), and additional in situ and remote sensing instruments are used in the analysis. The analysis focuses on a deep postfrontal period on 16 January 2012 (IOP2) when clouds extended throughout the troposphere and cloud liquid water was absent following the passage of a baroclinic front. A turbulent shear layer was observed in this postfrontal environment that was created by a midlevel cross-barrier jet riding over a decoupled Arctic air mass that extended above mountaintop. MRR and WCR observations indicate additional regions of turbulence aloft that favor rapid particle growth at upper levels of the cloud. Plunging flow in the lee of the Sierra Madre was also observed during this case, which caused sublimation of snow up to 20 km downwind. The multi-instrument analysis in this paper suggests that 1) shear-induced turbulent overturning cells do exist over cold continental mountain ranges like the Sierra Madre, 2) the presence of cross-barrier jets favors these turbulent shear zones, 3) this turbulence is a key mechanism in enhancing snow growth, and 4) snow growth enhanced by turbulence primarily occurs through deposition and aggregation in these cold (<−15°C) postfrontal continental environments. [ABSTRACT FROM AUTHOR]

Storm-scale and mesocyclone-scale processes occurring contemporaneously with a tornado in the Goshen County, Wyoming, supercell observed on 5 June 2009 during the second Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2) are examined using ensemble analyses produced by assimilating mobile radar and in situ observations into a high-resolution convection-resolving model. This paper focuses on understanding the evolution of the vertical structure of the storm, the outflow buoyancy, and processes affecting the vertical vorticity and circulation within the mesocyclone that correspond to changes in observed tornado intensity. Tornadogenesis occurs when the low-level mesocyclone is least negatively buoyant relative to the environment, possesses its largest circulation, and is collocated with the largest azimuthally averaged convergence during the analysis period. The average buoyancy, circulation, and convergence within the near-surface mesocyclone (on spatial scales resolved by the model) all decrease as the tornado intensifies and matures. The tornado and its parent low-level mesocyclone both dissipate surrounded by a weakening rear-flank downdraft. The decreasing buoyancy of parcels within the low-level mesocyclone may partly be responsible for the weakening of the updraft surrounding the tornado and decoupling of the mid- and low-level circulation. Although the supply of horizontal vorticity generated in the forward flank of the storm increases throughout the life cycle of the tornado, it is presumably less easily tilted and stretched on the mesocyclone-scale during tornado maturity owing to the disruption of the low-level updraft/downdraft structure. Changes in radar-measured tornado intensity lag those of ensemble Kalman filter (EnKF) mesocyclone vorticity and circulation. [ABSTRACT FROM AUTHOR]

The 2013 Phased Array Radar Innovative Sensing Experiment (PARISE) investigated the impacts of higher-temporal-resolution radar data on National Weather Service forecasters' warning decision processes during severe hail and wind events. In total, 12 forecasters participated in the 2013 PARISE over a 6-week period during the summer of 2013. Participants were assigned to either a control [5-min phased-array radar (PAR) updates] or experimental (1-min PAR updates) group, and worked two cases in simulated real time. This paper focuses on the qualitative retrospective reports of participants' warning decision processes that were collected using the recent case walk-through method. Timelines of participants' warning decision process were created for both cases, which were then thematically coded according to a situational awareness framework. Coded themes included perception, comprehension, and projection. It was found that the experimental group perceived significantly more information during both cases than the control group (case 1 p = 0.045 and case 2 p = 0.041), which may have improved the quality of their comprehensions and projections. Analysis of timelines reveals that 1-min PAR updates were important to the experimental group's more timely and accurate warning decisions. Not only did the 1-min PAR updates enable experimental participants to perceive precursor signatures earlier than control participants, but through monitoring trends in radar data, the experimental group was able to better detect storm motion, more accurately identify expected weather threats from severe thunderstorms, more easily observe strengthening and diminishing trends in storms, and make more correct tornado-related warning decisions. [ABSTRACT FROM AUTHOR]

Dual-polarization Doppler radar has proven useful for the estimation of hydrometeor content and the classification of hydrometeor type. Recent studies have leveraged dual-polarization-specific information to produce improved assimilated cloud and precipitation fields from the warm rain (above freezing) portion of deep convective storms. While the strengths of dual-polarization radar observations have been conclusively shown for rain and hail hydrometeors, it is less clear how much information is provided in mixed-phase and ice-only regions. In this paper, a Markov chain Monte Carlo (MCMC) algorithm is used to examine the information content of dual-polarization-specific variables in the ice-phase region of a convective storm. Results are used to quantify how much information is added by specific differential phase and radar correlation coefficient, as well as how this information is degraded when the assumed particle size distribution and particle density are allowed to vary. It is found that dual-polarization-specific observations ( Kdp and ρhv) provide significant information on rimed ice content, and moderate information on pristine ice, especially where snow mass is more than 10% of the total volume hydrometeor mass. There is a significant reduction in information content for rain and a near-complete loss of information for graupel-hail and snow when the particle size distribution and ice particle densities are not well known, and there are systematic changes in radar information gain and loss with changes in hydrometeor mass. The results highlight the need for a thorough exploration of forward model sensitivities prior to performing radar data assimilation. [ABSTRACT FROM AUTHOR]

This paper documents features that led to major forecast errors on the 12-24-h time scale in the nature and location of severe weather in the southern plains on 30 May 2012. Evidence is presented that the forecast errors were the result of 1) dry air that originated in a region of dissipating, elevated convective storms, and which was advected in a narrow tongue into western Oklahoma, inhibiting convective initiation; 2) the development of a cyclone along the dryline in western Texas, to the east of which several supercells formed; 3) the upscale development of the supercells into a mesoscale convective system (MCS) at nightfall; and 4) the dissipation of an MCS that had formed along a cold front in southwestern Kansas and was propagating into northwestern Oklahoma, as it encountered dry, subsiding air underneath the stratiform precipitation region of the rear portion of the MCS farther south. There was a meridionally oriented swath of high winds in clear air, in between the two MCSs. This swath of high winds may have been associated with a bore triggered at night by the MCSs approaching from the north, as the MCS collapsed, producing a gust front that propagated through stable, low-level air. This case study illustrates how the predictability of severe weather in a region can be extremely sensitive to the details of where nearby convective storms form and how they evolve. It also highlights the likely importance of the accurate representation of cloud microphysics and dynamics in numerical forecast models on predictability. [ABSTRACT FROM AUTHOR]

Although existing algorithms for storm tracking have been designed to operate in real time, they are also commonly used to do postevent data analysis and research. Real-time algorithms cannot use information on the subsequent positions of a storm because it is not available at the time that associations between frames are made, but postevent analysis is not similarly constrained. Therefore, it should be possible to obtain better tracks for postevent analysis than those that a real-time algorithm is capable of producing. In this paper, a statistical procedure for determining storm tracks from a set of identified storm cells over time is described. It is found that this procedure results in fewer, longer-lived tracks at the potential cost of a small increase in positional error. [ABSTRACT FROM AUTHOR]