An Examination of the Impact of Grid Spacing on WRF Simulations of Wintertime Precipitation in the Mid-Atlantic United States

A large set of deterministic and ensemble forecasts was produced to identify the optimal spacing for forecasting U.S. East Coast snowstorms. WRF forecasts were produced on cloud-allowing (~1-km grid spacing) and convection-allowing (3–4 km) grids, and compared against forecasts with parameterized convection (>~10 km). Performance diagrams were used to evaluate 19 deterministic forecasts from the winter of 2013–14. Ensemble forecasts of five disruptive snowstorms spanning the years 2015–18 were evaluated using various methods to evaluate probabilistic forecasts. While deterministic forecasts using cloud-allowing grids were not better than convection-allowing forecasts, both had lower bias and higher success ratios than forecasts with parameterized convection. All forecasts were underdispersive. Nevertheless, forecasts on the higher-resolution grids were more reliable than those with parameterized convection. Forecasts on the cloud-allowing grid were best able to discriminate areas that received heavy snow and those that did not, while the forecasts with parameterized convection were least able to do so. It is recommended to use convection-resolving and (if computationally possible) to use cloud-allowing forecast grids when predicting East Coast winter storms.

Evaluating U.S. East Coast Winter Storms in a Multimodel Ensemble Using EOF and Clustering Approaches

Empirical orthogonal function (EOF) and fuzzy clustering tools were applied to generate and validate scenarios in operational ensemble prediction systems (EPSs) for U.S. East Coast winter storms. The National Centers for Environmental Prediction (NCEP), European Centre for Medium-Range Weather Forecasts (ECMWF), and Canadian Meteorological Centre (CMC) EPSs were validated in their ability to capture the analysis scenarios for historical East Coast cyclone cases at lead times of 1–9 days. The ECMWF ensemble has the best performance for the medium- to extended-range forecasts. During this time frame, NCEP and CMC did not perform as well, but a combination of the two models helps reduce the missing rate and alleviates the underdispersion. All ensembles are underdispersed at all ranges, with combined ensembles being less underdispersed than the individual EPSs. The number of outside-of-envelope cases increases with lead time. For a majority of the cases beyond the short range, the verifying analysis does not lie within the ensemble mean group of the multimodel ensemble or within the same direction indicated by any of the individual model means, suggesting that all possible scenarios need to be taken into account. Using the EOF patterns to validate the cyclone properties, the NCEP model tends to show less intensity and displacement biases during 1–3-day lead time, while the ECMWF model has the smallest biases during 4–6 days. Nevertheless, the ECMWF forecast position tends to be biased toward the southwest of the other two models and the analysis.

Assessing the Ensemble Predictability of Precipitation Forecasts for the January 2015 and 2016 East Coast Winter Storms

The ensemble predictability of the January 2015 and 2016 East Coast winter storms is assessed, with model precipitation forecasts verified against observational datasets. Skill scores and reliability diagrams indicate that the large ensemble spread produced by operational forecasts was warranted given the actual forecast errors imposed by practical predictability limits. For the 2015 storm, uncertainties along the western edge’s sharp precipitation gradient are linked to position errors of the coastal low, which are traced to the positioning of the preceding 500-hPa wave pattern using the ensemble sensitivity technique. Predictability horizon diagrams indicate the forecast lead time in terms of initial detection, emergence of a signal, and convergence of solutions for an event. For the 2016 storm, the synoptic setup was detected at least 6 days in advance by global ensembles, whereas the predictability of mesoscale features is limited to hours. Convection-permitting WRF ensemble forecasts downscaled from the GEFS resolve mesoscale snowbands and demonstrate sensitivity to synoptic and mesoscale ensemble perturbations, as evidenced by changes in location and timing. Several perturbation techniques are compared, with stochastic techniques [the stochastic kinetic energy backscatter scheme (SKEBS) and stochastically perturbed parameterization tendency (SPPT)] and multiphysics configurations improving performance of both the ensemble mean and spread over the baseline initial conditions/boundary conditions (IC/BC) perturbation run. This study demonstrates the importance of ensembles and convective-allowing models for forecasting and decision support for east coast winter storms.

Surface Microphysical Observations within East Coast Winter Storms on Long Island, New York

Surface observations of ice habit and degree of riming were measured for 12 cyclone events over 3 winter seasons at Stony Brook, New York, on the northeast coast of the United States. A total of 205.6 cm of snow accumulated during these storms, with an average degree of riming of 1.25 (out of 5) and snow-to-liquid ratio ranging from 3:1 to 17:1. There were consistent spatial patterns of habit and riming intensity relative to the cyclone structure. Cold-type habits (side planes and bullets) commonly occurred within the outer comma head to the north and northeast of the cyclone center. In the middle of the comma head, moderately rimed dendrites, plates, and needles were observed. Close to the cyclone center, heavy riming was observed with needles and graupel. The western quadrant of the comma head had primarily plates and dendrites with little to no riming. Periods of light riming and high snow–liquid ratios (≥13:1) are dominated by cold-type habits, dendrites, and plates and have similar vertical motion and synoptic characteristics inferred from 13-km Rapid Update Cycle analyses. Maximum vertical motion occurred in a region of favored ice growth and less supercooled water (from −15° to −25°C). During heavy riming periods, needles and graupel are dominant and the vertical motion maximum occurs at temperatures from 0° to −5°C. Vertically pointing Micro Rain Radar indicates stronger vertical motions and turbulence for heavy riming as opposed to light rimming periods. Periods with low snow-to-liquid ratio (≤7:1) were observed to occur either as heavy rimed particles or as light riming of compact habits such as sideplanes, bullets, and needles.

Observed Microphysical Evolution for Two East Coast Winter Storms and the Associated Snow Bands

This paper presents the observed microphysical evolution of two coastal extratropical cyclones (19–20 December 2009 and 12 January 2011) and the associated passage of heavy snowbands in the cyclone comma head. The observations were made approximately 93 km east of New York City at Stony Brook, New York. Surface microphysical measurements of snow habit and degree of riming were taken every 15–30 min using a stereo microscope and camera, and snow depth and snow density were also recorded. A vertically pointing Ku-band radar observed the vertical evolution of reflectivity and Doppler vertical velocities. There were rapid variations in the snow habits and densities related to the changes in vertical motion and depth of saturation. At any one time, a mixture of different ice habits was observed. Certain ice habits were dominant at the surface when the maximum vertical motion aloft occurred at their favored temperature for depositional growth. Convective seeder cells above 4 km MSL resulted in relatively cold (less than −15°C) ice crystal habits (side planes, bullets, and dendrites). Needlelike crystals were prevalent during the preband period when the maximum vertical motion was in the layer from −5° to −10°C. Moderately rimed dendritic crystals were observed at snowband maturity associated with the strongest frontogenetical ascent on the warm (east) side of the bands. Riming rapidly decreased and more platelike crystals became more numerous as the strongest ascent moved east of Stony Brook. Snow-to-liquid density ratios ranged from 8:1 to 13:1 in both events, except during the period of graupel, when the ratio was as low as 4:1.

Aircraft Icing Measurements in East Coast Winter Storms

Analysis of the aircraft icing environments of East Coast winter storms have been made from 3 1 flights duringthe second Canadian Atlantic Storms Program. Microphysical parameters have been summarized and are compared to common icing intensity envelopes and to other icing datasets. Cloud regions with supercooled liquid water had an average horizontal extent of 4.3 km, with average droplet concentrations of 130 μ, liquid water contents of 0.13 g m-3, and droplet median volume diameters of 18 pm. In general, the icing intensity observed was classified as light, although moderate to severe icing was observed in several common synoptic situationsand several cases are discussed. Freezing drizzle was observed on four flights, and represented the most severeicing environment encountered.