Since the inception of the Cooperative Program for Operational Meteorological Education and Training (COMET) Outreach Program in 1990, over 250 collaborative projects have been funded nationwide, involving approximately 90 National Weather Service (NWS) offices and over 70 different universities. However, until now there have not been any attempts to objectively assess the impact of these collaborative projects on NWS warning performance.

A study was conducted to examine the impacts of COMET Cooperative and Partners collaborative research projects on NWS performance metrics for tornado, severe thunderstorm, flash flood, and winter storm warnings. The study evaluated relevant collaborative projects within the Eastern Region of the NWS completed between 1995 and 2001. In addition, the verification trends at the NWS Weather Forecast Office (WFO) in Raleigh, North Carolina, were examined to evaluate the influence of long-term collaborative activities on performance. WFO Raleigh has been continuously involved in collaborative projects with North Carolina State University since the 1980s, with the first COMET-funded project commencing in January 1991. There are many factors that influence warning program verification scores on the long term (e.g., technology infusion, implementation of applied research results, etc.) and the short term (e.g., weather “regime” impacts on event types and frequencies, office staffing issues and experience levels, etc.). The study was designed to try to isolate, to the extent possible, the impacts of the collaborative projects from these other factors.

The results indicate that warning program verification scores for offices involved in COMET collaborative research activities appear to improve at a greater rate than the overall performance of all NWS offices within the Eastern Region. The greatest impact was noted for warning lead times. Probabilities of detection (POD) also showed increased rates of improvement.

Abstract

WSR-88D depictions of two mountain wave–induced precipitation shadows observed near the Wyoming Valley of northeast Pennsylvania are presented. These mountain waves developed in similar synoptic environments that featured a strong south to southeast low-level jet, a stable layer situated near mountaintop level, and cross-barrier flow that decreased with height. One event was associated with a well-defined, singular precipitation shadow, while the second event displayed multiple precipitation shadows. Subtle differences in the vertical distribution of temperature and wind shear between the two cases appeared to be instrumental in defining what type of structure the mountain wave and their associated precipitation shadows displayed. This is supported by calculations of Froude number, Brunt–Väisälä frequency, Scorer parameter, and horizontal wavelength for the two events.

These mountain waves appear to have a significant effect on the local precipitation distribution in and near the heavily populated Wyoming Valley, with amounts reduced within and up to 15 km downstream of the valley. These effects are evident in the radar-estimated storm total precipitation products for both cases, and implied by rain gauge data for one of the events. Precipitation drift appears to play a role in the actual surface location of these precipitation minima with respect to the radar-indicated position, in cases of strong low-level flow.

Abstract

This article is the final installment of a four-part series that examines the challenge of forecasting winter weather throughout the eastern United States. This paper examines the problems and challenges of forecasting lake effect snows. The climatology of lake-induced snowfall is reviewed, and an overview of the characteristics and evolution of these mesoscale precipitation bands is presented. The atmospheric conditions associated with five different types of lake snow bands are discussed. The abilities of remote sensors to resolve, and dynamical models to simulate, these mesoscale events are also explored. Finally, several techniques designed to improve operational forecasts of lake effect snow are described in detail, along with representative case studies.

Abstract

Winter weather in the Carolinas and Virginia is highly variable and influenced by the area's diverse topography and geography. The Gulf Stream, the highest mountains in the Appalachians, the largest coastal lagoonal system in the United States, and the region's southern latitude combine to produce an array of weather events, particularly during the winter season, that pose substantial challenges to forecasters. The influence of the region's topography upon the evolution of winter weather systems, such as cold-air damming and frontogenesis, is discussed. Conceptual models and specific case studies are examined to illustrate the region's vast assortment of winter weather hazards including prolonged heavy sleet, heavy snow, strong convection, and coastal flooding.

The weather associated with these topographic and meteorological features is often difficult for operational dynamical models to resolve. Forecasting precipitation type within the region can be especially difficult. An objective technique to forecast wintry precipitation across North Carolina is presented to illustrate a 1ocally developed forecast tool used operationally to supplement the centrally produced numerical guidance. The development of other forecast tools is being pursued through collaborative studies between the National Weather Service Forecast Office in Raleigh–Durham, North Carolina, and the Department of Marine, Earth and Atmospheric Sciences at North Carolina State University.

Abstract

The complex combination of synoptic- and mesoscale interactions topographic influences, and large population densities poses a multitude of challenging problems to winter weather forecasters throughout the eastern United States. Over the years, much has been learned about the structure, evolution, and attendant precipitation within winter storms. As a result, numerous operational procedures, forecast applications, and objective techniques have been developed at National Weather Service offices to assess the potential for hazardous winter weather.

An overview of the challenge of forecasting winter weather in the eastern United States is presented, including a historical review of several legendary winter storms, from the Blizzard of 1888 to the Halloween Nor'easter of 1991. The synoptic-scale features associated with East Coast winter storms are described. The mesoscale nature of many eastern winter weather events is illustrated through an examination of the Veterans' Day Snowstorm of 11 November 1987, and the Long Island Snowstorm of 13 December 1988. The development of applied forecast techniques and the potential for new remote sensing technologies (e.g., Doppler weather radar and wind profilers) and mesoscale models to improve operational forecasts of winter weather hazards are also discussed. Companion papers focus on cyclogenesis, terrain-related winter weather forecast considerations in the Southeast, and lake effect snow forecasting.

Abstract

A climatological and composite study of banded precipitation in the northeast United States during the cold season (October–April) is presented. Precipitation systems in the northeast United States in April 1995 and from October 1996 to April 2001 that exhibited greater than 25.4 mm (1 in.) of rainfall, or 12.7 mm (0.5 in.) liquid equivalent, were identified as cases for study. A total of 111 cases were identified during this period, of which 88 had available radar data. Of these cases, 75 exhibited banded structure whereas 13 did not. A band classification scheme was developed from a subset of study cases. Application of the classification scheme to the 88 cases revealed that banded cases can exhibit a variety of banded events during their evolution. Single-banded events were the most common (48), followed by transitory (40), narrow cold frontal (36), multi (29), and undefined (9). Further investigation of the single-banded events highlighted banded structure in the comma-head portion of storms, with 81% of these events exhibiting a majority of their length in the northwest quadrant of the surface cyclone.

Composites were calculated for cases exhibiting single-banded events in the northwest quadrant of the surface cyclone and for nonbanded cases to distinguish synoptic and mesoscale flow regimes associated with banded events and nonbanded cases. The banded composite was marked by cyclogenesis and the development of a closed midlevel circulation. This flow configuration was associated with deformation and strong midlevel frontogenesis northwest of the surface cyclone center, which coincided with the mean band position. The nonbanded composite exhibited a much weaker cyclone located in the confluent entrance region of an upper-level jet. The absence of a closed midlevel circulation in the nonbanded composite limited deformation and associated frontogenesis northwest of the surface cyclone. Cross-section analysis through the respective composite frontogenesis maxima showed that the banded composite frontal zone exhibited stronger and deeper frontogenesis and weaker conditional stability than the nonbanded composite frontal zone.

Case studies from the northeast United States confirm the composite results, highlighting the importance of deep-layer frontogenesis coincident with weak conditional stability. These results are in qualitative agreement with the Sawyer–Eliassen equation, which predicts that the frontogenetical response will be enhanced (reduced) in the presence of small (large) moist symmetric stability.

Abstract

An ingredients-based, time- and scale-dependent forecast strategy for anticipating cold season mesoscale band formation within eastern U.S. cyclones is presented. This strategy draws on emerging conceptual models of mesoscale band development, advances in numerical weather prediction, and modern observational tools. As previous research has shown, mesoscale band development is associated with frontogenesis in the presence of weak moist symmetric stability and sufficient moisture. These three parameters—frontogenesis, weak moist symmetric stability, and moisture—are used as the ingredients for identifying mesoscale band development in this strategy. At forecast projections beyond 2 days, the strategy assesses whether cyclogenesis is expected. Within 2 days of the event, the strategy places the band ingredients in the context of the broader synoptic flow, with attention to where deformation zones are present, to assess whether banding is possible. Within 1 day of the event, the strategy focuses on assessment of the ingredients to outline when and where band formation is favored. Plan-view and cross-sectional analyses of gridded model fields in conjunction with high-resolution model guidance are used to assess the likelihood of banding and to outline the threat area. Within 12 h, short-range forecasts of the band ingredients are evaluated in concert with observations to make specific band predictions. Particular emphasis is placed on the evolution of the frontogenetic forcing and moist symmetric stability. During the event, trends in observations and short-range model forecasts are used to anticipate the movement, intensity, and dissipation of the band. The benefits and practical challenges associated with the proposed strategy are illustrated through its operational application to the 25 December 2002 northeast U.S. snowstorm, during which intense mesoscale snowband formation occurred. Forecast products from this event demonstrate how the forecast strategy can lead to heightened situational awareness, in this case resulting in accurate band forecasts. This application shows that accurate operational forecasts of mesoscale bands can be made based on our current conceptual understanding, observational tools, and modeling capabilities.

Abstract

The complex combination of synoptic and mesoscale interactions, topographic influences, and large population densities poses a multitude of challenging problems to winter weather forecasters throughout the eastern United States. Over the years, much has been learned about the structure, evolution, and attendant precipitation within winter storms. As a result, numerous operational procedures, forecast applications, and objective techniques have been developed at National Weather Service offices to assess the potential for, and forecast, hazardous winter weather. A companion paper by Maglaras et al. provided an overview of the challenge of forecasting winter weather in the eastern United States.

This paper focuses on the problem of cyclogenesis from an operational perspective. Since pattern recognition is an important tool employed by field forecasters, a review of several conceptual models of cyclogenesis often observed in the east is presented. These include classical Miller type A and B cyclogenesis, zipper lows, 500-mb cutoff lows, and cold-air cyclogenesis. The ability of operational dynamical models to predict East Coast cyclones and, in particular, explosive cyclogenesis is explored. An operational checklist that utilizes information from the Nested Grid Model to forecast the potential for rapid cyclogenesis is also described. A review of signatures related to cyclogenesis in visible, infrared, and water vapor satellite imagery is presented. Finally, a study of water vapor imagery for 16 cases of explosive cyclogenesis between 1988 and 1990 indicates that an acceleration of a dry (dark) surge with speeds exceeding 25 m s⁻¹, toward a baroclinic zone, is an excellent indicator of the imminent onset of rapid deepening.

Abstract

This study explores forecaster perceptions of emerging needs for probabilistic forecasting of winter weather hazards through a nationwide survey disseminated to National Weather Service (NWS) forecasters. Questions addressed four relevant thematic areas: 1) messaging timelines for specific hazards, 2) modeling needs, 3) current preparedness to interpret and communicate probabilistic winter information, and 4) winter forecasting tools. The results suggest that winter hazards are messaged on varying time scales that sometimes do not match the needs of stakeholders. Most participants responded favorably to the idea of incorporating new hazard-specific regional ensemble guidance to fill gaps in the winter forecasting process. Forecasters provided recommendations for ensemble run length and output frequencies that would be needed to capture individual winter hazards. Qualitatively, forecasters expressed more difficulties communicating, rather than interpreting, probabilistic winter hazard information. Differences in training and the need for social-science-driven practices were identified as a few of the drivers limiting forecasters’ ability to provide strategic winter messaging. In the future, forecasters are looking for new winter tools to address forecasting difficulties, enhance stakeholder partnerships, and also be useful to the local community. On the regional scale, an ensemble system could potentially accommodate these needs and provide specialized guidance on timing and sensitive/high-impact winter events.

Abstract

Winter storms are disruptive to society and the economy, and they often cause significant injuries and deaths. Innovations in winter storm forecasting have occurred across the value chain over the past two decades, from physical understanding, to observations, to model forecasts, to post-processing, to forecaster knowledge and interpretation, to products and services, and ultimately to decision support. These innovations enable more accurate and consistent forecasts, which are increasingly being translated into actionable information for decision makers. This paper reviews the current state of winter storm forecasting in the context of the U.S. National Weather Service operations and describes a potential future state. Given predictability limitations, a key challenge of winter storm forecasting has been characterizing uncertainty and communicating the forecast in ways that are understandable and useful to decision makers. To address this challenge, particular focus is placed on establishing a probabilistic framework, with probabilistic hazard information serving as a foundation for winter storm decision support services. The framework is guided by social science research to ensure effective communication of risk to meet users’ needs. Solutions to gaps impeding progress in winter storm forecasting are highlighted, including better understanding of mesoscale phenomenon, the need for better ensemble calibration, a rigorous and consistent database of observed impacts, and linking multi-parameter probabilities (e.g., probability of intense snowfall rates at rush hour) with users’ information needs and decisions.