Abstract

This paper describes the southerly New York Bight (NYB) jet (11–17 m s⁻¹) that develops primarily during the warm season just above the surface offshore (east) of the northern New Jersey coast and south of Long Island (the NYB). Observations from two offshore buoys are used to develop a 9-yr climatology of 134 jet events from 1997 to 2006. There is a seasonal maximum (2.5 events per month) during June and July, with a skew toward the spring months. The wind directions for the jet trace out a nearly elliptical orbit for the 24-h period around the time of jet maximum at ~2300 UTC [1900 eastern daylight time (EDT)] on average. Composites reveal that the NYB jet occurs on days with southwesterly synoptic flow, and the jet is part of a larger-scale (200–300 km) wind enhancement offshore of the mid-Atlantic and northeast U.S. coasts during the early evening hours.

High-resolution observations (surface mesonet, aircraft soundings, and a terminal Doppler weather radar) and Weather Research and Forecasting (WRF) model simulations down to 1.33-km grid spacing are used to diagnose the evolution of the NYB jet on 2 June 2007. The NYB jet at ~150 m MSL occurs within the sloping marine inversion near the coast. Low-level trajectories illustrate low-level diffluence and weak subsidence within the jet. A WRF momentum budget highlights the evolving pressure gradient and accelerations during jet formation. The maximum jet winds occur 1–2 h after the peak meridional pressure gradient is established through a geostrophic adjustment process. Sensitivity experiments show that jet occurrence is dependent on diurnal heating and that the concave bend in the southern New Jersey coast limits the southern extent of the jet.

Abstract

The forecast uncertainty of mesoscale snowband formation and evolution is compared using predictions from a 16-member multimodel ensemble at 12-km grid spacing for the 25 December 2002, 12 February 2006, and 14 February 2007 northeast U.S. snowstorms. Using these predictions, the case-to-case variability in the predictability of band formation and evolution is demonstrated. Feature-based uncertainty information is also presented as an example of what may be operationally feasible from postprocessing information from future short-range ensemble forecast systems. Additionally, the initial condition sensitivity of band location in each case is explored by contrasting the forecast evolutions of initial condition members with large differences in snowband positions. Considerable uncertainty in the occurrence, and especially timing and location, of band formation and subsequent evolution was found, even at forecast projections <24 h. The ensemble provided quantitative mesoscale band uncertainty information, and differentiated between high-predictability (14 February 2007) and low-predictability (12 February 2006) cases. Among the three cases, large (small) initial differences in the upper-level PV distribution and surface mean sea level pressure of the incipient cyclone were associated with large (small) differences in forecast snowband locations, suggesting that case-to-case differences in predictability may be related to the quality of the initial conditions. The complexity of the initial flow may also be a discriminator. Error growth was evident in each case, consistent with previous mesoscale predictability research, but predictability differences were not correlated to the degree of convection. Discussion of these results and future extensions of the work are presented.

Abstract

Key results of a comprehensive survey of U.S. National Weather Service operational forecast managers concerning the assessment and communication of forecast uncertainty are presented and discussed. The survey results revealed that forecasters are using uncertainty guidance to assess uncertainty, but that limited data access and ensemble underdispersion and biases are barriers to more effective use. Some respondents expressed skepticism as to the added value of formal ensemble guidance relative to simpler approaches of estimating uncertainty, and related the desire for feature-specific ensemble verification to address this skepticism. Respondents reported receiving requests for uncertainty information primarily from sophisticated users such as emergency managers, and most often during high-impact events. The largest request for additional training material called for simulator-based case studies that demonstrate how uncertainty information should be interpreted and communicated.

Respondents were in consensus that forecasters should be significantly involved in the communication of uncertainty forecasts; however, there was disagreement regarding if and how forecasters should adjust objective ensemble guidance. It is contended that whether forecasters directly modify objective ensemble guidance will ultimately depend on how the weather enterprise views ensemble output (as the final forecast or as a guidance supporting conceptual understanding), the enterprise’s commitment to provide the necessary supporting forecast infrastructure, and how rapidly ensemble weaknesses such as underdispersion, biases, and resolution are addressed.

The survey results illustrate that forecasters’ operational uncertainty needs are intimately tied to the end products and services they produce. Thus, it is critical that the process to develop uncertainty information in existing or new products or services be a sustained collaborative effort between ensemble developers, forecasters, academic partners, and users. As the weather enterprise strives to provide uncertainty information to users, it is asserted that addressing the forecaster needs identified in this survey will be a prerequisite to achieve this goal.

Abstract

This paper explores the mesoscale forcing and stability evolution of intense precipitation bands in the comma head sector of extratropical cyclones using the 32-km North American Regional Reanalysis, hourly 20-km Rapid Update Cycle analyses, and 2-km composite radar reflectivity data. A statistical and composite analysis of 36 banded events occurring during the 2002–08 cool seasons reveals a common cyclone evolution and associated band life cycle. A majority (61%) of banded events develop along the northern portion of a hook-shaped upper-level potential vorticity (PV) anomaly. During the 6 h leading up to band formation, lower-tropospheric frontogenesis nearly doubles and the conditional stability above the frontal zone is reduced. The frontogenesis increase is primarily due to changes in the kinematic flow associated with the development of a mesoscale geopotential height trough. This trough extends poleward of the 700-hPa low, and is the vertical extension of the surface warm front (and surface warm occlusion when present). The conditional stability near 500 hPa is reduced by differential horizontal potential temperature advection. During band formation, layers of conditional instability above the frontal zone are present nearly 3 times as often as layers of conditional symmetric instability. The frontogenetical forcing peaks during band maturity and is offset by an increase in conditional stability. Band dissipation occurs as the conditional stability continues to increase, and the frontogenesis weakens in response to changes in the kinematic flow.

A set of 22 null events, in which band formation was absent in the comma head, were also examined. Although exhibiting similar synoptic patterns as the banded events, the null events were characterized by weaker frontogenesis. However, statistically significant differences between the midlevel frontogenesis maximum of the banded and null events only appear ~2 h prior to band formation, illustrating the challenge of predicting band formation.

Abstract

The role of moist processes in regulating mesoscale snowband life cycle within the comma head portion of three northeast U.S. cyclones is investigated using piecewise potential vorticity (PV) inversion, modeling experiments, and potential temperature tendency budgets. Snowband formation in each case occurred along a mesoscale trough that extended poleward of a 700-hPa low. This 700-hPa trough was associated with intense frontogenetical forcing for ascent. A variety of PV evolutions among the cases contributed to midlevel trough formation and associated frontogenesis. However, in each case the induced flow from diabatic PV anomalies accounted for a majority of the midlevel frontogenesis during the band’s life cycle, highlighting the important role that latent heat release plays in band evolution. Simulations with varying degrees of latent heating show that diabatic processes associated with the band itself were critical to the development and maintenance of the band. However, changes in the meso-α-scale flow associated with the development of diabatic PV anomalies east of the band contributed to frontolysis and band dissipation. Conditional stability was reduced near 500 hPa in each case several hours prior to band formation. This stability remained small until band formation, when the stratification generally increased in association with the release of conditional instability. Previous studies have suggested that the dry slot is important for the initial stability reduction at midlevels, but this was not evident for the three banding cases examined. Rather, differential horizontal temperature advection in moist southwest flow ahead of the upper trough was the dominant process that reduced the midlevel conditional stability.

Abstract

This paper investigates the structural and dynamical evolution of an intense mesoscale snowband occurring 25–26 December 2002 over the northeastern United States. Dual-Doppler, wind profiler, aircraft, and water vapor observations in concert with the fifth-generation Pennsylvania State University–NCAR Mesoscale Model run at 4-km grid spacing are used to highlight evolutionary aspects of a snowband unresolved by previous studies. The high-resolution observations and model simulations show that band formation was coincident with a sharpening of a midlevel trough and associated increase in frontogenesis in an environment of conditional and inertial instability. Band maturity was marked by increasing conditional stability and a threefold increase in frontogenetical forcing. Band dissipation occurred as the midlevel trough and associated frontogenetical forcing weakened, while the conditional stability continued to increase. The effect of changing ascent is shown to dominate over changing moisture in explaining band dissipation in this case. Unconventional aspects of band structure and dynamics revealed by the high-resolution data are discussed, including the location of the band relative to the frontogenesis maximum, increasing stability during the band-formation process, and the presence of inertial instability. The model realistically predicted the band evolution; however, maximum precipitation was underforecast within the banded region by ∼30% at 4-km grid spacing, and the axis of heaviest precipitation was displaced ∼50 km to the southeast of the observed location. Higher horizontal model resolution is shown to contribute toward improved QPF in this case; however, it appears more dramatic improvement may be gained by better simulating the frontogenesis, stability, and moisture evolution.

Abstract

Extreme quantitative precipitation forecast (QPF) performance is baselined and analyzed by NOAA’s Hydrometeorology Testbed (HMT) using 11 yr of 32-km gridded QPFs from NCEP’s Weather Prediction Center (WPC). The analysis uses regional extreme precipitation thresholds, quantitatively defined as the 99th and 99.9th percentile precipitation values of all wet-site days from 2001 to 2011 for each River Forecast Center (RFC) region, to evaluate QPF performance at multiple lead times. Five verification metrics are used: probability of detection (POD), false alarm ratio (FAR), critical success index (CSI), frequency bias, and conditional mean absolute error (MAE_cond). Results indicate that extreme QPFs have incrementally improved in forecast accuracy over the 11-yr period. Seasonal extreme QPFs show the highest skill during winter and the lowest skill during summer, although an increase in QPF skill is observed during September, most likely due to landfalling tropical systems. Seasonal extreme QPF skill decreases with increased lead time. Extreme QPF skill is higher over the western and northeastern RFCs and is lower over the central and southeastern RFC regions, likely due to the preponderance of convective events in the central and southeastern regions. This study extends the NOAA HMT study of regional extreme QPF performance in the western United States to include the contiguous United States and applies the regional assessment recommended therein. The method and framework applied here are readily applied to any gridded QPF dataset to define and verify extreme precipitation events.

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

This paper is the first of two papers that examines the organization of the precipitation field in central U.S. cold-season cyclones involving inverted troughs. The first portion of the study examines the varying precipitation distribution that occurred during a 6-yr synoptic climatology of inverted trough cases. The definition of inverted trough cases has been expanded from the groundbreaking work by Keshishian et al. by 1) not requiring a closed cyclonic isobar along the frontal wave along the conventional surface front and 2) not requiring a surface thermal gradient to be present along the inverted trough. Only 8.5% of the expanded dataset produced the precipitation primarily occurring to the west of the inverted trough (“behind” cases) as seen in Keshishian et al. The largest group of cases, comprising about 40% of the cases, produced precipitation that primarily occurred between the inverted trough and the conventional warm front (“ahead” cases). A composite study compared a subset of the ahead cases with a subset of the behind cases. The ahead cases tended to be more progressive with a stronger jet stream located over the center of the parent low. Broad warm-air advection and frontogenesis in the lower troposphere were observed between the inverted trough and the surface warm front. Cold-air advection to the west of the inverted trough precluded the development of “wraparound precipitation.” In contrast, the behind cases had a stronger low-latitude wave couplet with a trough upstream of the surface low and a ridge downstream. The region of warm-air advection and frontogenesis were displaced to the west of the inverted trough and surface cyclone. In addition, the entrance region of a southwest–northeast-oriented jet streak aided the development of ascent to the west of the inverted trough while precluding the development of precipitation to the north of the conventional warm front. Thus, the inverted trough tended to act like a warm front in behind cases, as shown by Keshishian et al. Composites were also computed at both 12 and 24 h before inverted trough formation in order to generate comparisons useful to operational applications. Case study results for both ahead and behind cases will be compared with the composite cases in the companion paper.

Abstract

The role of the human forecaster in improving upon the accuracy of numerical weather prediction is explored using multiyear verification of human-generated short-range precipitation forecasts and medium-range maximum temperature forecasts from the Weather Prediction Center (WPC). Results show that human-generated forecasts improve over raw deterministic model guidance. Over the past two decades, WPC human forecasters achieved a 20%–40% improvement over the North American Mesoscale (NAM) model and the Global Forecast System (GFS) for the 1 in. (25.4 mm) (24 h)⁻¹ threshold for day 1 precipitation forecasts, with a smaller, but statistically significant, 5%–15% improvement over the deterministic ECMWF model. Medium-range maximum temperature forecasts also exhibit statistically significant improvement over GFS model output statistics (MOS), and the improvement has been increasing over the past 5 yr. The quality added by humans for forecasts of high-impact events varies by element and forecast projection, with generally large improvements when the forecaster makes changes ≥8°F (4.4°C) to MOS temperatures. Human improvement over guidance for extreme rainfall events [3 in. (76.2 mm) (24 h)⁻¹] is largest in the short-range forecast. However, human-generated forecasts failed to outperform the most skillful downscaled, bias-corrected ensemble guidance for precipitation and maximum temperature available near the same time as the human-modified forecasts. Thus, as additional downscaled and bias-corrected sensible weather element guidance becomes operationally available, and with the support of near-real-time verification, forecaster training, and tools to guide forecaster interventions, a key test is whether forecasters can learn to make statistically significant improvements over the most skillful of this guidance. Such a test can inform to what degree, and just how quickly, the role of the forecaster changes.