Abstract

Model simulations of the 2013 Colorado Front Range floods are performed using 4-km horizontal grid spacing to evaluate the impact of using explicit convection (EC) versus parameterized convection (CP) in the model convective physics “gray zone.” Significant differences in heavy precipitation forecasts are found across multiple regions in which heavy rain and high-impact flooding occurred. The relative contribution of CP-generated precipitation to total precipitation suggests that greater CP scheme activity in areas upstream of the Front Range flooding may have led to significant downstream model error.

Heavy convective precipitation simulated by the Kain–Fritsch CP scheme in particular led to an alteration of the low-level moisture flux and moisture transport fields that ultimately prevented the generation of heavy precipitation in downstream areas as observed. An updated, scale-aware version of the Kain–Fritsch scheme is also tested, and decreased model errors both up- and downstream suggest that scale-aware updates yield improvements in the simulation of this event. Comparisons among multiple CP schemes demonstrate that there are model convective physics gray zone considerations that significantly impact the simulation of extreme rainfall in this event.

Abstract

Analysis of a pair of three-dimensional simulations of mesoscale convective systems (MCSs) reveals a significant sensitivity of convective momentum transport (CMT), MCS motion, and the generation of severe surface winds to ambient moisture. The Weather Research and Forecasting model is used to simulate an idealized MCS, which is compared with an MCS in a drier midlevel environment. The MCS in the drier environment is smaller, moves slightly faster, and exhibits increased descent and more strongly focused areas of enhanced CMT near the surface in the trailing stratiform region relative to that in the control simulation.

A marked increase in the occurrence of severe surface winds is observed between the dry midlevel simulation and the control. It is shown that the enhanced downward motion associated with decreased midlevel relative humidity affects CMT fields and contributes to an increase in the number of grid-cell occurrences of severe surface winds. The role of a descending rear-inflow jet in producing strong surface winds at locations trailing the gust front is also analyzed, and is found to be associated with low-level CMT maxima, particularly in the drier midlevel simulation.

Abstract

The sensitivity of numerical model forecasts of coastal cyclogenesis and frontogenesis to the choice of model cumulus parameterization (CP) scheme is examined for the 17 February 2004 southeastern U.S. winter weather event. This event featured a complex synoptic and mesoscale environment, as the presence of cold-air damming, a developing coastal surface cyclone, and an upper-level trough combined to present a daunting winter weather forecast scenario. The operational forecast challenge was further complicated by erratic numerical model predictions. The most poignant area of disagreement between model runs was the treatment of a coastal cyclone and an associated coastal front, features that would affect the location and timing of precipitation and influence the precipitation type. At the time of the event, it was hypothesized that the Betts–Miller–Janjić (BMJ) CP scheme was dictating the location and intensity of the initial coastal cyclone center in operational Eta Model forecasts. For this reason, forecasts for this case were rerun with the workstation Eta Model using the Kain–Fritsch (KF) CP scheme to further examine the sensitivity to this parameterization choice. Results confirm that the model CP scheme played a major role in the forecast for this case, affecting the quantitative precipitation forecast as well as the strength, location, and structure of coastal cyclogenesis and coastal frontogenesis. The Eta Model forecast using the KF CP scheme produced a relatively uniform distribution of convective precipitation oriented along the axis of an inverted trough and strong coastal front. In contrast, the BMJ forecasts resulted in a weaker coastal front and the development of multiple distinct closed cyclonic circulations in association with more localized convective precipitation centers. An additional BMJ forecast in which the shallow mixing component of the scheme was disabled bore a closer semblance to the KF forecasts relative to the original BMJ forecast. Suggestions are provided to facilitate the identification of CP-driven cyclones using standard operational model output parameters.

Abstract

Operational forecasters in the southeast and mid-Atlantic regions of the United States have noted a positive quantitative precipitation forecast (QPF) bias in numerical weather prediction (NWP) model forecasts downstream of some organized, cold-season convective systems. Examination of cold-season cases in which model QPF guidance exhibited large errors allowed identification of two representative cases for detailed analysis. The goals of the case study analyses are to (i) identify physical mechanisms through which the upstream convection (UC) alters downstream precipitation amounts, (ii) determine why operational models are challenged to provide accurate guidance in these situations, and (iii) suggest future research directions that would improve model forecasts in these situations and allow forecasters to better anticipate such events. Two primary scenarios are identified during which downstream precipitation is altered in the presence of UC for the study region: (i) a fast-moving convective (FC) scenario in which organized convective systems oriented parallel to the lower-tropospheric flow are progressive relative to the parent synoptic system, and appear to disrupt poleward moisture transport, and (ii) a situation characterized by slower-moving convection (SC) relative to the parent system. Analysis of a representative FC case indicated that moisture consumption, stabilization via convective overturning, and modification of the low-level flow to a more westerly direction in the postconvective environment all appear to contribute to the reduction of downstream precipitation. In the FC case, operational Eta Model forecasts moved the organized UC too slowly, resulting in an overestimate of downstream moisture transport. A 4-km explicit convection model forecast from the Weather Research and Forecasting model produced a faster-moving upstream convective system and improved downstream QPF. In contrast to the FC event, latent heat release in the primary rainband is shown to enhance the low-level jet ahead of the convection in the SC case, thereby increasing moisture transport into the downstream region. A negative model QPF bias was observed in Eta Model forecasts for the SC event. Suggestions are made for precipitation forecasting in UC situations, and implications for NWP model configuration are discussed.

Abstract

Momentum transport is examined in a simulated midlatitude mesoscale convective system (MCS) to investigate its contribution to MCS motion. Momentum budgets are computed using model output to quantify the role of specific processes in determining the low-level wind field in the system’s surface-based cold pool. Results show that toward the leading convective line of the MCS and near the leading edge of the cold pool, the momentum field is most strongly determined by the vertical advection of the storm-induced perturbation wind. Across the middle rear of the system, the wind field is largely a product of the pressure gradient acceleration and, to a lesser extent, the vertical advection of the background environmental (i.e., base state) wind. The relative magnitudes of the vertical advection terms in an Eulerian momentum budget suggest that, for gust-front-driven systems, downward momentum transport by the MCS is a significant driver of MCS motion and potentially severe surface winds. Results further illustrate that the contribution of momentum transport to MCS speed occurs mainly via the enhancement of the cold pool propagation speed as higher-momentum air from aloft is transported into the surface-based cold pool.

Abstract

The use of the potential vorticity (PV) framework by operational forecasters is advocated through case examples that demonstrate its utility for interpreting and evaluating numerical weather prediction (NWP) model output for weather systems characterized by strong latent heat release (LHR). The interpretation of the dynamical influence of LHR is straightforward in the PV framework; LHR can lead to the generation of lower-tropospheric cyclonic PV anomalies. These anomalies can be related to meteorological phenomena including extratropical cyclones and low-level jets (LLJs), which can impact lower-tropospheric moisture transport.

The nonconservation of PV in the presence of LHR results in a modification of the PV distribution that can be identified in NWP model output and evaluated through a comparison with observations and high-frequency gridded analyses. This methodology, along with the application of PV-based interpretation, can help forecasters identify aspects of NWP model solutions that are driven by LHR; such features are often characterized by increased uncertainty due to difficulties in model representation of precipitation amount and latent heating distributions, particularly for convective systems.

Misrepresentation of the intensity and/or distribution of LHR in NWP model forecasts can generate errors that propagate through the model solution with time, potentially degrading the representation of cyclones and LLJs in the model forecast. The PV framework provides human forecasters with a means to evaluate NWP model forecasts in a way that facilitates recognition of when and how value may be added by modifying NWP guidance. This utility is demonstrated in case examples of coastal extratropical cyclogenesis and LLJ enhancement. Information is provided regarding tools developed for applying PV-based techniques in an operational setting.

Abstract

A series of precipitation events impacted the Pacific Northwest during the first two weeks of November 2006. This sequence was punctuated by a particularly potent inland-penetrating atmospheric river (AR) that produced record-breaking precipitation across the region during 5–7 November. The precipitation caused destructive flooding as far inland as Montana’s Glacier National Park, 800 km from the Pacific Ocean. This study investigates the inland penetration of moisture during the event using a 4–1.33-km grid spacing configuration of the Weather Research and Forecasting (WRF) modeling system. A high-resolution simulation allowed an analysis of interactions between the strong AR and terrain features such as the Cascade Mountains and the Columbia River Gorge (CR Gorge).

Moisture transport in the vicinity of the Cascades is assessed using various metrics. The most efficient pathway for moisture penetration was through the gap (i.e., CR Gap) between Mt. Adams and Mt. Hood, which includes the CR Gorge. While the CR Gap is a path of least resistance through the Cascades, most of the total moisture transport that survived transit past the Cascades overtopped the mountain barrier itself. This is due to the disparity between the length of the ridge (~800 km) and relatively narrow width of the CR Gap (~93 km). Moisture transport reductions were larger across the Washington Cascades and the southern-central Oregon Cascades than through the CR Gap. During the simulation, drying ratios through the CR Gap (9.3%) were notably less than over adjacent terrain (19.6%–30.6%). Drying ratios decreased as moisture transport intensity increased.

Abstract

This paper documents the characteristics of extreme precipitation events (EPEs) in the southeastern United States (SEUS) during 2002–11. The EPEs are identified by applying an object-based method to 24-h precipitation analyses from the NCEP stage-IV dataset. It is found that EPEs affected the SEUS in all months and occurred most frequently in the western portion of the SEUS during the cool season and in the eastern portion during the warm season. The EPEs associated with tropical cyclones, although less common, tended to be larger in size, more intense, and longer lived than “nontropical” EPEs. Nontropical EPEs in the warm season, relative to those in the cool season, tended to be smaller in size and typically involved more moist, conditionally unstable conditions but weaker dynamical influences. Synoptic-scale composites are constructed for nontropical EPEs stratified by the magnitude of vertically integrated water vapor transport (IVT) to examine distinct scenarios for the occurrence of EPEs. The composite results indicate that “strong IVT” EPEs occur within high-amplitude flow patterns involving strong transport of moist, conditionally unstable air within the warm sector of a cyclone, whereas “weak IVT” EPEs occur within low-amplitude flow patterns featuring weak transport but very moist and conditionally unstable conditions. Finally, verification of deterministic precipitation forecasts from a reforecast dataset based on the NCEP Global Ensemble Forecast System reveals that weak-IVT EPEs were characteristically associated with lower forecast skill than strong-IVT EPEs. Based on these results, it is suggested that further research should be conducted to investigate the forecast challenges associated with EPEs in the SEUS.

Abstract

NOAA’s second-generation reforecasts are approximately consistent with the operational version of the 2012 NOAA Global Ensemble Forecast System (GEFS). The reforecasts allow verification to be performed across a multidecadal time period using a static model, in contrast to verifications performed using an ever-evolving operational modeling system. This contribution examines three commonly used verification metrics for reforecasts of precipitation over the southeastern United States: equitable threat score, bias, and ranked probability skill score. Analysis of the verification metrics highlights the variation in the ability of the GEFS to predict precipitation across amount, season, forecast lead time, and location. Beyond day 5.5, there is little useful skill in quantitative precipitation forecasts (QPFs) or probabilistic QPFs. For lighter precipitation thresholds [e.g., 5 and 10 mm (24 h)⁻¹], use of the ensemble mean adds about 10% to the forecast skill over the deterministic control. QPFs have increased in accuracy from 1985 to 2013, likely due to improvements in observations. Results of this investigation are a first step toward using the reforecast database to distinguish weather regimes that the GEFS typically predicts well from those regimes that the GEFS typically predicts poorly.

Abstract

With funding provided by the 2012 Disaster Relief Act (Sandy Supplemental), NOAA’s Earth System Research Laboratory Physical Sciences Division has installed three Doppler wind-profiling radars and surface meteorology towers along the U.S. Gulf and southeast coasts to help detect and monitor landfalling tropical storms and other high-impact weather events. This same combination of instruments has been used to monitor landfalling atmospheric rivers on the U.S. West Coast. For this reason, we refer to the whole collection of instruments at each site as an Atmospheric River Observatory (ARO). These three new AROs supported by the Sandy Supplemental complement a fourth ARO deployed in coastal North Carolina as part of NOAA’s Hydrometeorology Testbed Southeast Pilot Study. These four AROs were installed in time to capture the 2014 hurricane season and will be operated through the 2015 hurricane season.