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John S. Kain

Abstract

Numerous modifications to the Kain–Fritsch convective parameterization have been implemented over the last decade. These modifications are described, and the motivating factors for the changes are discussed. Most changes were inspired by feedback from users of the scheme (primarily numerical modelers) and interpreters of the model output (mainly operational forecasters). The specific formulation of the modifications evolved from an effort to produce desired effects in numerical weather prediction while also rendering the scheme more faithful to observations and cloud-resolving modeling studies.

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Valliappa Lakshmanan
and
John S. Kain

Abstract

Verification methods for high-resolution forecasts have been based either on filtering or on objects created by thresholding the images. The filtering methods do not easily permit the use of deformation while identifying objects based on thresholds can be problematic. In this paper, a new approach is introduced in which the observed and forecast fields are broken down into a mixture of Gaussians, and the parameters of the Gaussian mixture model fit are examined to identify translation, rotation, and scaling errors. The advantages of this method are discussed in terms of the traditional filtering or object-based methods and the resulting scores are interpreted on a standard verification dataset.

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Michael E. Baldwin
and
John S. Kain

Abstract

The sensitivity of various accuracy measures to displacement error, bias, and event frequency is analyzed for a simple hypothetical forecasting situation. Each measure is found to be sensitive to displacement error and bias, but probability of detection and threat score do not change as a function of event frequency. On the other hand, equitable threat score, true skill statistic, and odds ratio skill score behaved differently with changing event frequency. A newly devised measure, here called the bias-adjusted threat score, does not change with varying event frequency and is relatively insensitive to bias. Numerous plots are presented to allow users of these accuracy measures to make quantitative estimates of sensitivities that are relevant to their particular application.

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John S. Kain
and
J. Michael Fritsch

Abstract

A new one-dimensional cloud model, specifically designed for application in mesoscale convective parameterization schemes (CPSs), is introduced. The model is unique in its representation of environmental entrainment and updraft detrainment rates. In particular, the two-way exchange of mass between clouds and their environment is modulated at each vertical level by a buoyancy sorting mechanism at the interface of clear and cloudy air. The new entrainment/detrainment scheme allows vertical profiles of both updraft moisture detrainment and updraft vertical mass flux to vary in a physically realistic way as a function of the cloud-scale environment. These performance characteristics allow the parameterized vertical distribution of convective heating and drying to be much more responsive to environmental conditions than is possible with a traditional one-dimensional entraining plume model.

The sensitivities of the new model to variations in environmental convective available potential energy and vertical moisture distribution in idealized convective environments are demonstrated and its sensitivities to several key control parameters are examined. Finally, the performance of the new model in the Fritsch–Chappell CPS is evaluated. Parameterized heating and drying profiles are elucidated as they relate to the convective environment and to the type of cloud model used in the CPS.

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John S. Kain
and
J. Michael Fritsch

Abstract

An analysis of how parameterized convection interacts with hydrostatic, explicitly resolved precipitation processes to represent multiscale convective overturning in a mesoscale-resolution numerical simulation is presented. Critically important ingredients of the successful simulation are identified and the degree to which simulations are consistent with observations and theoretical considerations is examined. Of particular concern is how convective parameterization routines reconcile the deep moist absolutely unstable structures that form in mesoscale convective systems.

It is found that these structures arise primarily from resolvable-scale vertical motion and that the model responds to these structures not only by maintaining parameterized convection, but also by developing a hydrostatic manifestation of convective overturning on its smallest resolvable horizontal scales. The strongest and most distinctive mesoscale perturbations develop in regions where the mesoscale contribution to convective overturning rivals, and often exceeds, the parameterized contribution.

Because the internal features of mesoscale convective systems are poorly resolved by meso-β-scale grid elements in this simulation, their scale tends to be overestimated. However, the model results and observations suggest that models must account for multiscale convective overturning in order to properly characterize convective mass transports. Therefore, it is argued that the manner of representation of the convective process, wherein deep convection is allowed to occur partly as a parameterized subgrid-scale process and partly as a hydrostatic manifestation of convective overturning, is likely to give the optimal numerical solution for modeling systems with meso-β-scale resolution.

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Ryan A. Sobash
and
John S. Kain

Abstract

Eight years of daily, experimental, deterministic, convection-allowing model (CAM) forecasts, produced by the National Severe Storms Laboratory, were evaluated to assess their ability at predicting severe weather hazards over a diverse collection of seasons, regions, and environments. To do so, forecasts of severe weather hazards were produced and verified as in previous studies using CAM output, namely by thresholding the updraft helicity (UH) field, smoothing the resulting binary field to create surrogate severe probability forecasts (SSPFs), and verifying the SSPFs against observed storm reports. SSPFs were most skillful during the spring and fall, with a relative minimum in skill observed during the summer. SSPF skill during the winter months was more variable than during other seasons, partly due to the limited sample size of events, but was often less than that during the warm season. The seasonal behavior of SSPF skill was partly driven by the relationship between the UH threshold and the likelihood of obtaining severe storm reports. Varying UH thresholds by season and region produced SSPFs that were more skillful than using a fixed UH threshold to identify severe convection. Accounting for this variability was most important during the cool season, when a lower UH threshold produced larger SSPF skill compared to warm-season events, and during the summer, when large differences in skill occurred within different parts of the continental United States (CONUS), depending on the choice of UH threshold. This relationship between UH threshold and SSPF skill is discussed within the larger scope of generating skillful CAM-based guidance for hazardous convective weather and verifying CAM predictions.

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Michael E. Baldwin
,
John S. Kain
, and
S. Lakshmivarahan

Abstract

An automated procedure for classifying rainfall systems (meso-α scale and larger) was developed using an operational analysis of hourly precipitation estimates from radar and rain gauge data. The development process followed two main phases: a training phase and a testing phase. First, 48 hand-selected cases were used to create a training dataset, from which a set of attributes related to morphological aspects of rainfall systems were extracted. A hierarchy of classes for rainfall systems, in which the systems are separated into general convective (heavy rain) and nonconvective (light rain) classes, was envisioned. At the next level of classification hierarchy, convective events are divided into linear and cellular subclasses, and nonconvective events belong to the stratiform subclass. Essential attributes of precipitating systems, related to the rainfall intensity and degree of linear organization, were determined during the training phase. The attributes related to the rainfall intensity were chosen to be the parameters of the gamma probability distribution fit to observed rainfall amount frequency distributions using the generalized method of moments. Attributes related to the degree of spatial continuity of each rainfall system were acquired from correlogram analysis. Rainfall systems were categorized using hierarchical cluster analysis experiments with various combinations of these attributes. The combination of attributes that resulted in the best match between cluster analysis results and an expert classification were used as the basis for an automated classification procedure.

The development process shifted into the testing phase, where automated procedures for identifying and classifying rainfall systems were used to analyze every rainfall system in the contiguous 48 states during 2002. To allow for a feasible validation, a testing dataset was extracted from the 2002 data. The testing dataset consisted of 100 randomly selected rainfall systems larger than 40 000 km2 as identified by an automated identification system. This subset was shown to be representative of the full 2002 dataset. Finally, the automated classification procedure classified the testing dataset into stratiform, linear, and cellular classes with 85% accuracy, as compared to an expert classification.

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Melissa S. Bukovsky
,
John S. Kain
, and
Michael E. Baldwin

Abstract

Bowing, propagating precipitation features that sometimes appear in NCEP's North American Mesoscale model (NAM; formerly called the Eta Model) forecasts are examined. These features are shown to be associated with an unusual convective heating profile generated by the Betts–Miller–Janjić convective parameterization in certain environments. A key component of this profile is a deep layer of cooling in the lower to middle troposphere. This strong cooling tendency induces circulations that favor expansion of parameterized convective activity into nearby grid columns, which can lead to growing, self-perpetuating mesoscale systems under certain conditions. The propagation characteristics of these systems are examined and three contributing mechanisms of propagation are identified. These include a mesoscale downdraft induced by the deep lower-to-middle tropospheric cooling, a convectively induced buoyancy bore, and a boundary layer cold pool that is indirectly produced by the convective scheme in this environment. Each of these mechanisms destabilizes the adjacent atmosphere and decreases convective inhibition in nearby grid columns, promoting new convective development, expansion, and propagation of the larger system. These systems appear to show a poor correspondence with observations of bow echoes on time and space scales that are relevant for regional weather prediction, but they may provide important clues about the propagation mechanisms of real convective systems.

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Michael C. Coniglio
,
Stephen F. Corfidi
, and
John S. Kain

Abstract

This study documents the complex environment and early evolution of the remarkable derecho that traversed portions of the central United States on 8 May 2009. Central to this study is the comparison of the 8 May 2009 derecho environment to that of other mesoscale convective systems (MCSs) that occurred in the central United States during a similar time of year. Synoptic-scale forcing was weak and thermodynamic instability was limited during the development of the initial convection, but several mesoscale features of the environment appeared to contribute to initiation and upscale growth, including a mountain wave, a midlevel jet streak, a weak midlevel vorticity maximum, a ““Denver cyclone,”” and a region of upper-tropospheric inertial instability.

The subsequent MCS developed in an environment with an unusually strong and deep low-level jet (LLJ), which transported exceptionally high amounts of low-level moisture northward very rapidly, destabilized the lower troposphere, and enhanced frontogenetical circulations that appeared to aid convective development. The thermodynamic environment ahead of the developing MCS contained unusually high precipitable water (PW) and very large midtropospheric lapse rates, compared to other central plains MCSs. Values of downdraft convective available potential energy (DCAPE), mean winds, and 0––6-km vertical wind shear were not as anomalously large as the PW, lapse rates, and LLJ. In fact, the DCAPE values were lower than the mean values in the comparison dataset. These results suggest that the factors contributing to updraft strength over a relatively confined area played a significant role in generating the strong outflow winds at the surface, by providing a large volume of hydrometeors to drive the downdrafts.

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Michael C. Coniglio
,
Stephen F. Corfidi
, and
John S. Kain

Abstract

This work presents an analysis of the vertical wind shear during the early stages of the remarkable 8 May 2009 central U.S. derecho-producing convective system. Comments on applying Rotunno–Klemp–Weisman (RKW) theory to mesoscale convective systems (MCSs) of this type also are provided. During the formative stages of the MCS, the near-surface-based shear vectors ahead of the leading convective line varied with time, location, and depth, but the line-normal component of the shear in any layer below 3 km ahead of where the strong bow echo developed was relatively small (6–9 m s−1). Concurrently, the midlevel (3–6 km) line-normal shear component had magnitudes mostly >10 m s−1 throughout.

In a previous companion paper, it was hypothesized that an unusually strong and expansive low-level jet led to dramatic changes in instability, shear, and forced ascent over mesoscale areas. These mesoscale effects may have overwhelmed the interactions between the cold pool and low-level shear that modulate system structure in less complex environments. If cold pool–shear interactions were critical to producing such a strong system, then the extension of the line-normal shear above 3 km also appeared to be critical. It is suggested that RKW theory be applied with much caution, and that examining the shear above 3 km is important, if one wishes to explain the formation and maintenance of intense long-lived convective systems, particularly complex nocturnal systems like the one that occurred on 8 May 2009.

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