Nocturnal low‐level jet (LLJ) events are commonly observed over the Great Plains region of the USA, thus making this region more favorable for wind energy production. At the same time, the presence of LLJs can significantly modify vertical shear and nocturnal turbulence in the vicinities of wind turbine hub height, and therefore has detrimental effects on turbine rotors. Accurate numerical modeling and forecasting of LLJs are thus needed for precise assessment of wind resources, reliable prediction of power generation and robust design of wind turbines. However, mesoscale numerical weather prediction models face a challenge in precisely forecasting the development, magnitude and location of LLJs. This is due to the fact that LLJs are common in nocturnal stable boundary layers, and there is a general consensus in the literature that our contemporary understanding and modeling capability of this boundary‐layer regime is quite poor. In this paper, we investigate the potential of the Weather Research and Forecasting (WRF) model in forecasting LLJ events over West Texas and southern Kansas. Detailed observational data from both cases were used to assess the performance of the WRF model with different model configurations. Our results indicate that the WRF model can capture some of the essential characteristics of observed LLJs, and thus offers the prospect of improving the accuracy of wind resource estimates and short‐term wind energy forecasts. However, the core of the LLJ tended to be higher as well as slower than what was observed, leaving room for improvement in model performance. Copyright © 2008 John Wiley & Sons, Ltd.

This study uses novel approaches to estimate the fall characteristics of hail, covering a size range from about 0.5 to 7 cm, and the drag coefficients of lump and conical graupel. Three-dimensional (3D) volume scans of 60 hailstones of sizes from 2.5 to 6.7 cm were printed in three dimensions using acrylonitrile butadiene styrene (ABS) plastic, and their terminal velocities were measured in the Mainz, Germany, vertical wind tunnel. To simulate lump graupel, 40 of the hailstones were printed with maximum dimensions of about 0.2, 0.3, and 0.5 cm, and their terminal velocities were measured. Conical graupel, whose three dimensions (maximum dimension 0.1–1 cm) were estimated from an analytical representation and printed, and the terminal velocities of seven groups of particles were measured in the tunnel. From these experiments, with printed particle densities from 0.2 to 0.9 g cm−3, together with earlier observations, relationships between the drag coefficient and the Reynolds number and between the Reynolds number and the Best number were derived for a wide range of particle sizes and heights (pressures) in the atmosphere. This information, together with the combined total of more than 2800 hailstones for which the mass and the cross-sectional area were measured, has been used to develop size-dependent relationships for the terminal velocity, the mass flux, and the kinetic energy of realistic hailstones.

The processes leading to the development of hail and the distribution of these events worldwide are reviewed. Microphysical and physical characteristics of hail development are described to provide context of the notable gaps in our understanding of what drives hail to grow large, or what determines how it falls to the ground. Distributional characteristics of hail are explored, utilizing both surface observations of hailstones and remotely sensed observational data sets to identify opportunities and needs for new observations. These observational deficiencies contribute to our limited capacity to both forecast hail or its expected size and reduce the effectiveness of using favorable conditions for hail development as a proxy to frequency where observations are unavailable. Given the substantive influences of both climate variability and the changing Earth system on hail, the latest understanding of their contributions to risk are addressed. Applying this understanding of the distribution and physical characteristics of hail, the damage by hail to agriculture and insured property is assessed. Much remains unknown about the processes leading to hail growth and environmental controls on hail occurrence, size, and magnitude, particularly outside of the United States and Europe. A better understanding of the global occurrence of hail is also needed to better anticipate the hazard and associated impacts.

A series of thunderstorms on 24 May 2011 produced significant hail in the Dallas-Fort Worth (DFW) metroplex, resulting in an estimated $876.8 million (U.S. dollars) in insured losses to property and automobiles, according to the Texas Department of Insurance. Insurance claims and policy-in-force data were obtained from five insurance companies for more than 67 000 residential properties located in 20 ZIP codes. The methodology for selecting the 20 ZIP codes is described. This study evaluates roofing material type with regard to resiliency to hailstone impacts and relative damage costs associated with roofing systems versus wall systems. A comparison of Weather Surveillance Radar-1988 Doppler (WSR-88D) radar-estimated hail sizes and damage levels seen in the claims data is made. Recommendations for improved data collection and quality of insurance claims data, as well as guidance for future property insurance claims studies, are summarized. Studies such as these allow insurance underwriters and claims adjusters to better evaluate the relative performance and vulnerability of various roofing systems and other building components as a function of hail size. They also highlight the abilities and limitations of utilizing radar horizontal reflectivity-based hail sizes, local storm reports, and Storm Data for claims processing. Large studies of this kind may be able to provide guidance to consumers, designers, and contractors concerning building product selections for improved resiliency to hailstorms, and give a glimpse into how product performance varies with storm exposure. Reducing hail losses would reduce the financial burden on property owners and insurers and reduce the amount of building materials being disposed of after storms.

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