Hailstone structures have been studied for over a century, but so far mainly by manual optical means. This paper presents new texture and microstructure data (i.e. crystal lattice orientations, grain sizes and shapes) measured with an Automatic Ice Texture Analyzer, which gives access to high spatial and angular resolutions. The hailstones show two main characteristics: (1) they are structured with several concentric layers composed of alternating fine equiaxed grains and coarse elongated and radially oriented grains, and (2) they show two texture types with c-axes oriented either parallel or perpendicular to the radial direction. Such textures are compared with the ones observed in lake S1 and S2 ices, respectively. The S1 texture type (with c-axes parallel to the columnar crystals that grew in the radial direction) may result from epitaxial growth from a polycrystalline embryo, while the S2 texture (c-axes in the plane perpendicular to the column direction) may result from the growth from an embryo made of a few crystals with mainly one crystallographic orientation. Our novel high-resolution maps and measurements of both microstructure and texture may help to shed new light on the long-term discussion on the growth mechanisms of large hailstones.

When grown without soybean [Glycine max (L.) Merr.] interference, eastern black nightshade (Solanum ptycanthum Dun.) planted in May produced as many as 7000 berries and 800000 seeds per plant. Eastern black nightshade planted in mid-July produced as many as 100 berries, but those planted in mid-August failed to produce berries. Eastern black nightshade produced less than 85 berries per plant when planted with soybeans in May, 0 to 3 berries per plant when planted into soybeans in June, and no berries when planted into soybeans in July. However, when soybeans were defoliated in July to simulate hail injury, eastern black nightshade that had been planted with soybeans in May produced up to 1600 berries per plant, and those planted into the defoliated soybeans in July produced up to 58 berries per plant. We suggest, therefore, that in vigorously growing soybeans, control of eastern black nightshade emerging in the row would only be required through June to prevent berry production. If, however, the soybean canopy were disturbed by hail or other factors, eastern black nightshade seedlings emerging in late July or early August might produce berries by soybean harvest.

In 2005 a hailstorm struck a long-term dose–response study of irrigation requirements and corn plant populations. This misfortune occurred again in 2006 at approximately the same growth stage. Therefore, the objectives of the studies were redirected to measure the impact of actual hail events on corn leaf area index (LAI) and the competitive interaction of escaped Palmer amaranth populations induced by hail across different levels of irrigation and corn populations. In 2005, the study treatment with the lowest corn population and level of irrigation had twice the Palmer amaranth biomass (PABM) at corn harvest compared with the highest corn population and irrigation level. Corn LAI produced simple linear models that predicted both corn grain yield and PABM. In 2007, the nonhail year, PABM was depressed 4- to 15-fold compared with hail years. PABM declined linearly from 417 kg/ha at the lowest level of irrigation and corn population to 48 kg/ha at the highest level of irrigation and corn plant population. Although economic return per increment of irrigation declined in both hail years, the trends in economic returns were still positive. This suggests that a producer with similar conditions should continue to irrigate even though his or her rate of economic return is reduced.

Most operational hail detection algorithms for single-polarisation radars are based on the analysis of the vertical profiles of radar reflectivity. At KNMI (Royal Netherlands Meteorological Institute) and RMI (Royal Meteorological Institute of Belgium) the probability of hail is derived from the height of the freezing level and the 45-dBZ radar echo top height (maximum height of the 45-dBZ echo). Echo tops are affected by errors in the measured reflectivity itself and by errors in the height assigned to these reflectivities. This study investigates the quality of radar echo top heights as a function of range and explores the implications for hail detection.

The method is based on the comparison between reflectivity measurements from two radars on the vertical cross-section extending between these radars. In a first step, sampling errors related to the radar Volume Coverage Patterns are analysed using idealised storm profiles. Subsequently, real reflectivity data for 25 thunderstorm episodes are compared. It is found that the quality of the maximum reflectivity measurements strongly deteriorates with range and that about half of this degradation can be attributed to overshooting effects. Height assignment differences between the two radars are limited to about 0.5 km. Errors on the reflectivity measurements strongly affect the frequency of 45-dBZ threshold exceedances. However, once the threshold is exceeded, errors in measuring the 45-dBZ echo top heights generally affect the derived probability of hail by less than 20%.

The three annual 2¼% interest coupons of the Winterthur Insurance convertible bond (face value Chf 4 700) will only be paid out if during their corresponding observation periods no major storm or hail storm on one single day damages at least 6 000 motor vehicles insured with Winterthur Insurance. Data for events, where storm or hail damaged more than 1 000 insured vehicles, are available for the last ten years. Using a constant-parameter model, the estimated discounted value of the three Wincat coupons together is Chf 263.29. A conservative evaluation, which accounts for the standard deviation of the estimate, gives a coupon value of Chf 238.25. However, fitting models which admit a trend or a change-point, leads to substantially higher knock-out probabilities of the coupons. The estimated discounted values of the coupons can drop below the above conservative value; a conservative evaluation as above leads to substantially lower values. Hence, already the model uncertainty is higher than the standard deviations of the used estimators. This shows the dominance of the model risk. Consistency, dispersion, robustness and sensitivity of the models are analysed by a simulation study.