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Hail has been identified as the largest contributor to insured losses from thunderstorms globally, with losses costing the insurance industry billions of dollars each year. Yet, of all precipitation types, hail is probably subject to the largest uncertainties. Some might go so far as to argue that observing and forecasting hail is as difficult, if not more difficult, than is forecasting tornadoes. The reasons why hail is challenging are many and varied and reflected by the fact that hailstones display a wide variety of shapes, sizes and internal structures. There is also an important clue in this diversity—nature is telling us that hail can grow by following a wide variety of trajectories within thunderstorms, each having a unique set of conditions. It is because of this complexity that modeling hail growth and forecasting size is so challenging. Consequently, it is understandable that predicting the occurrence and size of hail seems an impossible task. Through persistence, ingenuity and technology, scientists have made progress in understanding the key ingredients and processes at play. Technological advances mean that we can now, with some confidence, identify those storms that very likely contain hail and even estimate the maximum expected hail size on the ground hours in advance. Even so, there is still much we need to learn about the many intriguing aspects of hail growth.

Convective storms are the result of a disequilibrium created by solar heating in the presence of abundant low-level moisture, resulting in the development of buoyancy in ascending air. Buoyancy typically is measured by the Convective Available Potential Energy (CAPE) associated with air parcels. When CAPE is present in an environment with strong vertical wind shear (winds changing speed and/or direction with height), convective storms become increasingly organized and more likely to produce hazardous weather: strong winds, large hail, heavy precipitation, and tornadoes. Because of their associated hazards and their impact on society, in some nations (notably, the United States), there arose a need to have forecasts of convective storms. Pre-20th-century efforts to forecast the weather were hampered by a lack of timely weather observations and by the mathematical impossibility of direct solution of the equations governing the weather. The first severe convective storm forecaster was J. P. Finley, who was an Army officer, and he was ordered to cease his efforts at forecasting in 1887. Some Europeans like Alfred Wegener studied tornadoes as a research topic, but there was no effort to develop convective storm forecasting. World War II aircraft observations led to the recognition of limited storm science in the topic of convective storms, leading to a research program called the Thunderstorm Product that concentrated diverse observing systems to learn more about the structure and evolution of convective storms. Two Air Force officers, E. J. Fawbush and R. C. Miller, issued the first tornado forecasts in the modern era, and by 1953 the U.S. Weather Bureau formed a Severe Local Storms forecasting unit (SELS, now designated the Storm Prediction Center of the National Weather Service). From the outset of the forecasting efforts, it was evident that more convective storm research was needed. SELS had an affiliated research unit called the National Severe Storms Project, which became the National Severe Storms Laboratory in 1963. Thus, research and operational forecasting have been partners from the outset of the forecasting efforts in the United States—with major scientific contributions from the late T. T. Fujita (originally from Japan), K. A. Browning (from the United Kingdom), R. A. Maddox, J. M. Fritsch, C. F. Chappell, J. B. Klemp, L. R. Lemon, R. B. Wilhelmson, R. Rotunno, M. Weisman, and numerous others. This has resulted in the growth of considerable scientific understanding about convective storms, feeding back into the improvement in convective storm forecasting since it began in the modern era. In Europe, interest in both convective storm forecasting and research has produced a European Severe Storms Laboratory and an experimental severe convective storm forecasting group. The development of computers in World War II created the ability to make numerical simulations of convective storms and numerical weather forecast models. These have been major elements in the growth of both understanding and forecast accuracy. This will continue indefinitely.

Forecasting severe convective weather remains one of the most challenging tasks facing operational meteorology today, especially in the mid-latitudes, where severe convective storms occur most frequently and with the greatest impact. The forecast difficulties reflect, in part, the many different atmospheric processes of which severe thunderstorms are a by-product. These processes occur over a wide range of spatial and temporal scales, some of which are poorly understood and/or are inadequately sampled by observational networks. Therefore, anticipating the development and evolution of severe thunderstorms will likely remain an integral part of national and local forecasting efforts well into the future. Modern severe weather forecasting began in the 1940s, primarily employing the pattern recognition approach throughout the 1950s and 1960s. Substantial changes in forecast approaches did not come until much later, however, beginning in the 1980s. By the start of the new millennium, significant advances in the understanding of the physical mechanisms responsible for severe weather enabled forecasts of greater spatial and temporal detail. At the same time, technological advances made available model thermodynamic and wind profiles that supported probabilistic forecasts of severe weather threats. This article provides an updated overview of operational severe local storm forecasting, with emphasis on present-day understanding of the mesoscale processes responsible for severe convective storms, and the application of recent technological developments that have revolutionized some aspects of severe weather forecasting. The presentation, nevertheless, notes that increased understanding and enhanced computer sophistication are not a substitute for careful diagnosis of the current meteorological environment and an ingredients-based approach to anticipating changes in that environment; these techniques remain foundational to successful forecasts of tornadoes, large hail, damaging wind, and flash flooding.