The effectiveness of cloud seeding for hail suppression is evaluated as conducted by the North Dakota Cloud Modification Project. A total of 88 Western North Dakota convective storm cases from 2016-2018 that include both seeded and unseeded storms are analyzed using a radar-based hail size retrieval algorithm. The algorithm determined hail sizes are compared to forecasted hail sizes derived from proximity sounding analysis from the Weather Research and Forecasting (WRF) model. Hail was placed into one of three bins: no hail, hail less than 2 inches in diameter, and hail greater than 2 inches in diameter. Model analysis includes two hail-centric indices, five severe weather indices, and the HAILCAST model. Results show strong agreement between forecasted and observed hail sizes in unseeded cases with 56 percent of cases matching hail size bins for both the forecast and radar-derived observation. In contrast, seeded storms showed less than 50 percent of cases had matching hail sizes. Rather, seeded cases consistently produced radar derived hail sizes smaller than forecasted hail sizes in 20.8 percent more cases than the unseeded category, indicating a hail suppression effect. The hail suppression is statistically significant at the 90 percent confidence level, with a p-value of 0.079. These findings support the potential of cloud seeding to mitigate hail damage and enhance agricultural resilience in Western North Dakota.
Bestul et al. (Sun,) studied this question.
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