Can accounting for secondary ice production improve weather forecasts? This study examines the impact of secondary ice production (SIP) on simulating freezing rain (FR) events, finding that parameterized SIP substantially reduces FR due to increased collection of supercooled drops with ice particles, which leads to improved forecast skill relative to observations. Explicit freezing rain (FR) at the surface is often overestimated during the winter season for situations in which snow is observed. Simulations of 40 winter cases show that these results are systematic, and the decreased frequency of FR leads to improved forecast skill relative to observations. Accounting for SIP in the model is critical for accurately simulating precipitation types in winter storms.
Published in Geophysical Research Letters, this study aligns with the journal’s focus on timely and significant research in Earth and space sciences, which is an important factor in accurately simulating precipitation types. The findings are relevant to researchers in geophysics, meteorology, and atmospheric science, but has been a challenge due to the complicated underlying microphysical and dynamical processes.