Forecasting Mesoscale Snow Bands in Winter Storms: An R2O Success Story

As recently as the latter part of the 20th century, forecasters struggled to anticipate, diagnose, or even understand the cause and evolution of localized heavy snowfall within winter storms. Confused and frustrated forecasters would often find themselves playing catch-up as they received snowfall observations that exceeded current forecast amounts. The turn of the century brought a number of technological advances to observing and numerical weather prediction systems that facilitated new means to study and forecast these events. A national network of Doppler radars enabled new observations of the morphology of mesoscale snow bands within synoptic scale winter storms. New computational capabilities and associated advancements in global, regional, and local scale modeling systems resulted in not only improved real time operational forecasts, but also brought new possibilities for studying these snow bands. This enabled new understandings of the primary forcings and morphology of snow bands, and the development of new conceptual models. Similarly, the advancement of ensemble prediction systems brought the potential for additional insights into the predictability of these high impact events. However, to truly improve operational forecasts and enhance the information provided to critical transportation and emergency services decision makers, the advanced conceptual understanding developed through research activities needed to be integrated into operational forecast techniques and procedures.

Beginning in the late 1990s, a series of collaborative projects among university researchers and operational forecasters were undertaken to better understand mesoscale snow bands and their evolution, and to enhance forecasts and warnings for these events. Many of these projects were funded by the CSTAR (Cooperative Science, Technology and Applied Research) and COMET Outreach Programs. These efforts utilized a collaborative process of collecting and analyzing case studies and developing climatologies, exploring and testing hypotheses, formulating conceptual models that were easily adaptable within operational forecast techniques and paradigms, and the development of formal documentation (conference presentations and refereed journal articles) and training materials, to achieve beneficial research results that were successfully transitioned into operations. This paper will illustrate how these efforts directly resulted in substantial improvements to forecasts and decision support services during winter storms.