Detailed Record



P-Type Processes and Predictability: The Winter Precipitation Type Research Multiscale Experiment (WINTRE-MIX)


Abstract During near-0°C surface conditions, diverse precipitation types (p-types) are possible, including rain, drizzle, freezing rain, freezing drizzle, ice pellets, wet snow, snow, and snow pellets. Near-0°C precipitation affects wide swaths of the United States and Canada, impacting aviation, road transportation, power generation and distribution, winter recreation, ecology, and hydrology. Fundamental challenges remain in observing, diagnosing, simulating, and forecasting near-0°C p-types, particularly during transitions and within complex terrain. Motivated by these challenges, the field phase of the Winter Precipitation Type Research Multiscale Experiment (WINTRE-MIX) was conducted from 1 February to 15 March 2022 to better understand how multiscale processes influence the variability and predictability of p-type and amount under near-0°C surface conditions. WINTRE-MIX took place near the U.S.–Canadian border, in northern New York and southern Quebec, a region with plentiful near-0°C precipitation influenced by terrain. During WINTRE-MIX, existing advanced mesonets in New York and Quebec were complemented by deployment of 1) surface instruments, 2) the National Research Council Convair-580 research aircraft with W- and X-band Doppler radars and in situ cloud and aerosol instrumentation, 3) two X-band dual-polarization Doppler radars and a C-band dual-polarization Doppler radar from the University of Illinois, and 4) teams collecting manual hydrometeor observations and radiosonde measurements. Eleven intensive observing periods (IOPs) were coordinated. Analysis of these WINTRE-MIX IOPs is illuminating how synoptic dynamics, mesoscale dynamics, and microscale processes combine to determine p-type and its predictability under near-0°C conditions. WINTRE-MIX research will contribute to improving nowcasts and forecasts of near-0°C precipitation through evaluation and refinement of observational diagnostics and numerical forecast models.
Authors Justin R. Minder ORCID , Nick P. Bassill ORCID , Frédéric Fabry , Jeffrey R. French University of WyomingORCID , Katja Friedrich , Ismail Gültepe ORCID , John R. Gyakum ORCID , David E. Kingsmill ORCID , Karen Kosiba ORCID , Mathieu Lachapelle ORCID , Daniel Michelson ORCID , Leonid Nichman ORCID , Cuong M. Nguyen ORCID , Julie M. Thériault ORCID , Andrew C. Winters ORCID , Mengistu Wolde ORCID , Joshua Wurman
Journal Info American Meteorological Society | Bulletin of the American Meteorological Society , vol: 104 , iss: 8 , pages: E1469 - E1492
Publication Date 8/1/2023
ISSN 0003-0007
TypeKeyword Image article
Open Access bronze Bronze Access
DOI https://doi.org/10.1175/bams-d-22-0095.1
KeywordsKeyword Image Climate Modeling (Score: 0.551421) , Probabilistic Forecasting (Score: 0.520903) , Precipitation Extremes (Score: 0.509155)