Accompanying Dataset for "Assimilating NASA IMPACTS Data for 7 Feb 2020 Storm to Improve Winter Cyclone Prediction"

Accurate and timely forecasts for winter cyclones and their snowfall remains challenging, even with recent advancements in modeling and data assimilation. This research investigates the potential improvements from data assimilation of novel ER-2 and P-3 aircraft observations from the 2020-2023 NASA Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. This data is assimilated by the PSU-EnKF into five WRF model experiments simulating a 7 February 2020 Nor'easter to determine the resulting alterations to meteorological fields, focusing on mesoscale precipitation structures as observed in radar reflectivity. Results are assessed through qualitative comparison, five key quantitative error metrics, and algorithmic snowband tracking via single-linkage clustering and image registration. When comparing to WSR-88D radar reflectivity, there is a consistent small improvement to the numerical accuracy of the IMPACTS-assimilating experiment, especially in the NW quadrant of the storm; difference from a control experiment is statistically significant in 45% of examined instances. This effect is created by an increase in temperature and moisture over southeast NY, with realism evaluated relative to field campaign soundings. Snow accumulation is shifted accordingly, with neutral impact in accuracy relative to a NOAA analysis. A novel tracking algorithm is demonstrated via this case study in the companion paper to this study.