The UAlbany Parsivel IMPACTS dataset consists of precipitation data collected by a Parsivel2 disdrometer in support of the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. IMPACTS was a three-year sequence of winter season deployments conducted to study snowstorms over the U.S Atlantic Coast (2020-2023). The campaign aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to significantly advance prediction capabilities. The Parsivel disdrometer data include particle size distribution, fall speed, radar reflectivity and precipitation rate. The dataset files are available in netCDF-4 format from 30 January 2020 through 28 February 2022.

The SBU Parsivel IMPACTS dataset consists of precipitation data collected by the Parsivel disdrometer in support of the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. IMPACTS was a three-year sequence of winter season deployments conducted to study snowstorms over the U.S Atlantic Coast (2020-2022). The campaign aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to significantly advance prediction capabilities. The Parsivel disdrometer data include particle size distribution, fall speed, radar reflectivity and precipitation rate. The dataset files are available in netCDF-3 format from January 1 through February 27, 2020.

The Autonomous Parsivel Unit (APU) IMPACTS data were collected in support of the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. The IMPACTS field campaign addressed providing observations critical to understanding the mechanisms of snowband formation, organization, and evolution, examining how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands, and improving snowfall remote sensing interpretation and modeling to significantly advance prediction capabilities. This dataset consists of precipitation data including precipitation amount, precipitation rate, reflectivity in Rayleigh regime, liquid water content, drop diameter, and drop concentration. Data are available in ASCII format from January 15, 2020 through February 29, 2020.

The SBU Parsivel IMPACTS dataset consists of precipitation data collected by the Parsivel disdrometer in support of the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. IMPACTS was a three-year sequence of winter season deployments conducted to study snowstorms over the U.S. Atlantic Coast (2020-2023). The campaign aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to significantly advance prediction capabilities. The Parsivel disdrometer data include particle size distribution, fall speed, radar reflectivity, and precipitation rate. The dataset files are available in netCDF-3 format from January 1, 2020, through March 2, 2023.

The SBU Pluvio Precipitation Gauge IMPACTS dataset consists of precipitation intensity and precipitation accumulation collected using the OTT Pluvio2 weighing rain gauge during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. Funded by NASA’s Earth Venture program, IMPACTS is the first comprehensive study of East Coast snowstorms in 30 years. The campaign aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to significantly advance prediction capabilities. Data files in this dataset are available in ASCII-csv format from January 7, 2020 through February 27, 2020.

The Mission Reports IMPACTS dataset consists of flight plans, plans of the day, science plans, and science summaries logged by scientists during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. IMPACTS was a three-year sequence of winter season deployments conducted to study snowstorms over the U.S Atlantic Coast (2020-2022). The campaign aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to significantly advance prediction capabilities. The mission reports are available from January 17 through March 1, 2020 in PDF format. It should be noted that this dataset will be updated in subsequent years of the IMPACTS campaign.

The UND Cloud Microphysics IMPACTS dataset consists of cloud particle measurements collected during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. IMPACTS was a three-year sequence of winter season deployments conducted to study snowstorms over the U.S Atlantic Coast (2020-2023). The campaign aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to significantly advance prediction capabilities. The UND Cloud Microphysics IMPACTS dataset files are stored in ASCII format from January 25, 2020 through February 26, 2020, and from January 6, 2022 through February 25, 2022.

The Automated Surface Observing Systems (ASOS) IMPACTS dataset consists of a variety of ground-based observations during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. IMPACTS was a three-year sequence of winter season deployments conducted to study snowstorms over the U.S Atlantic coast. IMPACTS aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to significantly advance prediction capabilities. This ASOS dataset consists of 176 stations within the IMPACTS domain. Each station provides observations of surface temperature, dew point, precipitation, wind direction, wind speed, wind gust, sea level pressure, and the observed weather code. The ASOS data are available from December 29, 2019 through February 29, 2020 in netCDF-4 format.

The GPM Ground Validation Autonomous Parsivel Unit (APU) MC3E dataset was collected by the Autonomous Parsivel Unit (APU), which is an optical disdrometer that measures the size and fall velocity of single precipitation particles. The APU consists of the Parsivel (the precipitation measuring instrument), developed by OTT in Germany, and its support systems, which were designed and built by the University of Alabama in Huntsville. The APU dataset for the Midlatitude Continental Convective Clouds Experiment (MC3E) provides precipitation data including raindrop size, precipitation drop size, precipitation rate and amount. The Midlatitude Continental Convective Clouds Experiment (MC3E) took place in central Oklahoma during the April-June 2011 period. The experiment was a collaborative effort between the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility and the National Aeronautics and Space Administration's (NASA) Global Precipitation Measurement (GPM) mission Ground Validation (GV) program. The field campaign leveraged the unprecedented observing infrastructure currently available in the central United States, combined with an extensive sounding array, remote sensing and in situ aircraft observations, NASA GPM ground validation remote sensors, and new ARM instrumentation purchased with American Recovery and Reinvestment Act funding. The overarching goal was to provide the most complete characterization of convective cloud systems, precipitation, and the environment that has ever been obtained, providing constraints for model cumulus parameterizations and space-based rainfall retrieval algorithms.

The GPM Ground Validation Autonomous Parsivel Unit (APU) ICE POP dataset was collected during the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic Winter Games (ICE POP) field campaign in South Korea. The two major objectives of ICE POP were to study severe winter weather events in regions of complex terrain and improve the short-term forecasting of such events. These data contributed to Global Precipitation Measurements mission Ground Validation (GPM GV) campaign efforts to improve satellite estimates of orographic winter precipitation. This dataset consists of precipitation data including precipitation amount, precipitation rate, reflectivity in Rayleigh regime, liquid water content, drop diameter, and drop concentration. Data are available in ASCII format from October 31, 2015 through July 1, 2018. It should be noted that this dataset extends prior to the field campaign.