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 2023.

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 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.

The GPM Ground Validation Autonomous Parsivel Unit (APU) OLYMPEX dataset was collected during the OLYMPEX field campaign held at Washington's Olympic Peninsula during the intense observation period of November 2015 to the end of January 2016. The dataset consists of data collected by 16 APUs. The APU is an optical laser-disdrometer based on single particle extinction that measures particle size and fall velocity. It consists of the Parsivel2 developed by OTT in Germany and supporting hardware developed by University of Alabama. This APU dataset provides 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.

The Advanced Vertical Atmospheric Profiling System (AVAPS) IMPACTS dataset consists of vertical atmospheric profile measurements collected by the Advanced Vertical Atmospheric Profiling System (AVAPS) dropsondes released from the NASA P-3 aircraft 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. AVAPS uses a Global Positioning System (GPS) dropsonde to measure atmospheric state parameters (temperature, humidity, wind speed/direction, pressure) and location in 3-dimensional space during the dropsonde’s descent. The AVAPS dataset files are available from January 12, 2020, through February 28, 2023, in ASCII-ict format.

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 Advanced Vertical Atmospheric Profiling System (AVAPS) IMPACTS dataset consists of vertical atmospheric profile measurements collected by the Advanced Vertical Atmospheric Profiling System (AVAPS) dropsondes released from the NASA P-3 aircraft 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. AVAPS uses a Global Positioning System (GPS) dropsonde to measure atmospheric state parameters (temperature, humidity, wind speed/direction, pressure) and location in 3-dimensional space during the dropsonde’s descent. The AVAPS dataset files are available from January 12, 2020 through February 25, 2022 in ASCII-ict format.

The AAMH CPEX dataset contains products obtained from the MetOp-A, MetOp-B, NOAA-18, and NOAA-19 satellites. These data were collected in support of the NASA Convective Processes Experiment (CPEX) field campaign. The CPEX field campaign took place in the North Atlantic-Gulf of America-Caribbean Sea region from 25 May to 25 June 2017. CPEX conducted a total of sixteen DC-8 missions from 27 May to 24 June. The CPEX campaign collected data to help explain convective storm initiation, organization, growth, and dissipation in the North Atlantic-Gulf of America-Caribbean Oceanic region during the early summer of 2017. These data are available from May 26, 2017, through July 15, 2017, and are available in netCDF-4 format.

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 March 1, 2023, 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.