The NASA Global Hydrology Resource Center (GHRC) DAAC published the SBU Meteorological Station IMPACTS dataset. This dataset consists of weather station data collected at two Stony Brook University (SBU) weather stations (1 mobile radar truck and 1 stationary site in Manhattan, New York City, New York) 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 surface meteorological data variables include temperature, dew point, relative humidity, absolute humidity, mixing ratio, air pressure, windspeed, and wind direction. The dataset files are available from January 1 through February 27, 2020 in netCDF-4 and ASCII-CSV formats.GHRC Published SBU Meteorological Station IMPACTS dataset
The NASA Global Hydrology Resource Center (GHRC) DAAC published the SBU Meteorological Station IMPACTS dataset. This dataset consists of weather station data collected at two Stony Brook University (SBU) weather stations (1 mobile radar truck and 1 stationary site in Manhattan, New York City, New York) 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 surface meteorological data variables include temperature, dew point, relative humidity, absolute humidity, mixing ratio, air pressure, windspeed, and wind direction. The dataset files are available from January 1 through February 27, 2020 in netCDF-4 and ASCII-CSV formats.
