This Level 2 Snowfall Rate (SFR) product provides liquid equivalent, instantaneous snowfall rate. SFR is derived from ATMS, AMSU-A, MHS, and GMI observations onboard the S-NPP, NOAA-20, NOAA-21, Metop-B, Metop-C, and GPM satellites. GMI has a resolution of 6 km while the other sensors are 16 km at nadir. SFR observations provide a snow signature through cloud cover that can be used to quantify snowfall intensity and to identify the extent of a snowstorm and the location of the most intense snowfall. SFR data is most useful for filling observational gaps in radar poor regions such as mountains and remote locations. SFR is derived from two algorithms: a machine learning snowfall detection model and an 1DVAR-based snowfall rate estimation algorithm which is further enhanced with machine learning models. Data files are provided for each of the six satellites listed above in the netCDF-4 file format. SFR data from S-NPP, NOAA-20 and NOAA-21 are packaged into 9 minute Tar files consisting of 18 (30 second) netCDF (nc) granules. SFR data from Metop-B (M01), Metop-C (M03), and GPM are not packaged into Tar files. These data are provided as full orbit nc files (MO1), half-orbit nc files (M03), and 5-minute nc files (GPM). SFR data is produced by the NOAA Office of Satellite and Product Operations and is distributed by the Comprehensive Large Array-Data Stewardship System (CLASS) in the netCDF-4 file format with metadata attributes included.
About this Dataset
Title | NOAA Level-2 Snowfall Rate (SFR) |
---|---|
Description | This Level 2 Snowfall Rate (SFR) product provides liquid equivalent, instantaneous snowfall rate. SFR is derived from ATMS, AMSU-A, MHS, and GMI observations onboard the S-NPP, NOAA-20, NOAA-21, Metop-B, Metop-C, and GPM satellites. GMI has a resolution of 6 km while the other sensors are 16 km at nadir. SFR observations provide a snow signature through cloud cover that can be used to quantify snowfall intensity and to identify the extent of a snowstorm and the location of the most intense snowfall. SFR data is most useful for filling observational gaps in radar poor regions such as mountains and remote locations. SFR is derived from two algorithms: a machine learning snowfall detection model and an 1DVAR-based snowfall rate estimation algorithm which is further enhanced with machine learning models. Data files are provided for each of the six satellites listed above in the netCDF-4 file format. SFR data from S-NPP, NOAA-20 and NOAA-21 are packaged into 9 minute Tar files consisting of 18 (30 second) netCDF (nc) granules. SFR data from Metop-B (M01), Metop-C (M03), and GPM are not packaged into Tar files. These data are provided as full orbit nc files (MO1), half-orbit nc files (M03), and 5-minute nc files (GPM). SFR data is produced by the NOAA Office of Satellite and Product Operations and is distributed by the Comprehensive Large Array-Data Stewardship System (CLASS) in the netCDF-4 file format with metadata attributes included. |
Modified | 2025-04-20T08:36:43.173Z |
Publisher Name | N/A |
Contact | N/A |
Keywords | Earth Science > Cryoshpere > Snow/Ice > Snowfall Rate , Geographic Region > Global Land , ATMS > Advanced Technology Microwave Sounder , MHS > Microwave Humidity Sounding , AMSU-A > Advanced Microwave Sounding Unit - A , GMI > GPM Microwave Imager , S-NPP > Suomi National Polar-orbiting Partnership , NOAA-20 > Joint Polar Satellite System - 1 , NOAA-21 > Joint Polar Satellite System - 2 , Metop-B > Meteorological operational satellite - B , Metop-C > Meteorological operational satellite - C , GPM > Global Precipitation Measurement , 16 km , DOC/NOAA/NESDIS/STAR > Center for Satellite Applications and Research, NESDIS, NOAA, U.S. Department of Commerce , DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce , DOC/NOAA/NESDIS/OSPO > Office of Satellite and Product Operations, NESDIS, NOAA, U.S. Department of Commerce , gov.noaa.class:PRECIP , climatologyMeteorologyAtmosphere |
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