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  • A Comprehensive Northern Hemisphere Particle Microphysics Dataset from the Precipitation Imaging Package

    work
    Creator:
    King, Fraser and Pettersen, Claire
    Description:
    Microphysical observations of precipitating particles are crucial for numerical weather prediction models and remote sensing retrieval algorithms. This dataset provides a unified, comprehensive collection of particle microphysical observations from the Precipitation Imaging Package (PIP) over the Northern Hemisphere. Data spans from 2014-2023 across 10 measurement sites and encompasses over 775 thousand precipitating minutes. Within this dataset, users will find a range of microphysical attributes for rain and snow, along with higher-order products.
    Keyword:
    precipitation, imaging, package, PIP, snowfall, rainfall, disdrometer, particle, microphysics
    Discipline:
    Other

  • Merged and Gridded GPM and Atmospheric River Data Product

    work
    Creator:
    Mateling, Marian E. and Pettersen, Claire
    Description:
    This merged Global Precipitation Measurement (GPM) Core Observatory and atmospheric river dataset contains gridded Goddard Profiling (GPROF) algorithm v7 precipitation rates (Kummerow et al. 2015; Randel et al. 2020), Remote Sensing Systems (RSS) atmospheric water vapor (Meissner et al. 2012), and Mattingly et al. (2018) atmospheric rivers in the North Atlantic and North Pacific oceans. The GPROF precipitation rates and RSS atmospheric water vapor are both derived using the GPM Microwave Imager (GMI) brightness temperature observations. The atmospheric river data is derived from MERRA-2 (Modern-Era Retrospective analysis for Research and Applications Reanalysis, Version 2) integrated water vapor transport (Mattingly et al. 2018). , The data coverage starts at the beginning of the GPM data record (GPM launched in Feb 2014 and the processed data coverage starts in May 2014). Subsequent years will be added throughout the lifetime of the project. , The monthly files are compressed into year and basin: either the North Atlantic (NA) or the North Pacific (NP) (e.g., NA_2014) and zipped. The files have the basin name indicated and are by year and month (e.g., gridded_atlantic_201405.nc). The files produced are in NetCDF format ( https://www.unidata.ucar.edu/software/netcdf/) and conform to all standard NetCDF metadata conventions ( http://cfconventions.org/cf-conventions/cf-conventions.html), and Kummerow, C. D., Randel, D. L., Kulie, M., Wang, N. Y., Ferraro, R., Joseph Munchak, S., & Petkovic, V. (2015). The evolution of the Goddard profiling algorithm to a fully parametric scheme. Journal of atmospheric and oceanic technology, 32(12), 2265-2280.  https://doi.org/10.1175/JTECH-D-15-0039.1 Mattingly, K. S., Mote, T. L., & Fettweis, X. (2018). Atmospheric river impacts on Greenland Ice Sheet surface mass balance. Journal of Geophysical Research: Atmospheres, 123(16), 8538-8560.  https://doi.org/10.1029/2018JD028714 Meissner, T., F. J. Wentz, and D. Draper, 2012: GMI Calibration Algorithm and Analysis Theoretical Basis Document, Remote Sensing Systems, Santa Rosa, CA, report number 041912, 124 pp. Randel, D. L., Kummerow, C. D., & Ringerud, S. (2020). The Goddard Profiling (GPROF) precipitation retrieval algorithm. Satellite Precipitation Measurement: Volume 1, 141-152.  https://doi.org/10.1007/978-3-030-24568-9_8
    Keyword:
    Precipitation, satellite, microwave radiometer, atmospheric water vapor, and remote sensing
    Citation to related publication:
    Mateling et al., submitted to Earth and Space Science (updated when finalized)
    Discipline:
    Science