Data for Modeled Spatiotemporal Distributions of Airborne Allergenic Pollen CONUS

This dataset consists of a file describing the U.S. EPA data used in Ren et al. (2022), Modeling Past and Future Spatiotemporal Distributions of Airborne Allergenic Pollen across the Contiguous United States. This dataset is not publicly accessible because: The size of this meteorological input dataset (nearly 300 gigabytes) is too large for the ScienceHub portal. It can be accessed through the following means: Data are archived on the EPA High-Performance Environmental Supercomputing Center (HESC) Archival Storage Management (ASM) system under the directory /asm/cnolte/project/xren2022. Format: Data are in the Unidata Network Common Data Form (NetCDF). The names of each NetCDF variable and its associated units are provided within the dataset itself. Further information about the NetCDF format is available from Unidata at www.unidata.ucar.edu/netcdf. This dataset is associated with the following publication: Ren, X., T. Cai, Z. Mi, L. Bielory, C. Nolte, and P. Georgopoulos. Modeling Past and Future Spatiotemporal Distributions of Airborne Allergenic Pollen across the Contiguous United States. Frontiers in Allergy. Frontiers, Lausanne, SWITZERLAND, 3: 959594, (2022).

                                            [
  "020:00"
]
                                        

                                            {
  "fn": "Christopher Nolte",
  "hasEmail": "mailto:nolte.chris@epa.gov"
}
                                        

                                            []
                                        

                                            [
  "CMAQ",
  "Mesoscale meteorology",
  "climate change"
]
                                        

                                            [
  "020:000"
]
                                        

                                            {
  "name": "U.S. EPA Office of Research and Development (ORD)",
  "subOrganizationOf": {
    "name": "U.S. Environmental Protection Agency",
    "subOrganizationOf": {
      "name": "U.S. Government"
    }
  }
}
                                        

                                            [
  "https://doi.org/10.3389/falgy.2022.959594",
  "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9640548"
]
                                        

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