API

No documentation found for public binding RapidRefreshData.AbstractDataset.

Summary

abstract type RapidRefreshData.AbstractDataset

Subtypes

RapidRefreshData.GFSDataset
RapidRefreshData.HRRRDataset
RapidRefreshData.RAPDataset
Band

Information about a GRIB2 band/variable from an index file.

Fields

  • line_number::Int: Line number in GRIB2 file
  • byte_offset::Int: Starting byte position
  • date::String: Date string (format: d=YYYYMMDDHH)
  • variable::String: Variable name (e.g., “TMP”, “UGRD”, “VGRD”)
  • level::String: Level description (e.g., “10 m above ground”, “surface”)
  • forecast_type::String: Forecast type (e.g., “anl”, “0-1 hour”)
GFSDataset(; date, cycle, resolution, product, forecast)

NOAA Global Forecast System (GFS) dataset descriptor.

Fields

  • date::Date: Forecast initialization date (default: today)
  • cycle::String: Model run time - “00”, “06”, “12”, or “18” (default: “00”)
  • resolution::String: Grid resolution - “0p25” (0.25°), “0p50” (0.50°), or “1p00” (1.00°) (default: “0p25”)
  • product::String: Product type - “atmos” or “wave” (default: “atmos”)
  • forecast::String: Forecast hour - “f000” to “f384” (default: “f000”)
HRRRDataset(; date, cycle, region, product, forecast)

NOAA High-Resolution Rapid Refresh (HRRR) dataset descriptor.

Fields

  • date::Date: Forecast initialization date (default: today)
  • cycle::String: Model run hour - “00” to “23” (default: “00”)
  • region::String: Geographic region - “conus” (Continental US) or “alaska” (default: “conus”)
  • product::String: Product type - “wrfsfc” (surface), “wrfprs” (pressure), “wrfnat” (native), or “wrfsub” (subhourly) (default: “wrfsfc”)
  • forecast::String: Forecast hour - “f00” to “f48” (default: “f00”)
RAPDataset(; date, cycle, grid, product, forecast)

NOAA Rapid Refresh (RAP) dataset descriptor.

Fields

  • date::Date: Forecast initialization date (default: today)
  • cycle::String: Model run time - “t00z”, “t06z”, “t12z”, or “t18z” (default: “t00z”)
  • grid::String: Grid resolution - “awp130” (~13km) or “awp252” (~32km) (default: “awp130”)
  • product::String: Data type - “pgrb” (pressure), “sfcbf” (surface), or “isobf” (isentropic) (default: “pgrb”)
  • forecast::String: Forecast hour - “f00” to “f18” (default: “f00”)
bands(dset::AbstractDataset) -> Vector{Band}

Fetch and parse the index file to list all available bands/variables in the dataset.

Example

dset = HRRRDataset(date=Date(2024,1,15), cycle="12")
bands_list = bands(dset)
# Find wind variables
wind_bands = filter(b -> contains(b.variable, "GRD") && contains(b.level, "10 m"), bands_list)

No documentation found for public binding RapidRefreshData.clear_cache!!.

RapidRefreshData.clear_cache!! is a Function.

# 1 method for generic function "clear_cache!!" from RapidRefreshData:
 [1] clear_cache!!()
     @ ~/work/RapidRefreshData.jl/RapidRefreshData.jl/src/RapidRefreshData.jl:74
datasets(::Type{T}, start::DateTime, stop::DateTime) where {T <: AbstractDataset}

Return a Vector of all datasets of type T that cover the time period from start to stop.

Each dataset represents one model cycle (initialization time). The function returns all cycles whose initialization time falls within the specified range.

Examples

using Dates

# Get all HRRR datasets for a 6-hour window (hourly cycles)
datasets(HRRRDataset, DateTime(2024,1,15,0), DateTime(2024,1,15,6))

# Get all RAP datasets for a day (6-hourly cycles)
datasets(RAPDataset, DateTime(2024,1,15), DateTime(2024,1,16))

# Get all GFS datasets for a day (6-hourly cycles)
datasets(GFSDataset, DateTime(2024,1,15), DateTime(2024,1,16))
index_url(dset::AbstractDataset) -> String

Get the URL for the GRIB2 index file (.idx) corresponding to the dataset.

No documentation found for public binding RapidRefreshData.list.

RapidRefreshData.list is a Function.

# 1 method for generic function "list" from RapidRefreshData:
 [1] list(::Type{T}) where T<:RapidRefreshData.AbstractDataset
     @ ~/work/RapidRefreshData.jl/RapidRefreshData.jl/src/RapidRefreshData.jl:72
local_path(dset::AbstractDataset) -> String

Generate local cache path for the dataset based on its parameters.

metadata() -> NamedTuple

Return a table of dataset types with their field options and descriptions.

Example

meta = metadata()
meta.RAPDataset  # Options for RAPDataset
nextcycle(dset::RAPDataset) -> RAPDataset

Return a new RAPDataset with the cycle incremented to the next available cycle. Cycles progress: t00z -> t06z -> t12z -> t18z -> t00z (next day).

Example

dset = RAPDataset(date=Date(2024,1,15), cycle="t12z")
next = nextcycle(dset)  # Date(2024,1,15), cycle="t18z"

dset = RAPDataset(date=Date(2024,1,15), cycle="t18z")
next = nextcycle(dset)  # Date(2024,1,16), cycle="t00z"
nextcycle(dset::GFSDataset) -> GFSDataset

Return a new GFSDataset with the cycle incremented to the next available cycle. Cycles progress: 00 -> 06 -> 12 -> 18 -> 00 (next day).

Example

dset = GFSDataset(date=Date(2024,1,15), cycle="12")
next = nextcycle(dset)  # Date(2024,1,15), cycle="18"

dset = GFSDataset(date=Date(2024,1,15), cycle="18")
next = nextcycle(dset)  # Date(2024,1,16), cycle="00"
nextcycle(dset::HRRRDataset) -> HRRRDataset

Return a new HRRRDataset with the cycle incremented to the next hour. Cycles progress: 00 -> 01 -> 02 -> … -> 23 -> 00 (next day).

Example

dset = HRRRDataset(date=Date(2024,1,15), cycle="12")
next = nextcycle(dset)  # Date(2024,1,15), cycle="13"

dset = HRRRDataset(date=Date(2024,1,15), cycle="23")
next = nextcycle(dset)  # Date(2024,1,16), cycle="00"
resolution_km(dset::AbstractDataset) -> Float64

Return the approximate grid resolution in kilometers for the dataset.

Examples

resolution_km(RAPDataset(grid="awp130"))  # 13.0
resolution_km(RAPDataset(grid="awp252"))  # 32.0
resolution_km(GFSDataset(resolution="0p25"))  # 28.0
resolution_km(HRRRDataset())  # 3.0
url(dset::RAPDataset) -> String

Generate AWS S3 URL for the RAP dataset.

url(dset::GFSDataset) -> String

Generate AWS S3 URL for the GFS dataset.

url(dset::HRRRDataset) -> String

Generate AWS S3 URL for the HRRR dataset.