Skip to main content

Download and process NCEP GFS 0.25° data via ASCII interface

Reason this release was yanked:

NOAA Opendap is discontinued

Project description

ncep-data-req

Download and preprocess NCEP GFS 0.25° atmospheric forecast data from NOAA using ASCII interface.

Overview

This package provides utility functions to directly download and preprocess Global Forecast System (GFS) 0.25-degree resolution data from the NOAA NOMADS server. It supports extraction of pressure-level and surface-level variables for specific forecast hours, structured into usable xarray.Dataset objects.

Features

  • Access GFS 0.25° forecast data from NOAA
  • Support for both pressure-level and surface variables
  • Handles multiple or single forecast hours
  • Outputs structured xarray.Dataset objects for easy analysis

Installation

You can install the package from PyPI (after publishing):

pip install ncep_data_req

from ncep_data_req import get_data_preprocess, get_data_preprocess_s

# Example: Download temperature on pressure levels for 6 forecast hours
ds = get_data_preprocess(
    '2025-05-23', utc=0, ft=6, var='tmpprs', pvar='yes',lon_range=(45,90),lat_range=(10,20)
)

# Example: Download temperature on surface level for 6 forecast hours
ds = get_data_preprocess(
    '2025-05-23', utc=0, ft=6, var='pratesfc', pvar='no',lon_range=(45,90),lat_range=(10,20)
)




# Example: Download  variable at single forecast hour
ds_surface = get_data_preprocess_s(
    '2025-05-23', utc=0, ft=6, var='tmpprs', pvar='yes',lon_range=(45,90),lat_range=(10,20)
)


# Example: Download  variable on surface level at single forecast hour
ds = get_data_preprocess(
    '2025-05-23', utc=0, ft=6, var='pratesfc', pvar='no',lon_range=(45,90),lat_range=(10,20)
)


Parameters
Longitude: 0.00000000000°E to 359.75000000000°E (1440 points, avg. res. 0.25°)
Latitude: -90.00000000000°N to 90.00000000000°N (721 points, avg. res. 0.25°)
Altitude: 1000.00000000000 to 20. (26 points, )

utc: Initialization hour (0, 6, 12, or 18 UTC)

ft: Forecast hour (0 to 384 depending on GFS run)

var: GFS variable name (e.g., tmpprs, rhprs, ugrdprs, etc.)

pvar: 'yes' if pressure-level variable, 'no' for surface

Output
Returns an xarray.Dataset containing:

Dimensions: time/levels, lat, lon

Coordinates: pressure levels, lat/lon grid

Data variables: selected GFS variable 
check this link ( https://nomads.ncep.noaa.gov/dods/gfs_0p25_1hr/)


contact:subhrjitrath17@gmail.com

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ncep_data_req-0.1.2.3-py3-none-any.whl (4.3 kB view details)

Uploaded Python 3

File details

Details for the file ncep_data_req-0.1.2.3-py3-none-any.whl.

File metadata

File hashes

Hashes for ncep_data_req-0.1.2.3-py3-none-any.whl
Algorithm Hash digest
SHA256 137eff597d98b07cff57e447b506be8d807fd110b56b4b6cea96e6b7fdb3ac5f
MD5 a2d1123a77a07dd2bbf8e17f70e67e9c
BLAKE2b-256 c57a7643afed268bb06aa79224ea196e05b0c73ba36de848e4b7ab5c7465f0ac

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page