sdatmospheric 0.1.1

Easy lat/lon/altitude queries against NOAA HRRR/GFS weather data for rocketry.

SDAtmospheric

This package allows for arbitrary data decoding for variables related to high powered rocketry by querying HRRR and GFS data above the continental united states

Install

You can install SDAtmospheric using the PyPI package registry:

pip install sdatmospheric

If the installation fails due to the eccodes library missing, see the manual installation instructions below!

Installing eccodes

cfgrib needs the eccodes C library. Easiest on conda-forge:

conda install -c conda-forge eccodes cfgrib herbie-data
pip install -e .

Pip-only (Linux/macOS or recent Windows with eccodes wheels):

pip install eccodes
pip install -e .

Basic usage

The SDAtmospheric API is built around the Atmosphere class, which represents a snapshot of the atmospheric model above the continental US at any given time. The Atmosphere class provides only two methods:

from sdatmospheric import Atmosphere
atmos = Atmosphere()

atmos.q(LATITUDE, LONGITUDE)        # Returns a `State` function closure (described below)
atmost.preload(LATITUDE, LONGITUDE) # Preloads a certain GRIB grid square around a given point

In reality, the Atmosphere class is lazy, and only loads wind data for the times and the regions directly queried by the host application. Because GRIB downloads and decoding is an involved process, we implement the use of 2 caching levels:

• Hot Caching, where the data for a given location is stored within program memory, so queries within a region that is hot cached requires only a program memory lookup (~50ms)
• Warm Caching, which will store GRIB regions on disk and allow for a relatively quick disk lookup rather than a redownload from the NOAA servers (~3s)

Full cache misses will trigger a download from the NOAA servers, which (depending on server traffic) can take a few minutes.

State Return

The return type of Atmosphere.q is a State-returning function closure. This means that Atmosphere.q returns a function f that, given an altitude, returns a State object.

class State(NamedTuple):
    u: float        # east wind, m/s
    v: float        # north wind, m/s
    T: float        # K
    rho: float      # kg/m^3
    P: float        # Pa
    mach_v: float   # m/s, speed of sound

Models

Atmosphere(model="hrrr") # 3km spatial resolution, 1h temporal up to 48h, 20km ceiling
Atmosphere(model="gfs") # 0.25 degree spatial resolution, 6h temporal up to 384h, 50km ceiling 
Atmosphere(model="blend") # Blends between the hrrr and gfs models
Atmosphere(model="blend", blend_range=(15_000, 19_000)) # Adjusable blending range (default 17km)

Forecasting

The analysis time defaults to the latest available analysis for the given model. This can be overridden to provide future (and past) analyses of weather data at a location.

Atmosphere(time="2025-08-03T12:00Z") # Specific time
Atmosphere(forecast_hours=3) # Forecast 3h in the future

Conventions

• Altitude: MSL by default. alt_ref="agl" subtracts surface elevation at the query point.
• Longitude: accept within CONUS
• Ceiling: altitudes above the top pressure level emit a UserWarning and extrapolate based on a linear fit
• Cache: herbie stores subset GRIBs under ~/data/ by default, and can be overridden with cache_dir=....