easysnowdata

A Python package to easily retrieve data relevant to snow science.

easysnowdata unifies access to a wide range of snow-relevant geospatial datasets — weather stations, satellite imagery, climate reanalysis, DEMs, and more — under a consistent API that returns xarray objects. The emphasis is on minimising downloads and local computation by leveraging cloud-optimised data formats wherever possible.

Gallery

One executed script per product — browse them, each with the code, the figure and a downloadable notebook.

Data Source Status

Every route of every product is probed weekly. A failure opens an issue labelled data-source and a recovery closes it; latency and DMR++ readiness are on the status page.

Last updated: 2026-09-17 21:39 UTC
⚠️ = skipped (credentials not available in this run). Latency and virtualization probes are on the status page.

Installation

pip install easysnowdata

conda install -c conda-forge easysnowdata

mamba install -c conda-forge easysnowdata

Development install (with pixi)

git clone https://github.com/egagli/easysnowdata.git
cd easysnowdata
pixi install          # sets up the environment
pixi run test-unit    # offline tests (no network, no credentials)
pixi run test-live    # live tests against the data providers (credentialed ones skip without secrets)
pixi run docs-serve   # preview the docs locally

Services that require account setup

Some data sources need free accounts and credentials passed as environment variables:

Planetary Computer and anonymous GCS access require no credentials.

What is in it

28 products across 8 themes, each with one or more access routes:

Every product's routes, resolution, credentials, licence and health are on its own page: https://egagli.github.io/easysnowdata/catalog/.

Quick Start

import easysnowdata as esd

aoi = (-121.94, 46.72, -121.54, 46.99)          # Mount Rainier; any AOI form works

# Snow stations: which are here, then one water year of observations
inv = esd.stations.inventory(aoi, daily_only=True)
obs = esd.stations.load(inv, variables=["swe", "snwd"], time="2023-10/2024-09")

# Terrain, SAR and snow water equivalent — lazy, Dask-backed, CRS attached
dem = esd.terrain.dem.load(aoi)                             # Copernicus GLO-30
s1 = esd.sar.sentinel1.load(aoi, "2024-03", units="dB")     # Sentinel-1 RTC
swe = esd.snow.snodas.load(aoi, "2024-03")                  # SNODAS, no account

# Optical, masked and turned into a snow index
s2 = esd.optical.sentinel2.load(aoi, "2024-03", mask="scl-default")
ndsi = esd.processing.ndsi(s2)

# Categorical products carry CF flag attrs, so the legend draws itself
esd.plotting.categorical(esd.land.landcover.load(aoi))

# What is available, and what it needs
esd.catalog.search("swe")
esd.catalog.describe("snodas")
esd.auth.status()

The pre-0.1 API (easysnowdata.remote_sensing.get_*, automatic_weather_stations.StationCollection, …) still works and emits a DeprecationWarning naming its replacement. It is removed one minor release after 0.1.

Documentation

Full API reference and example notebooks: https://egagli.github.io/easysnowdata

Contributing

Contributions welcome! See CONTRIBUTING for guidelines.

Citing

If you use easysnowdata in your research, please cite the Zenodo archive: