The Snow Microwave Radiative Transfer (SMRT) model is a highly modular model to compute the thermal emission and backscattering coefficient of snowpacks and other cryospheric bodies in the microwave domain.
Project description
Snow Microwave Radiative Transfer model
SMRT is a radiative transfer model to compute emission and backscatter from snowpack.
Getting started is easy, follow the instructions and explore the other repositories with examples in the 'smrt-model' github organization or read the detailed 'documentation'.
If you want to try without installing anything on your computer, use free mybinder.org notenooks: .
If you want to try SMRT without coding, use SMRT-App.
You can also explore the documentation and find code examples via the AI Wiki. Please let us know your experience of using this via discussions.
Quick Installation
To install the latest stable release:
pip install smrt
Alternatively, the latest developments are available using:
pip install git+https://github.com/smrt-model/smrt.git
or by 'manual installation'.
A simple example
An example to calculate the brightness temperature from a one-layer snowpack.
from smrt import make_snowpack, sensor_list, make_model
# create a snowpack
snowpack = make_snowpack(thickness=[10.], # snowpack depth in m
microstructure_model="sticky_hard_spheres",
density=320.0, # density in kg/m3
temperature=260, # temperature in Kelvin
radius=100e-6) # scatterers raidus in m
# create the sensor (AMSRE, channel 37 GHz vertical polarization)
radiometer = sensor_list.amsre('37V')
# create the model including the scattering model (IBA) and the radiative transfer solver (DORT)
m = make_model("iba", "dort")
# run the model
result = m.run(radiometer, snowpack)
print(result.TbV())
License information
See the file LICENSE.txt
for terms & conditions for usage, and a DISCLAIMER OF ALL
WARRANTIES.
DISCLAIMER: This version of SMRT is under peer review. Please use this software with caution, ask for assistance if needed, and let us know any feedback you may have.
Copyright (c) 2016-2025 Ghislain Picard, Melody Sandells, Henning Löwe.
Other contributions
- Nina Maass: initial implementation of the sea-ice functions
- Ludovic Brucker: initial implementation of the saline snow functions
- Mai Winstrup: initial implementation of the sea-ice functions
- Marion Leduc-Leballeur: test&debuging (snow and ice)
- Carlo Marin: debuging of the wet permittivities.
- Fanny Larue: debuging (LRM altimetry)
- Justin Murfitt: debuging (lake-ice, LRM altimetry)
- Julien Meloche: debuging (snow). Help to user
- Janna Rücker: implementation of new sea-ice functions
- Jacqueline Boutin: implementation of new sea-ice permittivity functions
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file smrt-1.5.1.tar.gz
.
File metadata
- Download URL: smrt-1.5.1.tar.gz
- Upload date:
- Size: 280.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/6.1.0 CPython/3.12.9
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 |
016fe4b78295223c9d42e579564de60f13f34bf43a0eb61983e2b2714a6043e4
|
|
MD5 |
1b3a5d3c72e2681865354cdbafbf5934
|
|
BLAKE2b-256 |
958ad14a259feb59a9f6d98d57f8e4752aef25a7ed9d3e9e1287f227b1a1d645
|
Provenance
The following attestation bundles were made for smrt-1.5.1.tar.gz
:
Publisher:
publish.yml
on smrt-model/smrt
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1
-
Predicate type:
https://docs.pypi.org/attestations/publish/v1
-
Subject name:
smrt-1.5.1.tar.gz
-
Subject digest:
016fe4b78295223c9d42e579564de60f13f34bf43a0eb61983e2b2714a6043e4
- Sigstore transparency entry: 263326198
- Sigstore integration time:
-
Permalink:
smrt-model/smrt@70f0d56bb735b3345a99255e345c0f551dd0d2f4
-
Branch / Tag:
refs/tags/v1.5.1
- Owner: https://github.com/smrt-model
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com
-
Runner Environment:
github-hosted
-
Publication workflow:
publish.yml@70f0d56bb735b3345a99255e345c0f551dd0d2f4
-
Trigger Event:
release
-
Statement type:
File details
Details for the file smrt-1.5.1-py3-none-any.whl
.
File metadata
- Download URL: smrt-1.5.1-py3-none-any.whl
- Upload date:
- Size: 293.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/6.1.0 CPython/3.12.9
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 |
53d29ffbd6c23001775712e320298190e377f840f84e0b872d90249465fbac64
|
|
MD5 |
e753f6d19be34efd18ec0387b34d7c9f
|
|
BLAKE2b-256 |
2713bef4fc8385f2b3b3c181dd29e68296ee245c4eafd8232d13e8194a91780a
|
Provenance
The following attestation bundles were made for smrt-1.5.1-py3-none-any.whl
:
Publisher:
publish.yml
on smrt-model/smrt
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1
-
Predicate type:
https://docs.pypi.org/attestations/publish/v1
-
Subject name:
smrt-1.5.1-py3-none-any.whl
-
Subject digest:
53d29ffbd6c23001775712e320298190e377f840f84e0b872d90249465fbac64
- Sigstore transparency entry: 263326200
- Sigstore integration time:
-
Permalink:
smrt-model/smrt@70f0d56bb735b3345a99255e345c0f551dd0d2f4
-
Branch / Tag:
refs/tags/v1.5.1
- Owner: https://github.com/smrt-model
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com
-
Runner Environment:
github-hosted
-
Publication workflow:
publish.yml@70f0d56bb735b3345a99255e345c0f551dd0d2f4
-
Trigger Event:
release
-
Statement type: