Displaying 1 to 14 from 14 results

lowtran - LOWTRAN atmospheric absorption extinction, scatter and irradiance model--in Python and Matlab

  •    Python

LOWTRAN7 atmospheric absorption extinction model. Updated by Michael Hirsch to be platform independent and easily accessible from Python ≥ 3.6 and Matlab ≥ R2014b. The main LOWTRAN program has been made accessible from Python by using direct memory transfers instead of the cumbersome and error-prone process of writing/reading text files. xarray.Dataset high-performance, simple N-D array data is passed out, with appropriate metadata.

gchp_legacy - Repository for GEOS-Chem High Performance: software that enables running GEOS-Chem on a cubed-sphere grid with MPI parallelization

  •    Fortran

This repository (https://github.com/geoschem/geos-chem) contains the source code layer for GCHP (GEOS-Chem with the High-Performance option). Use the Github issue tracker (attached to this repository) to report bugs or technical issues with the GEOS-Chem code, or to ask general questions about GCHP.

gcpy - Python toolkit for GEOS-Chem.

  •    Python

GCPy is a Python-based toolkit containing useful functions for working specifically with the GEOS-Chem model of atmospheric chemistry and composition. GCPy aims to build on the well-established scientific Python technical stack, leveraging tools like cartopy and xarray to simplify the task of working with model output and performing atmospheric chemistry analyses.




geos-chem - GEOS-Chem "Science Codebase" repository

  •    Fortran

GEOS-Chem 12.9.3 was the last version in which this "Science Codebase" repository was used in a standalone manner. For this reason, the latest release is frozen at 12.9.3. GEOS-Chem 13.0.0 and later versions use this "Science Codebase" repository as a submodule within the GCClassic and GCHP repositories.

teb - 🏘️ The Town Energy Balance (TEB) model software and platform

  •    Fortran

This enhanced software and platform for TEB (Town Energy Balance; Masson, 2000 and subsequent papers), is intended to help scientists and practitioners wishing to use the TEB model in their research as a standalone software application or as a library (e.g. WRF-TEB) to calculate the urban surface energy balance at neighborhood scale assuming a simplified canyon geometry. By default, we set the real type to an 8 byte wide. This behavior is controlled by the optional USE_REAL8 flag (default ON).

Isca - Idealized GCM from the University of Exeter

  •    Fortran

Isca is a framework for the idealized modelling of the global circulation of planetary atmospheres at varying levels of complexity and realism. The framework is an outgrowth of models from GFDL designed for Earth's atmosphere, but it may readily be extended into other planetary regimes. Various forcing and radiation options are available. At the simple end of the spectrum a Held-Suarez case is available. An idealized grey radiation scheme, a grey scheme with moisture feedback, a two-band scheme and a multi-band scheme are also available, all with simple moist effects and astronomically-based solar forcing. At the complex end of the spectrum the framework provides a direct connection to comprehensive atmospheric general circulation models. For Earth modelling, options include an aqua-planet and configurable (idealized or realistic) continents with idealized or realistic topography. Continents may be defined by changing albedo, heat capacity and evaporative parameters, and/or by using a simple bucket hydrology model. Oceanic Q-fluxes may be added to reproduce specified sea-surface temperatures, with any continents or on an aquaplanet. Planetary atmospheres may be configured by changing planetary size, solar forcing, atmospheric mass, radiative, and other parameters.

climt - The official home of climt, a Python based climate modelling toolkit.

  •    Fortran

climt hopes to enable researchers to easily perform online analysis and make modifications to existing models by increasing the ease with which models can be understood and modified. It also enables educators to write accessible models that serve as an entry point for students into Earth system modeling, while also containing state-of-the-art components. Initially climt contains only components for the atmosphere, and does not yet include a coupler. But there are plans to extend climt to a fully coupled Earth system model in the future. The toolkit is also written in such a way that it could enable the development of non-climate models (e.g. weather prediction, large-eddy simulation). To do so requires only that the prognostic and diagnostic schemes are wrapped into the correct Python-accessible interface.


lowtran - LOWTRAN atmospheric absorption extinction, scatter and irradiance model--in Python and Matlab

  •    Python

LOWTRAN7 atmospheric absorption extinction model. Updated by Michael Hirsch to be platform independent and easily accessible from Python ≥ 3.6 and Matlab. The main LOWTRAN program has been made accessible from Python by using direct memory transfers instead of the cumbersome and error-prone process of writing/reading text files. xarray.Dataset high-performance, simple N-D array data is passed out, with appropriate metadata.

PyCHAM - PyCHAM: CHemistry with Aerosol Microphysics in Python box model for Windows, Linux and Mac

  •    Python

Welcome to the PyCHAM software for modelling of aerosol chambers. Funding has been provided by the EUROCHAMP-2020 research project and the National Centre for Atmospheric Science (NCAS). Please open an issue on the GitHub repository or contact Simon O'Meara (simon.omeara@manchester.ac.uk) with any issues, comments or suggestions. PyCHAM is an open-access computer code (written in Python) for simulating aerosol chambers. It is supplied under the GNU General Public License v3.0.

mptrac - Massive-Parallel Trajectory Calculations (MPTRAC) is a Lagrangian particle dispersion model for the analysis of atmospheric transport processes in the troposphere and stratosphere

  •    C

Massive-Parallel Trajectory Calculations (MPTRAC) is a Lagrangian particle dispersion model for the analysis of atmospheric transport processes in the troposphere and stratosphere. This documentation describes the installation of MPTRAC on a Linux system. A number of standard tools (gcc, git, make) and software libraries are needed to install MPTRAC. The GNU Scientific Library is required for numerical calculations and the Unidata netCDF library, the HDF5 library, and zlib are needed for file-I/O. Copies of these libraries are provided in the MPTRAC git repository.

LBLRTM - Line-By-Line Radiative Transfer Model by Atmospheric and Environmental Research

  •    Fortran

LBLRTM (Line-By-Line Radiative Transfer Model) is an accurate and efficient line-by-line radiative transfer model derived from the Fast Atmospheric Signature Code (FASCODE). LBLRTM has been, and continues to be, extensively validated against atmospheric radiance spectra from the ultraviolet to the sub-millimeter. The HITRAN database provides the basis for the line parameters used in LBLRTM. These line parameters, as well as additional line parameters from other sources, are extracted for use in LBLRTM by a line file creation program called LNFL. A line parameter database built from HITRAN and suitable for use with LNFL can be downloaded with the AER Line File retrieval code or directory from the Zenodo repository.

gis4wrf - QGIS toolkit 🧰 for pre- and post-processing 🔨, visualizing 🔍, and running simulations 💻 in the Weather Research and Forecasting (WRF) model 🌀

  •    Python

GIS4WRF is a free and open source QGIS plug-in to help researchers and practitioners with their Advanced Research Weather Research and Forecasting modelling workflows. GIS4WRF can be used to pre-process input data, run simulations, and visualize or post-process results. We offer MPI-enabled pre-built binary distributions for Windows, macOS and Linux through WRF-CMake. For information on how to install GIS4WRF, or check out the main documentation and tutorials, please refer to the GIS4WRF website. If you use GIS4WRF in a published work, please cite both the paper (https://doi.org/10.1016/j.envsoft.2018.10.018), and the specific version of GIS4WRF you are using (https://doi.org/10.5281/zenodo.1288569).






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