NOVAC: database of daily statistics of emission of SO2 from volcanoes of the Network for Observation of Volcanic and Atmospheric Change.
NDACC: database of composition measurements of tropospheric and stratospheric gases, part of the InfraRed Group of the Network for Detection of Atmospheric Composition Change.
CAMS: database of global and regional emissions from natural and anthropogenic sources for the Copernicus Atmosphere Monitoring Service.
ARTS microwave single scattering properties (TRO): a database supporting radiative transfer simulations between 1 and 890 GHZ, describing 35 habits at 3 temperatures assuming totally random orientation (TRO)
ARTS microwave single scattering properties (ARO): a database supporting radiative transfer simulations between 1 and 890 GHz, describing 2 habits at 3 temperatures assuming azimuthally random orientation (ARO)
BorealScat campaign data: tomographic tower-based radar observations of a boreal forest site at P-band (435 MHz), L-band (1270 MHz) and C-band (5400 MHz).
Odin-SMR: vertical profiles of multiple gases in the middle atmosphere (2002-today), retrieved from the Odin-SMR limb sounder
Rain over Africa: Machine learning-based near-instantaneous retrievals of rain covering the African continent at 15min / 3km temporal/spatial resolution
Models, packages and algorithms
MIMICA: a small-scale atmospheric model (large-eddy simulation model) that can simulate case studies of thermodynamics, clouds and aerosols including a detailed cloud microphysics and aerosol module.
NorESM: an Earth system model including different spheres of the Earth system and a detailed cloud and aerosol microphysics scheme.
The Atmospheric Radiative Transfer Simulator (ARTS): a modular and general radiative transfer model (with focus on the microwave and infrared regions), supporting simulations including polarization, scattering and other advanced features
Energy balance: some simple models of Earth's energy balance, for educational purposes
Quantile regression neural networks (QRNN): an implementation of this machine learning technique for Keras and Pytorch