The Atmosphere Virtual Lab (AVL) is a freely available Open Source software solution that can be used to analyze and visualize atmospheric earth observation data.
It is specifically designed to be used within a cloud environment, close to the data. But it can also be used on a local computer.
The basis for AVL is JupyterLab that already provides a large ecosystem of scientific software packages for both analysis and visualisation.
This environment is extended with CODA and HARP for the analysis functionality. CODA and HARP are part of the Atmospheric Toolbox.
The key feature of AVL is, however, its visualisation functionality.
AVL provides the capability to plot satellite pixels using the actual geographic footprint of the measurement.
Instead of converting the data to a raster image, AVL comes with the capability to plot millions of polygons as a single layer within leaflet plots.
To achieve this, two new Open Source components, leaflet-gl-vector-layer and ipyleaflet-gl-vector-layer-plugin, were developed.
AVL provides a simple high level API to allow plotting the result of a HARP ingestion using just a single function call:
l2product = harp.import_product('S5P_OFFL_L2__SO2____20210412T151823_20210412T165953_18121_01_020104_20210414T175908.nc', operations)
avl.Geo(l2product, "SO2_column_number_density", colorrange=(1, 8), colormap="batlow", opacity=0.9)
In order to better view data that covers the full globe, AVL also comes with an interactive 3D Geographic Plot.
Creating this is just as simple as creating a 2D plot:
tropomi_co = harp.import_product("S5P_OFFL_L2__CO_____20220718T123656_20220718T141826_24674_03_020400_20220720T110230.nc", operations, options="co=corrected")
avl.Geo3D(tropomi_co, "CO_column_volume_mixing_ratio", colorrange=(0, 200), colormap="rainbow", opacity=0.7)
To install AVL simply create a new conda environment and install the atmosphere-virtual-lab package.
$ conda create -n avl $ conda activate avl $ conda install -c conda-forge atmosphere-virtual-lab $ jupyter lab
Or install AVL inside your existing jupyterlab conda environment to extend its capabilities.
Examples can be found in the demo that was provided at the ESA Living Planet Symposium 2022 and in some of the more recent Atmospheric Toolbox Use Cases.
Source code of AVL can be found on GitHub and for feedback and support please visit the AVL section of the Atmospheric Toolbox Forum.