Surface Albedo product. Three case studies: data retrieval, visualisation, time-series creation, set up Python environment
LAI and fAPAR retrieved with satellite remote sensing. Computation of inverse variance weights
Introducing the theory of comparing satellite retrievals with model fields using averaging kernels and operators.
Analysing TROPOMI ozone profiles using averaging kernels to compare satellite retrievals with model vertical structure.
Comparing TROPOMI NO₂ observations with CAMS regional fields to assess spatial patterns and air-quality variability.
Evaluating CAMS global aerosol forecasts by comparing model AOD with AERONET observations at selected sites.
Exploring CAMS global reanalysis fields to study atmospheric composition, trends, and long-term variability.
Investigating CAMS regional air-quality forecasts to examine high-resolution pollutant fields and time series.
Access and use of satellite-derived Greenhouse Gas (GHG) atmospheric carbon dioxide (CO2) Level 2 data product.
How to access, read and use Greenhouse Gas atmospheric carbon dioxide and methane data: temporal and spatial variation.
This notebook demonstrates the conversion from effective to true LAI using a clumping factor. It includes the propagation of the uncertainty to the true LAI, including many but not all additional sources of uncertainty.
Retrieve data on Burned Area from the C3S Climate Data Store, examining, subsetting, saving and re-projecting it
