Practical introduction to the Sea level gridded data: plotting data during an El Niño event and over a strong current
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
Investigating and visualising CAMS NOx anthropogenic and natural emissions inventories.
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.
Exploring bias in CAMS forecasts using observations and introducing how MOS helps address systematic errors.
Investigating CAMS regional air-quality forecasts to examine high-resolution pollutant fields and time series.
Access hindcast data of 2-metre temperature; Compute anomalies, averages and verification metrics.
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.
