Post-Processing

Weather data are ofter submitted to additional processing steps to improve quality. Main reasons for Post-Processing are:

• Quality control: detection and removal of errors, filling of gaps,
• Accuracy: Improcing accuracy by quality control, bias correction, downscaling or other methods
• Transformation: turning a signal (e.g. reflection) into a meteorological (radiation) or other value.

Post-Processing methods are applied to different data sources: 

• measurements:  quality control , others.
• Observations: transformation, interpolation,
• Weather model: Downscaling, Ensemble, Multimodel, etc.
• or a combination thereof (e.g. MOS; mLM)

Some post-processing methods are described in the sub-bpages.