1. Post Processing

2. Model Output Can Usually Be Improved with Post Processing
Can remove systematic bias
Can produce probabilistic information from deterministic information
Can provide forecasts for parameters that the model incapable of modeling successfully due to resolution or physics issues (e.g., shallow fog)

3. Post Processing
Model Output Statistics was the first post-processing method used by the NWS (1969)
Based on multiple linear regression.
Essentially unchanged in 40 years.
Does not consider non-linear relationships between predictors and predictands.
Does take out much of systematic bias.

4. There are many other post-processing approaches
Neural nets
Attempts to duplicate the complex interactions between neurons in the human brain.

6. Dynamic MOS
MOS equations are updated frequently, not static like the NWS.
Example: DiCast used by the Weather Channel

7. They don’t MOS!

8. UW Bias Correction of WRF

9. And many others…