Transcript Posprocessing452.ppt

Post Processing
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)
Post Processing
• Model Output Statistics was the first postprocessing 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.
There are many other post-processing
approaches
• Neural nets
Attempts to duplicate the complex interactions
between neurons in the human brain.
Dynamic MOS
• MOS equations are updated frequently, not
static like the NWS.
• Example: DiCast used by the Weather
Channel
They don’t MOS!
UW Bias Correction of WRF
And many others…