Methodologies for converting NWP outputs into QPF and PQPF
MODEL OUTPUT STATISTICAL METHODS THAT CAN BE USED TO DEVELOP PROBABILITIES
Brier skill scores for six statistical methods for 3 precipitation thresholds
Non linear techniques like logistic regression improve forecasts for the higher probabilities (figures from Applequist et al.)
VERY USEFUL FOR LIGHTER THRESHOLDS BUT TREND TOWARDS CLIMATOLOGY AT LONGER RANGES
Bias (Forecast precipitation/Observed precipitation) for various models during September 2000 for northeast
Perfect Prog approach, Assume members are unbiased. Can show where at least 60% of the members exceeded a threshold.
A better way of using enemble forecasts to generate probability forecasts
The brier scores for higher thresholds were higher for forecasts applying various statistical methods to ensemble forecasts than those from the NGM MOS
If ensemble forecasts are used, which more cost effective
Accuracy of model forecasts decreases rapidly as threshold increases and as the scale of the event decreases
Because higher amounts or thresholds are relatively rare, it is difficult getting a big enough sample to calibrate forecasts using traditional statistical techniques. Verification of 24 hour QPF for various thresholds
For extreme events is there a better way?
Or is it? How Good Are the Forecasts?
What about assessing probability of precipitation occurring anywhere within a circle or hexagon? The probabilities would be influenced by the density of observations, but your probabilities might be high enough to allow emergency managers to assess the risk within their area.
Then how do we approach forecasting QPF , Probabilistically?
For high end, rare events