The scoring system for the 'regular' season is designed to determine
objectively
which forecast had the best overall synoptic quality. An
accurate...high-quality...
synoptic-scale snowfall forecast is defined as one capturing the
magnitude
and distribution of the storm/s total snowfall.
Forecast quality is evaluated by calculating its 'goodness of fit' between
all forecast
and observed snowfall amounts.
The scatter plot/s black diamonds show the forecast snowfall (x-axis)
plotted
against the observed snowfall (y-axis). The dashed line represents
the
forecast/s 'goodness of fit.' The magenta points represent a perfect
forecast...where each station forecast matched each station observation.
The 0.82 R² value indicates the forecaster accounted for 82% of the
variability
between forecast and observed snowfall amounts. A 'perfect' forecast would
have an R² value of 1...meaning 100% of the observed snowfall/s variability
was accounted for by the forecast.
The forecast error statistic is the Sum of Squared Errors (SUMSQ).
The arithmetic difference between the Forecast and Observed snowfall at
each
station is squared and the squared errors for all stations are summed. This
skill
measure rewards (penalizes) station forecasts with small (large) errors.
The smaller the SUMSQ...the better the synoptic-scale forecast.
If the absolute difference between your
Forecast snowfall and the Observed snowfall is:
one (1) inch = one (1) error point
two (2) inches = four (4) error points
three (3) inches = nine (9) error points
Each forecaster/s SUMSQ Error score is normalized to a
Z-Score for use
in
calculating Interim and End-of-Season standings.
Forecasts with normalized Z-scores greater than or equal to 2.5 standard
deviations above the mean are statistical outliers and may be excluded from
the final
Z-Score calculation.
If Snow is Observed and Snow is Not Forecast...
then the Forecaster/s Snowfall Amount is set to '0' for that
station.
If Snow is Forecast and Snow is Not Observed...
then the Observed Snowfall Amount is set to '0' for that station.
If Snow is not Forecast and Snow is Not Observed...
then the Forecaster is not scored for that station.
Other reported forecast statistics...such as average absolute error (AAE)
...total absolute error (TAE)...total snowfall error (STP)...R²...and
'batting averages'...are 'measures of forecaster skill' but do not
factor
into forecast rankings. |
