The scoring system 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 that best captures 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 R² value indicates the forecast 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
as accounted for by the forecast.
The forecast error statistic is the Sum of Squared Errors (SUMSQ).
The 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 difference between your Forecast snowfall and the Observed
snowfall is:
one-inch = one error point
two-inches = four error points
three-inches = nine 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 subject to exclusion as outliers.
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 forecast statistics are reported...such as average absolute error
(AAE)
...total absolute error (TAE)...total snowfall error (STP)...R²...and
'batting averages'...but these 'measures of skill' do not factor into
forecast
rankings. |
