NEWxSFC  Interim
Summary…as of 09FEB13 
AVG SUMSQ 
AVG STP 
AVG Total Absolute 
AVG Absolute 
Mean RSQ 


Previous Ranks 
Rank 
Forecaster 
Class 
Total STN 4casts 
Error (") 
Error Z 
% MPRV over AVG 
Rank 
4cast (") 
Error 
Error Z 
% MPRV over AVG 
Rank 
Error (") 
Error Z 
% MPRV over AVG 
Rank 
Error (") 
Error Z 
%MPRV over AVG 
Rank 
RSQ 
RSQ Z 
% MPRV over AVG 
Rank 
Forecaster 

1 
dryslot 
Intern 
46 
342 
0.913 
55% 
1 
174 
17 
0.609 
59% 
6 
55.4 
0.926 
31% 
4 
2.4 
1.000 
32% 
3 
79% 
1.331 
19% 
3 
dryslot 

2 
donsutherland1 
Chief 
43 
123 
0.794 
44% 
3 
57 
17 
0.231 
17% 
7 
34.7 
0.947 
28% 
3 
1.6 
0.907 
25% 
3 
67% 
0.806 
38% 
4 
donsutherland1 
 
3 
Donald
Rosenfeld 
Senior 
44 
127 
0.687 
40% 
4 
73 
1 
1.106 
95% 
1 
37.1 
0.732 
23% 
4 
1.7 
0.706 
21% 
4 
58% 
0.588 
12% 
7 
Donald Rosenfeld 

4 
herb
@maws 
Senior 
44 
500 
0.681 
41% 
4 
168 
17 
0.446 
43% 
5 
73.0 
0.548 
18% 
5 
3.3 
0.499 
16% 
5 
74% 
0.791 
12% 
5 
herb @maws 

5 
iralibov 
Senior 
48 
417 
0.560 
32% 
5 
196 
18 
0.265 
29% 
5 
74.4 
0.190 
7% 
6 
3.1 
0.340 
11% 
5 
64% 
0.661 
16% 
5 
iralibov 
 
6 
Roger
Smith 
Senior 
45 
491 
0.461 
27% 
6 
208 
24 
0.556 
54% 
6 
74.5 
0.315 
10% 
7 
3.3 
0.321 
10% 
7 
69% 
0.181 
2% 
5 
Roger Smith 
 
7 
snocat918 
Rookie 
45 
667 
0.396 
21% 
7 
162 
16 
0.734 
62% 
4 
79.0 
0.382 
11% 
7 
3.6 
0.317 
8% 
7 
56% 
0.112 
6% 
8 
snocat918 

8 
Mitchel
Volk 
Senior 
43 
715 
0.180 
11% 
8 
186 
19 
0.304 
29% 
5 
84.5 
0.124 
4% 
9 
3.8 
0.027 
1% 
10 
69% 
0.269 
5% 
6 
Mitchel Volk 
 
9 
Shillelagh 
Senior 
45 
680 
0.178 
11% 
9 
144 
42 
0.068 
7% 
10 
73.6 
0.497 
17% 
5 
3.2 
0.504 
16% 
6 
68% 
0.127 
2% 
7 
Shillelagh 
 
10 
snowman 
Senior 
46 
744 
0.140 
9% 
10 
197 
17 
0.597 
58% 
6 
91.9 
0.121 
4% 
11 
4.0 
0.078 
2% 
10 
57% 
1.036 
15% 
13 
snowman 
 
11 
weatherT 
Senior 
45 
733 
0.049 
3% 
10 
203 
38 
0.076 
7% 
11 
91.4 
0.091 
3% 
10 
3.9 
0.110 
3% 
11 
60% 
0.730 
11% 
11 
weatherT 
 
12 
TQ 
Senior 
44 
271 
0.266 
19% 
9 
78 
31 
0.548 
51% 
10 
49.0 
0.024 
2% 
7 
2.2 
0.005 
3% 
7 
52% 
0.208 
3% 
8 
TQ 
 
13 
quagmireweathercentral 
Rookie 
48 
1974 
2.355 
133% 
13 
304 
126 
2.093 
189% 
13 
162.2 
2.487 
77% 
14 
6.8 
2.448 
71% 
14 
35% 
1.467 
41% 
13 
quagmireweathercentral 
There have been three (3)
snowstorm forecasting Contests…as of 09FEB13. Under the ‘twothirds’ rule…forecasters who have entered at least
two (2) forecasts are included in this interim summary.
To qualify for ranking in
the Interim and final ‘EndofSeason’ standings…a forecaster must enter at
least twothirds of all Contests. If a forecaster has made more than
enough forecasts to qualify for ranking…only the lowest SUMSQ Zscores
necessary to qualify are used in the computing the average. IOW…if you
made nine forecasts…only your six best SUMSQ Zscores are used to evaluate your
seasontodate performance. You can think of it as dropping the
worse quiz score before your final grade is determined. The reason we
have this rule is to 1) make it possible to miss entering a forecast or two
throughout the season and still be eligible for Interim and ‘Endof Season’
ranking and 2) encourage forecasters to take on difficult and/or lateseason
storms without fear about how a bad forecast might degrade their overall 'seasontodate'
performance score(s).
The mean normalized ‘SUMSQ
error’ is the Contest/s primary measure of forecaster performance.
This metric measures how well the forecaster/s expected snowfall
'distribution and magnitude' for _all_ forecast stations captured the
'distribution and magnitude' of _all_ observed snowfall amounts. A
forecaster with a lower average SUMSQ Z Score has made more skillful forecasts
than a forecaster with higher average SUMSQ Z Score.
The 'Storm Total
Precipitation error’ statistic is the absolute arithmetic difference
between a forecaster/s sumtotal snowfall for all stations and the observed
sumtotal snowfall. This metric…by
itself…is not a meaningful measure of skill…but can provide additional insight
of forecaster bias.
The 'Total Absolute
error' statistic is the average of your forecast errors regardless of
whether you overforecast or underforecast.
This metric measures the magnitude of your errors.
The 'Average Absolute
Error' is the forecaster/s ‘Total Absolute Error’ divided by the
number of stations where snow was forecast or observed.
The ‘RSQ error’
statistic is a measure of the how well the forecast captured the variability of
the observed snowfall. Combined with
the SUMSQ error statistic…RSQ provides added information about how strong the
forecaster/s ‘model’ performed.