|
NEWxSFC - Interim
Summary…as of 28 JAN 2009 |
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 |
|
2,1,1,1 |
1 |
donsutherland1 |
Chief |
89 |
73 |
-1.042 |
51% |
2 |
70.9 |
10.4 |
-0.483 |
38% |
6 |
23.85 |
-1.196 |
35% |
2 |
1.32 |
-1.131 |
34% |
2 |
77.2% |
0.919 |
28% |
3 |
donsutherland1 |
|
5,2,2,3 |
2 |
shanabe |
Senior |
91 |
82 |
-0.816 |
35.5% |
4 |
73.8 |
17.9 |
0.036 |
0% |
8 |
27.58 |
-0.846 |
23% |
4 |
1.51 |
-0.816 |
21% |
4 |
75.2% |
0.998 |
31% |
4 |
shanabe |
|
10,6,3,4 |
3 |
Donald Rosenfeld |
Senior |
109 |
85 |
-0.788 |
33.7% |
4 |
76.9 |
13.1 |
-0.509 |
8% |
4 |
32.26 |
-0.677 |
14% |
4 |
1.47 |
-0.866 |
19% |
4 |
67.1% |
0.241 |
6% |
6 |
Donald Rosenfeld |
|
-,-,-,2 |
4 |
anthony |
Rookie |
92 |
118 |
-0.608 |
28% |
6 |
67.2 |
14.4 |
-0.545 |
34% |
6 |
34.72 |
-0.631 |
18% |
5 |
1.94 |
-0.284 |
7% |
7 |
62.5% |
0.210 |
13% |
9 |
anthony |
|
-,-,-,5 |
5 |
Raven |
Senior |
104 |
122 |
-0.547 |
23% |
5 |
79.1 |
21.2 |
0.043 |
-7% |
8 |
37.91 |
-0.384 |
9% |
6 |
1.83 |
-0.421 |
9% |
7 |
65.8% |
0.335 |
5% |
6 |
Raven |
|
8,-,-,8 |
6 |
Mitchel Volk |
Senior |
106 |
156 |
-0.207 |
9% |
7 |
94.7 |
18.8 |
-0.091 |
2% |
6 |
41.09 |
-0.334 |
9% |
7 |
1.97 |
-0.291 |
7% |
7 |
65.9% |
0.254 |
11% |
8 |
Mitchel Volk |
|
4,4,4,7 |
7 |
herb @maws |
Senior |
93 |
134 |
-0.194 |
9% |
8 |
65.2 |
17.5 |
-0.202 |
14% |
8 |
35.83 |
-0.172 |
4% |
8 |
1.90 |
-0.169 |
6% |
7 |
59.5% |
-0.004 |
-5% |
10 |
herb@maws |
|
6,5,5,9 |
8 |
TQ |
Senior |
90 |
126 |
-0.012 |
3% |
8 |
78.6 |
18.3 |
0.295 |
-19% |
10 |
32.26 |
-0.263 |
8% |
7 |
1.81 |
-0.062 |
4% |
7 |
71.5% |
0.131 |
2% |
8 |
TQ |
|
11,8,6,11 |
9 |
ilibov |
Senior |
108 |
206 |
0.377 |
-17% |
10 |
71.5 |
25.1 |
0.431 |
-28% |
10 |
47.90 |
0.565 |
-16% |
12 |
2.20 |
0.212 |
-4% |
10 |
59.7% |
-0.170 |
-12% |
10 |
ilibov |
|
14,11,10,14 |
10 |
weatherT |
Rookie |
95 |
156 |
0.468 |
-25% |
11 |
64.2 |
24.3 |
0.092 |
-6% |
9 |
42.13 |
0.535 |
-17% |
11 |
2.25 |
0.909 |
-32% |
11 |
62.0% |
0.095 |
-3% |
8 |
weatherT |
|
12,7,8,10 |
11 |
NYNJPAWx |
#N/A |
88 |
179 |
0.615 |
-32% |
10 |
83.2 |
17.9 |
0.166 |
0% |
10 |
41.51 |
0.529 |
-11% |
10 |
2.31 |
0.404 |
-13% |
10 |
52.8% |
-0.796 |
-19% |
11 |
NYNJPAWeather |
|
15,10,9,13 |
12 |
jackzig |
Senior |
100 |
256 |
0.937 |
-45% |
12 |
89.8 |
22.5 |
0.136 |
1% |
10 |
55.42 |
1.087 |
-32% |
13 |
2.74 |
0.987 |
-26% |
12 |
40.3% |
-1.364 |
-31% |
12 |
jackzig |
There have been seven (7)
snowstorm forecasting Contests to date.
Under the ‘two-thirds’ rule…forecasters who have entered at least five
(5) forecasts are included in this interim summary.
To qualify for ranking in
the Interim and final ‘End-of-Season’ standings…a forecaster must enter at
least two-thirds of all Contests. If a forecaster has made more than
enough forecasts to qualify for ranking…only the lowest SUMSQ Z-scores
necessary to qualify are used in the computing the average. IOW…if you
made nine forecasts…only your six best SUMSQ Z-scores are used to evaluate your
season-to-date 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 ‘End-of Season’
ranking and 2) encourage forecasters to take on difficult and/or late-season
storms without fear about how a bad forecast might degrade their overall
'season-to-date' 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 sum-total snowfall for all stations and the observed
sum-total 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 over-forecast or under-forecast.
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.