NEWxSFC - Winter '13 / '14:  Interim Standings...as of Storm #8

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

1,1,1,1,1

1

donsutherland1

Senior

138

97

-0.974

57%

2

107

15

-0.518

41%

6

33.3

-1.041

33%

2

1.4

-1.164

35%

2

82%

1.115

22%

2

donsutherland1

3,3,3,3,2

2

Brad Yehl

Journeyman

133

176

-0.762

49%

3

127

24

-0.365

32%

6

44.4

-0.874

32%

2

1.9

-0.776

27%

3

76%

1.147

38%

3

Brad Yehl

2,2,2,2,3

3

Herb@MAWS

Senior

136

189

-0.727

51%

4

128

25

-0.486

43%

6

50.3

-0.681

25%

4

2.2

-0.663

24%

5

70%

0.708

20%

3

Herb@MAWS

5,4,5,5,4

4

TQ

Senior

125

122

-0.693

48%

4

97

18

-0.481

38%

5

36.5

-0.617

23%

5

1.8

-0.696

24%

5

78%

0.680

12%

4

TQ

6,5,4,4,5

5

WeatherT

Senior

134

192

-0.487

36%

5

111

18

-0.507

40%

6

50.0

-0.406

16%

6

2.2

-0.340

14%

6

67%

0.399

21%

6

WeatherT

3,6,6,6,6

6

Shillelagh

Senior

135

285

-0.394

31%

7

118

32

-0.328

28%

6

56.9

-0.467

19%

6

2.4

-0.416

17%

6

64%

0.317

6%

6

Shillelagh

8,7,7,8,8

7

Donald Rosenfeld

Senior

133

285

-0.338

28%

7

111

33

-0.057

-2%

7

59.4

-0.195

10%

8

2.5

-0.112

7%

8

63%

0.280

1%

7

Donald Rosenfeld

7,8,8,7,7

8

Roger Smith

Senior

149

347

-0.038

8%

8

142

21

-0.313

37%

6

63.4

-0.094

6%

7

2.5

-0.273

10%

6

60%

0.074

-1%

8

Roger Smith

12,11,9,11,10

9

snocat918

Intern

136

399

0.235

-18%

9

148

40

0.110

-19%

7

74.3

0.320

-17%

9

3.2

0.374

-16%

10

56%

-0.321

-13%

9

snocat918

11,12,10,10,11

10

MarkHofmann

Senior

140

1196

2.230

-186%

13

205

105

2.024

-193%

12

126.4

2.141

-87%

13

5.5

2.132

-84%

13

34%

-1.570

-47%

13

MarkHofmann

 

 

Interim standings after eight (8) snow storm-forecasting Contests…as of 21-MAR-14.

Under the ‘two-thirds’ rule…forecasters who have entered at least six (6) forecasts are included in this interim summary.

Forecasters’ storm summary data here

 

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 scores 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.