NEWxSFC - Interim Summary…as of 15 FEB 2010

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

ilibov

Senior

100

317

-0.983

48%

5

133.6

9.9

-1.080

72%

3

54.45

-1.014

25%

5

2.17

-1.139

32%

4

63.7%

1.269

38%

7

ilibov

2

2

Shillelagh

Senior

83

434

-0.864

30%

6

105.6

30.9

0.194

-12%

13

57.66

-0.928

21%

6

2.70

-0.554

14%

8

61.3%

0.898

27%

7

Shillelagh

3

3

donsutherland1

Chief

100

320

-0.835

51%

3

155.8

19.8

-0.547

43%

7

57.50

-0.998

31%

3

2.32

-0.985

31%

3

68.0%

0.866

29%

2

donsutherland1

6

4

herb@maws

Senior

97

354

-0.738

45%

5

154.5

20.4

-0.583

42%

8

62.36

-0.774

25%

4

2.60

-0.683

23%

6

63.5%

0.493

19%

6

herb@maws

4

5

Raven

Senior

91

518

-0.726

36%

6

167.0

19.2

-0.425

37%

10

70.33

-0.506

17%

9

3.13

-0.367

14%

10

69.6%

0.686

23%

6

Raven

5

6

millersville_bauers

Journeyman

93

431

-0.704

28%

7

130.9

28.8

0.027

2%

11

62.82

-0.461

13%

9

2.63

-0.614

18%

7

59.3%

0.626

22%

6

millersville_bauers

7

7

wxfox51

Journeyman

96

512

-0.574

38%

6

149.5

22.0

-0.171

15%

8

62.27

-0.771

25%

4

2.65

-0.784

26%

5

68.9%

0.523

21%

7

wxfox51

8

8

Newa2010

Journeyman

94

567

-0.538

30%

8

146.1

20.0

-0.346

33%

10

71.26

-0.421

15%

9

3.06

-0.402

15%

9

68.0%

0.552

20%

7

Newa2010

10

9

Donald Rosenfeld

Senior

100

432

-0.490

33%

6

125.4

21.8

-0.209

14%

8

57.60

-0.808

24%

4

2.33

-0.874

26%

4

55.2%

0.451

19%

5

Donald Rosenfeld

9

10

weatherT

Rookie

99

365

-0.358

20%

7

107.3

44.0

0.268

-19%

12

63.15

-0.180

9%

8

2.51

-0.417

14%

7

52.3%

0.492

17%

7

weatherT

12

11

TQ

Senior

91

414

-0.073

8%

10

104.2

33.2

-0.098

3%

11

67.16

-0.042

4%

9

2.92

0.108

-1%

10

42.2%

-0.305

-5%

10

TQ

11

12

Mitchel Volk

Senior

92

852

0.041

-2%

15

159.8

37.9

0.342

-23%

15

82.38

-0.423

7%

11

3.53

-0.273

4%

12

53.4%

-0.133

-6%

15

Mitchel Volk

15

13

Roger Smith

Senior

104

779

0.305

-22%

12

218.6

71.1

0.992

-90%

14

106.37

0.632

-23%

13

4.07

0.429

-18%

12

55.4%

0.063

2%

10

Roger Smith

13

14

snowman

Intern

92

1033

0.708

-22%

17

135.4

30.7

0.380

-25%

13

100.93

0.417

-14%

15

4.39

0.620

-18%

15

40.9%

-1.014

-28%

18

snowman

14

15

nnjwxguy78

Journeyman

90

930

0.802

-39%

15

162.5

19.2

-0.612

41%

8

101.80

0.878

-25%

15

4.34

0.977

-26%

16

42.8%

-0.791

-17%

15

nnjwxguy78

 

 

There have been six (6) snowstorm forecasting Contests to as of 15-FEB-10.  Under the ‘two-thirds’ rule…forecasters who have entered at least four (4) 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.