NEWxSFC - Interim Summary…as of 21 JAN 2011					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	donsutherland1	Senior	81	324	-1.101	48%	2	161.9	17.9	-0.677	52%	3	66.97	-1.256	28%	2	2.48	-1.260	28%	2	57.7%	1.323	62%	2	donsutherland1
2	2	Donald Rosenfeld	Senior	81	373	-1.016	44%	2	173.2	12.8	-0.746	57%	6	74.95	-1.000	22%	3	2.78	-1.004	22%	3	54.2%	1.239	55%	3	Donald Rosenfeld
6	3	Brad Yehl	Rookie	78	237	-0.821	36%	3	115.8	19.5	-0.332	30%	6	51.90	-0.743	19%	4	1.96	-0.750	18%	4	60.3%	0.839	28%	4	Brad Yehl
5	4	ejbauers	Intern	79	425	-0.685	31%	6	190.9	40.5	0.140	-14%	9	77.63	-0.519	12%	5	2.91	-0.532	12%	5	64.5%	0.750	36%	4	ejbauers
3	5	emoran	Senior	78	231	-0.682	28%	4	119.4	5.8	-0.785	65%	4	51.74	-0.698	14%	5	1.97	-0.663	13%	5	53.4%	0.441	18%	6	emoran
7	6	Shillelagh	Senior	79	313	-0.566	28%	6	113.6	18.7	-0.563	51%	5	57.52	-0.643	19%	6	2.16	-0.678	19%	5	45.6%	0.023	3%	9	Shillelagh
8	7	TQ	Senior	78	375	-0.491	24%	6	104.8	27.0	-0.062	6%	9	63.23	-0.594	16%	6	2.38	-0.591	15%	6	42.9%	0.010	-2%	9	TQ
4	8	Mitchel Volk	Senior	78	308	-0.342	15%	5	120.7	11.1	-0.660	56%	5	56.86	-0.797	19%	4	2.16	-0.765	17%	4	42.7%	0.258	24%	6	Mitchel Volk
10	9	herb@maws	Senior	78	344	-0.318	15%	7	105.3	33.3	0.177	-12%	8	60.68	-0.149	4%	7	2.30	-0.126	3%	7	54.8%	0.446	15%	7	herb@maws
9	10	iralibov	Chief	80	588	-0.247	11%	8	195.8	37.8	-0.315	26%	6	92.51	-0.008	1%	9	3.48	0.048	0%	9	40.2%	0.169	13%	7	iralibov
13	11	WeatherT	Journeyman	78	744	0.435	-20%	9	131.9	48.5	0.050	4%	7	100.00	0.518	-15%	9	3.78	0.596	-16%	10	36.7%	-0.781	-24%	9	WeatherT
12	12	MarkHofmann	Journeyman	81	1094	0.704	-33%	10	173.0	12.0	-0.723	55%	5	123.81	0.843	-20%	10	4.59	0.837	-20%	10	16.7%	-1.033	-50%	11	MarkHofmann
16	13	Roger Smith	Intern	81	738	0.950	-46%	12	163.2	58.9	1.023	-82%	13	96.92	0.971	-27%	13	3.59	0.882	-23%	12	25.2%	-1.162	-43%	12	Roger Smith

There have been four (4) snowstorm forecasting Contests…as of 21-JAN-11. Under the ‘two-thirds’ rule…forecasters who have entered at least three (3) 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.