I don't think you and others who are being critical of the Equal Chance outlook category really understand what it means. First of all, it does not mean everything will EXACTLY match the averages - there is some room on either side of the (lets say 20 year) average for temperature and precipitation that would fall into the normal range. And don't take this the wrong way - I am not trying to be personal, this is for anyone to consider what might be used to create these maps and why the EC category makes perfect sense (the unshaded area includes areas where conditions are expected to be close to normal). I chose to respond to you because you said they should guess and I strongly disagree with that. If you like, you can come back and argue your point. I think more importantly, the models do not always favor above or below average by a large enough probability to use one of the above or below normal categories - IF THE MODELS PREDICT A35% CHANCE OF BELOW NORMAL TEMPERATURES, THAT'S A LOT CLOSER TO THE EC CATEGORY where above and below normal conditions are equally likely THAN IT IS TO THE 40% PROBABILITY NEEDED TO USE THE LIGHT BLUE SHADING. Instructions for reading the probability maps for monthly and seasonal outlooks can be found here:http://www.cpc.ncep.noaa.gov/products/predictions/long_range/seasonal_info.php . As was already explained, the models do not always provide a result that favors one category over the other. If the most likely outcome is near normal conditions or the models do not provide output favoring a better chance of above or below average. All three categories could have a very near equal chance, but it should be possible for the probability of above average and below average to be 40% and near average 20% if these models produce the kind of output I suspect and this would still fall in the EC category. You say to GUESS!, but I do not think that is a good move at all - if the data does not provide enough useful information to make a choice that is more likely to be correct, guessing would be lying to everyone who assumes the maps are based on data and models, not guesses and perhaps deviations from normal conditions are less likely to be large when the models are in too much disagreement. In any case, it would help nobody for them to just guess. It could be that these maps are based entirely on computer models and maybe mathematical formulas and the people making the forecasts do not have any input into what the maps look like, they just enter data recordings or those are collected and processed automatically by computers. It could all just be the output of combined models either with no alterations by forecasters or only changing things by removing data/influences from significantly outlying models - if most models produce results within a certain range but maybe a couple give results far outside that range, it may improve the forecast if those outliers are removed. If there is no significant indication favoring above or below normal conditions, it would be utter nonsense to just guess. You say it is an improbable statistical anomaly. This is only true if you are talking an exactly equal chance (the EC and normal category covers a range of percentages centered on 33%, not just that exact value) and/or you consider normal conditions to be exactly what the 30 year or whatever average is - lets say it is 41deg, instead of a range such as 40-42 or 39-43. They are not saying the probability is exactly equal, but that the chance of above and below average conditions are both less than 40% or maybe the different models are in too much disagreement about what is happening to make a prediction. I'm wondering how much you know about statistics and these maps when you say EC is an improbable statistical anomaly. I do not have the information to run any kind of statistical test to find out if your assertion is false, but it just doesn't sound right to me and I see it differently and feel I understand very well what these maps mean. I could be wrong about ways EC can be assigned but at least I put some thought into it and also realize sometimes there is a better or equal chance of near normal conditions as opposed to conditions being toward one extreme or the other. These maps make perfect sense to me and I feel I understand why the EC category is used and how models can be in such disagreement as to make the output not very useful or even useless, I have looked at the output of many computer models for the same tropical systems and the model forecasts were all over the place with no tracks very close together and wide variation in forecast intensity.I do not know what goes into making these outlook maps and do not know exactly when EC is used (for instance, maybe it would be rounded to the nearest category% - if models show 38% above average maybe it would fall in 40% above instead of EC, where it would be in the 33% probability shade). I do not think I have explained my thoughts very well and I have assumed certain things could go toward assigning an EC that may not contribute to its use at all. I think there is often a better chance of near average conditions which would warrant the use of the EC category over the others and that simple explanation takes care of at least part of the map - maybe there is a 40% of near normal and 20% each above/below in some areas.