I would like to start out by trying to differentiate between seasonal forecasting and weather forecasting for the next week or so. All weather forecasting involves a percentage of guessing. A forecast for the next 24-48 hours might be 90% science and 10% guesswork, and by the time you are trying to forecast for days 7, 8, 9 and 10, the percentages might be more like 50% science and 50% guesswork. By the time you get into seasonal forecasting, there is little proven science and methodology behind those forecasts- at least methods that truly work. Most seasonal forecasts are really just creative writing using meteorological terms!

Things like "Analog Years" is a favorite among some forecasters out there. The problem with that method is that we do not fully understand what causes large scale weather patterns to persist. Thus saying something like: "We had a similar weather pattern or happenings back in the summer and autumn of 1956, so that means this winter will be like the winter of 1956-57" is similar to saying: "The last time I had a sore throat it turned out to be strept throat. So the sore throat I have now must also be strept throat."

What I am trying to say is that it takes more than an observation of what is happening in the weather to be able to forecast future events. It takes a good understanding of what is causing the current weather trends to be able to say what factors will influence the weather in the coming months and we are just not there yet. So as you read this, keep in mind that all my schooling and experience does not really give me much of an advantage over anyone else with an interest in the weather and a yearning to say what he/she things will happen this winter and no one else with formal training in meteorology is any further along than me (no matter what they might claim!). So ALL SEASONAL FORECASTS SHOULD BE TAKEN WITH A GRAIN OF SALT OR EVEN A BIT OF HUMOR.

With that now said, there is one mechanism that has proven to have an effect on the weather in the US on a seasonal scale and that is El Nino- the dreaded "Boy Child", or anomalous warming of the surface waters in the Pacific Ocean in the vicinity of the Equator. El Nino’s have been connected to many weather anomalies around the world and have even been blamed for some things they do not do! Over the past decade or so, most snow lovers were trained to hate El Nino because it was being blamed for just about everything that happened in the weather, including poor snow years in the Midwest. As scientists begin to understand El Nino more, they are discovering that each El Nino has it’s own personality and thus each will have it’s own set of impacts. It is being discovered that Weak, Moderate and Strong El Ninos all have different impacts on the weather in the US and Midwest.

The most popular notion given out in the past decade or two was that when an El Nino was going on, warmer than average temps were an almost sure bet across the Canadian Prairie Provinces as well as the north central US, including many of the favorite snowmobiling areas of the Midwest and into central and western Canada. The good news for us snow lovers is that this idea has been modified some. It now seems like weak El Nino’s can actually lead to below average temps across the eastern 2/3rds of the US, which includes most areas east of the Rockies. The winter of 2003-2004 was spent with weak El Nino conditions and this resulted in most areas of the Midwest seeing a cold and fairly snowy Jan and Feb and a good portion of the northern Midwest seeing below average temps and above average snowfall for the winter of 2003-2004.

A strong El Nino still means bad news for the northern US, with temps generally running above average and snowfall generally below average. The stronger the El Nino, the worse the news in most cases.

El Nino’s sister- La Nina, also can provide her own set of weather anomalies and weak La Nina’s tend to produce the best chances for below average temps from the Canadian Prairies south into the north central US- including the northern Midwest. In contrast to El Nino, the stronger the La Nina, the less likely this cold anomaly is like to be. La Nina also can produce above average temps in the far southern Midwest, although these warm anomalies rarely reach as far north as the true snow grounds for the Midwest.

A method that I have talked about in the past and like to use to try and get some kind of a heads up on what the winter will bring is also very simplistic, but does hold some merit. And that is to observe what happens in the weather with respect to the "averages" for a particular region. To be more specific, the larger the period of time you are looking at, the closer to "normal" the numbers will be for temp and precip. If you look at one day, the temps might be 10-20 degrees warmer/colder than average, and precip might be 200% of average for that day. Look at 5 days combined, including that initial day, and the temps will likely be less than 15 degrees above/below average and the precip might be something like 150% of average for that time frame. Expand the period of study to 30 days at the temps are likely to be 1-3 degrees above/below and precip might be something like 100-130% of average. Go all the way out to a year and it is hard to find an area or even station that is more than 1 degree above/below the average for temp and more than about 110-120% of average for precip.

No drought lasts forever, they are always broken, it always rains again. No flood lasts forever, the rains always stop and within a period of time, things return to "normal". The same can be said for temps. Cold snaps come and go, so do heat waves. Nothing lasts forever in the weather. If it did, I would be out of a job!

So with that thought process in mind, the longer an area is seeing a certain weather anomaly occur, the better the chances that the anomaly will break down and, in many cases, the reverse of what was happening will occur. The time period can be a few days, a few weeks, a few months and even a few years.

Another method I like to use is similar to the previously mentioned method, only it looks at what the pervious several seasons have been like not just the past few months, examines them for any anomalous weather and then sees if there is any imbalance that has occurred in the past 5-15 years. If there is some kind of imbalance, then my idea is that the more types of seasons a particular region sees, the greater the chances that it will see the opposite occur. I find that the best way to illustrate things is to give an example and so I will do that here; I probably do not have to tell persons in areas of central WI that the past several winters have been rather poor in the snowfall department. So it can be said that they have had an unusually high amount of low snow seasons in the past several years. So unless the climate is changing in central WI, they have a greater chance that one of the next few or several of the next few winters will be the opposite and provide above average snow.

So where does that leave us? Well, first I hope that I have made my point that most seasonal forecasts are just plain old guesses and in many cases, your guess will be as good as any meteorologist’s (no matter what they might think!).

Secondly, there are a few things that might lead to a statistical advantage of one type of weather to be expected over another, but there really is no way to say with much confidence at all what a season might bring.

-John