In 1999, places like Chicago, Green Bay and Milwaukee had their first snowless November in more than a century, and even Bismarck, North Dakota didn't receive any snow until mid December. The winter of 1999-2000 was the warmest ever recorded in the US. Temperatures for the months December through February were 0.6 F degrees warmer than the previous warmest winter, just the year before. Furthermore, more than a fifth of the contiguous U.S. was near record warmth each month from January through May.

How quickly things can change in the weather business. This year, Chicago and Milwaukee had their snowiest December ever, and for the nation as a whole, it was the coldest November and December combined since 1985! The average temperature for December was a paltry 29 degrees F. It's typical that the cold air arrived concomitant with the higher fuel bills. You might think that since most of the winters were warm during the 1990s, we would have sufficient oil, gas and hydroelectric reserves, but it doesn't seem to work that way.

The cold, snowy weather hasn't just been confined to the US. Northern and western Europe, Russia, China, and even northern India have all been experiencing bone-chilling conditions since late December. For instance, a big snowstorm hit the United Kingdom on the 28th of December, dumping more than a foot of snow in some parts of Ireland, northern England and Scotland - London had about 3 inches of snow. Also, nearly 100 people have died in northern and eastern India from hypothermia during a particularly bitter and rare cold wave. In addition, Korea, and most of northern and northeastern China were buried under their worst blizzard in more than 50 years.

Of course, things can change just as fast in terms of precipitation. The old expression "when it rains it pours" was certainly appropriate for parts of the deep south and southern plains in 2000. Severe drought was prevalent for much of the growing season. It was the driest May through October period ever in Georgia, Florida, Alabama, Mississippi, and Louisiana, and the driest July through September on record in Oklahoma, Kansas, and Texas. However, in many of these same places, it was the wettest November ever.

While the average temperature in the US has increased about 1.6 degrees F since 1975, we're not warming each and every year and in all parts of the country. It's not at all unusual for temperatures to be several degrees cooler or warmer for a particular month from one year to the next, but it's indeed unexpected when temperatures swing from record warmth for a given month to record cold for the same month the following year.

Where the polar jet stream happens to reside can make all the difference in the winter weather from one year to another. This past autumn, the jet stream was positioned more southerly than it was for the same period the previous year. This allows incursions of cold from Alaska and Canada to more frequently push into the contiguous US. If the jet stream in located more northward or moves across the US in a west to east or zonal flow, these cold air outbreaks will occur less often. This was the case throughout most of the 1990s.

The position of the jet stream, and the very large temperature fluctuations observed between the beginning and end of 2000 can't really be attributed to volcanic eruptions, El Nino or La Nina, although, fairly strong La Nina conditions were present at the beginning of 2000. With improving forecasting skills in more recent years and having a better understanding of factors that govern our weather and climate, we've grown somewhat accustomed to having various phenomenon, such as El Nino, help explain the changes we observe from year to year and season to season. However, the natural variability of weather patterns and climate systems still plays a dominant role in our seasonal and annual temperature and precipitation regimes. Of course, we're not yet to the point that we can reliably predict what the weather will be like next winter, and we may never get to that point. In fact, it's unlikely that we will.

Weather systems sometimes cooperate with forecasters and move in repeatable patterns. For example, a storm that approaches California from the Pacific Ocean will generally take 4 to 6 days to makes its way across the country. If the jet stream has a zonal flow, and if several storms are lined up in the Pacific, they'll take a similar track as they move eastward. As a result, your local area may end up with several consecutive wet weekends. These patterns eventually breakdown, thank goodness, and are replaced by others. In terms of forecasting, it's extremely difficult to predict when in the future a pattern, like the Pacific storm pattern, will become established. It's true, that the models used by meteorologists to simulate the shifting motions of the atmospheric have become increasingly sophisticated and have been largely responsible for the improved forecast accuracy in recent decades. But the problem is that no two atmospheric states have ever been or are apt to be, exactly the same. In modeling, there is sensitive dependence to initial conditions, and when the initial atmospheric conditions aren't well known, this can result in chaos. Since the models can't possibly know the conditions for every point on the globe, estimates of what the conditions are though to be are used for most points.

Perhaps you've heard of the "butterfly effect." Can the casual flapping of a butterfly in a garden in Santa Fe, New Mexico, for example, eventually lead to the development of a severe thunderstorm over the plains of Nebraska? In chaos theory, a very small perturbation can makes things happen quite differently than they would have if the perturbation never occurred. The "butterfly effect" magnifies the initial imperfections inherent in all models. The models may agree with observations for a few days, but soon the errors are compounded and grow so large that the model simulations are virtually useless.

Think of it this way. Suppose you drop a cork in a small stream in the head-waters of a major river, and say eventually the cork makes it to the sea. Imagine how difficult it would be to know just where it will end up along the way. In order to forecast this, you have to have a lot of information about the river, otherwise, you're simply making a guess. Atmospheric modelers are confronted with this type of scenario, except they have to deal with an atmosphere that is considerably more complex and many times deeper than the river.

Forecasters have been working with different ideas to enable their models to try to partially overcome the "butterfly effect." For instance, when a butterfly flaps its wings within an unstable air mass, the effect will cascade downstream, however, if the same butterfly is in a stable air mass, nothing much will happen. At least, that's the thinking. So, knowing precisely where (in which air mass) and to what degree to adjust a model's initial conditions may be one way to help to deal with chaos. If the tiny ripple caused by butterflies fluttering about could even remotely effect the weather somewhere in the world, is it any wonder that millions of years ago, before pterodactyls became extinct, the climate was vastly different from todays.

For more about this see the following; Science News for May 5, 1990 and Weatherwise for August, 1990. Also see the following see the Earth Science Picture of the Day for January 4, 10 and 11 http://epod.usra.edu/archive/bymonth/arch_1_2001.php3