How It works

Our customers often ask us, “How in the world do you do this?” The long answer is complex and involved, and beyond the scope of this explanation. There is a short answer, however, and it has to do with the ClimaTrends research model. At ClimaTrends we analyze normally static data points in a dynamic context. This has become possible since several zones of influence in the atmosphere have been discovered after almost three decades of persistent observation of upper air maps. We have linked these high-atmosphere maps with mapping techniques borrowed and customized from the discipline of projective geometry. The results of this research can be seen in the first image.

On this chart of North America and the eastern Pacific, several sets of curves can be seen. About twenty years ago we observed that storms traveling across the eastern Pacific seemed to “run into” conditions for deepening that couldn't be explained simply from standard analysis. We also saw that for some unseen reason blocking ridges would suddenly release their moorings and start drifting along in the polar jet stream. Again, for no apparently good reason, a weak high that was in motion would suddenly stop moving and transform into a drought-producing ridge. We noticed at that time that the zone for the greatest influence — whether towards high pressure or low pressure — was consistently found in the same area in a given season.

The first chart shows the zone of greatest influence over the central Gulf of Alaska. This chart depicts a high that is blocking at that longitude, sending the jet stream (arrow) north and then south around the high, ultimately bringing cold wet weather to the West Coast. In the same chart a green diamond formed by the curved lines is seen, a ClimaTrends indicator of another significant area where the maximum disturbance at any given time can be found. The placement of these curves and the diamond (another part of ClimaTrendsʼ trade secret) have been determined by dynamic geometrical techniques, coupled with many years of climate observation. In the same chart it can be seen that there is a family of similar curves stretching eastward from the zone of greatest influence. Our research has shown that these other areas can also be counted on to produce harmonic effects similar to the area of greatest influence, but on a smaller scale. In particular, placement of these geometric curves allows our research to pinpoint the emergence of the all important blocking ridges that consistently determine the character of extended trends. To know the position of these features in advance allows for a more dynamic and fluid modeling technique that can approximate future conditions more accurately.

In the second image the same zones are depicted but this time the influence is in support of low pressure. The same longitudinal spread is present here but a different influence is active. Our research has shown that the fluctuation of high and low pressure influences on these zones alternates rhythmically in observable cadences that can be predicted well before hand. This rhythmic alternation is the heartbeat of our work at ClimaTrends. These cadences are linked geometrically to the placement of the grid lines and have proved to be capable of robust modeling of systems in flux.

A third piece of the puzzle is the discovery that these curves are also not static, but move sedately and elegantly through time marking each seasonal passage in approximately ten year intervals. This makes the forming of modeling experiments highly effective when used to analyze decadal and inter-decadal patterns widely accepted as highly influential on climate trends. With these tools it is possible to approach a 70% overall accuracy rate on general trends in weather one or even two years in advance.

What about the Rhythms?

Another question often asked is, ”How can ClimaTrends offer such long range forecasts?” The short answer is that even when it is possible to say that high or low pressure has the greatest chance of showing up in a specific locale, the real art is to tell when that will happen and how strong it will be. As we mentioned, ClimaTrends is a dynamic system of modeling rather than a static system. This means that in our research we use models that focus on the what we call the rhythmic signatures of weather events rather than focusing on the statistical physical data linked to each event. Standard forecasters use what is happening today as the basis for the unfolding of the future. This works for about three to five days. To go out longer than that puts the forecast on thin ice. This fundamental dilemma of weather forecasting is the reason that weather forecasters are often the brunt of jokes.

The ClimaTrends system does not build complex computer modeling systems that compute the fixed data points of today's weather and then try to extrapolate next month's weather. We start with a projective geometric gridwork that is designed to simulate any complexity that is part of a large process. These techniques were found in the late 1940ʼs and were a curiosity for almost half a century because no practical application could be made from them. At Climatrends we think that we have found the ideal practical applications for these geometries.

Since our study is rhythm, fifteen years ago we found that the rhythms of the atmosphere in the upper layers are driven by the movements of the moon. This fact is standard knowledge to those scientists who study the Aurora Borealis. What happens in the upper atmosphere is often a good indicator of the weather a few days in advance. We use this rhythmic counter-point of the flow in the upper atmosphere interwoven with the models from projective geometry to create the dynamic modeling used in ClimaTrends forecasts.

In this unusual image the monthly rhythmic motions of Earth, Sun and Moon are depicted. The Sun is at the top. It generates a field of activity known as the solar wind. The solar wind moves through space and interacts with the magnetic fields and the upper atmosphere of the Earth. The small circle with the E in it is the Earth. It sits within the orbit of the Moon represented by the dotted circle. It orbits the Earth in a counter clockwise motion depicted by the dark arrows. The solar wind, interacting with the Earth creates a bow wave similar to the wave in the front of a moving ship. This is depicted by the tear-drop shaped field of lines streaming around the Earth. The streaming of the tail of this large formation is known as the magneto-tail of the Earth. The force of the solar wind pushes the magnetic field of the Earth far out into space in a trailing tail similar to a comet. The magneto–tail is composed of streaming particles that are stripped from the Earths magnetic field. The small arrows in the magneto-tail show the direction of the flow around the Earth.

The movement of the Moon around the Earth interacts with the flow of the magneto-tail. When the Moon is moving with the flow of the magneto-tail at first quarter there is little turbulence in the streamlines. When the Moon moves into the full position in its orbit it crosses through the very center of the inner area of the tail and creates strong disturbances. From these disturbances ripples and eddies form in the stream, depicted here by the red eddies in the center of the diagram. These eddies are the Aurora Borealis. Similar eddies are created in the upper atmosphere that work down into the lower layers of the weather sphere creating stronger than normal tendencies towards storm formation. This effect lasts for about three days after the full Moon. It is especially pronounced when it is coincident with solar flare events.

As the Moon moves towards the third quarter things settle down again until just at third quarter there is a slight tendency towards storming. However as the Moon approaches the dark it is once again moving across the core of the magnet-tail and once again for three days there is a strong tendency towards increased storm formation. This is also enhanced when it is coincident with a solar flare event.

Using these rhythms along with projective geometry grids, ClimaTrends researchers can work into the future in a dynamic way to pinpoint trends long before they happen in the atmosphere.

Of course, all of these explanations are only parts of the short answers. Over three decades the models developed are much more sophisticated than these short descriptions can illustrate. What the models do allow for is a different way of looking at long range forecasting emphasizing the dynamic aspects of weather data rather than simply computing the static aspects, computed averages, and potentialities based on past statistical information. The models themselves are geometrically rhythmical, not merely computational, reflecting the living, breathing nature of our Earth's weather.

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