Not all clear night skies are created equal. This realization normally comes early to budding stargazers who have taken ownership of their first telescope. The image of Saturn through the eyepiece may appear clear, sharp and rock-steady one evening, but degrade into a fuzzy, "swimming" blob of light that just can’t be focused the next. Why the difference? Let’s start by ruling out some possible causes. It is a good instrument. The curve of the objective mirror is well within design tolerances and the optical system is accurately collimated. In addition, we’ve eliminated such things as the scope not being at thermal equilibrium and viewing targets too close to the horizon. So, what’s left? In all likelihood, the observed difference in image quality is the result of an atmospheric phenomenon called "seeing".

There is a significant amount of literature to suggest that if seeing quality can be sufficiently linked to specific meteorological parameters, then it should be possible to forecast seeing conditions using available weather data. Although not yet completed, the following scheme attempts to accomplish this objective.

Simply put, poor seeing is caused by atmospheric turbulence. It can occur in three main regions within the telescope viewing path, each of which is associated with different mechanisms of turbulence generation. From the highest to the lowest altitudes, these regions are the free atmosphere (above the boundary layer), the boundary layer (from the surface to as high as about 3,000 feet--where the ground exerts an influence), and the area in and around the immediate observing site. It is also customary to group weather features by their size and extent of influence. An extra-tropical (non-tropical) storm, for example, can grow to 1,000 miles or more, while a thunderstorm seldom exceeds a diameter of about 10 miles. In meteorology, these scales are defined (roughly) as the macro-scale (greater than 300 miles), the meso-scale (10-300 miles) and the micro-scale (less than 10 miles). The task now is to identify which weather processes that are known to cause turbulence operate in each of these scale "zones".

One of the major causes of turbulence is the strong wind (speeds sometimes exceeding 300 mph) and steep temperature gradients found in the vicinity of the jet stream at an altitude of 30,000-40,000 feet. As wind velocities quickly drop off at increasing distances from the jet’s core, eddies are generated that mix air parcels of different temperatures. Extreme levels of turbulence are often found in these regions. In his article How to Predict Seeing (January 2000 issue of Sky and Telescope magazine), Eric J. Douglass found that seeing improved significantly when the jet stream was located at increasingly greater distances from his observing site. We propose implementing a similar grading system. A 300mb or 500mb upper air chart will probably be used to for this evaluation.

A weather front exists at the interface of two air masses of different temperatures and/or moisture content. We call this boundary a cold front when the colder air is advancing toward the warmer air. Since it is more dense, the cold air undercuts warm air, forcing it aloft. Because of this vertical lifting, and because cold air is susceptible to convection, the turbulence in the vicinity of a cold front is usually great. Not surprisingly, then, Douglass also noticed a correlation between the proximity of a cold front and seeing quality. Weather fronts are normally depicted on surface weather charts.

Instability is a term used to describe the tendency for the air to undergo vertical motion. An unstable atmosphere encourages air to rise initially, then fall after undergoing adiabatic cooling. This tends to result in the generation of convective currents of air. Strong surface heating and cold temperatures aloft will produce the greatest levels of instability. Conversely, a stable atmosphere tends to discourage vertical air motion. Atmospheric processes that tend to cause cooling at the surface and warming aloft (thermal inversion) produce highly stable air that is largely free of this type of turbulence. A stability index needs to be developed to measure this effect.

Winds at the ground normally blow in response to broad-scale pressure patterns (important exceptions to this rule include thunderstorm downdrafts, tornadoes and the local effects of unequal surface heating). Once it is set into motion, air becomes susceptible to certain kinds of turbulence. While in theory it is true that extremely stable moving air can be turbulent-free (laminar flow), such conditions rarely, if ever, occur outside the laboratory. The assumption here is that higher wind velocities tend to result in higher levels of turbulence. Using a surface weather chart, the key here is to determine the pressure gradient within, say, a 300-mile radius of the observing site.

At the lowest level of the atmosphere the horizontal movement of air is impeded by the ground. This frictional drag introduces a form of mechanical turbulence into the boundary layer of the atmosphere. A relatively smooth, uncluttered ground will produce low levels of turbulence, while a rough ground with high relief will disturb the air to a greater degree. A scale developed by wind engineers will be utilized here.

The type of terrain that surrounds an observing site may cause movements of air that degrade the quality of seeing. If there are uneven ground features nearby (such as the steep slopes of a mountain or hill, gorges or gullies), then nocturnal drainage may generate moving currents of relatively dense air that can adversely impact image quality.

The type of ground cover immediately surrounding an observing site will often impact the quality of seeing. If the ground is allowed to heat up during the daylight hours by absorbing the sun’s short-wave radiation, that stored heat will be reradiated back into space during the night, causing micro-scale turbulence in the process. Black asphalt is an extreme example of this effect. Surfaces that either dissipate or reflect sunlight minimize this effect. Natural ground cover such as grass or leafy shrubs tends to distribute the sun’s energy in ways that keep the temperature of these surfaces relatively cool.

In its most usable form, this tool for predicting seeing consists of a set of tables that attempts to grade each of the seven potential causes of turbulence by assigning numerical values based on the magnitude of its occurrence.  Atmospheric Effects Table

Paul Couteau on Seeing

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