Figure 10-3-16.Change in frontal clouds where an upper level trough interacts a front.

Figure 10-3-17.Shadow line cast by high cirrus cloud deck.

these features are detectable in IR imagery than visual imagery, but both systems have strong and weak points with regard to surface features, just as they do with cloud types. All of the above surface features are detectable in IR imagery when adequate temperature contrast exists across the feature or between the feature and its surroundings. However, since temperature differences and temperature gradients vary with latitude, season, and time of day, these features may or may not be seen all the time. For instance, coastlines with good temperature contrast between the land and seawater will show up well, but those coasts where little or no contrast exists will be hard to distinguish. Another IR effect you must be aware of is gray-shade reversal. The contrast seen at land-water boundaries often reverses at night. In the daytime, land usually warms to a temperature greater than that of the water, and the land appears darker than the water in imagery. But at night, the land cools to a temperature lower than that of the adjacent water, creating a reversal in shading. The land now appears lighter than the water.

Water surfaces always appear dark in visual imagery, but in IR imagery they maybe shaded. The shading is created by seawater temperature differences. Therefore, the IR imagery permits us to distinguish ocean eddies and currents. The boundaries of strong ocean currents, such as the Gulf Stream, are seen clearly, and sea-surface temperatures are obtainable where clouds are absent. Oceanic features as seen in imagery will be discussed in more detail after our units on oceanography and oceanographic analysis in volume 2 of the AG2 rate training manual.

Figure 10-3-18.Transverse cirrus bands associated with jet stream.

Figure 10-3-19.Dendritic pattern created by snow on mountain tops.

Some mountain ranges are easily detectable in IR imagery. Those with large temperature dif-ferences between the top and lower adjacent land and those with steep slopes produce a strong temperature gradient visible in the IR image. The Sierra Nevada mountain range, which rises from near sea level, is more visible in IR imagery than the equally high and cold Rockies.

Distinguishing mountain ranges in visual pic-tures is almost impossible. However, snow-capped mountains can be distinguished from surrounding terrain. Light snow on the tops of high mountains is better detected in visual pictures than IR, because the albedo difference between the snow and bare ground is quite large. In IR, the temperature difference between the two is small, and it is less likely to be differentiated by the radiometer.

Snow-covered terrain usually appears whiter in IR imagery than its surroundings. The brightness of the snow area depends on the temperature of the surrounding ground, which is not snow covered, whether there is vegetation within the snow-covered area, the type of vegeta-tion, and on how much of the vegetation is snow covered.

In visual pictures, differentiating between snow, ice, fog, clouds, and land is difficult at best. Differentiating between snow and ice is hard, and it becomes more difficult when the ice field is old. Snow cover on mountains is the easiest to detect in visual pictures, as the valleys are dark (due to vegetation) while the mountain ridges are bright (due to the reflection from the snow). This com-bination of bright snow and dark valleys produces a dendritic (branching) pattern, as seen in figure 10-3-19. With regard to albedo, snow shows up very bright, then clouds and ice fields, and then land, which is darkest. Ice has an albedo slightly less than clouds, and it shows up gray when it is beside snow. Frozen lakes appear as bright spots in visual pictures. They are easily distinguished from clouds in sequential satellite pictures, because they are stationary and the clouds move. The same method of comparison is used to deter-mine snow and ice fields from clouds.

At shore stations, it is advisable to post satellite imagery of your forecast area(s) that show land and water features at various times of the year under clear skies. Prominent Earth features should be highlighted. This is especially helpful to the satellite interpretation novice.

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