Methods Employing Local Thermal Parameters

The following text discusses methods of employing surface temperature, upper-level temperatures, 1000- to 700-hPa and 1000- to 500-hPa thicknesses, the height of the freezing level, and combined parameters for the prediction of snow versus rain. All of these are interdependent, and should be considered simultaneously.

SURFACE TEMPERATURE. Surface temperature considered by itself is not an effective criterion. Its use in the snow versus rain problem has generally been used in combination with other thermal parameters. One study for the Northeastern United States found that at 35F snow and rain occurred with equal frequency, and by using 35F as the critical value (predict snow at 35F and below, rain above 35F), 85 percent of the original cases could be classified, Another study based on data from stations in England suggested a critical temperature of 34.2F, and found that snow rarely occurs at temperatures higher than 39F. However, it is obvious from these studies that even though surface temperature is of some value in predicting snow versus rain, it is often inadequate. Thus, most forecasters look to upper-level temperatures as a further aid to the problem.

UPPER-LEVEL TEMPERATURES. Two studies of the Northeastern United States found that temperatures at the 850-hPa level proved to be a good discriminating parameter, and that including the surface temperature did not make any significant contribution. The discriminating temperatures at the 850-hPa level were -2 to -4C. Another study found that the area bounded by the 0C isotherm at 850-hPa level and the 32F isotherm at the surface, when superimposed upon the precipitation area, separated the snow-rain precipitation shield in a high percentages of cases. A range of -2 to -4C at the 850-hPa level should be used along coastal areas, and also behind deep cold lows, At mountain stations a higher level would have to be used.

A technique that uses temperatures at mandatory levels (surface, 1000-, 850-, 700-, and 500-hPa, etc.) is advantageous because of the availability of charts at these levels. There is, however, the occasional problem where temperature inversions are located near the 850- or 700-hPa levels, so that the temperature of one level may not be indicative of the layer above or below. This difficulty can be overcome by using thickness, which is a measure of the mean temperature of the layer.

THICKNESS. The National Weather Service has examined both the 1,000- to 700-hPa and 1,000- to 500-hPa thickness limits for the eastern half of the United States.

A generalized study of 1,000- to 500-hPa thickness as a predictor of precipitation forms in the United States was made by A. J. Wagner, More complete details on this study can be found in The Prediction of Snow vs Rain, Forecasting Guide No. 2.

Wagners data was taken from a study of 40 locations in the United States for the colder months of a 2-year period. Cases were limited to surface temperatures between 10F and 50F. The form of precipitation in each case was considered as belonging in one of two categories-frozen which includes snow, sleet, granular snow, and snow crystals; and unfrozen, which includes rain, rain and snow mixed, drizzle, and freezing rain and drizzle.

Equal probability, or critical thickness values, were obtained from the data at each location. From this study it was clear that the critical thickness values increase with increasing altitude. This altitude relationship is attributable to the fact that a sizable portion of the thickness stratum is nonexistent for high-altitude stations, and obviously does not participate in the melting process. To compensate for this, the equal probability thickness values must increase with station elevation. For higher altitude stations, thickness values between the 850- to 500-hPa or 700- to 500-hPa stratums, as appropriate, should prove to be better dated to precipitation form.

The Wagner equal probability chart is reproduced in figure 4-21. 

Wagners study also indicates that the form of precipitation can be specified with a certainty of 75 percent at plus or minus 30 meters from the equal probability value, increasing to 90 percent certainty at plus or minus 90 meters from this value. Stability is the parameter that accounts for the variability of precipitation for a given thickness at a given point. This fact is taken into account in the following reamer: if the forecast precipitation is due to a warm front that is more stable than usual, the line separating rain from frozen precipitation is shifted toward higher thickness values. Over the Great Lakes, where snow occurs in unstable, or stable conditions, the equal probability thickness is lower than that shown in figure 4-21 for snow showers, and higher than that shown in figure 4-21 for warm frontal snow.

HEIGHT OF THE FREEZING LEVEL. The height of the freezing level is one of the most critical thermal parameters in determining whether snow can reach the ground. It was pointed out earlier that theoretical and observational evidence indicates that a freezing level averaging 1,200 feet or more above the surface is usually required to ensure that most of the snow will melt before reaching the surface. This figure of 1,200 feet can thus be considered as a critical or equal probability value of the freezing level.

COMBINED THERMAL PARAMETERS. From the foregoing discussion, you can conclude that no one method, when used alone, is a good discriminator in the snow versus rain forecasting problem. Therefore, you should use a combination of the surface temperature, height of the freezing level, 850-hPa temperature, and the 1,000-to 700-hPa and /or 1,000- to 500-hPa thicknesses to arrive at the forecast, There is generally a high correlation between the 850-hPa temperature, and the 1,000- to 700-hPa thickness and between the 700-hPa temperature and the 1,000- to 500-hPa thickness. Certainly an accurate temperature forecast for these two levels would yield an approximate thickness value for discriminating purposes.

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