Reflection strength is normally not enough on its own to provide a reliable and useable identification between some weather types (or if it is considered this way, it is often inaccurate). Additional processing such as Doppler shift techniques or polarisation are often employed
Reflection strength is normally not enough on its own to provide a reliable and useable identification between some weather types (or if it is considered this way, it is often inaccurate). Additional processing such as Doppler shift techniques or polarisation are often employed.
The composition and type of rain clouds themselves is also important. The drop size has an important effect on the attenuation and reflectivity of the weather. In addition, depending on the precipitation rate, there can be some degree of confidence that certain volumes of drop size will be found in a cloud. When this is known, the reflectivity of these drop types can be estimated and the comparative reflectivity by rainfall rate estimated. The following table helps to illustrate this.
The expected percentage of drops of specific sizes over precipitation rates is shown below.
(D - cm)
|Precipitation Rate (mm/hr)|
|Percentage of given volume containing drops of diameter D|
Table 1: percentage of drops of specific sizes
Based upon this information, it is possible to estimate the comparative reflectivity of different rainfall rates. This knowledge of cloud formations also allows more detailed modeling and identification of clouds.
In addition, it is noted that the temperature is also another factor in the equation. Attenuation of the transmitted microwave energy varies by temperature.
It is noted that the identification of the scale of weather, based on the returns received, is often not a precise science. One source (MIT Labs in the USA) estimates that the use of pre-defined scales can give errors of 50%-100%! However, tuning of stations using physical measuring techniques can improve this considerably (e.g. rainfall gauges are accurate to within 5% to 10%). Additional, more sophisticated, techniques to correct the interpolation can bring these errors down further to between 20% and 50%. Again, it depends on the sophistication of the processing and tuning at each site.
The identification of hail is an important function of a weather radar.
Some methods of identification require complex radars which are currently only used in research.