A Multisensor Approach to Detecting Drizzle on ASOS

Abstract

National Weather Service Automated Surface Observing System (ASOS) stations do not currently report drizzle because the precipitation identification sensor, called the light-emitting diode weather identifier (LEDWI), is thought not to have the capability to be able to detect particles smaller than about 1 mm in diameter. An analysis of the LEDWI 1-min channel data has revealed, however, that the signal levels in these data are sufficiently strong when drizzle occurs; thus, they can be used to detect drizzle and distinguish it from light rain or snow. In particular, it is shown that there is important information in the LEDWI particle channel that has not been previously used for precipitation identification. A drizzle detection algorithm is developed, based on these data, and is presented in the paper. Since noise in the LEDWI channels can sometimes obscure the drizzle signal, a technique is proposed that uses data from other ASOS sensors to identify nondrizzle periods and eliminate them from consideration in the drizzle algorithm. These sensors include the ASOS ceilometer, temperature, and dewpoint sensors, and the visibility sensor. Data from freezing rain and freezing drizzle events are used to illustrate how the algorithm can differentiate between these precipitation types. A comparison is made between the results obtained using the algorithm presented here and those obtained from the Ramsay freezing drizzle algorithm, and precipitation type recorded by the ASOS observer. The paper shows that by using data from the LEDWI particle channel, in combination with data from other ASOS sensors, the ability exists to detect drizzle with the current suite of ASOS instrumentation.