Abstract

When flying through clouds that co ntain supercooled liquid water, aircraft can accumulate ice at levels that can be dangerous to flight. Similarly, in the field of weather modification, the amount and distribution of a cloud's supercooled water content is an important indicator of artificial precipitation. The G-band water Vapor Radiometer (GVR) is a small instrument that can be mounted on aircraft. Its operating frequency is highly sensitive to low liquid water content, which is particularly suitable for detecting supercooled water in different parts of clouds during changes in flight position. In order to explore supercooled water, we installed such an instrument with four double-sideband receiver channels centered at 183.31 ± 1, ±3, ±7, and ±14GHz, under the right wing of a King Air B-10KL that we used to perform a series of outfield observations and artificial precipitation missions. In this paper, we discuss the feasibility of detecting supercooled liquid water in the clouds over North China with a GVR. A Back Propagation (BP) neural network algorithm that takes into account flight details including aircraft altitude, climate background and geographic location variations was developed to retrieve supercooled liquid water path (SLWP). A numerical simulation test using the radiosonde data as test samples showed that the retrieval results correlate highly with the radiosonde data calculation results, and that the algorithm was applicable for different seasons and different geographical locations. The algorithm was then applied to the aircraft outfield observations of supercooled liquid water and the results were compared with hotwire, another cloud liquid water observation instrument installed on the aircraft. Results here showed agreement in terms of trend. The observation of SLWPs over clouds thought to be of 0-value shows that the root mean square error of retrieval results is as low as 0.2 g m−2. This paper demonstrates that it is feasible to measure supercooled water over North China with GVR using the retrieval algorithm used here, which obtained good results and is able to compensate for the lack of reliable supercooled water detection instruments on the aircraft.

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