Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on artificial intelligence is now available. According to news reporting from Christchurch, New Zealand, b y NewsRx journalists, research stated, “The use of depolarization lidar to measu re atmospheric volume depolarization ratio (VDR) is a common technique to classi fy cloud phase (liquid or ice).” The news journalists obtained a quote from the research from University of Cante rbury: “Previous work using a machine learning framework, applied to peak proper ties derived from co-polarized attenuated backscatter data, has been demonstrate d to effectively detect supercooled-liquid-water-containing clouds (SLCCs). Howe ver, the training data from Davis Station, Antarctica, include no warm liquid wa ter clouds (WLWCs), potentially limiting the model’s accuracy in regions where W LWCs are present. In this work, we apply the same framework used on the Davis da ta to a 9-month micro-pulse lidar dataset collected in Otautahi / Christchurch, Aotearoa / New Zealand, a location which includes WLWC. We then evaluate the res ults relative to a reference VDR cloud-phase mask. We found that the Davis model performed relatively poorly at detecting SLCC with a recall score of 0.18, ofte n misclassifying WLWC as SLCC. The performance of our new model, trained using d ata from Otautahi / Christchurch, displays recall scores as high as 0.88 for ide ntification of SLCC, although it generally underestimates SLCC occurrence.”
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