Information from the abstract
We evaluate binary rainfall occurrence classification in southern Thailand using 00 UTC radiosonde profiles from Phuket Airport and rainfall observations at Phuket, Krabi, Takua Pa (Phang-nga) and Nakhon Si Thammarat. Of 2631 soundings from 2011 to 2021, 1487 met quality-control and layer-continuity criteria. Five classifiers (logistic regression, support vector machines, random forests, extreme gradient boosting, and multilayer perceptrons) were evaluated using year-grouped cross-validation (2011–2019) and a chronological holdout (2020–2021). Holdout receiver operating characteristic area under the curve (ROC-AUC) reached 0.845 at Phuket, 0.793 at Krabi and 0.873 at Takua Pa, exceeding station-specific climatological baselines. At Nakhon Si Thammarat, the maximum holdout ROC-AUC was 0.691, indicating reduced spatial representativeness. Tree-based Shapley Additive Explanations (TreeSHAP) identified the K-index as the leading thermodynamic contributor across western stations, with geographically varying secondary contributions. Because daily rainfall windows include pre- and post-sounding periods, separate six-hour post-sounding evaluations (07:00–13:00, 13:00–19:00 and 19:00–01:00 local time) were conducted. Evening discrimination was consistently lower than morning discrimination across station–classifier combinations. A localized terrain–wind proxy provided negligible improvement. These results support temporally validated, station-specific rainfall occurrence classification while highlighting spatial representativeness and lead-time limitations for prospective operational use.
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Related topics: Meteorological Phenomena and Simulations · Precipitation Measurement and Analysis · Hydrological Forecasting Using AI
Thai researcher and institutional participation
Thanayut Changruenngam · Rattana Prommai · Suruswadee Nanglae · Weerapon Naitip · Hathaiwan Yodsuwan · Jumrus Klinhnu · Aree Binprathan · Chiang Rai Rajabhat University · University of Phayao · Thai Health Promotion Foundation
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