日本地球惑星科学連合2023年大会

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[E] オンラインポスター発表

セッション記号 A (大気水圏科学) » A-TT 計測技術・研究手法

[A-TT29] Machine Learning Techniques in Weather, Climate, Ocean, Hydrology and Disease Predictions

2023年5月23日(火) 10:45 〜 12:15 オンラインポスターZoom会場 (7) (オンラインポスター)

コンビーナ:Jayanthi Venkata Ratnam(Application Laboratory, JAMSTEC)、Patrick Martineau(Japan Agency for Marine-Earth Science and Technology)、土井 威志(JAMSTEC)、Behera Swadhin(Climate Variation Predictability and Applicability Research Group, Application Laboratory, JAMSTEC, 3173-25 Showa-machi, Yokohama 236-0001)

現地ポスター発表開催日時 (2023/5/22 17:15-18:45)

10:45 〜 12:15

[ATT29-P04] Prediction of surface air maximum temperature over India one week ahead

*Venkata Ratnam Jayanthi1Swadhin Behera1Masami Nonaka1Patrick Martineau1Kalpesh Ravindra Patil1 (1.Application Laboratory, JAMSTEC)

キーワード:heatwave, machine learning

In this study we used various machine learning models to predict the surface air maximum temperature one week ahead over India in the months March to June, the period when India experiences heat waves. The input attributes to the machine learning models are derived using lag correlation analysis between observed surface air maximum temperature anomalies and sea surface temperature as well as with soil moisture anomalies. Several model experiments were carried out by varying a) feature reduction techniques b) pre-processing methods, c) the number of neurons, and d) the activation function and solvers. The results indicate choosing the right combination of pre-processing methods and parameters is essential for predicting extreme temperatures over India using machine learning techniques.