Spatiotemporal Modes Characteristics and SARIMA Prediction of Total Column Water Vapor over China during 2002–2022 Based on AIRS Dataset

Spatiotemporal Modes Characteristics and SARIMA Prediction of Total Column Water Vapor over China during 2002–2022 Based on AIRS Dataset

The total column water vapor (TCWV) is a relatively active component in the atmosphere and an important detection object of climate change. Exploring the spatiotemporal modes characteristics of TCWV and predicting its changing trends can provide a reference for human beings to deal with climate chan...

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Autors principals: Shanshan Shangguan, Han Lin, Yuanyuan Wei, Chaoli Tang
Format: Article
Idioma:English
Publicat: MDPI AG 2022-05-01
Col·lecció:Atmosphere
Matèries:
water vapor column
spatiotemporal distribution
EOF modes analysis
Mann-Kendall mutation test
SARIMA model
Accés en línia:https://www.mdpi.com/2073-4433/13/6/885

Internet

https://www.mdpi.com/2073-4433/13/6/885

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