Comparison of seasonal prediction outputs based on dynamic atmosphere model and observations (case study: seasonal prediction in 2016 - 2017)

International Conference On Tropical Meteorology And Atmospheric Sciences

生态环境科学;原子能学

Satyawardhana, H.^1 ; Gammamerdianti^1

Center for Atmospheric Science and Technology, National Institute of Aeronautics and Space, Bandung, Indonesia^1

关键词: Agriculture sectors;    Atmosphere modeling;    Atmospheric phenomena;    CCAM;    Satellite rainfalls;    seasonal;    Seasonal characteristics;    Seasonal prediction;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/303/1/012050/pdf
DOI  :  10.1088/1755-1315/303/1/012050

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Seasonal predictions are considered as an important factor for many sectors in Indonesia, especially for the agriculture sector. In Indonesia, the variability of seasonal characteristics is influenced by various regional atmospheric phenomena, such as monsoon, ENSO, and IOD. With such urgency, this research is conducted using dynamic models to generate accurate medium-term predictions. The dynamical atmospheric model, Cubical Conformal Atmospheric Model (CCAM) is used to produce daily predictions up to 8 months. CCAM result has been tested on major islands in Indonesia such as Java, Sumatra, Sulawesi, Borneo and Papua. It shows that during the rainy season, the value of rainfall predictions is lower than observations. Meanwhile, the rainfall predictions are overestimate when compared to observations during dry season. Nevertheless, the patterns of rainfall predictions are following satellite rainfall observations patterns, especially in Java.