Weather forecasting process needs many weather components, big data size and forecaster experience. They cause the accuracy and rapid of forecasting were not well-fulfilled. In order to solve this problem, the research of prediction model was done by using Association Rule and Classification (C4.5, Classification Tree and Random Forest) methods. The input of model production were wind speed, cloud cover, dew point temperature and temperature from 9 marine stations in 2009. The input for testing the resulted model was synoptic data of Tanjung Priok Marine Station since 2002-2010. The result shows the accuracy of C4.5 is highest than others. Accuracy of C4.5 and Association Rule are about 68.5%, and 60.9%, respectively. Thus, the appropriate prediction model is the C4.5. Dominant weather component of C4.5 are cloud cover, dew point temperatur and temperature.
We detected a robust cyclonic eddy in the northeastern Natuna Island in the Northwest Monsoon during an extremely negative El Niño-Southern Oscillation (ENSO) period (i.e., extreme La Niña event) using the Copernicus Marine Environment Monitoring Service (CMEMS) reanalysis results. In the intense La Niña event from 1999 to 2001, we also found an increase in the abundance of chlorophyll coincided with the eddy strength pattern using the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data. Furthermore, this chlorophyll intensity may be related to the upwelling of water mass to the surface at the eddy’s center. The intensification of chlorophyll compared to the average value at the corresponding year is 83,4% (1999), 37.8% (2000), 37.3% (2008), and 72.5% (2011). In this paper, we revisit the identification of solid eddies in extreme La Niña events from 1999 to 2012 and further discuss the mechanism of the relationship between chlorophyll intensity and eddy strength, especially during the months of the extreme La Niña event.
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