Aiming to improve the seasonal and El Nino forecast system, we develop the El Nino forecasting system, and enrich scientific knowledge and technological bases of mechanism of inter-seasonal to inter-annual variations, the land surface processes and the sea surface processes.
In order to achieve this objective, we develop the El Nino forecasting system that consists of the atmosphere-ocean coupled general circulation model (CGCM [AGCM: TL95L40, OGCM:1x1L50]) and the global ocean assimilation system.
To improve the forecasting technology, through the El Nino hindcast experiments using the CGCM, the atmospheric general circulation model (AGCM), or the ocean general circulation model (OGCM), moreover using long-range reanalysis, we examine the property of variability of energy and water cycle processes associated with the global scale or the Asian Monsoon, and the seasonal predictability.
We develop the El Nino forecasting system that consists of CGCM and the 3D-VAR global ocean assimilation system. To improve the model, we improve the fluxes between atmosphere and land surface, and between atmosphere and ocean.
The seasonal predictability is examined using these models.
Through the atmospheric reanalysis, global soil wetness experiment, and various data assimilation experiments, we examine the property of variability of energy and water cycle processes associated with the global scale or the Asian Monsoon, and the reproducibility of extreme valure about precipitation.
(1) Development of the El Nino Forecasting System
(2) Study on improvement in land surface model and ocean surface model
(3) Study on mechanism of inter-annual variations in the atmosphere-ocean-land processes and seasonal predictability
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