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Yosuke Fujii, Toshiyuki Nakaegawa, Satoshi Matsumoto, Tamaki Yasuda, Goro Yamanaka, and Masafumi Kamachi

Abstract

The authors developed a system for simulating climate variation by constraining the ocean component of a coupled atmosphere–ocean general circulation model (CGCM) through ocean data assimilation and conducted a climate simulation [Multivariate Ocean Variational Estimation System–Coupled Version Reanalysis (MOVE-C RA)]. The monthly variation of sea surface temperature (SST) is reasonably recovered in MOVE-C RA. Furthermore, MOVE-C RA has improved precipitation fields over the Atmospheric Model Intercomparison Project (AMIP) run (a simulation of the atmosphere model forced by observed daily SST) and the CGCM free simulation run. In particular, precipitation in the Philippine Sea in summer is improved over the AMIP run. This improvement is assumed to stem from the reproduction of the interaction between SST and precipitation, indicated by the lag of the precipitation change behind SST. Enhanced (suppressed) convection tends to induce an SST drop (rise) because of cloud cover and ocean mixing in the real world. A lack of this interaction in the AMIP run leads to overestimating the precipitation in the Bay of Bengal in summer. Because it is recovered in MOVE-C RA, the overestimate is suppressed. This intensifies the zonal Walker circulation and the monsoon trough, resulting in enhanced convection in the Philippine Sea. The spurious positive correlation between SST and precipitation around the Philippines in the AMIP run in summer is also removed in MOVE-C RA. These improvements demonstrate the effectiveness of simulating ocean interior processes with the ocean model and data assimilation for reproducing the climate variability.

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