arXiv subjects

Daisuke Takasuka

Publications and source records attributed to Daisuke Takasuka.

4 recordsLinked to original sources

arXiv2026

Climate and ocean circulation changes toward a modern snowball Earth

It has been hypothesized that the Earth may have experienced snowball events in the past, during which its surface became completely covered with ice. Previous studies used general circulation models to investigate the onset and climate of such snowball events. Using the MIROC4m coupled atmosphere--ocean climate model, this study examined the changes in the oceanic circulation during the onset of a modern snowball Earth and elucidated their evolution to steady states under the snowball climate. Abruptly changing the solar constant to 94% of its present-day value caused the modern Earth climate to turn into a snowball state after ~1300 years and initiated rapid increase in sea ice thickness. During onset of the snowball, extensive sea ice formation and melting of sea ice in the mid-latitudes caused substantial freshening of surface waters and salinity stratification. By contrast, such salinity stratification was absent if the duration between the change in the solar flux and the snowball onset was short. After snowball onset, the global sea ice cover and the buildup of salinity stratification caused drastic weakening in the deep ocean circulation. However, the meridional overturning circulation resumed within several hundred years after the snowball onset because the density flux by sea ice production weakens the salinity stratification. While the evolution of the oceanic circulation would depend on the continental distribution and the evolution of continental ice sheets, our results highlight the gradual growth of sea ice and associated brine rejection are essential factors for the transient evolution of the oceanic circulation in the snowball events.

physics.geo-ph↗

arXiv2025

Propagation of the Madden-Julian oscillation as a deterministic chaotic phenomenon

The Madden-Julian oscillation (MJO), a gigantic tropical weather system, is marked by eastward travel of cumulus cloud clusters over the Indo-Pacific region and often causes severe weather and climate events worldwide. The physics and predictability of MJO propagation remain elusive, partly because of little attention to untangling roles of multi-scale processes relevant to the MJO. Here, we reveal the chaotic nature of MJO propagation arising from cross-scale nonlinear interactions, based on 4,000-member ensemble global cloud-system-resolving simulations of two MJO events. Against conventional linearized thinking, multiple regimes with distinct timings of MJO propagation emerge under a single atmosphere-ocean background. The bifurcation emergence depends critically on the equatorial asymmetry of climatological sea surface temperature. Selection of the bifurcated regimes is probabilistic, influenced by whether tropical-extratropical interplay promotes moistening associated with westward-propagating tropical waves over the western Pacific. These aspects help build a comprehensive MJO model and foresee when the MJO propagates.

physics.ao-ph↗

arXiv2022

Machine learning prediction of the MJO extends beyond one month

The prediction of the Madden-Julian Oscillation (MJO), a massive tropical weather event with vast global socio-economic impacts, has been infamously difficult with physics-based weather prediction models. Here we construct a machine learning model using reservoir computing technique that forecasts the real-time multivariate MJO index (RMM), a macroscopic variable that represents the state of the MJO. The training data was refined by developing a novel filter that extracts the recurrency of MJO signals from the raw atmospheric data and selecting a suitable time-delay coordinate of the RMM. The model demonstrated the skill to forecast the state of MJO events for a month from the pre-developmental stages. Best-performing cases predicted the RMM sequence over two months, which exceeds the expected inherent predictability limit of the MJO.

physics.ao-ph↗

arXiv2022

Climate of high obliquity exo-terrestrial planets with a three-dimensional cloud system resolving climate model

Planetary climates are strongly affected by planetary orbital parameters such as obliquity, eccentricity, and precession. In exoplanetary systems, exo-terrestrial planets should have various obliquities. High-obliquity planets would have extreme seasonal cycles due to the seasonal change of the distribution of the insolation. Here, we introduce the Non-hydrostatic ICosahedral Atmospheric Model(NICAM), a global cloud-resolving model, to investigate the climate of high-obliquity planets. This model can explicitly simulate a three-dimensional cloud distribution and vertical transports of water vapor. We simulated exo-terrestrial climates with high resolution using the supercomputer FUGAKU. We assumed aqua-planet configurations with 1 bar of air as a background atmosphere, with four different obliquities ($0^{\circ}$, $23.5^{\circ}$, $45^{\circ}$, and $60^{\circ}$). We ran two sets of simulations: 1) low-resolution (~ 220 km-mesh as the standard resolution of a general circulation model for exoplanetary science) with parametrization for cloud formation, and 2) high-resolution (~ 14 km-mesh) with an explicit cloud microphysics scheme. Results suggest that high-resolution simulations with an explicit treatment of cloud microphysics reveal warmer climates due to less low cloud fraction and a large amount of water vapor in the atmosphere. It implies that treatments of cloud-related processes lead to a difference between different resolutions in climatic regimes in cases with high obliquities.

astro-ph.EP↗