Research

Climate Change Impact Assessment

Global & Basin-Scale Hydrological Projections

Climate change adaptation and mitigation are pressing priorities in Japan and worldwide. Developing effective countermeasures requires a rigorous scientific understanding of how a warming climate alters hydrological systems. Our laboratory assesses the impacts of climate change across a wide range of atmospheric and hydrological processes, from global trends to local river basins.

1. Global-Scale Climate Change Impact Assessment

Atmospheric Reanalysis Datasets

Atmospheric reanalysis datasets combine numerical weather models with diverse observational records through data assimilation, providing spatially complete, physically consistent reconstructions of past climate. Because reanalysis products cover the entire globe, they enable long-term climate change assessments even in data-sparse regions where in-situ gauges are limited.

CMIP6 Future Climate Projections

Under Phase 6 of the Coupled Model Intercomparison Project (CMIP6), which informs the IPCC assessment reports, modeling centers worldwide conduct coordinated Global Climate Model (GCM) simulations. Paired with Shared Socioeconomic Pathways (SSPs)—scenarios representing alternative trajectories of socioeconomic development and emissions policies—CMIP6 projections allow us to evaluate future warming and hydroclimatic shifts across plausible futures. Using these multi-model ensembles, we conduct global-scale assessments of hydroclimatic change.

Historical precipitation trends derived from ERA5 reanalysis

Historical precipitation trends derived from ERA5 reanalysis

2. High-Resolution Climate Projections

Dynamical Downscaling of Global Climate Projections

Future climate projections rely primarily on Global Climate Models (GCMs). Because of computational constraints, however, GCMs typically run at horizontal grid spacings of 100 km or coarser—too coarse for regional or watershed-scale analysis and unable to resolve the atmospheric dynamics of extreme rainfall over Japan. We therefore dynamically downscale GCM outputs using regional atmospheric models to generate high-resolution climate fields.

Nationwide 2 km Grid Simulations Across Japan

We are conducting dynamical downscaling across all Class A river basins in Japan. After dividing the country into multiple computational domains and calibrating the regional atmospheric model for the watersheds within each domain, we downscale future climate projections onto a fine 2 km horizontal grid—capturing the complex topographic effects essential for reliable regional projections across Japan.

Computational domains covering all Class A river basins in Japan

Computational domains covering all Class A river basins in Japan

3. Regional and Basin-Scale Hydrological Impact Assessment

Leveraging high-resolution dynamically downscaled climate projections, we evaluate diverse hydrological impacts of climate change at regional and watershed scales.

Changes in Precipitation

Because precipitation is directly simulated by the regional atmospheric models used for downscaling, evaluating shifts in rainfall intensity, seasonality, and extremes serves as the foundation for watershed-scale water cycle assessments.

Impacts on Snow Accumulation and Melt

Snowfall, snowpack accumulation, and snowmelt are highly sensitive to warming temperatures. In snow-dominated basins, seasonal snowmelt provides a vital water supply from spring through early summer, meaning warming-induced shifts in snowpack volume and melt timing pose major challenges for water resources management.

Changes in River Discharge

River discharge responds not only to shifts in rainfall and snowmelt but also to warming-driven increases in evapotranspiration and land-surface feedbacks. Because changes in precipitation do not translate linearly into runoff, dedicated hydrological modeling is required to project future streamflow regimes in each basin.

Projected future changes in precipitation

Projected future changes in precipitation

Projected future changes in snowpack

Projected future changes in snowpack (Ishida et al., 2018)