Research

Extreme precipitation

Extreme weather is changing its form all over the world due to climate change. I am working on research focusing on atmospheric rivers, that are known to bring extreme precipitation and flooding to the US West Coast.

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• Subseasonal forecast of atmospheric rivers

It is known that the Madden-Julian Oscillation (MJO) in the tropical atmosphere modulates atmospheric river activity in 2-5 weeks time scale. However, there is large uncertainty in actual forecasts due to many other factors. We demonstrated that low-frequency variability of the Pacific/North American (PNA) mode can significantly improve atmospheric forecasts in this time scale. Read more in Toride and Hakim (2021) & Toride and Hakim (2022).

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• Probable maximum precipitation (PMP) estimation

PMP is the theoretical maximum precipitation that could fall over a particular region. The concept of PMP is widely used for the design and risk assessment of water resource infrastructure. We estimated PMP with realistically maximized storms in a Pacific Northwest region using an atmospheric model. We proposed a method that only perturbs moisture along the path of atmospheric rivers based on vertically integrated water vapor flux. We found that it creates more realistic atmospheric fields and more severe precipitation compared to the method used in previous studies. Read more in Toride et al. (2019).

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• Climate change analysis

We analyzed long-term trends in 160-year precipitation reconstructed over two watersheds along the US West Coast using a regional atmospheric model. We found increasing trends in extreme precipitation, a sharp increase in the variability of annual precipitation, and inconsistency with the trends at a regional scale. Read more in Toride et al. (2018) & Toride et al. (2019).

Water vapor isotopes for weather forecasting

Water isotopes refer to water molecules with heavier isotopes such as deuterium D and 18O than regular atoms (H and 16O). Water isotopes are useful tracers in the hydrological cycle due to the link to condensation and diabatic heating processes. We are exploring the impacts of assimilating high-density water vapor isotope data retrieved from the thermal nadir spectra IASI sensor to improve weather forecasting. We use an isotope-enabled atmospheric model and a data assimilation technique called ensemble Kalman filter in this study. Read more in Toride et al. (2021).

Reconstructing historical weather using old diaries

There is a large amount of documented weather information all over the world before instrumental weather records became available. We developed a system that incorporates qualitative data from old diaries into a numerical atmospheric model using a data assimilation technique. We demonstrated the potential to reconstruct historical weather by an experiment using visually observed cloud cover data over Japan. Read more in Toride et al. (2017).

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Currently, I am working on reconstructing historical weather using real diaries during the 19th century and improving the relationship between the description in old diaries and actual atmospheric variables.

Land surface hydrology - spatial heterogeneity

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The land surface is the most heterogeneous region in hydrology due to various factors including land use, soil characteristics, vegetation, and topography. 

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We proposed a new downscaling approach to observe soil moisture using two types of microwave sensors. We combined data from a passive sensor with a high temporal resolution and an active sensor with a high spatial resolution through a land data assimilation system. We demonstrated that the system can capture high spatiotemporal resolution soil moisture at two lightly vegetated sites. Read more in Toride et al. (2019).

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I also conducted a theoretical study to incorporate spatial heterogeneity in the soil water flow equation with a stochastic differential equation (so-called Fokker-Planck equation).