Tetsu Ohta

Improving the AMSR-E Soil Moisture Algorithm of the University of Tokyo through Field Experiments and Parameters Optimization

This paper reports the progresses of AMSR-E soil moisture algorithm development at the University of Tokyo. The first progress is made through improving the forward model, i.e. radiative transfer model (RTM), based on field experiment and numerical simulation. The second progress is the development of a new parameterization method, through which the parameters necessary for the algorithm are optimized by a land data assimilation system developed at the University of Tokyo (LDAS-UT). The capability of LDAS-UT was validated successfully with winter wheat experiment data. Finally, the new RTM and parameterization method was validated on AMSR-E match up data set. The results demonstrate that the simulated brightness temperature is in good agreements with the one observed by AMSR-E.

Optimizing Multidam Releases in Large River Basins by Combining Distributed Hydrological Inflow Predictions with Rolling-Horizon Decision Making

AbstractFor the purpose of real-time dam operation in large river basins, an integrated simulation and optimization system (ISOS) has been constructed by combining distributed hydrological inflow predictions with rolling horizon decision making. First, with operational quantitative precipitation forecasts (QPFs) over a forecast horizon (FH), the ISOS is applied to obtain an optimal rule for dam releases; second, with the corrected satellite precipitation, the prescribed rule is employed for the reservoir operation over a decision horizon (DH). The ISOS is applied to the Red River Basin (169,000  km2), to test its performance for optimizing multidam releases in the large river basin. Results show that by using the ISOS, two things were simultaneously achieved, reducing the water level at Hanoi to avoid flooding while raising water storage in Hoa Binh reservoir at the end of flood season for better hydropower generation. Through comparing reservoir performances with different FHs, the effective forecast hor...

Climate Change Assessment Due to Long Term Soil Moisture Change and Its Applicability Using Satellite Observations

© 2013 Lu et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Climate Change Assessment Due to Long Term Soil Moisture Change and Its Applicability Using Satellite Observations

Monitoring soil moisture change in North Africa with using satellite remote sensing and land data assimilaiton system

In this study, we generated and compared two sets of soil moisture data in the North Africa region, by using the land data assimilation system developed at the University of Tokyo (LDAS-UT) which is driven by the NECP reanalysis data and UKMO forcing data, separately. GPCP precipitation data was used as reference data for the indirect validation, after its accuracy was confirmed by comparing it with the in-situ observation in the Medjerdah Basin. The soil moisture generated by LDAS-UT with NECP forcing is in a good relationship to the GPCP rainfall data, while that generated by LDAS-UT with UKMO forcing is mismatching with the GPCP precipitation patterns.