Data assimilation, which minimizes the difference between modeled and observed statuses statistically along with objective criteria, has been applied frequently for terrestrial biosphere models in recent years. This approach enables highly accurate estimation, gap-filling of missing or sparsely distributed data, optimizing model parameters and initial state. The Markov chain Monte Carlo method is a useful data assimilation approach because of its relative simplicity in program cording. However, this approach has been applied mainly for plot-scale simulation, which does not have any lateral interaction with other distant plots and does not require a large computational load. Ensemble Kalman filter, which has advantages in the simplicity of coding and the affordability of computational load despite the unavoidable reduction in the numbers of assimilated data points and optimized parameters, has been demonstrated recently in many field sites. The adjoint (4D-VAR) method enables us to estimate the uncertainty of parameters chronologically forward and backward with moderate computational load, but we also need to find a way to avoid the problems induced by the non-linearity of terrestrial biosphere models. In addition to the expectation for high accuracy simulations, those data assimilation approaches would also offer great potential for producing useful bi-products, e.g. objective analysis data sets, and supplemental evidence of the changes in physiological and ecological responses to environmental variations by looking at the chronological variation in their responses. While much greater effort should be made to overcome the variety of operational problems in those data assimilations, greater attention has been paid to improving terrestrial biosphere modeling through multi-disciplinary research fields, including ecological, climatological and global environmental studies.

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To analyze how physical factors vary from hour to hour in ponded water of paddy fields, techniques that allow continuous measurement of these factors are required. Until recently, a lack of proper instrumentation made this type of measurement difficult to do. The development of measurement instrumentation and information processing technology has now made the continuous measurements of these physical factors feasible. Making these types of measurements practical has also required the design of instruments suitable for use under field conditions. This paper reviews the progress in the development of these measurement and instrumentation technologies with respect to four specific physical parameters of ponded water in paddy fields. Dissolved oxygen (DO) in paddy fields is important for the creation of an aerobic environment. DO in ponded water is considered one of the most abundant forms of DO in the world. The improvement of DO-measuring methods is reviewed, ranging from earlier methods requiring periodical manual sampling to current continuous automated sampling methods. The acidic or alkaline nature of the environment is critical for plant growth. The large variation in pH throughout the day in ponded water, factors that affect pH, and the influence of ponded water pH on the surrounding environment are discussed. Methods for measurement of pH in the field are reviewed. Soil redox potential (Eh) has been an area of great interest. Methods for the measurement of soil Eh have been improved. Two types of approaches are used to measure soil Eh: direct and indirect. However, continuous measurement of paddy soil Eh in the field remains difficult. Finally, convective flow is an important physical parameter in ponded paddy water. The discovery of convective flow and the progress made to date in meeting the challenge of developing methods to measure convection velocity in the field are reviewed.

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We evaluated the factors of salty wind damage of rice plants in the Shonai area of Yamagata prefecture after 1971. The number of typhoons that occurred in the North Pacific Ocean decreased significantly, and those that passed over the Japan Sea indicated no trend. Seawater temperature in midsummer in the southern part of the East China Sea became significantly higher. Typhoon numbers that blew over 15 m s^-1 increased, and those under 1,000 hPa increased in decadal units. This showed a significant linear correlation between atmospheric pressure and maximum wind velocity, maximum wind velocity and hours over 10 m s^-1, respectively. Wind directions were from north-northwest to southwest when wind speed was at its maximum in the Shonai area, excluding Typhoon No.16 in 1974 and No.8 in 1978. Precipitations during the 24 hours after a typhoon had passed were 15 mm or less, excluding Typhoon No.8 in 1974. Typhoon numbers that passed in the 30 days after the heading showed no tendency in decadal units.

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