Several pre-harvest rice yield estimation methods have often failed to accurately estimate rice yields due to weather variability. We attempted to assess the APEC Climate Center Multimodel Ensemble (APCC MME) seasonal hindcasts to a satellite-based rice yield prediction model to timely provide estimates of rice yields for efficacious intervention plans. The developed model by a multiple regression analysis is Yield = 5.635NDVI - 0.0012P₉ + 0.91 (where yield is the white rice yield in t ha^-1 and P₉ is the observed monthly precipitation in September in mm month^-1). The goodness-of-fit measures were 0.66, -0.14%, 0.13 t ha^-1, and 2.25%, for adjusted R² (coefficient of determination), Percent bias (PBIAS), Root Mean Square Error (RMSE), and Mean Absolute percentage Error (MAPE), respectively. A statistical downscaling method using Empirical Orthogonal Function Analysis (EOFA) and Singular Value Decomposition Analysis (SDVA) was used to predict monthly precipitation hindcasts in September required for the developed model. Even though the estimates of rice yield using the predicted monthly precipitation for whole study period were not as good as the estimates using the 9.15 sampling method, the estimates for the two years of 2008 and 2009, when the 9.15 sampling method largely underestimated, were better than those using the 9.15 sampling method. It is concluded that the proposed approach can be used to timely provide rice yield estimates that reflect the meteorological conditions for more effective intervention plans in the rice market.

　An artificial rainfall technique of liquid carbon dioxide (LCD) was used in experiments operated on Nii, Miyake and Mikura Islands in the Izu Islands of Tokyo in Japan on December 15-16, 2013. On Dec. 15, rain particles or graupel pellets struck the aircraft front window and virga or rain was observed under a cloud from the aircraft on the east leeward-side of the seeded area under the condition of thin cloud of 760 m in depth until 30 minutes. On Dec. 16, rain or graupel struck the aircraft front window at 15 minutes after seeding and virga or rain under the cloud was observed at 37 minutes after the seeding under the condition of a thinner cloud of 610 m in depth. On Dec. 15, rain was recognized along the route of the seeding and a line-type trail of cloud disappeared was visibly recognized with an average width of 2 km. The development and disappearance of clouds were evaluated using satellite images near Mikura Island. On Dec. 16, a cloud developed immediately after the seeding and a line-type cloud running in the NNE-SSW direction was recognized on the satellite image. The cloud developed decreased in scale due to rain and the cloud disappeared was also recognized on a satellite image near Nii Island. On Dec. 15, an analysis showed the existence of following local effects of the seeding; the development of clouds at 700 hPa level higher than the seeding height, the appearance of rain at 850 hPa level around the seeding height, rainfall (virga) and a drastic increase in relative humidity at 925 hPa level lower than the seeding height, and finally the occurrence of artificial rains that were clarified by the upper weather maps based on meso scale model (MSM). The artificial rainfall experiments were succeeded.

　From a morphological point of view, we attempted to estimate rice (Oryza sativa L.) yields by multiplication of four yield components considering seasonal changes in meteorological conditions. We focused on the rice cultivar Kirara397, for which large amounts of cultivation test data were available. The multiple linear regression method was applied for modeling between each yield component of Kirara397 and meteorological data. The compensation effect between yield components of rice was also considered. For other varieties (Nanatsuboshi as a panicle weight-type cultivar and Fukkurinko as a panicle number-type cultivar, relative to Kirara397) with less cultivation test data available, we formed the following two assumptions: 1) the type of weather elements affecting the yield components would be the same, regardless of the rice variety; and 2) the ratios of each yield component among rice varieties would be constant under the same weather conditions. Therefore, yield components for these varieties were estimated using correction ratios determined previously with yield component data. The determination coefficients for brown rice yield of Kirara397, Nanatsuboshi, and Fukkurinko were 0.440, 0.698, and 0.669, respectively. This method was thought to be a convenient and useful method for evaluation of yield and four yield components with only two meteorological data (daily air temperature and solar radiation) and dates of rice development. However, both our assumptions for rice cultivars with a small number of cultivation data were not fully adequate for estimating the yield and four yield components quantitatively, while it could be useful for determining relative quantities, particularly for panicle number, thousand kernel weight, and brown rice yield.

　Detailed analyses are presented of cropping intensity (CI) and crop-seasonality parameters, such as the start and end of a season, the length of a season, and the seasonal amplitude for the period 1999-2010 across Mainland Asia. The analyses used fitted Normalized Difference Vegetation Index (NDVI) time-series data derived from SPOT VEGETATION 10-day synthesis (VGT S10) instruments. Savitzky-Golay noise filtering was applied to the NDVI time series, and the results of an automated extraction procedure were compared with the results of other research analyses. The results indicated that: 1) the projected spatial distribution of CI agreed with other analyses; 2) detected double-cropping regions generally extend over large areas equipped for irrigation; 3) the developed extracting algorithm was capable of estimating CI within Mainland Asia; 4) measured spatial variation at the start of a season adequately represented the crop calendar for each grid and region; 5) low standard deviations (SD) for the start of seasons and seasonal amplitude of NDVI across the period 1999-2010 were closely related to the presence of irrigated cropland, and SD values were relatively high for arid, rainfed zones; 6) there were large elements of uncertainty in estimations of cropping-seasonality parameters caused by (i) cloud contamination of images, (ii) the single setting of the smoothing filter and determinations of seasons' starts/ends, and (iii) spatial and temporal resolution of satellite data. Detailed analyses of crop seasonality will contribute to progress across a range of agricultural concerns, including local and large-scale food security and the management of complex agricultural systems.

　This paper presents the application results of the Global Change Observation Mission-Climate (GCOM-C) global ET_index estimation algorithm to the entire globe over the seven years from 2001 to 2007 using MODIS daily thermal observation data as a substitute for GCOM-C thermal observation data. The GCOM-C global ET_index estimation algorithm was developed to automatically provide global ET_index information for the Global Change Observation Mission (GCOM) of the Japan Aerospace Exploration Agency (JAXA).
　The ET_index maps resulting from this study were compared with global precipitation, Köppen's climate classification, and forest distribution maps in order to investigate the general correspondence between the ET_index and climate/ecosystem distributions. The estimated ET_index was confirmed to be in general agreement with the distributions of climate and forest at the global and continental scales and at annual and seasonal timescales.
　The resultant global evapotranspiration (ET) maps were evaluated using point-measured precipitation for 199 locations worldwide and measured ET data in Mongolia. The relationship between precipitation and ET supported the adequacy of the ET estimation method for annual timescales. A monthly comparison of the ET_index with precipitation implied that the algorithm is functional in summer but nonfunctional in winter under some conditions. An accuracy assessment of the algorithm using actual ET measurement data from Mongolia indicated that the algorithm showed good performance at annual timescales. The error in the 4-year average of estimated ET was equivalent to 12% of the actual ET or 0.7% of the reference ET.

　Assuming that the composting process, which is a type of ecosystem, may be linked to an integral functional maximization problem, the author discusses how the temporal spatial distribution of state variables can be treated as an extremal problem. The object item of maximization is recognized as the net released exergy at each moment in the process.
　As composting is accompanied by bifurcations due to nonlinear temperature dependence of reaction rate, it is uncertain whether an exact integral functional exists that can precisely predict the temporal progress of the phenomenon. However, the fact that the maximization principle of the net released exergy at each moment holds is considered to support Jorgensen's theory that exergy can be regarded as a Lyapunov function of the process for periods under temporal stable conditions before and after bifurcation. The mathematical treatment herein is an approximation that assumes that temperature is the only dependent variable, provided that the other dependent variables—moisture content and oxygen concentration—are not restriction factors in the system progress.
　It is substantially difficult at this stage to obtain an exact integral functional considering the mutual dependence of temperature, moisture content, and oxygen concentration with biochemical reactions. If the permissible extent of the calculated results is not extremely narrow, there is a high possibility of obtaining an approximate integral functional and using it to formulate the maximization problem.

　This paper investigates the shifts in climatic suitability for cultivating grapes (Vitis vinifera) in Hokkaido, Japan, throughout the 20th and 21st century. To assess area suitability over time, we used two climate model datasets and three climatic criteria (summer temperature, summer precipitation, and winter temperature). The optimum area for growth gradually enlarged from the 1990s to present (2010s), and this area will cover almost all of the Hokkaido region by the 2050s. Even when considering model uncertainties, almost all low elevation areas in Hokkaido are projected to be suitable for V. vinifera cultivation in the future.

　With the increasing cost of fossil fuels, the use of air source heat pumps (ASHPs) for greenhouse heating has become widespread in Japan. In general, the coefficient of performance (COP) of a ASHP depends on the outside air conditions, while the same is not expected for an underground water source heat pump (UWS-HP) system. Few studies have examined these comparisons in colder regions. In the present study, a UWS-HP system is developed, and the COPs of a UWS-HP (COP_uws) and a ASHP (COP_air) for use in greenhouse heating are investigated. The key results of the study can be summarized as follows:
1) COP_uws ranged from 4.0 to 5.7 and had an average value of 4.9. COP_uws was generally higher than COP_air regardless of the outside temperature.
2) COP_air ranged from 2.2 to 4.5 and had an average value of 3.4. Using the average hourly heat transfer coefficient obtained from the analysis of the UWS-HP, COP_air was found to decrease with decreasing outside temperature.
3) COP_air decreased with increasing frequency of the reverse cycle defrosting.
4) COP_uws was not affected by the outside temperature, and inlet and outlet water temperature was approximately 1°C and 11.5°C respectively.