In this study, the ability of dynamical downscaling for reduction of artificial climate trends in global reanalysis is tested in China. Dynamical downscaling is performed using a 60-km horizontal resolution Regional I...In this study, the ability of dynamical downscaling for reduction of artificial climate trends in global reanalysis is tested in China. Dynamical downscaling is performed using a 60-km horizontal resolution Regional Integrated Environmental Model System （RIEMS） forced by the NCEP-Department of Energy （DOE） reanalysis II （NCEP-2）. The results show that this regional climate model （RCM） can not only produce dynamically consis- tent fine scale fields of atmosphere and land surface in the regional domain, but it also has the ability to minimize artificial climate trends existing in the global reanalysis to a certain extent. As compared to the observed 2-meter temperature anomaly averaged across China, our model can simulate the observed inter-annual variation and variability as well as reduce artificial climate trends in the reanalysis by approximately 0.10℃ decade-1 from 1980 to 2007. The RIEMS can effectively reduce artificial trends in global reanalysis for areas in western China, especially for regions with high altitude mountains and deserts, as well as introduce some new spurious changes in other local regions. The model simulations overesti- mated observed winter trends for most areas in eastern China with the exception of the Tibetan Plateau, and it greatly overestimated observed summer trends in the Si- chuan Basin located in southwest China. This implies that the dynamical downscaling of RCM for long-term trends has certain seasonal and regional dependencies due to imperfect physical processes and parameterizations.展开更多
The global population is increasing rapidly as compared to food production;approximately three times more food would be required in 2050.Climate change affects crop production by causing sudden changes in weather cond...The global population is increasing rapidly as compared to food production;approximately three times more food would be required in 2050.Climate change affects crop production by causing sudden changes in weather conditions,including rain,storms,heat waves,doughiness,and water shortages.Farming with smart technology provides a productive solution.Smart farming is a productive solution that provides a great resource of income and improves the countries’economy by exporting consumable goods and preventing food security problems.Smart agriculture provides a combination of flexibility,remote access,and automation through the use of intelligent control technologies.Many countries are working towards smart and intelligent agriculture farming that analyzes crop,soil fertility,pests and weeds,and other problems caused by mismanagement and incompetence.However,smart agricultural farming is less widely adopted in agriculture as a result of high costs and little understanding of technology.In this study,An artificial climate control chamber(ACCC)was designed for cultivating plants by controlling the optimal parameters,especially the light spectrum.In ACCC,influential plant factors such as light,moisture,humidity,and fertilizer concentration have been controlled intelligently.Light spectrum was controlled by time periods in the previous system,while in the system proposed in this study,the light was controlled by image processing.In an artificial control chamber,the plant growth stages have been determined through image processing techniques.Datasets of image images have been used to organize specific intensities of the light spectrum.This intelligent system provides aid in the speed breeding procedure through variant spectrums of light and fertilizers combinations.In the research study,the yield and quality of intelligent farming are enhanced.展开更多
Large quantities of radionuclides were released from the Fukushima Daiichi Nuclear Power Plant(FDNPP)into the atmosphere,which then contaminated the soil and vegetation surrounding the FDNPP.The research on radiocesiu...Large quantities of radionuclides were released from the Fukushima Daiichi Nuclear Power Plant(FDNPP)into the atmosphere,which then contaminated the soil and vegetation surrounding the FDNPP.The research on radiocesium contamination of agricultural products and wild plants is important.Therefore,we developed a simple beta ray scanner to obtain radiographs of the transport and foliar uptake of radiocesium.This simple beta ray scanner comprised a beta ray detector,a motorized sample stage,a shielding box,and a personal computer.Beta rays released from radiocesium were detected effectively using a plastic scintillator plate coupled to multipixel photon counter devices.The spatial resolving power was approximately 6 mm×4 mm(FWHM).In a preliminary experiment,a drop of radiocesium solution was placed on the upper surface of a radish leaf.Time-lapse images of radiocesium in the leaf were obtained by the beta ray scanner.Images of isotope transport in the leaf were successfully obtained with the beta ray scanner.The beta ray scanner will be used in our future research on the mechanism of the foliar uptake of radiocesium.展开更多
基金supported by the Knowledge Innovation Program of the Chinese Academy of Sciences(Grant No. KGCX2-YW-356)the R & D Special Fund for Public Welfare Industry (Meteorology) (Grant No. GYHY201006023)the National Natural Science Foundation of China (Grant No.40805032)
文摘In this study, the ability of dynamical downscaling for reduction of artificial climate trends in global reanalysis is tested in China. Dynamical downscaling is performed using a 60-km horizontal resolution Regional Integrated Environmental Model System （RIEMS） forced by the NCEP-Department of Energy （DOE） reanalysis II （NCEP-2）. The results show that this regional climate model （RCM） can not only produce dynamically consis- tent fine scale fields of atmosphere and land surface in the regional domain, but it also has the ability to minimize artificial climate trends existing in the global reanalysis to a certain extent. As compared to the observed 2-meter temperature anomaly averaged across China, our model can simulate the observed inter-annual variation and variability as well as reduce artificial climate trends in the reanalysis by approximately 0.10℃ decade-1 from 1980 to 2007. The RIEMS can effectively reduce artificial trends in global reanalysis for areas in western China, especially for regions with high altitude mountains and deserts, as well as introduce some new spurious changes in other local regions. The model simulations overesti- mated observed winter trends for most areas in eastern China with the exception of the Tibetan Plateau, and it greatly overestimated observed summer trends in the Si- chuan Basin located in southwest China. This implies that the dynamical downscaling of RCM for long-term trends has certain seasonal and regional dependencies due to imperfect physical processes and parameterizations.
文摘The global population is increasing rapidly as compared to food production;approximately three times more food would be required in 2050.Climate change affects crop production by causing sudden changes in weather conditions,including rain,storms,heat waves,doughiness,and water shortages.Farming with smart technology provides a productive solution.Smart farming is a productive solution that provides a great resource of income and improves the countries’economy by exporting consumable goods and preventing food security problems.Smart agriculture provides a combination of flexibility,remote access,and automation through the use of intelligent control technologies.Many countries are working towards smart and intelligent agriculture farming that analyzes crop,soil fertility,pests and weeds,and other problems caused by mismanagement and incompetence.However,smart agricultural farming is less widely adopted in agriculture as a result of high costs and little understanding of technology.In this study,An artificial climate control chamber(ACCC)was designed for cultivating plants by controlling the optimal parameters,especially the light spectrum.In ACCC,influential plant factors such as light,moisture,humidity,and fertilizer concentration have been controlled intelligently.Light spectrum was controlled by time periods in the previous system,while in the system proposed in this study,the light was controlled by image processing.In an artificial control chamber,the plant growth stages have been determined through image processing techniques.Datasets of image images have been used to organize specific intensities of the light spectrum.This intelligent system provides aid in the speed breeding procedure through variant spectrums of light and fertilizers combinations.In the research study,the yield and quality of intelligent farming are enhanced.
基金This study was supported in part by a JSPS KAKENHI Grant(No.24561041).
文摘Large quantities of radionuclides were released from the Fukushima Daiichi Nuclear Power Plant(FDNPP)into the atmosphere,which then contaminated the soil and vegetation surrounding the FDNPP.The research on radiocesium contamination of agricultural products and wild plants is important.Therefore,we developed a simple beta ray scanner to obtain radiographs of the transport and foliar uptake of radiocesium.This simple beta ray scanner comprised a beta ray detector,a motorized sample stage,a shielding box,and a personal computer.Beta rays released from radiocesium were detected effectively using a plastic scintillator plate coupled to multipixel photon counter devices.The spatial resolving power was approximately 6 mm×4 mm(FWHM).In a preliminary experiment,a drop of radiocesium solution was placed on the upper surface of a radish leaf.Time-lapse images of radiocesium in the leaf were obtained by the beta ray scanner.Images of isotope transport in the leaf were successfully obtained with the beta ray scanner.The beta ray scanner will be used in our future research on the mechanism of the foliar uptake of radiocesium.
