In this study,we employed a three-dimensional mesoscale cold-cloud seeding model to simulate the microphysical impacts of artificial ice crystals used as cloud seeding catalysts.Our objective was to elucidate the mech...In this study,we employed a three-dimensional mesoscale cold-cloud seeding model to simulate the microphysical impacts of artificial ice crystals used as cloud seeding catalysts.Our objective was to elucidate the mechanism of snowfall enhancement in stratiform clouds in the Bayanbulak test area of Xinjiang,China.The results indicated that the optimal seeding time was the early stages of weather system development.In this case,the optimal seeding zone was identified as the northwest of the test area,especially near the cloud top(altitudes between 3500 and 4000 m,temperatures range−11 to−15℃),and the ideal concentration of catalyst was with ice crystal density of 1.0×10^(7)kg^(−1)within the target area.Under such conditions,the total precipitation rate in the seeding-affected area increased to 50.1 mm h^(−1).The results also showed that the favorable seeding region was featured by high content of supercooled water and low population of natural ice crystals,where artificial ice crystals could substantially increase the snowfall.This augmentation typically appeared in a unimodal pattern,with the peak formed within 2–3 h after seeding.Seeding in the ice–water mixed zone of a supercooled cloud facilitated rapid ice crystal growth to snow-flake pieces via the Bergeron process,which in turn consumed more supercooled water via collision–coalescence with cloud water droplets.Simultaneously,the intensive consumption of supercooled water impeded the riming process and reduced the formation of graupel particles within the cloud.The dispersion of artificial ice crystals extended over tens of kilometers horizontally;however,in the vertical direction most particles remained approximately 1 km below the seeding layer,due to limited vertical ascent rate in the stratiform clouds restricting upward movement of artificial ice crystals.The above results help better understand the snowfall enhancement mechanism in stratiform clouds and facilitate related weather modification practice.展开更多
The probit analysis has been an important tool to predict seed longevity during storage and has been applied for seed drying simulation. Sealed aluminum pouches containing approximately 50 g of canola seed at moisture...The probit analysis has been an important tool to predict seed longevity during storage and has been applied for seed drying simulation. Sealed aluminum pouches containing approximately 50 g of canola seed at moisture range of 7% to 21% of water content web basis （%） were conditioned in water-bath at 50, 60 and 70℃ to obtain the model to evaluate the reduction of canola seed germination. This model was included in the drying simulation program and the estimated germination was compared to the experimental values of germination during drying to validate the model. Canola seeds at 21% of moisture content and germination of 93% were dried at 51℃ and 61 ℃, and the model represented significantly the drying experiments. The aim of this study was to propose a germination model to evaluate the quality of canola seeds during the drying process and to offer the seed producers an important tool to control the drying process. The experimental data validated the objectives of the proposed drying model, optimizing the process at given conditions, managing the energy consumption, according to the minimum germination or maximum moisture content limitation for seed storage. For 51℃, the drying time for canola seed would be about 6 h to maintain germination above 90% and for 61℃, 4 h of drying time maintained germination up to 89%.展开更多
基金Supported by the Scientific Research Project of the Bayingol Mongolian Autonomous Prefecture in Xinjiang(202318)China Meteorological Administration(CMA)Weather Modification Centre Innovation Team Project(WMC2023IT01)CMA Key Innovation Team Project(CMA2022ZD10).
文摘In this study,we employed a three-dimensional mesoscale cold-cloud seeding model to simulate the microphysical impacts of artificial ice crystals used as cloud seeding catalysts.Our objective was to elucidate the mechanism of snowfall enhancement in stratiform clouds in the Bayanbulak test area of Xinjiang,China.The results indicated that the optimal seeding time was the early stages of weather system development.In this case,the optimal seeding zone was identified as the northwest of the test area,especially near the cloud top(altitudes between 3500 and 4000 m,temperatures range−11 to−15℃),and the ideal concentration of catalyst was with ice crystal density of 1.0×10^(7)kg^(−1)within the target area.Under such conditions,the total precipitation rate in the seeding-affected area increased to 50.1 mm h^(−1).The results also showed that the favorable seeding region was featured by high content of supercooled water and low population of natural ice crystals,where artificial ice crystals could substantially increase the snowfall.This augmentation typically appeared in a unimodal pattern,with the peak formed within 2–3 h after seeding.Seeding in the ice–water mixed zone of a supercooled cloud facilitated rapid ice crystal growth to snow-flake pieces via the Bergeron process,which in turn consumed more supercooled water via collision–coalescence with cloud water droplets.Simultaneously,the intensive consumption of supercooled water impeded the riming process and reduced the formation of graupel particles within the cloud.The dispersion of artificial ice crystals extended over tens of kilometers horizontally;however,in the vertical direction most particles remained approximately 1 km below the seeding layer,due to limited vertical ascent rate in the stratiform clouds restricting upward movement of artificial ice crystals.The above results help better understand the snowfall enhancement mechanism in stratiform clouds and facilitate related weather modification practice.
文摘The probit analysis has been an important tool to predict seed longevity during storage and has been applied for seed drying simulation. Sealed aluminum pouches containing approximately 50 g of canola seed at moisture range of 7% to 21% of water content web basis （%） were conditioned in water-bath at 50, 60 and 70℃ to obtain the model to evaluate the reduction of canola seed germination. This model was included in the drying simulation program and the estimated germination was compared to the experimental values of germination during drying to validate the model. Canola seeds at 21% of moisture content and germination of 93% were dried at 51℃ and 61 ℃, and the model represented significantly the drying experiments. The aim of this study was to propose a germination model to evaluate the quality of canola seeds during the drying process and to offer the seed producers an important tool to control the drying process. The experimental data validated the objectives of the proposed drying model, optimizing the process at given conditions, managing the energy consumption, according to the minimum germination or maximum moisture content limitation for seed storage. For 51℃, the drying time for canola seed would be about 6 h to maintain germination above 90% and for 61℃, 4 h of drying time maintained germination up to 89%.
