The process of riming significantly impacts the microphysical characteristics of clouds.This study uses aircraft and radar observation data in stratiform clouds with convection embedded that occurred in the central an...The process of riming significantly impacts the microphysical characteristics of clouds.This study uses aircraft and radar observation data in stratiform clouds with convection embedded that occurred in the central and southern regions of North China on 22 May 2017.The microphysical structural characteristics and processes near the embedded convection core and in the stratiform cloud are analyzed comparatively.Particular attention is given to the effect of riming on the microphysical properties near the upper boundary of the melting layer and to the factors influencing riming efficiency.The collaborative observations reveal that the particle size distributions observed near the convection core and in the stratiform region are close,while the particle properties like habit and riming degree are quite different.Above the melting layer,larger plate-like ice particles and supercooled water droplets(D>50μm)are more abundant near the convective core,leading to higher collision efficiencies between ice particles and supercooled water droplets.Larger fluctuation amplitudes of vertical airflow near the convective core also contribute to the increased riming activity and the formation of more heavily rimed particles,such as graupel.Furthermore,in situ measurements from airborne probes also revealed that above the melting layer,the riming process involves two stages:the mass of snow crystals grows as supercooled droplets merge internally without changing size,followed by external freezing that significantly enlarges the crystals.展开更多
[Objective]Accurate prediction of crop canopy temperature is essential for comprehensively assessing crop growth status and guiding agricultural production.This study focuses on kiwifruit and grapes to address the cha...[Objective]Accurate prediction of crop canopy temperature is essential for comprehensively assessing crop growth status and guiding agricultural production.This study focuses on kiwifruit and grapes to address the challenges in accurately predicting crop canopy temperature.[Methods]A dynamic prediction model for crop canopy temperature was developed based on Long Short-Term Memory(LSTM),Variational Mode Decomposition(VMD),and the Rime Ice Morphology-based Optimization Algorithm(RIME)optimization algorithm,named RIME-VMD-RIME-LSTM(RIME2-VMDLSTM).Firstly,crop canopy temperature data were collected by an inspection robot suspended on a cableway.Secondly,through the performance of multiple pre-test experiments,VMD-LSTM was selected as the base model.To reduce crossinterference between different frequency components of VMD,the K-means clustering algorithm was applied to cluster the sample entropy of each component,reconstructing them into new components.Finally,the RIME optimization algorithm was utilized to optimize the parameters of VMD and LSTM,enhancing the model's prediction accuracy.[Results and Discussions]The experimental results demonstrated that the proposed model achieved lower Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)(0.3601 and 0.2543°C,respectively)in modeling different noise environments than the comparator model.Furthermore,the R2 value reached a maximum of 0.9947.[Conclusions]This model provides a feasible method for dynamically predicting crop canopy temperature and offers data support for assessing crop growth status in agricultural parks.展开更多
Parameter extraction of photovoltaic(PV)models is crucial for the planning,optimization,and control of PV systems.Although some methods using meta-heuristic algorithms have been proposed to determine these parameters,...Parameter extraction of photovoltaic(PV)models is crucial for the planning,optimization,and control of PV systems.Although some methods using meta-heuristic algorithms have been proposed to determine these parameters,the robustness of solutions obtained by these methods faces great challenges when the complexity of the PV model increases.The unstable results will affect the reliable operation and maintenance strategies of PV systems.In response to this challenge,an improved rime optimization algorithm with enhanced exploration and exploitation,termed TERIME,is proposed for robust and accurate parameter identification for various PV models.Specifically,the differential evolution mutation operator is integrated in the exploration phase to enhance the population diversity.Meanwhile,a new exploitation strategy incorporating randomization and neighborhood strategies simultaneously is developed to maintain the balance of exploitation width and depth.The TERIME algorithm is applied to estimate the optimal parameters of the single diode model,double diode model,and triple diode model combined with the Lambert-W function for three PV cell and module types including RTC France,Photo Watt-PWP 201 and S75.According to the statistical analysis in 100 runs,the proposed algorithm achieves more accurate and robust parameter estimations than other techniques to various PV models in varying environmental conditions.All of our source codes are publicly available at https://github.com/dirge1/TERIME.展开更多
This is an in-depth journey to experience the ice and snow of Changbai Mountain.In these few days,you will explore Changbai Mountain and enjoy powder skiing;gallop on the ski trail;watch the stunning wonders of snow r...This is an in-depth journey to experience the ice and snow of Changbai Mountain.In these few days,you will explore Changbai Mountain and enjoy powder skiing;gallop on the ski trail;watch the stunning wonders of snow rime on thousands of trees;conquer the ice and snow wilderness on a snowmobile and start an in depth magical mystery tour in lilin Province.展开更多
In the vast tand of Northeast China,we are slowly starting an ultimate journey of the ice and snow carnival and exploration of folk customs.This is a magic kingdom of ice and snow ,from the meticulously crafted wonder...In the vast tand of Northeast China,we are slowly starting an ultimate journey of the ice and snow carnival and exploration of folk customs.This is a magic kingdom of ice and snow ,from the meticulously crafted wonders of the ice city to the snowcovered wonderland of rime ice.展开更多
The roughness effect based on the wall function method is introduced into the numerical simulation of the rime ice accretion and the resulting effect on the aerodynamic performance of the airfoil. Incorporating the tw...The roughness effect based on the wall function method is introduced into the numerical simulation of the rime ice accretion and the resulting effect on the aerodynamic performance of the airfoil. Incorporating the two-phase model of air/super-cooled droplets in the Eulerian coordinate system, this paper presents the simulation of the rime ice accretion on the NACA 0012 airfoil. The predicted rime ice shape is compared with those results of measurements and simulations by other icing codes. Also the resulting effects of rime ice on airfoil aerodynamic performance are discussed. Results indicate that the rime ice accretion leads to the loss of the maximum lift coefficient by 26%, the decrease of the stall angle by about 3° and the considerable increase of the drag coefficient.展开更多
Using the Weather Research and Forecasting(WRF)model with two different microphysics schemes,the Predicted Particle Properties(P3)and the Morrison double-moment parameterizations,we simulated a stratiform rainfall eve...Using the Weather Research and Forecasting(WRF)model with two different microphysics schemes,the Predicted Particle Properties(P3)and the Morrison double-moment parameterizations,we simulated a stratiform rainfall event on 20–21 April 2010.The simulation output was compared with precipitation and aircraft observations.The aircraft-observed moderate-rimed dendrites and plates indicated that riming contributed significantly to ice particle growth at the mature precipitation stage.Observations of dendrite aggregation and capped columns suggested that aggregation coexisted with deposition or riming and played an important role in producing many large particles.The domain-averaged values of the 24-h surface precipitation accumulation from the two schemes were quite close to each other.However,differences existed in the temporal and spatial evolutions of the precipitation distribution.An analysis of the surface precipitation temporal evolution indicated faster precipitation in Morrison,while P3 indicated slower rainfall by shifting the precipitation pattern eastward toward what was observed.The differences in precipitation values between the two schemes were related to the cloud water content distribution and fall speeds of rimed particles.P3 simulated the stratiform precipitation event better as it captured the gradual transition in the mass-weighted fall speeds and densities from unrimed to rimed particles.展开更多
Three cases of microphysical characteristics and kinematic structures in the negative temperature region of summer mesoscale cloud systems over the eastern Tibetan Plateau(TP)were investigated using X-band dual-polari...Three cases of microphysical characteristics and kinematic structures in the negative temperature region of summer mesoscale cloud systems over the eastern Tibetan Plateau(TP)were investigated using X-band dual-polarization radar.The time-height series of radar physical variables and mesoscale horizontal divergenceδderived by quasi-vertical profiles(QVPs)indicated that the dendritic growth layer(DGL,-20°C to-10°C)was ubiquitous,with large-value zones of K_(DP)(specific differential phase),Z_(DR)(differential reflectivity),or both,and corresponded to various dynamic fields(ascent or descent).Ascents in the DGL of cloud systems with vigorous vertical development were coincident with large-value zones of Z_(DR),signifying ice crystals with a large axis ratio,but with no obvious large values of K_(DP),which differs from previous findings.It is speculated that ascent in the DGL promoted ice crystals to undergo further growth before sinking.If there was descent in the DGL,a high echo top corresponded to large values of K_(DP),denoting a large number concentration of ice crystals;but with the echo top descending,small values of K_(DP)formed.This is similar to previous results and reveals that a high echo top is conducive to the generation of ice crystals.When ice particles fall to low levels(-10℃to 0℃),they grow through riming,aggregation,or deposition,and may not be related to the kinematic structure.It is important to note that this study was only based on a limited number of cases and that further research is therefore needed.展开更多
To evaluate the ability of the Predicted Particle Properties(P3)scheme in the Weather Research and Forecasting(WRF)model,we simulated a stratiform rainfall event over northern China on 22 May 2017.WRF simulations with...To evaluate the ability of the Predicted Particle Properties(P3)scheme in the Weather Research and Forecasting(WRF)model,we simulated a stratiform rainfall event over northern China on 22 May 2017.WRF simulations with two P3 versions,P3-nc and P3-2ice,were evaluated against rain gauge,radar,and aircraft observations.A series of sensitivity experiments were conducted with different collection efficiencies between ice and cloud droplets.The comparison of the precipitation evolution between P3-nc and P3-2ice suggested that both P3 versions overpredicted surface precipitation along the Taihang Mountains but underpredicted precipitation in the localized region on the leeward side.P3-2ice had slightly lower peak precipitation rates and smaller total precipitation amounts than P3-nc,which were closer to the observations.P3-2ice also more realistically reproduced the overall reflectivity structures than P3-nc.A comparison of ice concentrations with observations indicated that P3-nc underestimated aggregation,whereas P3-2ice produced more active aggregation from the self-collection of ice and ice-ice collisions between categories.Efficient aggregation in P3-2ice resulted in lower ice concentrations at heights between 4 and 6 km,which was closer to the observations.In this case,the total precipitation and precipitation pattern were not sensitive to riming.Riming was important in reproducing the location and strength of the embedded convective region through its impact on ice mass flux above the melting level.展开更多
The paper addresses some of the problems surrounding the relation between ice core chemical signals and atmospheric chemical composition in polar areas. The topic is important as the reconstruction of past climate and...The paper addresses some of the problems surrounding the relation between ice core chemical signals and atmospheric chemical composition in polar areas. The topic is important as the reconstruction of past climate and past atmospheric chemical composition is based on the assumption that chemical concentrations in the air, snow, firn and ice core are correlated. Ice core interpretation of aerosol is more straightforward than that of reactive gases. The transfer functions of gaseous species strongly interacting with ice are complex and additional field and laboratory experiments are required. Ice core chemical signals depend on the chemical composition of precipitations, which are related to the physics of precipitation formation, the chemical composition of the atmosphere, and post-depositional processes. Published papers reporting data on the chemical composition of snow seldom consider the fact that crystal formation and growth in cloud (rimed or unrimed) or near the ground (clear-sky precipitations), hoar-frost formation and surface riming determine different chemical concentrations, even assuming constant background concentration in the atmosphere. This paper discusses the physical and chemical processes affecting the formation of precipitations in polar areas, and the process of scavenging gases from non-growing and growing crystals. Attention is mainly focused on the processes involving nitrate anion in snow, hoar frost and firn. Knowledge of the chemical relationship between surface snow and atmospheric chemical concentration could be enhanced by considering specific events, such as snow falling from cloud, clear sky precipitation, and surface hoar or riming surface, with simultaneous air sampling. In conclusion, field and laboratory experiments are still required to study the scavenging processes during crystal formation.展开更多
Offshore wind energy resources are operational in cold regions,while offshore wind turbines will face the threat of icing.Therefore,it is necessary to study icing of offshore wind turbines under different icing condit...Offshore wind energy resources are operational in cold regions,while offshore wind turbines will face the threat of icing.Therefore,it is necessary to study icing of offshore wind turbines under different icing conditions.In this study,icing sensitivity of offshore wind turbine blades are performed using a combination of FLUENT and FENSAP-ICE software,and the effects of liquid water content(LWC),medium volume diameter(MVD),wind speed and air temperature on blade icing shape are analyzed by two types of ice,namely rime ice and glaze ice.The results show that the increase of LWC and MVD will increase the amount of ice that forms on the blade surface for either glaze ice or rime ice,and an increase of MVD will expand the adhesion surface between ice and blade.Before reaching the rated wind speed of 11.4 m/s,it does not directly affect the icing shape.However,after reaching the rated wind speed,the attack angle of the incoming flow decreases obviously,and the amount of ice increases markedly.When the ambient air temperature meets the icing conditions of glaze ice(i.e.,−5℃ to 0℃),the lower the temperature,the more glaze ice freezes,whereas air temperature has no impact on the icing of rime ice.Compared with onshore wind turbines,offshore wind turbines might face extreme meteorological conditions,and the wind speed has no impact on the amount of ice that forms on the blade surface for most wind speeds.展开更多
When building a classification model,the scenario where the samples of one class are significantly more than those of the other class is called data imbalance.Data imbalance causes the trained classification model to ...When building a classification model,the scenario where the samples of one class are significantly more than those of the other class is called data imbalance.Data imbalance causes the trained classification model to be in favor of the majority class(usually defined as the negative class),which may do harm to the accuracy of the minority class(usually defined as the positive class),and then lead to poor overall performance of the model.A method called MSHR-FCSSVM for solving imbalanced data classification is proposed in this article,which is based on a new hybrid resampling approach(MSHR)and a new fine cost-sensitive support vector machine(CS-SVM)classifier(FCSSVM).The MSHR measures the separability of each negative sample through its Silhouette value calculated by Mahalanobis distance between samples,based on which,the so-called pseudo-negative samples are screened out to generate new positive samples(over-sampling step)through linear interpolation and are deleted finally(under-sampling step).This approach replaces pseudo-negative samples with generated new positive samples one by one to clear up the inter-class overlap on the borderline,without changing the overall scale of the dataset.The FCSSVM is an improved version of the traditional CS-SVM.It considers influences of both the imbalance of sample number and the class distribution on classification simultaneously,and through finely tuning the class cost weights by using the efficient optimization algorithm based on the physical phenomenon of rime-ice(RIME)algorithm with cross-validation accuracy as the fitness function to accurately adjust the classification borderline.To verify the effectiveness of the proposed method,a series of experiments are carried out based on 20 imbalanced datasets including both mildly and extremely imbalanced datasets.The experimental results show that the MSHR-FCSSVM method performs better than the methods for comparison in most cases,and both the MSHR and the FCSSVM played significant roles.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.42025501)the Natural Science Foundation of Hebei Province(Grant No.D2024304015)+4 种基金the Fundamental Research Funds for the Central Universities,including Grant No.020714380217the Cemac“GeoX”Interdisciplinary Program(Grant No.020714380210)the Open Grants of the Key Laboratory of Radar Meteorology,China Meteorological Administration(Grant No.2023LRM-B05)the Hebei Meteorological Service Scientific Research and Development Project(Grant No.23ky08)the Open Research Program of the State Key Laboratory of Severe Weather(Grant No.2023LASW-A01)。
文摘The process of riming significantly impacts the microphysical characteristics of clouds.This study uses aircraft and radar observation data in stratiform clouds with convection embedded that occurred in the central and southern regions of North China on 22 May 2017.The microphysical structural characteristics and processes near the embedded convection core and in the stratiform cloud are analyzed comparatively.Particular attention is given to the effect of riming on the microphysical properties near the upper boundary of the melting layer and to the factors influencing riming efficiency.The collaborative observations reveal that the particle size distributions observed near the convection core and in the stratiform region are close,while the particle properties like habit and riming degree are quite different.Above the melting layer,larger plate-like ice particles and supercooled water droplets(D>50μm)are more abundant near the convective core,leading to higher collision efficiencies between ice particles and supercooled water droplets.Larger fluctuation amplitudes of vertical airflow near the convective core also contribute to the increased riming activity and the formation of more heavily rimed particles,such as graupel.Furthermore,in situ measurements from airborne probes also revealed that above the melting layer,the riming process involves two stages:the mass of snow crystals grows as supercooled droplets merge internally without changing size,followed by external freezing that significantly enlarges the crystals.
文摘[Objective]Accurate prediction of crop canopy temperature is essential for comprehensively assessing crop growth status and guiding agricultural production.This study focuses on kiwifruit and grapes to address the challenges in accurately predicting crop canopy temperature.[Methods]A dynamic prediction model for crop canopy temperature was developed based on Long Short-Term Memory(LSTM),Variational Mode Decomposition(VMD),and the Rime Ice Morphology-based Optimization Algorithm(RIME)optimization algorithm,named RIME-VMD-RIME-LSTM(RIME2-VMDLSTM).Firstly,crop canopy temperature data were collected by an inspection robot suspended on a cableway.Secondly,through the performance of multiple pre-test experiments,VMD-LSTM was selected as the base model.To reduce crossinterference between different frequency components of VMD,the K-means clustering algorithm was applied to cluster the sample entropy of each component,reconstructing them into new components.Finally,the RIME optimization algorithm was utilized to optimize the parameters of VMD and LSTM,enhancing the model's prediction accuracy.[Results and Discussions]The experimental results demonstrated that the proposed model achieved lower Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)(0.3601 and 0.2543°C,respectively)in modeling different noise environments than the comparator model.Furthermore,the R2 value reached a maximum of 0.9947.[Conclusions]This model provides a feasible method for dynamically predicting crop canopy temperature and offers data support for assessing crop growth status in agricultural parks.
基金supported by the National Natural Science Foundation of China[grant number 51775020]the Science Challenge Project[grant number.TZ2018007]+2 种基金the National Natural Science Foundation of China[grant number 62073009]the Postdoctoral Fellowship Program of CPSF[grant number GZC20233365]the Fundamental Research Funds for Central Universities[grant number JKF-20240559].
文摘Parameter extraction of photovoltaic(PV)models is crucial for the planning,optimization,and control of PV systems.Although some methods using meta-heuristic algorithms have been proposed to determine these parameters,the robustness of solutions obtained by these methods faces great challenges when the complexity of the PV model increases.The unstable results will affect the reliable operation and maintenance strategies of PV systems.In response to this challenge,an improved rime optimization algorithm with enhanced exploration and exploitation,termed TERIME,is proposed for robust and accurate parameter identification for various PV models.Specifically,the differential evolution mutation operator is integrated in the exploration phase to enhance the population diversity.Meanwhile,a new exploitation strategy incorporating randomization and neighborhood strategies simultaneously is developed to maintain the balance of exploitation width and depth.The TERIME algorithm is applied to estimate the optimal parameters of the single diode model,double diode model,and triple diode model combined with the Lambert-W function for three PV cell and module types including RTC France,Photo Watt-PWP 201 and S75.According to the statistical analysis in 100 runs,the proposed algorithm achieves more accurate and robust parameter estimations than other techniques to various PV models in varying environmental conditions.All of our source codes are publicly available at https://github.com/dirge1/TERIME.
文摘This is an in-depth journey to experience the ice and snow of Changbai Mountain.In these few days,you will explore Changbai Mountain and enjoy powder skiing;gallop on the ski trail;watch the stunning wonders of snow rime on thousands of trees;conquer the ice and snow wilderness on a snowmobile and start an in depth magical mystery tour in lilin Province.
文摘In the vast tand of Northeast China,we are slowly starting an ultimate journey of the ice and snow carnival and exploration of folk customs.This is a magic kingdom of ice and snow ,from the meticulously crafted wonders of the ice city to the snowcovered wonderland of rime ice.
文摘The roughness effect based on the wall function method is introduced into the numerical simulation of the rime ice accretion and the resulting effect on the aerodynamic performance of the airfoil. Incorporating the two-phase model of air/super-cooled droplets in the Eulerian coordinate system, this paper presents the simulation of the rime ice accretion on the NACA 0012 airfoil. The predicted rime ice shape is compared with those results of measurements and simulations by other icing codes. Also the resulting effects of rime ice on airfoil aerodynamic performance are discussed. Results indicate that the rime ice accretion leads to the loss of the maximum lift coefficient by 26%, the decrease of the stall angle by about 3° and the considerable increase of the drag coefficient.
基金supported by the National Key Research and Development Program of China (Grant No. 2018YFC1507900)the National Natural Science Foundation of China (Grant Nos. 41575131, 41530427 and 41875172)
文摘Using the Weather Research and Forecasting(WRF)model with two different microphysics schemes,the Predicted Particle Properties(P3)and the Morrison double-moment parameterizations,we simulated a stratiform rainfall event on 20–21 April 2010.The simulation output was compared with precipitation and aircraft observations.The aircraft-observed moderate-rimed dendrites and plates indicated that riming contributed significantly to ice particle growth at the mature precipitation stage.Observations of dendrite aggregation and capped columns suggested that aggregation coexisted with deposition or riming and played an important role in producing many large particles.The domain-averaged values of the 24-h surface precipitation accumulation from the two schemes were quite close to each other.However,differences existed in the temporal and spatial evolutions of the precipitation distribution.An analysis of the surface precipitation temporal evolution indicated faster precipitation in Morrison,while P3 indicated slower rainfall by shifting the precipitation pattern eastward toward what was observed.The differences in precipitation values between the two schemes were related to the cloud water content distribution and fall speeds of rimed particles.P3 simulated the stratiform precipitation event better as it captured the gradual transition in the mass-weighted fall speeds and densities from unrimed to rimed particles.
基金jointly funded by the Northwest Regional Weather Modification Capacity Building Project of the China Meteorological Administration(Grant No.ZQC-R18209)the National Natural Science Foundation of China(Grant Nos.41875172 and 42075192)。
文摘Three cases of microphysical characteristics and kinematic structures in the negative temperature region of summer mesoscale cloud systems over the eastern Tibetan Plateau(TP)were investigated using X-band dual-polarization radar.The time-height series of radar physical variables and mesoscale horizontal divergenceδderived by quasi-vertical profiles(QVPs)indicated that the dendritic growth layer(DGL,-20°C to-10°C)was ubiquitous,with large-value zones of K_(DP)(specific differential phase),Z_(DR)(differential reflectivity),or both,and corresponded to various dynamic fields(ascent or descent).Ascents in the DGL of cloud systems with vigorous vertical development were coincident with large-value zones of Z_(DR),signifying ice crystals with a large axis ratio,but with no obvious large values of K_(DP),which differs from previous findings.It is speculated that ascent in the DGL promoted ice crystals to undergo further growth before sinking.If there was descent in the DGL,a high echo top corresponded to large values of K_(DP),denoting a large number concentration of ice crystals;but with the echo top descending,small values of K_(DP)formed.This is similar to previous results and reveals that a high echo top is conducive to the generation of ice crystals.When ice particles fall to low levels(-10℃to 0℃),they grow through riming,aggregation,or deposition,and may not be related to the kinematic structure.It is important to note that this study was only based on a limited number of cases and that further research is therefore needed.
基金supported by the National Key R&D Program of China(2019YFC1510305)the National Natural Science Foundation of China(Grant Nos.41705119 and 41575131)+2 种基金Baojun CHEN also acknowledges support from the CMA Key Innovation Team(CMA2022ZD10)Qiujuan FENG was supported by the General Project of Natural Science Research in Shanxi Province(20210302123358)the Key Projects of Shanxi Meteorological Bureau(SXKZDDW20217104).
文摘To evaluate the ability of the Predicted Particle Properties(P3)scheme in the Weather Research and Forecasting(WRF)model,we simulated a stratiform rainfall event over northern China on 22 May 2017.WRF simulations with two P3 versions,P3-nc and P3-2ice,were evaluated against rain gauge,radar,and aircraft observations.A series of sensitivity experiments were conducted with different collection efficiencies between ice and cloud droplets.The comparison of the precipitation evolution between P3-nc and P3-2ice suggested that both P3 versions overpredicted surface precipitation along the Taihang Mountains but underpredicted precipitation in the localized region on the leeward side.P3-2ice had slightly lower peak precipitation rates and smaller total precipitation amounts than P3-nc,which were closer to the observations.P3-2ice also more realistically reproduced the overall reflectivity structures than P3-nc.A comparison of ice concentrations with observations indicated that P3-nc underestimated aggregation,whereas P3-2ice produced more active aggregation from the self-collection of ice and ice-ice collisions between categories.Efficient aggregation in P3-2ice resulted in lower ice concentrations at heights between 4 and 6 km,which was closer to the observations.In this case,the total precipitation and precipitation pattern were not sensitive to riming.Riming was important in reproducing the location and strength of the embedded convective region through its impact on ice mass flux above the melting level.
文摘The paper addresses some of the problems surrounding the relation between ice core chemical signals and atmospheric chemical composition in polar areas. The topic is important as the reconstruction of past climate and past atmospheric chemical composition is based on the assumption that chemical concentrations in the air, snow, firn and ice core are correlated. Ice core interpretation of aerosol is more straightforward than that of reactive gases. The transfer functions of gaseous species strongly interacting with ice are complex and additional field and laboratory experiments are required. Ice core chemical signals depend on the chemical composition of precipitations, which are related to the physics of precipitation formation, the chemical composition of the atmosphere, and post-depositional processes. Published papers reporting data on the chemical composition of snow seldom consider the fact that crystal formation and growth in cloud (rimed or unrimed) or near the ground (clear-sky precipitations), hoar-frost formation and surface riming determine different chemical concentrations, even assuming constant background concentration in the atmosphere. This paper discusses the physical and chemical processes affecting the formation of precipitations in polar areas, and the process of scavenging gases from non-growing and growing crystals. Attention is mainly focused on the processes involving nitrate anion in snow, hoar frost and firn. Knowledge of the chemical relationship between surface snow and atmospheric chemical concentration could be enhanced by considering specific events, such as snow falling from cloud, clear sky precipitation, and surface hoar or riming surface, with simultaneous air sampling. In conclusion, field and laboratory experiments are still required to study the scavenging processes during crystal formation.
基金financially supported by the National Natural Science Foundation of China(Grant No.51879125)the Jiangsu Provincial Higher Education Natural Science Research Major Project(Grant No.18KJA580003)+1 种基金the Natural Science Foundation of Jiangsu Province(Grant No.BK20211342)the Jiangsu Province“Six Talents Peak”High-level Talents Support Project(Grant No.2018-KTHY-033).
文摘Offshore wind energy resources are operational in cold regions,while offshore wind turbines will face the threat of icing.Therefore,it is necessary to study icing of offshore wind turbines under different icing conditions.In this study,icing sensitivity of offshore wind turbine blades are performed using a combination of FLUENT and FENSAP-ICE software,and the effects of liquid water content(LWC),medium volume diameter(MVD),wind speed and air temperature on blade icing shape are analyzed by two types of ice,namely rime ice and glaze ice.The results show that the increase of LWC and MVD will increase the amount of ice that forms on the blade surface for either glaze ice or rime ice,and an increase of MVD will expand the adhesion surface between ice and blade.Before reaching the rated wind speed of 11.4 m/s,it does not directly affect the icing shape.However,after reaching the rated wind speed,the attack angle of the incoming flow decreases obviously,and the amount of ice increases markedly.When the ambient air temperature meets the icing conditions of glaze ice(i.e.,−5℃ to 0℃),the lower the temperature,the more glaze ice freezes,whereas air temperature has no impact on the icing of rime ice.Compared with onshore wind turbines,offshore wind turbines might face extreme meteorological conditions,and the wind speed has no impact on the amount of ice that forms on the blade surface for most wind speeds.
基金supported by the Yunnan Major Scientific and Technological Projects(Grant No.202302AD080001)the National Natural Science Foundation,China(No.52065033).
文摘When building a classification model,the scenario where the samples of one class are significantly more than those of the other class is called data imbalance.Data imbalance causes the trained classification model to be in favor of the majority class(usually defined as the negative class),which may do harm to the accuracy of the minority class(usually defined as the positive class),and then lead to poor overall performance of the model.A method called MSHR-FCSSVM for solving imbalanced data classification is proposed in this article,which is based on a new hybrid resampling approach(MSHR)and a new fine cost-sensitive support vector machine(CS-SVM)classifier(FCSSVM).The MSHR measures the separability of each negative sample through its Silhouette value calculated by Mahalanobis distance between samples,based on which,the so-called pseudo-negative samples are screened out to generate new positive samples(over-sampling step)through linear interpolation and are deleted finally(under-sampling step).This approach replaces pseudo-negative samples with generated new positive samples one by one to clear up the inter-class overlap on the borderline,without changing the overall scale of the dataset.The FCSSVM is an improved version of the traditional CS-SVM.It considers influences of both the imbalance of sample number and the class distribution on classification simultaneously,and through finely tuning the class cost weights by using the efficient optimization algorithm based on the physical phenomenon of rime-ice(RIME)algorithm with cross-validation accuracy as the fitness function to accurately adjust the classification borderline.To verify the effectiveness of the proposed method,a series of experiments are carried out based on 20 imbalanced datasets including both mildly and extremely imbalanced datasets.The experimental results show that the MSHR-FCSSVM method performs better than the methods for comparison in most cases,and both the MSHR and the FCSSVM played significant roles.
