This study evaluates the vertical profiles of aerosol and cloud optical properties in 40 dominated dust and smoke regions in Western-Northern Africa (WNA) and Central-Southern Africa (CSA), respectively, from the surf...This study evaluates the vertical profiles of aerosol and cloud optical properties in 40 dominated dust and smoke regions in Western-Northern Africa (WNA) and Central-Southern Africa (CSA), respectively, from the surface to 10km and from 2008 to 2011 based on LIVAS (LIdar climatology of Vertical Aerosol Structure for space-based lidar simulation studies). Aerosol extinction (AE), aerosol backscatter (AB), and aerosol depolarization (AD) generally increase from the surface to 1.2 km and decrease from 1.2 km to the upper layers in both WNA and CSA. AE and AB in CSA (maximum of 0.13 km<sup>-1</sup>, 0.14 km<sup>-1</sup>, 0.0021 km<sup>-1</sup>‧sr<sup>-1</sup>, 0.0033 km<sup>-1</sup>‧sr<sup>-1</sup>) are higher than in WNA (maximum of 0.07 km<sup>-1</sup>, 0.08 km<sup>-1</sup>, 0.0017 km<sup>-1</sup>‧sr<sup>-1</sup>, 0.0015 km<sup>-1</sup>‧sr<sup>-1</sup>) at 532 and 1064 nm respectively. AD in WNA (maximum of 0.25) is significantly higher than in CSA (maximum of 0.05). There is a smooth change with the height of cloud extinction and backscatter in WNA and CSA, while there is a remarkable increase of cloud depolarization with height, whereby it is high in CSA and low in WNA due to high and low fraction of cirrus respectively. Altocumulus has the highest extinction in NA (0.0139 km<sup>-1</sup>), CA (0.058 km<sup>-1</sup>), WA (0.013 km<sup>-1</sup>), while low overcast transparent (0.76 km<sup>-1</sup>) below 1 km in SA. The major findings of this study may contribute to the improvement of our understanding of aerosol-cloud interaction studies in dominated dust and smoke aerosol regions.展开更多
Aircraft wake turbulence is an inherent outcome of aircraft flight,presenting a substan-tial challenge to air traffic control,aviation safety and operational efficiency.Building upon data obtained from coherent Dopple...Aircraft wake turbulence is an inherent outcome of aircraft flight,presenting a substan-tial challenge to air traffic control,aviation safety and operational efficiency.Building upon data obtained from coherent Doppler Lidar detection,and combining Dynamic Bayesian Networks(DBN)with Genetic Algorithm-optimized Backpropagation Neural Networks(GA-BPNN),this paper proposes a model for the inversion of wake vortex parameters.During the wake vortex flow field simulation analysis,the wind and turbulent environment were initially superimposed onto the simulated wake velocity field.Subsequently,Lidar-detected echoes of the velocity field are simulated to obtain a data set similar to the actual situation for model training.In the case study validation,real measured data underwent preprocessing and were then input into the established model.This allowed us to construct the wake vortex characteristic parameter inversion model.The final results demonstrated that our model achieved parameter inversion with only minor errors.In a practical example,our model in this paper significantly reduced the mean square error of the inverted velocity field when compared to the traditional algorithm.This study holds significant promise for real-time monitoring of wake vortices at airports,and is proved a crucial step in developing wake vortex interval standards.展开更多
文摘This study evaluates the vertical profiles of aerosol and cloud optical properties in 40 dominated dust and smoke regions in Western-Northern Africa (WNA) and Central-Southern Africa (CSA), respectively, from the surface to 10km and from 2008 to 2011 based on LIVAS (LIdar climatology of Vertical Aerosol Structure for space-based lidar simulation studies). Aerosol extinction (AE), aerosol backscatter (AB), and aerosol depolarization (AD) generally increase from the surface to 1.2 km and decrease from 1.2 km to the upper layers in both WNA and CSA. AE and AB in CSA (maximum of 0.13 km<sup>-1</sup>, 0.14 km<sup>-1</sup>, 0.0021 km<sup>-1</sup>‧sr<sup>-1</sup>, 0.0033 km<sup>-1</sup>‧sr<sup>-1</sup>) are higher than in WNA (maximum of 0.07 km<sup>-1</sup>, 0.08 km<sup>-1</sup>, 0.0017 km<sup>-1</sup>‧sr<sup>-1</sup>, 0.0015 km<sup>-1</sup>‧sr<sup>-1</sup>) at 532 and 1064 nm respectively. AD in WNA (maximum of 0.25) is significantly higher than in CSA (maximum of 0.05). There is a smooth change with the height of cloud extinction and backscatter in WNA and CSA, while there is a remarkable increase of cloud depolarization with height, whereby it is high in CSA and low in WNA due to high and low fraction of cirrus respectively. Altocumulus has the highest extinction in NA (0.0139 km<sup>-1</sup>), CA (0.058 km<sup>-1</sup>), WA (0.013 km<sup>-1</sup>), while low overcast transparent (0.76 km<sup>-1</sup>) below 1 km in SA. The major findings of this study may contribute to the improvement of our understanding of aerosol-cloud interaction studies in dominated dust and smoke aerosol regions.
基金supported by the National Natural Science Foundation of China (No.U2133210).
文摘Aircraft wake turbulence is an inherent outcome of aircraft flight,presenting a substan-tial challenge to air traffic control,aviation safety and operational efficiency.Building upon data obtained from coherent Doppler Lidar detection,and combining Dynamic Bayesian Networks(DBN)with Genetic Algorithm-optimized Backpropagation Neural Networks(GA-BPNN),this paper proposes a model for the inversion of wake vortex parameters.During the wake vortex flow field simulation analysis,the wind and turbulent environment were initially superimposed onto the simulated wake velocity field.Subsequently,Lidar-detected echoes of the velocity field are simulated to obtain a data set similar to the actual situation for model training.In the case study validation,real measured data underwent preprocessing and were then input into the established model.This allowed us to construct the wake vortex characteristic parameter inversion model.The final results demonstrated that our model achieved parameter inversion with only minor errors.In a practical example,our model in this paper significantly reduced the mean square error of the inverted velocity field when compared to the traditional algorithm.This study holds significant promise for real-time monitoring of wake vortices at airports,and is proved a crucial step in developing wake vortex interval standards.
