Presented is a review of the radiative properties of ice clouds from three perspectives： light scattering simulations, remote sensing applications, and broadband radiation parameterizations appropriate for numerical ...Presented is a review of the radiative properties of ice clouds from three perspectives： light scattering simulations, remote sensing applications, and broadband radiation parameterizations appropriate for numerical models. On the subject of light scattering simulations, several classical computational approaches are reviewed, including the conventional geometric-optics method and its improved forms, the finite-difference time domain technique, the pseudo-spectral time domain technique, the discrete dipole approximation method, and the T-matrix method, with specific applications to the computation of the singlescattering properties of individual ice crystals. The strengths and weaknesses associated with each approach are discussed.With reference to remote sensing, operational retrieval algorithms are reviewed for retrieving cloud optical depth and effective particle size based on solar or thermal infrared（IR） bands. To illustrate the performance of the current solar- and IR-based retrievals, two case studies are presented based on spaceborne observations. The need for a more realistic ice cloud optical model to obtain spectrally consistent retrievals is demonstrated. Furthermore, to complement ice cloud property studies based on passive radiometric measurements, the advantage of incorporating lidar and/or polarimetric measurements is discussed.The performance of ice cloud models based on the use of different ice habits to represent ice particles is illustrated by comparing model results with satellite observations. A summary is provided of a number of parameterization schemes for ice cloud radiative properties that were developed for application to broadband radiative transfer submodels within general circulation models（GCMs）. The availability of the single-scattering properties of complex ice habits has led to more accurate radiation parameterizations. In conclusion, the importance of using nonspherical ice particle models in GCM simulations for climate studies is proven.展开更多
In the Mexican Intertropical Convergence Zone, particle size distributions within 500 m of cloud boundaries at altitudes of 1000, 2500, and 4200 m, were compared against size distributions at the same levels but 1500 ...In the Mexican Intertropical Convergence Zone, particle size distributions within 500 m of cloud boundaries at altitudes of 1000, 2500, and 4200 m, were compared against size distributions at the same levels but 1500 m away from the clouds. The differences in the distributions near and far from the cloud are related to processes that may change particle properties inside the cloud. Chemical changes in the aerosols are deduced from the particles＇ refractive index, as derived from comparisons with the scattering coeflcient measured by a nephelometer. An analysis of ten cloud systems indicates that vertical transport of cloud base aerosol followed by entrainment/detrainment is the cloud processing signature most frequently observed in the comparisons （65%）. Changes in the chemical composition are observed in approximately 20% of the cases and another 20% of the cases showed removal by precipitation. About 5% of the comparisons showed clear evidence of changes by coalescence. The principal effect of these cloud-processed aerosols is observed in the increase of optical depth in the layer from 30 m to 4200 m in the near-cloud regions, in comparison with the atmosphere further from clouds.展开更多
Concave clouds will cause miscalculation by the power prediction model based on cloud ieatures for distributed photovoltaic （PV） plant. The algorithm for decomposing concave cloud into convex images is proposed. Ado...Concave clouds will cause miscalculation by the power prediction model based on cloud ieatures for distributed photovoltaic （PV） plant. The algorithm for decomposing concave cloud into convex images is proposed. Adopting minimum polygonal approximation （MPP） to demonstrate the contour of concave cloud, cloud features are described and the subdivision lines of convex decomposition for the concave clouds are determined by the centroid point scattering model and centroid angle func- tion, which realizes the convex decomposition of concave cloud. The result of MATLAB simulation indicates that the proposed algorithm can accurately detect cloud contour comers and recognize the concave points. The proposed decomposition algorithm has advantages of less time complexity and decomposition part numbers compared to traditional algorithms. So the established model can make the convex decomposition of complex concave clouds completely and quickly, which is available for the existing prediction algorithm for the ultra-short-term power output of distributed PV system based on the cloud features.展开更多
基金supported by the NSF (Grants AGS-1338440 and AGS-0946315)the endowment funds related to the David Bullock Harris Chair in Geosciences at the College of Geosciences, Texas A&M University
文摘Presented is a review of the radiative properties of ice clouds from three perspectives： light scattering simulations, remote sensing applications, and broadband radiation parameterizations appropriate for numerical models. On the subject of light scattering simulations, several classical computational approaches are reviewed, including the conventional geometric-optics method and its improved forms, the finite-difference time domain technique, the pseudo-spectral time domain technique, the discrete dipole approximation method, and the T-matrix method, with specific applications to the computation of the singlescattering properties of individual ice crystals. The strengths and weaknesses associated with each approach are discussed.With reference to remote sensing, operational retrieval algorithms are reviewed for retrieving cloud optical depth and effective particle size based on solar or thermal infrared（IR） bands. To illustrate the performance of the current solar- and IR-based retrievals, two case studies are presented based on spaceborne observations. The need for a more realistic ice cloud optical model to obtain spectrally consistent retrievals is demonstrated. Furthermore, to complement ice cloud property studies based on passive radiometric measurements, the advantage of incorporating lidar and/or polarimetric measurements is discussed.The performance of ice cloud models based on the use of different ice habits to represent ice particles is illustrated by comparing model results with satellite observations. A summary is provided of a number of parameterization schemes for ice cloud radiative properties that were developed for application to broadband radiative transfer submodels within general circulation models（GCMs）. The availability of the single-scattering properties of complex ice habits has led to more accurate radiation parameterizations. In conclusion, the importance of using nonspherical ice particle models in GCM simulations for climate studies is proven.
文摘In the Mexican Intertropical Convergence Zone, particle size distributions within 500 m of cloud boundaries at altitudes of 1000, 2500, and 4200 m, were compared against size distributions at the same levels but 1500 m away from the clouds. The differences in the distributions near and far from the cloud are related to processes that may change particle properties inside the cloud. Chemical changes in the aerosols are deduced from the particles＇ refractive index, as derived from comparisons with the scattering coeflcient measured by a nephelometer. An analysis of ten cloud systems indicates that vertical transport of cloud base aerosol followed by entrainment/detrainment is the cloud processing signature most frequently observed in the comparisons （65%）. Changes in the chemical composition are observed in approximately 20% of the cases and another 20% of the cases showed removal by precipitation. About 5% of the comparisons showed clear evidence of changes by coalescence. The principal effect of these cloud-processed aerosols is observed in the increase of optical depth in the layer from 30 m to 4200 m in the near-cloud regions, in comparison with the atmosphere further from clouds.
基金Supported by the National High Technology Research and Development Programme of China(No.2013AA050405)Doctoral Fund of Ministry of Education(No.20123317110004)+1 种基金Foundation of Zhejiang Province Key Science and Technology Innovation Team(No.2011R50011)the Natural Science Foundation of Zhejiang Province(No.LY15E070004)
文摘Concave clouds will cause miscalculation by the power prediction model based on cloud ieatures for distributed photovoltaic （PV） plant. The algorithm for decomposing concave cloud into convex images is proposed. Adopting minimum polygonal approximation （MPP） to demonstrate the contour of concave cloud, cloud features are described and the subdivision lines of convex decomposition for the concave clouds are determined by the centroid point scattering model and centroid angle func- tion, which realizes the convex decomposition of concave cloud. The result of MATLAB simulation indicates that the proposed algorithm can accurately detect cloud contour comers and recognize the concave points. The proposed decomposition algorithm has advantages of less time complexity and decomposition part numbers compared to traditional algorithms. So the established model can make the convex decomposition of complex concave clouds completely and quickly, which is available for the existing prediction algorithm for the ultra-short-term power output of distributed PV system based on the cloud features.
