scholarly journals Using polarimetric observations to detect and quantify the three-dimensional radiative transfer effects in passive satellite cloud property retrievals: Theoretical framework and feasibility study

2020 ◽  
Vol 246 ◽  
pp. 106920
Author(s):  
Chamara Rajapakshe ◽  
Zhibo Zhang
Keyword(s):  
Radiative Transfer ◽  
Feasibility Study ◽  
Three Dimensional ◽  
Theoretical Framework ◽  
Transfer Effects ◽  
Cloud Property

scholarly journals Three-dimensional radiative transfer effects of clouds in the microwave spectral range

1996 ◽  
Vol 101 (D2) ◽  
pp. 4289-4298 ◽  
Author(s):  
Quanhua Liu ◽  
Clemens Simmer ◽  
Eberhard Ruprecht
Keyword(s):  
Radiative Transfer ◽  
Spectral Range ◽  
Three Dimensional ◽  
Transfer Effects

scholarly journals Retrieval of optical thickness and droplet effective radius of inhomogeneous clouds using deep learning

2017 ◽  
Author(s):  
Rintaro Okamura ◽  
Hironobu Iwabuchi ◽  
K. Sebastian Schmidt
Keyword(s):  
Deep Learning ◽  
Radiative Transfer ◽  
Optical Thickness ◽  
Three Dimensional ◽  
Cloud Droplet ◽  
Effective Radius ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Transfer Effects ◽  
Cloud Properties

Abstract. Three-dimensional (3D) radiative transfer effects are a major source of retrieval errors in satellite-based optical re- mote sensing of clouds. In this study, we present two retrieval methods based on deep learning. We use deep neural networks (DNNs) to retrieve multipixel estimates of cloud optical thickness and column-mean cloud droplet effective radius simultane- ously from multispectral, multipixel radiances. Cloud field data are obtained from large-eddy simulations, and a 3D radiative transfer model is employed to simulate upward radiances from clouds. The cloud and radiance data are used to train and test the DNNs. The proposed DNN-based retrieval is shown to be more accurate than the existing look-up table approach that assumes plane-parallel, homogeneous clouds. By using convolutional layers, the DNN method estimates cloud properties robustly, even for optically thick clouds, and can correct the 3D radiative transfer effects that would otherwise affect the radiance values.

scholarly journals An Exit Strategy for the Definitional Elusiveness: A Three-Dimensional Framework for Social Entrepreneurship

2021 ◽  
Vol 13 (2) ◽  
pp. 563
Author(s):  
Bing Ran ◽  
Scott Weller
Keyword(s):  
Social Change ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Social Entrepreneurship ◽  
Common Ground ◽  
Three Dimensional ◽  
Theoretical Framework ◽  
Future Research ◽  
Exit Strategy ◽  
Conceptual Paper

Despite the growing utility and prevalence of social entrepreneurship, an accepted definition remains elusive and infeasible. Yet, it is imperative that the principles guiding social entrepreneurship are identified so that common ground is established to facilitate future research. On the basis of a systematic literature review, this conceptual paper proposes a theoretical framework outlining social entrepreneurship as a three-dimensional framework as a function of continua of “social” and “business” logics, “beneficial” and “detrimental” social change logics, and “innovation” and “mundane” logics. The framework accommodates the fuzziness and ambiguity associated with social entrepreneurship whilst remaining a workable, identifiable construct. By accounting for the shifting logics practiced by social entrepreneurship that both influence and are influenced by the organizational environment, this framework provides an exit strategy for the definitional elusiveness of social entrepreneurship. The resultant structures and functions of social entrepreneurship are shaped by these constraints as reflected by the fluidity and flexibility endorsed by the framework. Four avenues for future research regarding social entrepreneurship are recommended on the basis of the framework proposed in this article.

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