A framework for quantifying the impacts of sub-pixel reflectance variance and covariance on cloud optical thickness and effective radius retrievals based on the bispectral method

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dc.contributor.authorZhang, Z.
dc.contributor.authorWerner, F.
dc.contributor.authorWind, G.
dc.contributor.authorPlatnick, S.
dc.contributor.authorAckerman, A. S.
dc.contributor.authorGirolamo, L. Di
dc.contributor.authorMarshak, A.
dc.contributor.authorMeyer, Kerry
dc.contributor.authorCho, H. M.
dc.date.accessioned2018-09-19T20:15:07Z
dc.date.available2018-09-19T20:15:07Z
dc.date.issued2017-02-22
dc.description.abstractThe so-called bi-spectral method retrieves cloud optical thickness (τ) and cloud droplet effective radius (rₑ) simultaneously from a pair of cloud reflectance observations, one in a visible or near infrared (VIS/NIR) band and the other in a shortwave-infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring sub-pixel variations of cloud reflectances can lead to a significant bias in the retrieved τ and rₑ. In this study, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of sub-pixel variances of VIS/NIR and SWIR cloud reflectances and their covariance on the τ and rₑ retrievals. This framework takes into account the fact that the retrievals are determined by both VIS/NIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how sub-pixel cloud reflectance variations impact the τ and rₑ retrievals based on the bi-spectral method. In particular, our framework provides a mathematical explanation of how the sub-pixel variation in VIS/NIR band influences the rₑ retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in rₑ retrievals, leading to a potential contribution of positive bias to the rₑ retrieval.en_US
dc.description.sponsorshipThis research is supported by NASA grants NNX14AJ25G and NNX15AC77Gen_US
dc.description.urihttps://aip.scitation.org/doi/pdf/10.1063/1.4975502en_US
dc.format.extent7 pagesen_US
dc.genrejournal articleen_US
dc.identifierdoi:10.13016/M2TB0XZ84
dc.identifier.citationZ. Zhang, F. Werner, H. M. Cho, G. Wind, S. Platnick, A. S. Ackerman, L. Di Girolamo, A. Marshak, and Kerry Meyer, A framework for quantifying the impacts of sub-pixel reflectance variance and covariance on cloud optical thickness and effective radius retrievals based on the bispectral method, 2017, https://doi.org/10.1063/1.4975502en_US
dc.identifier.urihttps://doi.org/10.1063/1.4975502
dc.identifier.urihttp://hdl.handle.net/11603/11324
dc.language.isoen_USen_US
dc.publisherAmerican Institute of Physics (AIP)en_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Joint Center for Earth Systems Technology
dc.relation.ispartofUMBC Physics Department
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please contact the author.
dc.subjectbi-spectral methoden_US
dc.subjectUMBC High Performance Computing Facility (HPCF)en_US
dc.subjectcloud optical thickness
dc.subjectloud droplet effective radius
dc.subjectcloud reflectance observations in a visible or near infrared (VIS/NIR) band
dc.subjectcloud reflectance observations, in a shortwave-infrared (SWIR) band
dc.subjectsub-pixel variations of cloud reflectances
dc.titleA framework for quantifying the impacts of sub-pixel reflectance variance and covariance on cloud optical thickness and effective radius retrievals based on the bispectral methoden_US
dc.typeTexten_US

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