| dc.contributor.author | Mikhail D. Alexandrov | |
| dc.contributor.author | Alexander Marshak | |
| dc.contributor.author | Brian Cairns | |
| dc.contributor.author | Andrew S. Ackerman | |
| dc.date.accessioned | 2023-04-12T18:40:45Z | |
| dc.date.available | 2023-04-12T18:40:45Z | |
| dc.date.copyright | 2022/12/02 | |
| dc.date.issued | 2022 | |
| dc.identifier.other | JAS-D-22-0125.1.pdf | |
| dc.identifier.uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4290058 | |
| dc.description.abstract | We present a generalization of the binary-value Markovian model previously used for statistical characterization of cloud masks to a continuous-value model describing 1D fields of cloud optical thickness (COT). This model has simple functional expressions and is specified by four parameters: the cloud fraction, the autocorrelation (scale) length, and the two parameters of the normalized probability density function of (nonzero) COT values (this PDF is assumed to have gamma-distribution form). Cloud masks derived from this model by separation between the values above and below some threshold in COT appear to have the same statistical properties as in binary-value model described in our previous publications. We demonstrate the ability of our model to generate examples of various cloud-field types by using it to statistically imitate actual cloud observations made by the Research Scanning Polarimeter (RSP) during two field experiments. | |
| dc.publisher | American Meteorological Society | |
| dc.title | Markovian Statistical Model of Cloud Optical Thickness. Part I: Theory and Examples | |
| dc.type | Journal Paper | |
| dc.journal.volume | 79 | |
| dc.journal.issue | 12 | |
| dc.journal.title | Journal of the Atmospheric Sciences | |
| dc.identifier.doi | 10.1175/JAS-D-22-0125.1 | |
| dc.journal.fristpage | 3315 | |
| dc.journal.lastpage | 3332 | |
| dc.page | 3315–3332 | |
| dc.tree | Journal of the Atmospheric Sciences:;2022:;volume( 079 ):;issue: 012 | |
| dc.contenttype | Fulltext | |