Idealized models of the joint probability distribution of wind speeds
| dc.contributor.author | Monahan, Adam H. | |
| dc.date.accessioned | 2019-09-13T19:31:04Z | |
| dc.date.available | 2019-09-13T19:31:04Z | |
| dc.date.copyright | 2018 | en_US |
| dc.date.issued | 2018 | |
| dc.description.abstract | The joint probability distribution of wind speeds at two separate locations in space or points in time completely characterizes the statistical dependence of these two quantities, providing more information than linear measures such as correlation. In this study, we consider two models of the joint distribution of wind speeds obtained from idealized models of the dependence structure of the horizontal wind velocity components. The bivariate Rice distribution follows from assuming that the wind components have Gaussian and isotropic fluctuations. The bivariate Weibull distribution arises from power law transformations of wind speeds corresponding to vector components with Gaussian, isotropic, mean-zero variability. Maximum likelihood estimates of these distributions are compared using wind speed data from the mid-troposphere, from different altitudes at the Cabauw tower in the Netherlands, and from scatterometer observations over the sea surface. While the bivariate Rice distribution is more flexible and can represent a broader class of dependence structures, the bivariate Weibull distribution is mathematically simpler and may be more convenient in many applications. The complexity of the mathematical expressions obtained for the joint distributions suggests that the development of explicit functional forms for multivariate speed distributions from distributions of the components will not be practical for more complicated dependence structure or more than two speed variables. | en_US |
| dc.description.reviewstatus | Reviewed | en_US |
| dc.description.scholarlevel | Faculty | en_US |
| dc.description.sponsorship | This work was supported by the Natural Sciences and Engineering Research Council of Canada. The author gratefully acknowledges the provision of the 500 hPa data by the ECMWF, the tower data by the Cabauw Experimental Site for Atmospheric Research (CESAR), and the sea surface wind data by the NASA Jet Propulsion Laboratory Physical Oceanography Distributed Active Archive Center. | en_US |
| dc.identifier.citation | Monahan, A.H. (2018). Idealized models of the joint probability distribution of wind speeds. Nonlinear Processes in Geophysics, 25(2), 335-353. https://doi.org/10.5194/npg-25-335-2018 | en_US |
| dc.identifier.uri | https://doi.org/10.5194/npg-25-335-2018 | |
| dc.identifier.uri | http://hdl.handle.net/1828/11137 | |
| dc.language.iso | en | en_US |
| dc.publisher | Nonlinear Processes in Geophysics | en_US |
| dc.subject.department | School of Earth and Ocean Sciences | |
| dc.title | Idealized models of the joint probability distribution of wind speeds | en_US |
| dc.type | Article | en_US |