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- Creators: Chen, Kangping
Description
The formation and stability of a slowly evolving zonal jet in 2-D flow with beta effect is analyzed using the model developed by Manfroi and Young in which the final governing equation was derived by means of a perturbation analysis of a barotropic vorticity equation with sinusoidal meridional mean flow. However in the original study the term β0, that represents the effect of large-scale Rossby waves, was dropped and was proceeded on a path of finding solutions for a simplified 1-D flow. The idea of this study is to understand the effects of the dropped term on the overall dynamics of the zonal jet evolution. For this purpose the system that is entirely deterministic with no additional forcing is solved by means of a standard finite difference scheme. The Numerical solutions are found for varying β0 and μ values where μ represents the bottom drag. In addition to this the criteria for the formation of zonal jets developed originally for the 1-D system is verified for the 2-D system as well. The study reveals the similarity in some of the results of the 1-D and the 2-D system like the merging of jets in the absence of bottom drag, formation of steady jets in presence of a non-zero bottom drag and the adherence to the boundary criteria for the formation of zonal jets. But when it comes to the formation of steady jets, a finite β0 value is required above which the solution is similar to the 1-D system. Also the jets formed under the presence of non-zero bottom drag seem wavy in nature which is different from the steady horizontal jets produced in the 1-D system.
ContributorsRaghunathan, Girish Nigamanth (Author) / Huang, Huei-Ping (Thesis advisor) / Herrmann, Marcus (Committee member) / Chen, Kangping (Committee member) / Arizona State University (Publisher)
Created2017
Description
Environmental remote sensing has seen rapid growth in the recent years and Doppler wind lidars have gained popularity primarily due to their non-intrusive, high spatial and temporal measurement capabilities. While lidar applications early on, relied on the radial velocity measurements alone, most of the practical applications in wind farm control and short term wind prediction require knowledge of the vector wind field. Over the past couple of years, multiple works on lidars have explored three primary methods of retrieving wind vectors viz., using homogeneous windfield assumption, computationally extensive variational methods and the use of multiple Doppler lidars.
Building on prior research, the current three-part study, first demonstrates the capabilities of single and dual Doppler lidar retrievals in capturing downslope windstorm-type flows occurring at Arizona’s Barringer Meteor Crater as a part of the METCRAX II field experiment. Next, to address the need for a reliable and computationally efficient vector retrieval for adaptive wind farm control applications, a novel 2D vector retrieval based on a variational formulation was developed and applied on lidar scans from an offshore wind farm and validated with data from a cup and vane anemometer installed on a nearby research platform. Finally, a novel data visualization technique using Mixed Reality (MR)/ Augmented Reality (AR) technology is presented to visualize data from atmospheric sensors. MR is an environment in which the user's visual perception of the real world is enhanced with live, interactive, computer generated sensory input (in this case, data from atmospheric sensors like Doppler lidars). A methodology using modern game development platforms is presented and demonstrated with lidar retrieved wind fields. In the current study, the possibility of using this technology to visualize data from atmospheric sensors in mixed reality is explored and demonstrated with lidar retrieved wind fields as well as a few earth science datasets for education and outreach activities.
Building on prior research, the current three-part study, first demonstrates the capabilities of single and dual Doppler lidar retrievals in capturing downslope windstorm-type flows occurring at Arizona’s Barringer Meteor Crater as a part of the METCRAX II field experiment. Next, to address the need for a reliable and computationally efficient vector retrieval for adaptive wind farm control applications, a novel 2D vector retrieval based on a variational formulation was developed and applied on lidar scans from an offshore wind farm and validated with data from a cup and vane anemometer installed on a nearby research platform. Finally, a novel data visualization technique using Mixed Reality (MR)/ Augmented Reality (AR) technology is presented to visualize data from atmospheric sensors. MR is an environment in which the user's visual perception of the real world is enhanced with live, interactive, computer generated sensory input (in this case, data from atmospheric sensors like Doppler lidars). A methodology using modern game development platforms is presented and demonstrated with lidar retrieved wind fields. In the current study, the possibility of using this technology to visualize data from atmospheric sensors in mixed reality is explored and demonstrated with lidar retrieved wind fields as well as a few earth science datasets for education and outreach activities.
ContributorsCherukuru, Nihanth Wagmi (Author) / Calhoun, Ronald (Thesis advisor) / Newsom, Rob (Committee member) / Huang, Huei Ping (Committee member) / Chen, Kangping (Committee member) / Dahm, Werner (Committee member) / Arizona State University (Publisher)
Created2017