Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
A toolkit for three-dimensional reconstruction andvisualization of weather radar images
Download
index.pdf
Date
2019
Author
Pesen, Mustafa Ahmet
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
198
views
142
downloads
Cite This
Weather radars are among key instruments that feed numerical weather prediction models. They form two-dimensional (2D) images at various elevation angles with radii of tens of kilometers. These images are actually sections from three-dimensional (3D) time-dependent volumetric data. In modern radars, each cell can be assigned a type of hydrometeor after processing. However, the visual interpretation of these images is not easy due to the complicated viewing geometry. Nevertheless, computer graphics can make weather radar images easily observable and analyzable. In this thesis, a method and a toolkit for 3D reconstruction and visualization of weather radar images are presented. The toolkit enables users to process and visualize NEXRAD Level III hydrometeor classification images in the form of closed-volumes and collected images are converted into volumetric display of precipitation types in following steps: Firstly, continuous and smooth density estimates are obtained for each precipitation type in these 2D images and the type with the maximum density is assigned to the corresponding cell if it is above a threshold. Secondly, the resulting image is segmented using connected components analysis. Then, the boundaries of each segment are extracted and transferred to the 3D space by using metadata. Subsequently, the 3D polygons from different levels but belonging to the same object are matched. Finally, a 3D wireframe structure is created from the matched 3D polygons and displayed sequentially to create 3D visual animation using computer graphics algorithms. The toolkit can help weather radar operators to better grasp the complicated weather events in 3D.
Subject Keywords
Meteorology.
,
Meteorology
,
Three-dimensional Modeling
,
Three-dimensional Visualization
,
Image Processing,Weather Radar
,
Hydrometeor Classification
URI
http://etd.lib.metu.edu.tr/upload/12623568/index.pdf
https://hdl.handle.net/11511/43833
Collections
Graduate School of Natural and Applied Sciences, Thesis
Suggestions
OpenMETU
Core
Evaluation of the performance of WRF model in extreme precipitation estimation concerning the changing model configuration and the spatial and temporal variations
Duzenli, Eren; Pilatin, Heves; Yücel, İsmail; Kılıçarslan, Berina; Yılmaz, Mustafa Tuğrul (2020-05-08)
Global numerical weather prediction models (NWP) such as the European Centre for Medium-Range Weather Forecasts (ECMWF) and Global Forecast System (GFS) generate atmospheric data for the entire world. However, these models provide the data at large spatiotemporal resolutions because of computational limitations. Weather Research and Forecasting (WRF) Model is one of the models, which is capable of dynamically downscaling the NWP models’ output. In this study, all combinations of 4 microphysics and 3 cumulus...
Analyses of atmospheric and marine observations along the Turkish coast
Tutsak, Ersin; Özsoy, Emin; Department of Physical Oceanography (2012)
Time series and spectral analyses are applied to meteorological data (wind velocity, air temperature, barometric pressure) and sea level measurements from a total of 13 monitoring stations along the Turkish Coast. Analyses of four-year time series identify main time scales of transport and motion while establishing seasonal characteristics, i.e. distinguishing, for instance, between winter storms and summer sea-breeze system. Marine flow data acquired by acoustic doppler current pro filers (ADCP) is also a...
Evaluating the use of different precipitation datsets in flood modelling
Akyürek, Sevda Zuhal (2016-04-17)
Satellite based precipitation products, numerical weather prediction model precipitation forecasts and weather radar precipitation estimates can be a remedy for gauge sparse regions especially in flood forecasting studies. However, there is a strong need for evaluation of the performance and limitations of these estimates in hydrology. This study compares the Hydro-Estimator precipitation product, Weather Research and Forecasting (WRF) model precipitation and weather radar values with gauge data in Samsun-T...
Evaluation of gauge adjustment methods in improving radar precipitation estimation quality over Antalya radar in Turkey.
Yousufi, Kaveh Patakchi; Yılmaz, Mustafa Tuğrul; Ozturk, Kurtulus; Yücel, İsmail; Yılmaz, Koray Kamil (null; 2019-11-28)
Radar-based precipitation estimates rely on algorithms that utilize observations of backscattered waves sent from the radar. By utilizing these backscattered observations and different reflectivity-rainfall (Z-R) equations, radar-based precipitation estimates are obtained. However, this process contains uncertainties due to used Z-R equations or other error sources such as beam blockage, attenuation, etc. on the radar beams. The majority of the studies in the literature focused on reducing errors caused by ...
A decision support system for combining forecasting results
Bilkay, Tunç; Şen, Tayyar; Department of Industrial Engineering (2003)
The present study aims to develop an analysis package for combining forecasts that are obtained from different forecast methods. The package is composed of three modules, namely, the data input module, the data analysis module and the combination module. In data input module, the data is entered and saved as an Excel file with the given name. In data analysis module, the program computes the forecasts of the selected methods and displays the forecast results, the mean absolute errors, the mean square errors...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
M. A. Pesen, “A toolkit for three-dimensional reconstruction andvisualization of weather radar images,” Thesis (M.S.) -- Graduate School of Natural and Applied Sciences. Geodetic and Geographical Information Technologies., Middle East Technical University, 2019.