EXTRACTION AND VISUALIZATION OF WIND SPEED IN A GIS ENVIRONMENT FROM A WEATHER RESEARCH AND FORECASTING (WRF) OUTPUT USING PYTHON

摘要

Wind is one of the rapidly developing sources of renewable energy in the Philippines. However, determining wind speed and wind pattern poses a tough challenge to developers and researchers. The Weather Research and Forecasting (WRF) model is an open source Numerical Weather Prediction (NWP) system used for determining meteorological data like wind speed in a specific area. The default format of each WRF output is in netCDF which can be viewed in a GIS environment. Even though GIS can handle large files, it will take long processing time. An alternative is to convert the netCDF file into a format that is readable by the Grid Analysis and Display System (GrADS), which is an open source post-processing tool used to access, manipulate and visualize earth science data. However, creating a script for GrADS is very complex. Thus, this study developed a Python-based GUI software for extraction of wind speed using the PyGrADS library, a Python interface for GrADS. After extraction, these can be interpolated in a GIS environment to produce a raster file. The extracted and averaged wind speed data are from 2008 (La Nina), 2010 (El Nino) and 2014 of Quezon City WRF output with a domain of 1km by 1km resolution. Given the amount and number of data points, using python script in extracting and averaging wind speed is faster than doing it manually. A GIS environment can now project the extracted output because it has a smaller file compared to the raw netCDF file. It was also able to show that the output visualized in the GIS environment has a similar trend with the output of the previous NREL study. It can be concluded that this study has shown that extracting and averaging wind speed using Python is more flexible than other post-processing softwares.