- CHECK MY NEW PUBLICATION on Atmospheric Research >>> Boundary-dependent urban impacts on timing, pattern, and magnitude of heavy rainfall in Istanbul
- M.Sc.: Atmospheric Sciences from Istanbul Technical University with a GPA of 3.94/4
- Thesis Topic: Future Changes in Hourly Extreme Precipitation, Return Levels, and Non-stationary Impacts in Türkiye.
- B.Sc.: Meteorological Engineering from Istanbul Technical University with a GPA of 3.45/4
- Thesis Topic: Assessment of Urbanization Impact On Heavy Precipitation in Istanbul, Turkey.
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I have been improving myself to think like an engineer and observe like an atmospheric scientist, which has led me to develop new ideas to assist Climate Science. One of those ideas was to create a website, Climaturk, that reveals the climate conditions of atmospheric variables in Turkey, using comprehensive statistical and thermodynamic methods. I processed the state-of-art climate data utilizing various data types (NETCDF, HDF5, GRIB, CSV) with popular Python libraries (Xarray, Numpy, Pandas, Salem, Matplotlib) and visualized it to the end-user in very engaging ways.
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I developed a Python library called Visjobs (downloaded over 22.000 times according to pepy.tech that makes it easy for atmospheric scientists to access model and observation data (ERA5, GFS, GEFS, NAM, GHCN) without even having to download them (OpenDAP).
- In my MSc project, I am applying a non-stationary extreme value analysis to high-resolution future projections of extreme precipitation indices. During the research, I become familiar with the concept of downscaling (of COSMO-CLM model) and statistical modeling. Further, I gained extensive practical experience using Xarray, Pandas, and Metpy to analyze various data formats (netCDF, GRIB, HDF) and types (reanalysis, projections, satellite data).
- Python:
- e.g. Numpy, Pandas, Xarray, Sklearn, Keras, Matplotlib, Metpy
- Data Science:
- Weather, Climate Data Science/Analytics
- Climate Science:
- Climate Modelling (COSMO)
- Machine Learning:
- Time Series Modelling
- WRF Model:
- Weather Modelling, Case Studies
- Visualization:
- e.g. Matplotlib, Plotly
- Renewable Energy:
- Wind, Solar Power Data Science/Analytics
- Dashboards:
- e.g. Plotly-Dash, Streamlit