tcpyPI, aka "pyPI": Tropical Cyclone Potential Intensity Calculations in Python
Repository for studies on data visualization in weather/climate science
Here's the code associated with my Machine Learning (ML) based hurricane forecasting system
Automated downloads of geographic information system data posted by the National Oceanic and Atmospheric Administration's National Hurricane Center and Central Pacific Hurricane Center
Master's thesis
A streamlit web app for hurricane mapping
An ASP.NET web service that parses tropical cyclone CSV data from NOAA IBTrACS, stores it in a MongoDB database and provides a RESTful JSON API to access it.
A study evaluating and verifying the accuracy of hurricane precipitation forecasting in Louisiana, between the years 2000 and 2015.
A detailed dashboard of the history of severe storms in the Atlantic Basin. The data is provided by NOAA HURDAT2 (https://www.nhc.noaa.gov/data/hurdat/hurdat2-1851-2019-052520.txt) which has data from 1851 to 2019.
Scripts to replicate the analyses and figures from "Scaling of tropical-cyclone dissipation" by Corral et al.
Parse and Explore Data from Tropical-cyclone Databases
Code for my study titled "Identifying Thermokarst Lakes in the Qinghai-Tibetan Plateau Using Discrete Wavelet Transform-Based Deep Learning", published in the 2023 Iberian Conference on Pattern Recognition and Image Analysis
Basic Geoprocessing Tools
TropiTracker is an open-source tropical cyclone tracker that provides you with details on active and upcoming tropical cyclones such as wind speed, satellite imagery, movement speed, future tracks, and more. TropiTracker's update feature ensures that you get vital updates when they happen. Get prepared and stay ahead of the storm with TropiTracker!
Data journalism project on power access across income levels in Gainesville, Florida in the wake of Hurricane Irma.
Analyzing Tropical Storms with Tidyverse Tools
The scripts in this repository align with work done in: https://iopscience.iop.org/article/10.1088/1748-9326/ab9794
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