https://www.kaggle.com/competitions/widsdatathon2023/overview

In this year’s datathon challenges participants will use data science to improve longer-range weather forecasts to help people prepare and adapt to extreme weather events caused by climate change.

Extreme weather events are sweeping the globe and range from heat waves, wildfires and drought to hurricanes, extreme rainfall and flooding. These weather events have multiple impacts on agriculture, energy, transportation, as well as low resource communities and disaster planning in countries across the globe.

Accurate long-term forecasts of temperature and precipitation are crucial to help people prepare and adapt to these extreme weather events. Currently, purely physics-based models dominate short-term weather forecasting. But these models have a limited forecast horizon. The availability of meteorological data offers an opportunity for data scientists to improve sub-seasonal forecasts by blending physics-based forecasts with machine learning. Sub-seasonal forecasts for weather and climate conditions (lead-times ranging from 15 to more than 45 days) would help communities and industries adapt to the challenges brought on by climate change.

This year’s datathon, organized by the WiDS Worldwide team at Stanford University, Harvard University IACS, Arthur, and the WiDS Datathon Committee, will focus on longer-term weather forecasting to help communities adapt to extreme weather events caused by climate change.

The dataset was created in collaboration with Climate Change AI (CCAI). Participants will submit forecasts of temperature and precipitation for one year, competing against the other teams as well as official forecasts from NOAA

The dataset and challenge is accessible to both beginners and experienced participants from industry, government, NGOs and academia. Whether you’re currently working in the field or just starting to learn about data science, we welcome all participants. For those who have never tried machine learning, we will provide a series of guides to help you get started with the algorithms and dataset.

Many WiDS ambassadors will host datathon workshops, where participants will be able to receive mentorship, form teams, and hone their data science skills. Check back frequently, as workshops are posted daily.

The WiDS Datathon will run until March 1, 2023.

Data analysis can be completed using your preferred tools. Tutorials, sample code, and other resources will be posted throughout the competition on the Kaggle Tutorial and Resources page. You will then upload your predictions for a test set to Kaggle and these will be used to determine the public leaderboard rankings and the winners of the competition.