Published February 4, 2025
| Version 1
OEMC project use case: Meteo support tool for wildfire risk
- Creators
- GILAB DOO Beograd
Description
High resolution (1 km) daily climate element (max., min., mean temperature, sea level pressure, total precipitation) maps. This data set is valuable for wildfire risk identification modeling.
Stakeholder needs:
- To provide daily min, max, mean temperature, precipitation, sea level pressure at 1 km spatial resolution to serve as an input to ML/AI models
- To cover the 1990-present period
- To cover Europe or to have global spatial coverage if possible
Planned implementation: High resolution historical meteorological data can be used to estimate the wildfires risk and predict future events
Implementation steps include:
- Create a daily gridded meteorological dataset for the entire World with a spatial resolution of 1 km, covering the period from 1961 to 2020. The dataset includes five daily variables: maximum, minimum, and mean temperature, mean sea level pressure, and total precipitation. Spatio-temporal regression Kriging is used for interpolation.
- Develop https://dailymeteo.com/ web portal to provide access to the data
- Develop MeteoAI chatbot to interact with the meteorological data
Visit the use-case page on the OEMC website to learn more: https://earthmonitor.org/use-cases/meteo-support-tool-for-wildfire-risk/