CDTI Meteorology Project

As part of project IDI-20220299,  “Desarrollo de una nueva solución software de predicción meteorológica de alta precisión” , the specialized Machine Learning team developed a system for characterizing and predicting meteorological patterns related to different significant events (pollution, fires, energy).

Through the use of unsupervised neural networks, we’ve been able to identify the meteorological patterns linked to health risk events in the metropolitan area of Madrid.

We’ve also been able to identify meteorological patterns that are prone to triggering large-scale fires in Galicia, and assess different potential levels of risk in different zones during a wildfire.

In addition, the meteorological conditions surrounding the peninsula have been analyzed to discover the influence of weather in wind power production on a broad scale, letting us define four major production groups based on generated capacity.

The major challenge in this project was to integrate machine learning techniques applied to meteorological data into a single tool, as well as the design of a user-friendly dashboard to enable anyone to characterize future forecasts from meteorological models based on the criteria obtained from these machine learning models.

This project is co-funded by the European Regional Development Fund (ERDF) with the aim of promoting technological development, innovation, and high-quality research.

Project:  IDI-20220299: DESARROLLO DE UNA NUEVA SOLUCIÓN SOFTWARE DE PREDICCIÓN METEOROLÓGICA DE ALTA PRECISIÓN.

Open Call: Proyecto de INVESTIGACIÓN Y DESARROLLO – IDI-20220299

Goal: Develop a new operational prediction methodology using Machine Learning techniques to identify atmospheric patterns that may impact human development and renewable energy in the current reality of Climate Change

Timeframe: 18 months. Start date 01/11/2021 – 30/04/2023

Budget: 458.013,00 €

Funding: 389.311,05 €