H2020Индивидуална стипендия2022–2024

ARTIST · ARTificial Intelligence for Seasonal forecast of Temperature extremes

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2022-04-01 → 2024-03-31
Финансиране от ЕС: 172 932 €
Участници: 1
Схема: MSCA-IF

Линиите свързват координатора с партньорите.

Накратко на български

Изкуственият интелект се използва за по-добро предвиждане на горещите вълни в Европа. Този евтин и бърз метод помага на земеделците и енергийните компании да се подготвят за екстремните температури.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

ARTificial Intelligence for Seasonal forecast of Temperature extremes

The project ARTIST had the overarching objective of improving seasonal foreacsts of heat waves in Europe and providing a better understanding of what drives this predictability, making use of artificial intelligence techniques to complement dynamical models. Using a data-driven approach, a prediction of seasonal heat wave intesity is made over ten different European areas. The results are promising, with heat waves in a few regions that demonstrated to be possibly skilfully predicted by a data-driven model, much cheaper than a dynamical system. The architecture developed is potentially important for the society, since it introduces an innovative and very cheap methodology to perform seasonal forecasting. In fact, once the training is performed and the model has passed a benchmark for the evaluation of its performance, steps already done in the framework of ARTIST, the seasonal forecast for the following season can be performed in a few minutes with a personal laptop, an internet connection and basic knowledge of the software python. Farmers, energy providers, tourist operators are among the potential users of the project results.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

Seasonal Forecasts are critical tools for early-warning decision support systems, that can help reduce the related risk associated with hot or cold weather and other events that can strongly affect a multitude of socio-economic sectors. Recent advances in both statistical approaches and numerical modeling have improved the skill of Seasonal Forecasts. However, especially in mid-latitudes, they are still affected by large uncertainties that make their application often complicated.The ARTIST project aims at improving our knowledge of climate predictability at the seasonal time-scale, focusing on the role of unexplored drivers, to finally enhance the performance of current prediction systems. This effort is meant to reduce uncertainties and make forecasts efficiently usable by regional met-services and private bodies. A statistical/dynamical hybrid model will be designed through the synthesis of (a) a cutting-edge dynamical Seasonal Prediction System and (b) a statistical model based on advanced Machine Learning (ML) techniques. Such a hybrid approach may become critical to improve climate forecasts, because it combines the theoretical foundation and interpretability of physical modeling with the power of Artificial Intelligence (AI), that can reveal unknown or disregarded spatio-temporal features.ARTIST will focus on seasonal prediction of temperature hot/cold extremes in Europe, but its scalable nature can make it applicable across a wide range of variables and geographical areas. Besides the employment of AI, a strength of the action stands in the use of local land surface predictors to instruct the empirical model. The fellowship, which includes a variety of training activities, will be mainly conducted at the Barcelona Supercomputing Centre (Spain), a world-renowned institute for climate predictions and applications. A secondment period is projected at the Max Planck Institute for BGC (Germany), prominent in land studies and ML employment in earth science.

Оригинален текст от CORDIS (на английски).

Участници

BARCELONA SUPERCOMPUTING CENTER CENTRO NACIONAL DE SUPERCOMPUTACION · BARCELONAКоординаторИспания