extrAIM in a nutshell
-
The development of an AI-enhanced, yet explainable and operational approach capable of optimally combining multiple SPPs into a single, and improved integrated SPP.
-
The development of a general probabilistic framework for the uncertainty modelling and quantification of the quantitative precipitation estimates obtained by SPPs (with focus on extremes).
-
The creation of a first-of-its-kind UA satellite-based precipitation dataset for the Mediterranean region.
-
The development of a user-friendly data analysis and visualization platform, which will enable the easy data retrieval and visualization, aiming to increase understanding and awareness against hydroclimatic risks arising from individual and compound extreme events.
A new era
A new era of satellite-based products
New technologies such as ICT and remote sensing, has opened new frontiers in monitoring earth observations (EO) from space. Underpinning that we are transitioning in new era of satellite-data-driven EO systems.
Vision
Our vision
Quantify the differences between gauge-based data and quantitative estimates of satellite-based hydroclimatic products, with focus on extremes, an aspect that will increase end-users confidence and trust on the quality and potential utility of such data products.
The challenge
The challenge of satellite-based products.
In comparison with gauge-based data, satellite-based products exhibit significant differences, especially in extremes, uncertainty, and bias, which arguably hinders their wide adoption by engineers and scientists. In this respect, developing innovative methods able to model and quantify the uncertainty of satellite-based hydroclimatic products, becomes urgent.
Mission
Our mission
Develop a general-purpose framework (using AI and stochastics) capable of modelling and quantifying the uncertainty of satellite-based products. extrAIM will develop a first-of-its-kind, satellite-based, low-latency, uncertainty-aware precipitation dataset for the Mediterranean region, adjusted to account for the extremes’ probabilistic behavior.