AIREN – AI Radar Enhancing & Nowcasting
AIREN is an advanced software suite built on state-of-the-art artificial intelligence models designed specifically for radar data. It provides enhanced accuracy for nowcasting, product generation, and advanced radar data interpretation. The system leverages global radar datasets and modern AI techniques to deliver unmatched precision and operational reliability.
AIREN provides fully automated severe weather warning generation, processing radar data from measurement to model prediction and final message delivery.
The system issues timely and precise alerts based on dual-polarization radar data, ensuring communities and decision-makers receive rapid, reliable, and actionable information without the need for manual intervention.
AIREN delivers the world’s most accurate radar reflectivity nowcasting, providing precise short-term forecasts up to two hours ahead.
It can be used both for meteorological operations and for public dissemination, enabling high-resolution situational awareness and proactive decision-making during severe weather events.
The Beam Blockage module reconstructs radar signals in sectors partially or fully obstructed by terrain or obstacles.
Using deep learning, it infills missing data from higher elevation scans or surrounding sectors, producing continuous and realistic radar coverage even in complex terrain.
In locations affected by strong ground clutter — such as urban or mountainous regions — the AIREN Clutter In-fill detects and reconstructs masked radar signals. The cluttered areas to be corrected are automatically detected from the total (unfiltered) reflectivity product.
This restores clean, high-quality data and improves the reliability of all subsequent meteorological products. Clutter In-fill can be seamlessly combined with AIREN Beam Blockage.
Wind farms create persistent radar artifacts that can distort measurements. Because turbine blades produce rapidly changing Doppler signatures, traditional filtering methods struggle to distinguish these echoes from true meteorological signals.
AIREN’s neural network automatically identifies and removes these effects, recovering accurate meteorological signals and ensuring the integrity of radar observations across wind farm-affected areas.
AIREN enhances quantitative precipitation estimation (QPE) by combining AI-based learning with dual-polarization radar data.
It produces precise, self-adapting precipitation estimates in real time using available rain-gauge networks, providing accurate rainfall analysis for hydrological and severe weather forecasting.
The AI-based Hydrometeor Classification (HMC) module refines traditional classification methods with fine-tuned deep models.
It accurately identifies each hydrometeor type – rain, hail, snow, graupel — and can also detect non-meteorological targets such as smoke, fire, dust, chaff, and other atmospheric phenomena, ensuring comprehensive and robust classification.