Aug 31, 2022 · This study compares two approaches and introduces a model suitable for the task of forecasting changes in hail frequency for ongoing decades.

Sep 30, 2023 · This study aims to develop a machine-learning model capable of working with various climatic models and climate change scenarios.

Sep 30, 2023 · This study compares the effectiveness of these two approaches and introduces a model suitable for forecasting changes in hail frequency.

Aug 31, 2022 · This study compares two approaches and introduces a model suitable for the task of forecasting changes in hail frequency for ongoing decades.

Hail risk assessment is crucial for businesses, particularly in the agricultural and insurance sectors, as it helps estimate and mitigate potential losses.

Mar 11, 2024 · We present a novel open-source hail damage model for buildings and cars based on single-polarization radar data and 250 000 geolocated hail damage reports in ...

Long-term hail risk assessment with deep neural networks ... But there are no machine learning models for data-driven forecasting of changes in hail frequency for ...

Our neural network exhibited strong discrimination between hail-days and non-hail days on a random validation set of 100,000 space-time grid points, with an ...

We present a hail model that has been developed to describe the hail hazard over Italy. This model relies on several ERA5 large-scale meteorological variables.

Dec 9, 2024 · We use these datasets coupled with environmental information to calculate a hail damage estimate (HDE) using a deep neural network approach ...