Philippe Ear joined Hydroclimat in October 2022 as an engineer, associate actuary and climate data scientist, as part of a CIFRE thesis conducted in partnership with the Université Côte d'Azur. His doctoral thesis focuses on the analysis of extreme values in hydroclimatology, a crucial issue for understanding and assessing the risks associated with climate change.

His mission at Hydroclimat is to design innovative statistical methods to better characterise rare climatic events, such as extreme precipitation. He develops advanced models for post-processing climate and meteorological data, integrating machine learning and artificial intelligence techniques, particularly for bias correction and downscaling of climate model outputs (CMIP6).

Philippe works in particular on modelling daily precipitation and producing very high-resolution climate datasets (up to 30 metres), using algorithms such as Random Forest. These tools enable detailed, localised assessment of climate risks, which is useful for operational applications in water management, land use planning and insurance.