weather

NVIDIA Days at KAUST

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B2/3 A0215

Join us (registration required) for the KAUST Supercomputing Lab (KSL) NVIDIA Days from September 15 to 17, 2026, a three-day program supporting the community's ongoing work in AI and High Performance Computing (HPC) through expert-led sessions, personalized clinics, and hands-on training.

Mathematical modeling of the stochastic climate system

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B9 L2 H1

​Author of more than 290 journal and conference publications, Professor Stenchikov's research interests are in multi-scale modeling of environmental processes and numerical methods; global climate change, climate downscaling, atmospheric convection; assessment of anthropogenic impacts and geoengineering; air-sea interaction, evaluating environmental consequences of catastrophic events like volcanic eruptions, nuclear explosions, forest and urban fires; and air pollution, transport of aerosols, chemically and optically active atmospheric tracers, their radiative forcing and effect on climate.

A safe sweep of weather data

1 min read ·
A statistical technique for automatically cleaning erroneous data from weather-balloon observations will improve the accuracy of weather forecasting.

Revealing hidden relationships in data

1 min read ·
A method to visualize hidden statistical structure helps make sense of environmental data.

Challenging statistics of weather extremes

1 min read ·
More accurate statistical modeling of extreme weather will improve forecasting and disaster mitigation.