Atomfair Brainwave Hub: SciBase II / Artificial Intelligence and Machine Learning / AI-driven climate and disaster modeling

AI-driven climate and disaster modeling

Showing 217-228 of 295 articles

Stratospheric aerosol injection calibration using AI-driven atmospheric modeling for precise climate intervention

Across magma chamber dynamics during supervolcano unrest using distributed fiber-optic sensing

Decoding gamma-ray burst afterglows with multi-messenger astrophysics during tectonic plate movements

Combining quantum dot spectroscopy with Milankovitch cycle analysis for paleoclimate reconstruction

Spanning tectonic plate movements to predict megathrust earthquake hotspots

Uniting paleoclimatology with AI prediction to model abrupt climate shifts in geological time

Employing retrieval-augmented generation for real-time climate model refinement

Calibrating stratospheric aerosol injection effects using volcanic eruption plume analogs

Forecasting urban infrastructure demands for 2040 climate migration scenarios

Decoding ancient climate patterns via scientific folklore methods and dendrochronology

Using AI-driven wildfire prediction models with real-time satellite and sensor data fusion

Predicting 2100 sea level rise impacts on coastal cities at picometer precision using AI