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UID:pretalx-juliacon-2026-UETBSG@pretalx.com
DTSTART;TZID=CET:20260812T160000
DTEND;TZID=CET:20260812T161000
DESCRIPTION:Global land surface and hydrological models are crucial compone
 nts of Earth System Models (ESMs). In addition to providing realistic boun
 dary conditions for the atmosphere and ocean components\, they also play a
  key role in understanding Earth’s changing energy imbalance and the res
 ponse of the terrestrial carbon and water cycles to anthropogenic climate 
 change. Unlike atmosphere and ocean models\, however\, land models lack a 
 fluid dynamical core and rely heavily on empirical parameterizations to re
 present many key processes. As such\, there is a continued need for a new 
 generation of land models which can facilitate the incorporation of data-d
 riven components. Here we present Terrarium.jl\, a Julia-based land modeli
 ng framework for GPU-accelerated and automatically differentiable simulati
 ons of soil\, snow\, and vegetation dynamics\, along with their correspond
 ing land-atmosphere exchange fluxes. We highlight how Julia’s key featur
 es enable unprecedented modularity in the model design and seamless GPU pa
 rallelization through KernelAbstractions.jl. We further demonstrate the va
 lue of GPU acceleration and differentiability through a series of performa
 nce benchmarks and sensitivity analyses. We also detail our initial experi
 ments in achieving stable coupling to a reduced-complexity atmosphere mode
 l\, SpeedyWeather.jl.
DTSTAMP:20260502T104506Z
LOCATION:Room 3
SUMMARY:Terrarium.jl: Fully differentiable and GPU-accelerated land modelin
 g at all scales in Julia - Brian Groenke\, Maximilian Gelbrecht
URL:https://pretalx.com/juliacon-2026/talk/UETBSG/
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