activity
20202026
most citedClimSim-Online: A Large Multi-scale Dataset and Framework for Hybrid ML-physics Climate Emulation

19 citations · 28 across the 7 of their papers we have counts for

collaborators

8 papers

physics.ao-ph2026

Video Diffusion for Satellite-based High-Dynamical-Fidelity Precipitation (HiDFiP) Field Generation

Runze Li, Yan Xia, Yongquan Qu +6

High spatiotemporal fidelity precipitation products that accurately capture storm spatial organization, propagation, and lifecycle evolution, are essential for advancing hydrometeo…

cs.LG2026

A Scale-Adaptive Framework for Joint Spatiotemporal Super-Resolution with Diffusion Models

Max Defez, Filippo Quarenghi, Mathieu Vrac +2

Deep-learning video super-resolution has progressed rapidly, but climate applications typically super-resolve (increase resolution) either space or time, and joint spatiotemporal m…

cs.LG2023★ 1 cited

Understanding and Visualizing Droplet Distributions in Simulations of Shallow Clouds

Justus C. Will, Andrea M. Jenney, Kara D. Lamb +7

Thorough analysis of local droplet-level interactions is crucial to better understand the microphysical processes in clouds and their effect on the global climate. High-accuracy si…

cs.LG2023★ 19 cited

ClimSim-Online: A Large Multi-scale Dataset and Framework for Hybrid ML-physics Climate Emulation

Sungduk Yu, Zeyuan Hu, Akshay Subramaniam +44

Modern climate projections lack adequate spatial and temporal resolution due to computational constraints, leading to inaccuracies in representing critical processes like thunderst…

physics.ao-ph2022★ 1 cited

Understanding Extreme Precipitation Changes through Unsupervised Machine Learning

Griffin Mooers, Tom Beucler, Mike Pritchard +1

Despite the importance of quantifying how the spatial patterns of extreme precipitation will change with warming, we lack tools to objectively analyze the storm-scale outputs of mo…

physics.ao-ph2022★ 4 cited

Comparing Storm Resolving Models and Climates via Unsupervised Machine Learning

Griffin Mooers, Mike Pritchard, Tom Beucler +5

Global Storm-Resolving Models (GSRMs) have gained widespread interest because of the unprecedented detail with which they resolve the global climate. However, it remains difficult…

physics.ed-ph2021★ 3 cited

Proposals for High School Teaching of Quantum Physics

Enzo Bonacci

In the Italian education system, secondary students (ages 14-19) face the foundations of quantum physics during the final term of scientific high school (pre-university year). The…

physics.ao-ph2020

Generative Modeling for Atmospheric Convection

Griffin Mooers, Jens Tuyls, Stephan Mandt +2

While cloud-resolving models can explicitly simulate the details of small-scale storm formation and morphology, these details are often ignored by climate models for lack of comput…