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The evolution of space technology in recent years, fueled by advancements in computing such as Artificial Intelligence (AI) and machine learning (ML), has profoundly transformed our capacity to explore the cosmos. Missions like the James…
Clouds are ubiquitous\, -- \,they arise for every solar system planet that possesses an atmosphere and have also been suggested as a leading mechanism for obscuring spectral features in exoplanet observations. As exoplanet observations…
Hybrid modeling combining data-driven techniques and numerical methods is an emerging and promising research direction for efficient climate simulation. However, previous works lack practical platforms, making developing hybrid modeling a…
To identify promising exoplanets for atmospheric characterization and to make the best use of observational data, a thorough understanding of their atmospheres is needed. 3D general circulation models (GCMs) are one of the most…
1D climate models are less sophisticated than 3D global circulation models (GCMs), however their computational time is much less expensive, allowing a large number of runs in a short period of time to explore a wide parameter space.…
Global Climate Models (GCMs) are the primary tool to simulate climate evolution and assess the impacts of climate change. However, they often operate at a coarse spatial resolution that limits their accuracy in reproducing local-scale…
Earth System Models (ESMs) are essential for understanding the interaction between human activities and the Earth's climate. However, the computational demands of ESMs often limit the number of simulations that can be run, hindering the…
Modern climate projections lack adequate spatial and temporal resolution due to computational constraints, leading to inaccuracies in representing critical processes like thunderstorms that occur on the sub-resolution scale. Hybrid methods…
Future climate change impacts depend on temperatures not only through changes in their means but also through changes in their variability. General circulation models (GCMs) predict changes in both means and variability; however, GCM output…
Understanding the climates of terrestrial exoplanets and the detectability of biosignatures is an inherently interdisciplinary challenge, requiring the integration of insights from Solar System exploration, exoplanet observations and…
Energy balance models (EBMs) are one- or two-dimensional climate models that can provide insight into planetary atmospheres, particularly with regard to habitability. Because EBMs are far less computationally intensive than…
Cloud is critical for planetary climate and habitability, but it is also one of the most challenging parts of studying planets in and beyond the solar system. Here we use a cloud-resolving model (CRM) with high resolution (2 km) in a…
Planetary climates are strongly affected by planetary orbital parameters such as obliquity, eccentricity, and precession. In exoplanetary systems, exo-terrestrial planets should have various obliquities. High-obliquity planets would have…
A key challenge for computationally intensive state-of-the-art Earth System models is to distinguish global warming signals from interannual variability. Here we introduce DLESyM, a parsimonious deep learning model that accurately simulates…
Datacenters are vital to our digital society, but consume a considerable fraction of global electricity and demand is projected to increase. To improve their sustainability and performance, we envision that simulators will become primary…
Inferring the properties of transiting exoplanet atmospheres relies on comparing models to spectroscopic observations. Atmosphere models, however, make a range of assumptions, from one-dimensional (1D, varying with altitude)…
Climate change is one of the most critical challenges that our planet is facing today. Rising global temperatures are already bringing noticeable changes to Earth's weather and climate patterns with an increased frequency of unpredictable…
Modeling the atmospheres of exoplanets is fundamental to understanding their atmospheric physics and chemical processes. While one-dimensional (1D) atmospheric models with 1D radiative transfer (RT) have been widely used, advances in…
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 to quantify objective differences in how GSRMs resolve…
Climate change impacts a broad spectrum of human resources and activities, necessitating the use of climate models to project long-term effects and inform mitigation and adaptation strategies. These models generate multiple datasets by…