Scientific Discovery through Advanced Computing

Scientific Discovery through Advanced Computing

Recent Content

Recent Highlights

Algorithms and software were developed to solve a key challenge, property preservation, in modeling atmospheric transport of trace constituent species, such as water vapor, trace gases, and aerosols. These methods will speed up global climate models.
We improved the fidelity of surface-atmosphere longwave radiation coupling over Sahara and Sahel region in the climate model. We showed such improvement can affect simulated climate, regional and beyond. 
In order to provide credible predictions of sea level rise to policymakers and stakeholders, scientists need accurate representations of land ice as simulated within Earth system models.  Confidence in the simulations is attained through a robust validation of these models that is available to the...
Most earth system models still rely on imperfect parameterizations of unresolved cloud processes. Cloud SuperParameterization (SP) – embedding thousands of limited-domain cloud-resolving arrays in a global climate model – has proved a promising alternative for deep convection, but its computational...
The biggest uncertainty in near-future sea level rise (SLR) comes from the Antarctic Ice Sheet. Antarctic ice flows in relatively fast-moving ice streams from the interior to the ocean, where it is carried into enormous floating ice shelves which push back on their feeder ice streams, buttressing...
Most earth system models still rely on imperfect parameterizations of unresolved cloud processes. SuperParameterization (SP) – embedding thousands of limited-domain cloud-resolving arrays in a global climate model -- is a promising alternative but its computational cost has been prohibitive. Here...
Various phytoplankton groups contribute differently to the emission of dimethyl sulfide (DMS), which affects atmospheric sulfate aerosol loading and cloud brightness. Shifts in phytoplankton community composition without changing total biomass could potentially influence clouds and climate via the...
DMS, originated from phytoplankton, is a significant source of marine sulfate aerosol and plays an important role in climate via modifying cloud properties. The sign and strength of phytoplankton-DMS-climate feedbacks are examined for the first time using fully coupled climate simulations with...
The consensus of recent literature is that both the Greenland and Antarctic ice sheets have “tipping points,” where exceeding certain climate thresholds can lead to feedbacks that result in sustained loss of ice-sheet mass, if global warming from human causes were to exceed 1.5 °C above pre-...
Hyperdiffusion is used in atmospheric models to eliminate spurious, unphysical noise that emerges from the way numerical methods represent the atmosphere.  This paper uses a theoretical analysis to compute the optimal amount of hyperdiffusion needed by atmospheric models using the spectral element...

Recent Publications

Atmospheric tracer transport is a computationally demanding component of the atmospheric dynamical core of weather and climate simulations. Simulations typically have tens to hundreds of tracers. A tracer field is required to preserve several properties, including mass, shape, and tracer...
This study quantifies the impact of the inclusion of realistic surface spectral emissivity in the Sahara and Sahel on the simulated local climate and beyond. The surface emissivity in these regions can be as low as 0.6-0.7 over the infrared window band while close to unity in other spectral bands,...
A collection of scientific analyses, metrics, and visualizations for robust validation of ice sheet models is presented using the Land Ice Verification and Validation toolkit (LIVVkit), version 2.1, and the LIVVkit Extensions repository (LEX), version 0.1. This software collection targets stand-...
We study the cloud response to a +4K surface warming in a new multiscale climate model that uses enough interior resolution to begin explicitly resolving boundary layer turbulence (i.e., ultraparameterization or UP). UP's predictions are compared against those from standard superparameterization (...
The Antarctic Ice Sheet (AIS) remains the largest uncertainty in projections of future sea level rise. A likely climate‐driven vulnerability of the AIS is thinning of floating ice shelves resulting from surface‐melt‐driven hydrofracture or incursion of relatively warm water into subshelf ocean...
The representation of nonlinear subgrid processes, especially clouds, has been a major source of uncertainty in climate models for decades. Cloud-resolving models better represent many of these processes and can now be run globally but only for short-term simulations of at most a few years because...
Dimethyl sulfide (DMS) is a significant source of marine sulfate aerosol and plays an important role in modifying cloud properties. Fully coupled climate simulations using dynamic marine ecosystem and DMS calculations are conducted to estimate DMS fluxes under various climate scenarios and to...
Even if anthropogenic warming were constrained to less than 2 °C above pre-industrial, the Greenland and Antarctic ice sheets will continue to lose mass this century, with rates similar to those observed over the past decade. However, nonlinear responses cannot be excluded, which may lead to larger...
We perform the first uncertainty quantification analysis of the turn-of-the-century drought in the Western United States using a large perturbed-parameter ensemble of the Community Atmosphere Model version 4.0 (CAM4). We develop several metrics to characterize the aridity bias, spatial extent and...
The spectral element method (SEM) is a mimetic finite element method with several properties that make it a desirable choice for numerical modeling. Although the linear dispersion properties of this method have been analyzed extensively for the case of the 1D inviscid advection equation, practical...

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