Environmental Science Division (EVS)a Division of Argonne National Laboratory

Events

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Past Events

 
NOVEMBER 14, 2017

This presentation will provide an overview of storm surge modeling followed by results for the 2017 Atlantic hurricane season. This talk will also present results of an impact assessment of climate change on coastal hazards in the Northwest Pacific Ocean, based on ensemble atmospheric downscaling experiments for Haiyan-like super storms in the Philippines.

 
OCTOBER 27, 2017

Society is demanding more sustainable bioenergy and agricultural systems, but farmers who could provide both do not have sufficient information to confidently change from the status quo. This seminar will present results of novel modelling assessments that indicate the agriculturally dominate state of Iowa, USA, could achieve nearly half of state water quality improvement targets simply by converting highly unprofitable parts of corn/soybean fields to switchgrass (Panicum virgatum L.) using a precision conservation approach.

 
OCTOBER 23, 2017

The adjoint of a numerical weather prediction model, computed as the transpose of the tangent linear approximation to the fully nonlinear model, computes the sensitivity of some aspect of the final forecast state to changes to the model state at earlier times. The adjoint is best known as an integral part of 4-dimensional variational data assimilation (4DVAR).

 
SEPTEMBER 25, 2017

Satellite observations of cloudy hurricane canopies have shown a universal, daily, wave-like feature that propagates radially outward, as far as 600 km. Daytime solar heating of a hurricane's upper eyewall is surely responsible, but the mechanism for the wave was previously unknown. This seminar will discuss numerical experiments that suggest these waves are internal inertia-gravity waves, and in fact propagate through (almost!) the entire depth of the hurricane.

 
SEPTEMBER 18, 2017

This presentation will summarize results of two studies that combined long term field observation data with simulation and geospatial models to study the role of conservation agriculture to mitigate land use change emissions.

 
AUGUST 22, 2017

Aerosol radiative properties depend on the size and chemical composition of individual particles, but particle-level characteristics are not fully resolved in global-scale models. This talk will describe two different particle-based methods for advancing aerosol representations in large-scale models.

 
AUGUST 14, 2017

Incomplete knowledge of both greenhouse gas (GHG) sources and sinks, and atmospheric transport of these gases limits our ability to use atmospheric observations to infer surface fluxes. For instance, detailed understanding of the impact of frontal systems on the spatiotemporal variability of GHGs on regional scales is needed for the evaluation of transport models and for improving knowledge of GHG sources and sinks. This seminar will report on the frontal gradient features in GHGs based on 12 selected research flights.

 
AUGUST 10, 2017

Physics-based mathematical-computational models provide an invaluable tool for repository design, performance/safety assessments, site clean-up, and environmental remediation in nuclear spent fuel and high level waste disposal in shallow or deep geological media. The migration of nuclear wastes is controlled by coupled THMC (Thermal-Hydrology-Mechanics-Chemical) processes. This talk presents the development of a series of computational models that fully or partially couple these processes.

 
JULY 25, 2017

Aerosol-climate interactions are the leading uncertainty in understanding anthropogenic climate forcing, and aerosol particles negatively impact human and ecosystem health. Ground- and satellite-based remote sensing measurements are used to quantify the spatiotemporal coherence of mean and extreme aerosol properties, and identify the drivers of the observed aerosol variability.

 
JUNE 27, 2017

In this talk, Frank Giraldo will describe the GNuMe framework that he has been using to develop and test geophysical fluid dynamics models. GNuMe is, in essence, a modeling environment that contains local element-based numerical discretization methods (spectral elements and discontinuous Galerkin methods), as well as a suite of time-integrators (explicit, fully-implicit, and implicit-explicit methods).