Wally Erickson and Dr. Trent McDonald will provide an overview of the state of science relative to wind and solar energy direct and indirect impacts on wildlife. A large amount of data has been collected to understand bird and bat mortality impacts from wind energy, while there is limited data available for characterizing these impacts for solar energy.
Large-scale implementation of conservation practices and alternative practices (e.g., bioenergy landscapes) that effectively prevent excess nutrients from entering downstream waterways while maintaining productive agriculture is critical for managing water quality. Dr. Christopher will discuss a project in which she evaluated implementation of inset floodplains ("two-stage ditch") in formerly channelized waterways in the River Raisin Watershed (RRW), a major subbasin in the Wester Lake Erie Basin.
This talk presents an approach to integrate physical and statistical models to estimate extreme storm surge. Specifically, a physically-based hydrodynamics model is used to provide the needed interpolation in space and extrapolation in both time and atmospheric conditions. Statistical modeling is needed to 1) estimate the input distribution for running the computer model, 2) develop a statistical emulator in place of the computer simulator, and 3) quantify estimate uncertainty due to input distribution, statistical emulator, missing/unresolved physics.
Every commercial energy technology depends on at least two materials or processes that provide the available energy for driving useful work. These two sides of the equation typically involve renewable and non-renewable components. In this seminar, a novel framework is proposed for categorizing the renewability of commercial energy systems. This framework will be presented, with application to vehicle transportation technologies.
In the first part of the talk, an overview of the regional climate modeling will be given, and cutting-edge modeling methods will be introduced including traditional dynamical downscaling models and variable-resolution options. With a well-developed modeling framework, a case study will be discussed in the second part of the talk, focusing on the most extreme wet year (i.e., 2016-2017) of the historical record since 1895 over California, after an extraordinary long-term drought.
Inspired by early convection-tank experiments (e.g., Deardorff and Willis) and diffusion-chamber experiments, Michigan Tech has developed a cloud chamber that operates on the principle of isobaric mixing within turbulent Rayleigh-Bénard convection. The “Pi cloud chamber” at Michigan Tech has been online for five years and has been used for studies of atmospheric aerosol and cloud processes.
Dr. Yeo will present a deep learning model (DE-LSTM) for the simulation of a stochastic process with an underlying nonlinear dynamics. The deep learning model aims to identify the probability density function of a stochastic process via numerical discretization and the underlying nonlinear dynamics is modeled by the Long Short-Term Memory (LSTM) network.
Mr. Conboy will provide an overview of the Formerly Utilized Sites Remedial Action Program (FUSRAP) and discuss innovative means and methods that have been used to effectively and efficiently determine the nature and extent of the contamination as remediation alternatives are developed in accordance with Comprehensive Environmental Response Compensation and Liability Act (CERCLA) requirements.
Recent developments into a global 2D storm tide modeling system (ADCIRC-based model) show that the fluctuations in the mean sea level can be reasonably accounted for by dynamically incorporating the internal density structure from an ocean general circulation model, which has coarse coastal resolution. Moreover, Dr. Pringle will show that this approach improves coastal sea level fluctuations across a broad frequency spectrum compared to the barotropic storm tide model.
Despite their climatic importance, multi-scale models continue to have persistent biases produced by insufficient representation of convective clouds. To increase our understanding of convective cloud lifecycles and aerosol-convection interactions, the TRacking Aerosol Convection interactions ExpeRiment (TRACER) will take place in the Houson, TX region from April 2021 through April 2022 with an intensive observation period from June to September 2022.
In this presentation, Dr. Bajgain will focus on quantifying biophysical and biogeochemical feedbacks of ecosystems to climate and management variability using field observations (eddy covariance and automated chamber), remote sensing data, and process-based modeling approaches.