Atmospheric Modeling for Modern Wind Energy and Fire Applications

Redfern, Stephanie

Graduate Thesis Or Dissertation

Atmospheric Modeling for Modern Wind Energy and Fire Applications 公开 Deposited

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Citeable URL: https://scholar.colorado.edu/concern/graduate_thesis_or_dissertations/s1784m844

Abstract

Climate change is rapidly becoming an increasingly dangerous threat. As average global temperatures have risen, extreme weather events have increased in frequency and expanded in intensity. More violent forest fires and more powerful storms have begun to take place. In this dissertation, we explore several ways that models can assist with climate change mitigation and adaptation efforts.

First, we explore the prospective benefit of changing the physics of the wind farm parameterization in the Weather Research and Forecasting Model (WRF). As the world shifts to renewable energy sources to try and reduce and offset carbon emissions, it has become all the more important to accurately forecast wind power production, to maintain grid stability and ensure accurate day-ahead scheduling for utilities. We find that using the rotor-equivalent wind speed (REWS) in lieu of the hub height wind speed for making wind power forecasts can be beneficial in some situations.

The next study changes focus from wind energy forecasting to fire modeling. As fires have become more intense in recent years, their potential for upper tropospheric and lower stratospheric (UTLS) smoke injection has increased. More frequent UTLS aerosol anomalies could have widespread climatic impacts that must be understood. Additionally, with the renewed threat of nuclear war, it has become all the more important to best quantify smoke lofting from fires ignited by weapons detonation. Here, we conduct a sensitivity study focused on plume rise response to local atmospheric conditions. We find that relative humidity plays a crucial role in enhancing lofting, while higher wind speeds have the opposite effect by dampening smoke ascent.

The final section focuses on the challenges of accurately forecasting pyrocumulus (pyroCu) and pyrocumulonimbus (pyroCb) in fire models. PyroCb can generate deep convection, thereby injecting fire combustion aerosols into the UTLS. PyroCb can also produce lightning, which can then spark further ignitions. It is therefore important that these events are correctly represented in models. We compare simulations of a 2014 California fire that use different microphysics schema--one without any aerosol coupling, and two with different coupling mechanisms. We find that including aerosol-cloud interactions changes the nature of cloud and precipitation formation and requires further research for us to develop a better understanding of its implications for fire forecasting.

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