Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2009. / Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3378. Adviser: Atul Jain. Includes bibliographical references (leaves 137-150) Available on microfilm from Pro Quest Information and Learning.

<p> In this study, the Weather Research and Forecasting Model (WRF) is coupled with the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA), a high complexity land surface model (LSM). Although WRF is a state-of-the-art regional atmospheric model with high spatial and temporal resolutions, the land surface schemes available in WRF are simple and lack the capability to simulate carbon dioxide, for example, the popular NOAH LSM. ACASA is a complex multilayer land surface model with interactive canopy physiology and full surface hydrological processes. It allows microenvironmental variables such as air and surface temperatures, wind speed, humidity, and carbon dioxide concentration to vary vertically. </p><p> Simulations of surface conditions as well as reference and actual evapotranspiration from WRF-ACASA and WRF-NOAH are compared with surface observations for year 2005 and 2006. Results show that the increase in complexity in the WRF-ACASA model not only maintains model accuracy, it also properly accounts for the dominant biological and physical processes describing ecosystem-atmosphere interactions that are scientifically valuable. The different complexities of physical and physiological processes in the WRF-ACASA and WRF-NOAH models also highlight the impacts of different land surface and model components on atmospheric and surface conditions. </p><p> Lastly, unlike the simple big-leaf WRF-NOAH model with no carbon dioxide simulation, the high complexity WRF-ACASA model is used to quantify the carbon dioxide exchange between the biosphere and atmosphere and to examine the importance of atmospheric carbon dioxide concentration on surface processes on a regional scale. A new carbon dioxide (COCO₂) tracer is introduced into the WRF-ACASA coupled model to allow atmospheric CO₂ concentration to vary spatially and temporally according to surface plant physiological processes. The comparison between the two model simulations with and without a COCO₂ tracer shows that the impact of atmospheric COCO₂ concentration and transportation are important, and therefore these should not be neglected when simulating COCO₂ flux at regional scales. Overall, this study shows that the high complexity WRF-ACASA model is robust and able to simulate the surface conditions and COCO₂ fluxes well across the region, particularly when given accurate surface representations. </p>

Thesis (Ph. D.)--University of Illinois at Urbana-Champaign, 2007. / Source: Dissertation Abstracts International, Volume: 68-07, Section: B, page: 4335. Adviser: Atul K. Jain. Includes bibliographical references (leaves 133-154). Available on microfilm from Pro Quest Information and Learning.