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Description
The implications of a changing climate have a profound impact on human life, society, and policy making. The need for accurate climate prediction becomes increasingly important as we better understand these implications. Currently, the most widely used climate prediction relies on the synthesis of climate model simulations organized by the

The implications of a changing climate have a profound impact on human life, society, and policy making. The need for accurate climate prediction becomes increasingly important as we better understand these implications. Currently, the most widely used climate prediction relies on the synthesis of climate model simulations organized by the Coupled Model Intercomparison Project (CMIP); these simulations are ensemble-averaged to construct projections for the 21st century climate. However, a significant degree of bias and variability in the model simulations for the 20th century climate is well-known at both global and regional scales. Based on that insight, this study provides an alternative approach for constructing climate projections that incorporates knowledge of model bias. This approach is demonstrated to be a viable alternative which can be easily implemented by water resource managers for potentially more accurate projections. Tests of the new approach are provided on a global scale with an emphasis on semiarid regional studies for their particular vulnerability to water resource changes, using both the former CMIP Phase 3 (CMIP3) and current Phase 5 (CMIP5) model archives. This investigation is accompanied by a detailed analysis of the dynamical processes and water budget to understand the behaviors and sources of model biases. Sensitivity studies of selected CMIP5 models are also performed with an atmospheric component model by testing the relationship between climate change forcings and model simulated response. The information derived from each study is used to determine the progressive quality of coupled climate models in simulating the global water cycle by rigorously investigating sources of model bias related to the moisture budget. As such, the conclusions of this project are highly relevant to model development and potentially may be used to further improve climate projections.
ContributorsBaker, Noel C (Author) / Huang, Huei-Ping (Thesis advisor) / Trimble, Steve (Committee member) / Anderson, James (Committee member) / Clarke, Amanda (Committee member) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Modern day gas turbine designers face the problem of hot mainstream gas ingestion into rotor-stator disk cavities. To counter this ingestion, seals are installed on the rotor and stator disk rims and purge air, bled off from the compressor, is injected into the cavities. It is desirable to reduce the

Modern day gas turbine designers face the problem of hot mainstream gas ingestion into rotor-stator disk cavities. To counter this ingestion, seals are installed on the rotor and stator disk rims and purge air, bled off from the compressor, is injected into the cavities. It is desirable to reduce the supply of purge air as this decreases the net power output as well as efficiency of the gas turbine. Since the purge air influences the disk cavity flow field and effectively the amount of ingestion, the aim of this work was to study the cavity velocity field experimentally using Particle Image Velocimetry (PIV). Experiments were carried out in a model single-stage axial flow turbine set-up that featured blades as well as vanes, with purge air supplied at the hub of the rotor-stator disk cavity. Along with the rotor and stator rim seals, an inner labyrinth seal was provided which split the disk cavity into a rim cavity and an inner cavity. First, static gage pressure distribution was measured to ensure that nominally steady flow conditions had been achieved. The PIV experiments were then performed to map the velocity field on the radial-tangential plane within the rim cavity at four axial locations. Instantaneous velocity maps obtained by PIV were analyzed sector-by-sector to understand the rim cavity flow field. It was observed that the tangential velocity dominated the cavity flow at low purge air flow rate, its dominance decreasing with increase in the purge air flow rate. Radially inboard of the rim cavity, negative radial velocity near the stator surface and positive radial velocity near the rotor surface indicated the presence of a recirculation region in the cavity whose radial extent increased with increase in the purge air flow rate. Qualitative flow streamline patterns are plotted within the rim cavity for different experimental conditions by combining the PIV map information with ingestion measurements within the cavity as reported in Thiagarajan (2013).
ContributorsPathak, Parag (Author) / Roy, Ramendra P (Thesis advisor) / Calhoun, Ronald (Committee member) / Lee, Taewoo (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Climate change has been one of the major issues of global economic and social concerns in the past decade. To quantitatively predict global climate change, the Intergovernmental Panel on Climate Change (IPCC) of the United Nations have organized a multi-national effort to use global atmosphere-ocean models to project anthropogenically induced

Climate change has been one of the major issues of global economic and social concerns in the past decade. To quantitatively predict global climate change, the Intergovernmental Panel on Climate Change (IPCC) of the United Nations have organized a multi-national effort to use global atmosphere-ocean models to project anthropogenically induced climate changes in the 21st century. The computer simulations performed with those models and archived by the Coupled Model Intercomparison Project - Phase 5 (CMIP5) form the most comprehensive quantitative basis for the prediction of global environmental changes on decadal-to-centennial time scales. While the CMIP5 archives have been widely used for policy making, the inherent biases in the models have not been systematically examined. The main objective of this study is to validate the CMIP5 simulations of the 20th century climate with observations to quantify the biases and uncertainties in state-of-the-art climate models. Specifically, this work focuses on three major features in the atmosphere: the jet streams over the North Pacific and Atlantic Oceans and the low level jet (LLJ) stream over central North America which affects the weather in the United States, and the near-surface wind field over North America which is relevant to energy applications. The errors in the model simulations of those features are systematically quantified and the uncertainties in future predictions are assessed for stakeholders to use in climate applications. Additional atmospheric model simulations are performed to determine the sources of the errors in climate models. The results reject a popular idea that the errors in the sea surface temperature due to an inaccurate ocean circulation contributes to the errors in major atmospheric jet streams.
ContributorsKulkarni, Sujay (Author) / Huang, Huei-Ping (Thesis advisor) / Calhoun, Ronald (Committee member) / Peet, Yulia (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Due to decrease in fossil fuel levels, the world is shifting focus towards renewable sources of energy. With an annual average growth rate of 25%, wind is one of the foremost source of harnessing cleaner energy for production of electricity. Wind turbines have been developed to tap power from wind.

Due to decrease in fossil fuel levels, the world is shifting focus towards renewable sources of energy. With an annual average growth rate of 25%, wind is one of the foremost source of harnessing cleaner energy for production of electricity. Wind turbines have been developed to tap power from wind. As a single wind turbine is insufficient, multiple turbines are installed forming a wind farm. Generally, wind farms can have hundreds to thousands of turbines concentrated in a small region. There have been multiple studies centering the influence of weather on such wind farms, but no substantial research focused on how wind farms effect local climate. Technological advances have allowed development of commercial wind turbines with a power output greater than 7.58 MW. This has led to a reduction in required number of turbines and has optimized land usage. Hence, current research considers higher power density compared to previous works that relied on wind farm density of 2 to 4 W/m 2 . Simulations were performed using Weather Research and Forecasting software provided by NCAR. The region of simulation is Southern Oregon, with domains including both onshore and offshore wind farms. Unlike most previous works, where wind farms were considered to be on a flat ground, effects of topography have also been considered here. Study of seasonal effects over wind farms has provided better insight into changes in local wind direction. Analysis of mean velocity difference across wind farms at a height of 10m and 150m gives an understanding of wind velocity profiles. Results presented in this research tends to contradict earlier belief that velocity reduces throughout the farm. Large scale simulations have shown that sometimes, more than 50% of the farm can have an increased wind velocity of up to 1m/s

at an altitude of 10m.
ContributorsKadiyala, Yogesh Rao (Author) / Huang, Huei-Ping (Thesis advisor) / Rajagopalan, Jagannathan (Committee member) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2015
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Description
This research work uses the Weather Research and Forecasting Model to study the effect of large wind farms with an area of 900 square kilometers and a high power density of 7.58 W/m2 on regional climate. Simulations were performed with a wind farm parameterization scheme turned on in south Oregon.

This research work uses the Weather Research and Forecasting Model to study the effect of large wind farms with an area of 900 square kilometers and a high power density of 7.58 W/m2 on regional climate. Simulations were performed with a wind farm parameterization scheme turned on in south Oregon. Control cases were also run with the parameterization scheme turned off. The primary emphasis was on offshore wind farms. Some analysis on onshore wind farms was also performed. The effects of these wind farms were studied on the vertical profiles of temperature, wind speed, and moisture as well as on temperature and on wind speed near the surface and at hub height. The effects during the day and at night were compared. Seasonal variations were also studied by performing simulations in January and in July. It was seen that wind farms produce a reduction in wind speed at hub height and that the downward propagation of this reduction in wind speed lessens as the atmosphere becomes more stable. In all the cases studied, the wind farms produced a warming effect near the surface, with greater atmospheric stability leading to higher near-surface temperatures. It was also observed that wind farms caused a drying effect below the hub height and a moistening effect above it, because they had facilitated vertical transport of moisture in the air from the lower layers of the atmosphere to the layers of the atmosphere above the wind farm.
ContributorsGeorge, Sushant (Author) / Huang, Huei-Ping (Thesis advisor) / Wang, Zhihua (Committee member) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2016
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Description
This study uses the Weather Research and Forecasting (WRF) model to simulate and predict the changes in local climate attributed to the urbanization for five desert cities. The simulations are performed in the fashion of climate downscaling, constrained by the surface boundary conditions generated from high resolution land-use maps. For

This study uses the Weather Research and Forecasting (WRF) model to simulate and predict the changes in local climate attributed to the urbanization for five desert cities. The simulations are performed in the fashion of climate downscaling, constrained by the surface boundary conditions generated from high resolution land-use maps. For each city, the land-use maps of 1985 and 2010 from Landsat satellite observation, and a projected land-use map for 2030, are used to represent the past, present, and future. An additional set of simulations for Las Vegas, the largest of the five cities, uses the NLCD 1992 and 2006 land-use maps and an idealized historical land-use map with no urban coverage for 1900.

The study finds that urbanization in Las Vegas produces a classic urban heat island (UHI) at night but a minor cooling during the day. A further analysis of the surface energy balance shows that the decrease in surface Albedo and increase effective emissivity play an important role in shaping the local climate change over urban areas. The emerging urban structures slow down the diurnal wind circulation over the city due to an increased effective surface roughness. This leads to a secondary modification of temperature due to the interaction between the mechanical and thermodynamic effects of urbanization.

The simulations for the five desert cities for 1985 and 2010 further confirm a common pattern of the climatic effect of urbanization with significant nighttime warming and moderate daytime cooling. This effect is confined to the urban area and is not sensitive to the size of the city or the detail of land cover in the surrounding areas. The pattern of nighttime warming and daytime cooling remains robust in the simulations for the future climate of the five cities using the projected 2030 land-use maps. Inter-city differences among the five urban areas are discussed.
ContributorsKamal, Samy (Author) / Huang, Huei-Ping (Thesis advisor) / Anderson, James (Thesis advisor) / Herrmann, Marcus (Committee member) / Calhoun, Ronald (Committee member) / Myint, Soe (Committee member) / Arizona State University (Publisher)
Created2015