Matching Items (12)
Filtering by
- All Subjects: Climate Change
- Creators: Huang, Huei-Ping
- Resource Type: Text
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 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
Description
Mycorrhizal fungi form symbiotic relationships with plant roots, increasing nutrient and water availability to plants and improving soil stability. Mechanical disturbance of soil has been found to reduce mycorrhizal inoculum in soils, but findings have been inconsistent. To examine the impact of restoration practices on riparian mycorrhizal inoculum potential, soil samples were collected at the Tres Rios Ecosystem Restoration and Flood Control Project located at the confluence of the Salt, Gila, and Agua Fria rivers in central Arizona. The project involved the mechanical removal of invasive Tamarix spp.( tamarisk, salt cedar) and grading prior to revegetation. Soil samples were collected from three stages of restoration: pre-restoration, soil banks with chipped vegetation, and in areas that had been graded in preparation for revegetation. Bioassay plants were grown in the soil samples and roots analyzed for arbuscular mycorrhizal (AM) and ectomycorrhizal (EM) infection percentages. Vegetations measurements were also taken for woody vegetation at the site. The mean number of AM and EM fungal propagules did not differ between the three treatment area, but inoculum levels did differ between AM and EM fungi with AM fungal propagules detected at moderate levels and EM fungi at very low levels. These differences may have been related to availability of host plants since AM fungi form associations with a variety of desert riparian forbs and grasses and EM fungi only form associations with Populus spp. and Salix spp. which were present at the site but at low density and canopy cover. Prior studies have also found that EM fungi may be more affected by tamarisk invasions than AM fungi. Our results were similar to other restoration projects for AM fungi suggesting that it may not be necessary to add AM fungi to soil prior to planting native vegetation because of the moderate presence of AM fungi even in soils dominated by tamarisk and exposed to soil disturbance during the restoration process. In contrast when planting trees that form EM associations, it may be beneficial to augment soil with EM fungi collected from riparian areas or to pre-inoculate plants prior to planting.
ContributorsArnold, Susanne (Author) / Stutz, Jean (Thesis advisor) / Alford, Eddie (Committee member) / Green, Douglas (Committee member) / Arizona State University (Publisher)
Created2012
Description
The numerical climate models have provided scientists, policy makers and the general public, crucial information for climate projections since mid-20th century. An international effort to compare and validate the simulations of all major climate models is organized by the Coupled Model Intercomparison Project (CMIP), which has gone through several phases since 1995 with CMIP5 being the state of the art. In parallel, an organized effort to consolidate all observational data in the past century culminates in the creation of several "reanalysis" datasets that are considered the closest representation of the true observation. This study compared the climate variability and trend in the climate model simulations and observations on the timescales ranging from interannual to centennial. The analysis focused on the dynamic climate quantity of zonal-mean zonal wind and global atmospheric angular momentum (AAM), and incorporated multiple datasets from reanalysis and the most recent CMIP3 and CMIP5 archives. For the observation, the validation of AAM by the length-of-day (LOD) and the intercomparison of AAM revealed a good agreement among reanalyses on the interannual and the decadal-to-interdecadal timescales, respectively. But the most significant discrepancies among them are in the long-term mean and long-term trend. For the simulations, the CMIP5 models produced a significantly smaller bias and a narrower ensemble spread of the climatology and trend in the 20th century for AAM compared to CMIP3, while CMIP3 and CMIP5 simulations consistently produced a positive trend for the 20th and 21st century. Both CMIP3 and CMIP5 models produced a wide range of the magnitudes of decadal and interdecadal variability of wind component of AAM (MR) compared to observation. The ensemble means of CMIP3 and CMIP5 are not statistically distinguishable for either the 20th- or 21st-century runs. The in-house atmospheric general circulation model (AGCM) simulations forced by the sea surface temperature (SST) taken from the CMIP5 simulations as lower boundary conditions were carried out. The zonal wind and MR in the CMIP5 simulations are well simulated in the AGCM simulations. This confirmed SST as an important mediator in regulating the global atmospheric changes due to GHG effect.
ContributorsPaek, Houk (Author) / Huang, Huei-Ping (Thesis advisor) / Adrian, Ronald (Committee member) / Wang, Zhihua (Committee member) / Anderson, James (Committee member) / Herrmann, Marcus (Committee member) / Arizona State University (Publisher)
Created2013
Description
Ten regional climate models (RCMs) and atmosphere-ocean generalized model parings from the North America Regional Climate Change Assessment Program were used to estimate the shift of extreme precipitation due to climate change using present-day and future-day climate scenarios. RCMs emulate winter storms and one-day duration events at the sub-regional level. Annual maximum series were derived for each model pairing, each modeling period; and for annual and winter seasons. The reliability ensemble average (REA) method was used to qualify each RCM annual maximum series to reproduce historical records and approximate average predictions, because there are no future records. These series determined (a) shifts in extreme precipitation frequencies and magnitudes, and (b) shifts in parameters during modeling periods. The REA method demonstrated that the winter season had lower REA factors than the annual season. For the winter season the RCM pairing of the Hadley regional Model 3 and the Geophysical Fluid-Dynamics Laboratory atmospheric-land generalized model had the lowest REA factors. However, in replicating present-day climate, the pairing of the Abdus Salam International Center for Theoretical Physics' Regional Climate Model Version 3 with the Geophysical Fluid-Dynamics Laboratory atmospheric-land generalized model was superior. Shifts of extreme precipitation in the 24-hour event were measured using precipitation magnitude for each frequency in the annual maximum series, and the difference frequency curve in the generalized extreme-value-function parameters. The average trend of all RCM pairings implied no significant shift in the winter annual maximum series, however the REA-selected models showed an increase in annual-season precipitation extremes: 0.37 inches for the 100-year return period and for the winter season suggested approximately 0.57 inches for the same return period. Shifts of extreme precipitation were estimated using predictions 70 years into the future based on RCMs. Although these models do not provide climate information for the intervening 70 year period, the models provide an assertion on the behavior of future climate. The shift in extreme precipitation may be significant in the frequency distribution function, and will vary depending on each model-pairing condition. The proposed methodology addresses the many uncertainties associated with the current methodologies dealing with extreme precipitation.
ContributorsRiaño, Alejandro (Author) / Mays, Larry W. (Thesis advisor) / Vivoni, Enrique (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2013
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 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
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. 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.
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
Description
This study performs numerical modeling for the climate of semi-arid regions by running a high-resolution atmospheric model constrained by large-scale climatic boundary conditions, a practice commonly called climate downscaling. These investigations focus especially on precipitation and temperature, quantities that are critical to life in semi-arid regions. Using the Weather Research and Forecast (WRF) model, a non-hydrostatic geophysical fluid dynamical model with a full suite of physical parameterization, a series of numerical sensitivity experiments are conducted to test how the intensity and spatial/temporal distribution of precipitation change with grid resolution, time step size, the resolution of lower boundary topography and surface characteristics. Two regions, Arizona in U.S. and Aral Sea region in Central Asia, are chosen as the test-beds for the numerical experiments: The former for its complex terrain and the latter for the dramatic man-made changes in its lower boundary conditions (the shrinkage of Aral Sea). Sensitivity tests show that the parameterization schemes for rainfall are not resolution-independent, thus a refinement of resolution is no guarantee of a better result. But, simulations (at all resolutions) do capture the inter-annual variability of rainfall over Arizona. Nevertheless, temperature is simulated more accurately with refinement in resolution. Results show that both seasonal mean rainfall and frequency of extreme rainfall events increase with resolution. For Aral Sea, sensitivity tests indicate that while the shrinkage of Aral Sea has a dramatic impact on the precipitation over the confine of (former) Aral Sea itself, its effect on the precipitation over greater Central Asia is not necessarily greater than the inter-annual variability induced by the lateral boundary conditions in the model and large scale warming in the region. The numerical simulations in the study are cross validated with observations to address the realism of the regional climate model. The findings of this sensitivity study are useful for water resource management in semi-arid regions. Such high spatio-temporal resolution gridded-data can be used as an input for hydrological models for regions such as Arizona with complex terrain and sparse observations. Results from simulations of Aral Sea region are expected to contribute to ecosystems management for Central Asia.
ContributorsSharma, Ashish (Author) / Huang, Huei-Ping (Thesis advisor) / Adrian, Ronald (Committee member) / Herrmann, Marcus (Committee member) / Phelan, Patrick E. (Committee member) / Vivoni, Enrique (Committee member) / Arizona State University (Publisher)
Created2012
Description
Microarthropods play important roles in the decomposition process of the detrital food web, where they break down organic matter and return nutrients to the soil. However, only a small percentage of the belowground microarthropod population has been studied or even discovered, leading to a decrease in the knowledge of all of the processes carried out by these organisms and their importance to the soil. This is because microarthropod extraction methods are not 100% effective at collecting specimens. This study aimed to find an ideal quantitative procedure to better record the number of microarthropods existing in the soil and to determine if a seasonal variation exists that effects the success of extraction. Two extraction methods, including dynamic extraction and heptane flotation extraction, were compared across two seasons, a dry season (June) and a wet season (September). Average biomasses and average richness were calculated for four different functional groups, including Prostigmata, Mesostigmata, Cryptostigmata, and Collembola, across the two seasons, and statistical analysis was performed to determine if any differences that existed were statistically significant. Results indicate that the dynamic extraction method was significantly more effective for the collection of microarthropods during the wet season, and the heptane extraction method was significantly more effective during the dry season. In addition, the heptane procedure recovered samples of higher average richness than the dynamic method during both seasons. The heptane procedure works best for extraction during the dry season because it is able to collect organisms that entered into an ametabolic anhydrobiotic state to escape desiccation. These organisms form a protective lipid layer around their exoskeletons to retain water, and the non-polar exoskeletons display a chemical affinity to the heptane fluid, allowing for collection out of the soil and into the heptane layer. Despite these results, no one method is entirely superior to the other, and the most efficacious procedure depends on the researcher's aim of study.
ContributorsAntol, Rachel Lynn (Author) / Sabo, John L. (Thesis director) / Hall, Sharon (Committee member) / Wyant, Karl A. (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2014-12
Description
ABSTRACT The February 2008 study of a Snowflake, Arizona site measured changes in soil organic carbon, total nitrogen, extractable phosphorus, and soil moisture, to determine what affect One-seed Juniper (Juniperus monosperma) trees have on surrounding soil, thus affecting native grass growth. Increasing juniper densities in grasslands also decrease populations of some grassland bird species. Measurements were taken each meter along a twelve meter line transect, moving from juniper trees, through a bare soil area and into a grassland. Non-linear relationships were examined, in regard to distance from the tree and juniper root mass. Relationships were examined to determine any affect of the juniper tree on soil characteristics along the transect. Organic carbon decreased as distance increased from the trees (F=4.25, df=46, p=0.020). Soil moisture increased with distance from the trees (F=5.42, df=46, p=0.008), and juniper root mass, of roots less than 1 mm diameter, significantly decreased with distance away from the trees (F=11.29, df=46, p=0.0001). Total nitrogen and extractable phosphorus did not significantly change with distance from the tree, or presence of juniper roots. This data is important as grassland restoration projects rely on the availability of soil nutrients and water for reestablishment of native grass species.
ContributorsWeller, Christopher (Author) / Green, Douglas (Thesis advisor) / Miller, William H. (Committee member) / Alford, Edward (Committee member) / Arizona State University (Publisher)
Created2010
Description
The species distribution model DISTRIB was used to model and map potential suitable habitat of ponderosa pine throughout Arizona under current and six future climate scenarios. Importance Values for each climate scenario were estimated from 24 predictor variables consisting of climate, elevation, soil, and vegetation data within a 4 km grid cell. Two emission scenarios, (A2 (high concentration) and B1 (low concentration)) and three climate models (the Parallel Climate Model, the Geophysical Fluid Dynamics Laboratory, and the HadleyCM3) were used to capture the potential variability among future climates and provide a range of responses from ponderosa pine. Summary tables for federal and state managed lands show the potential change in suitable habitat under the different climate scenarios; while an analysis of three elevational regions explores the potential shift of habitat upslope. According to the climate scenarios, mean annual temperature in Arizona could increase by 3.5% while annual precipitation could decrease by 36% over this century. Results of the DISTRIB model indicate that in response to the projected changes in climate, suitable habitat for ponderosa pine could increase by 13% throughout the state under the HadleyCM3 high scenario or lose 1.1% under the average of the three low scenarios. However, the spatial variability of climate changes will result in gains and losses among the ecoregions and federally and state managed lands. Therefore, alternative practices may need to be considered to limit the loss of suitable habitat in areas identified by the models.
ContributorsPeters, Matthew P. (Author) / Brady, Ward W (Thesis advisor) / Green, Douglas (Committee member) / Tridane, Abdessamad (Committee member) / Arizona State University (Publisher)
Created2011