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- Creators: Arizona State University
Description
The characteristics of the wintertime 500hPa height surface, the level of non-divergence and used for identifying/observing synoptic-scale features (ridges and troughs), and their impact on precipitation are of significance to forecasters, natural resource managers and planners across the southwestern United States. For this study, I evaluated the location of the 500hPa mean Pacific ridge axis over the winter for the period of 1948/49 to 2011/12 and derived the mean ridge axis in terms of location (longitude) and intensity (geopotential meters) from the NCEP/NCAR Reanalysis dataset. After deriving a mean ridge axis climatology and analyzing its behavior over time, I correlated mean location and intensity values to observed wintertime precipitation in select U.S. Climate Divisions in Arizona, Colorado, Nevada, Utah and New Mexico. This resulted in two findings. First specific to the 500hPa ridge behavior, the ridge has been moving eastward and also has been intensifying through time. Second, results involving correlation tests between mean ridge location and intensity indicate precipitation across the selected Southwest Climate Divisions are strongly related to mean ridge intensity slightly more than ridge location. The relationships between mean ridge axis and observed precipitation also are negative, indicating an increase of one of the ridge parameters (i.e. continued eastward movement or intensification) lead to drier winter seasons across the Southwest. Increased understanding of relationships between upper-level ridging and observed wintertime precipitation aids in natural resource planning for an already arid region that relies heavily on winter precipitation.
ContributorsNolte, Jessica Marie (Author) / Cerveny, Randall S. (Thesis advisor) / Selover, Nancy J. (Committee member) / Brazel, Anthony J. (Committee member) / Arizona State University (Publisher)
Created2013
Description
This thesis outlines the development of a vector retrieval technique, based on data assimilation, for a coherent Doppler LIDAR (Light Detection and Ranging). A detailed analysis of the Optimal Interpolation (OI) technique for vector retrieval is presented. Through several modifications to the OI technique, it is shown that the modified technique results in significant improvement in velocity retrieval accuracy. These modifications include changes to innovation covariance portioning, covariance binning, and analysis increment calculation. It is observed that the modified technique is able to make retrievals with better accuracy, preserves local information better, and compares well with tower measurements. In order to study the error of representativeness and vector retrieval error, a lidar simulator was constructed. Using the lidar simulator a thorough sensitivity analysis of the lidar measurement process and vector retrieval is carried out. The error of representativeness as a function of scales of motion and sensitivity of vector retrieval to look angle is quantified. Using the modified OI technique, study of nocturnal flow in Owens' Valley, CA was carried out to identify and understand uncharacteristic events on the night of March 27th 2006. Observations from 1030 UTC to 1230 UTC (0230 hr local time to 0430 hr local time) on March 27 2006 are presented. Lidar observations show complex and uncharacteristic flows such as sudden bursts of westerly cross-valley wind mixing with the dominant up-valley wind. Model results from Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS®) and other in-situ instrumentations are used to corroborate and complement these observations. The modified OI technique is used to identify uncharacteristic and extreme flow events at a wind development site. Estimates of turbulence and shear from this technique are compared to tower measurements. A formulation for equivalent wind speed in the presence of variations in wind speed and direction, combined with shear is developed and used to determine wind energy content in presence of turbulence.
ContributorsChoukulkar, Aditya (Author) / Calhoun, Ronald (Thesis advisor) / Mahalov, Alex (Committee member) / Kostelich, Eric (Committee member) / Huang, Huei-Ping (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2013
Description
Conformance of a manufactured feature to the applied geometric tolerances is done by analyzing the point cloud that is measured on the feature. To that end, a geometric feature is fitted to the point cloud and the results are assessed to see whether the fitted feature lies within the specified tolerance limits or not. Coordinate Measuring Machines (CMMs) use feature fitting algorithms that incorporate least square estimates as a basis for obtaining minimum, maximum, and zone fits. However, a comprehensive set of algorithms addressing the fitting procedure (all datums, targets) for every tolerance class is not available. Therefore, a Library of algorithms is developed to aid the process of feature fitting, and tolerance verification. This paper addresses linear, planar, circular, and cylindrical features only. This set of algorithms described conforms to the international Standards for GD&T.; In order to reduce the number of points to be analyzed, and to identify the possible candidate points for linear, circular and planar features, 2D and 3D convex hulls are used. For minimum, maximum, and Chebyshev cylinders, geometric search algorithms are used. Algorithms are divided into three major categories: least square, unconstrained, and constrained fits. Primary datums require one sided unconstrained fits for their verification. Secondary datums require one sided constrained fits for their verification. For size and other tolerance verifications, we require both unconstrained and constrained fits
ContributorsMohan, Prashant (Author) / Shah, Jami (Thesis advisor) / Davidson, Joseph K. (Committee member) / Farin, Gerald (Committee member) / Arizona State University (Publisher)
Created2014
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
The North American Monsoon System (NAMS) contributes ~55% of the annual rainfall in the Chihuahuan Desert during the summer months. Relatively frequent, intense storms during the NAMS increase soil moisture, reduce surface temperature and lead to runoff in ephemeral channels. Quantifying these processes, however, is difficult due to the sparse nature of coordinated observations. In this study, I present results from a field network of rain gauges (n = 5), soil probes (n = 48), channel flumes (n = 4), and meteorological equipment in a small desert shrubland watershed (~0.05 km2) in the Jornada Experimental. Using this high-resolution network, I characterize the temporal and spatial variability of rainfall, soil conditions and channel runoff within the watershed from June 2010 to September 2011, covering two NAMS periods. In addition, CO2, water and energy measurements at an eddy covariance tower quantify seasonal, monthly and event-scale changes in land-atmosphere states and fluxes. Results from this study indicate a strong seasonality in water and energy fluxes, with a reduction in Bowen ratio (B, the ratio of sensible to latent heat fluxes) from winter (B = 14) to summer (B = 3.3). This reduction is tied to shallow soil moisture availability during the summer (s = 0.040 m3/m3) as compared to the winter (s = 0.004 m3/m3). During the NAMS, I analyzed four consecutive rainfall-runoff events to quantify the soil moisture and channel flow responses and how water availability impacted the land-atmosphere fluxes. Spatial hydrologic variations during events occur over distances as short as ~15 m. The field network also allowed comparisons of several approaches to estimate evapotranspiration (ET). I found a more accurate ET estimate (a reduction of mean absolute error by 38%) when using distributed soil moisture data, as compared to a standard water balance approach based on the tower site. In addition, use of spatially-varied soil moisture data yielded a more reasonable relationship between ET and soil moisture, an important parameterization in many hydrologic models. The analyses illustrates the value of high-resolution sampling for quantifying seasonal fluxes in desert shrublands and their improvements in closing the water balance in small watersheds.
ContributorsTempleton, Ryan (Author) / Vivoni, Enrique R (Thesis advisor) / Mays, Larry (Committee member) / Fox, Peter (Committee member) / Arizona State University (Publisher)
Created2011
Description
Isentropic analysis is a type of analysis that is based on using the concept of potential temperatures, the adiabatically established temperature at 1000 hPa. In the 1930s and 1940s this type of analysis proved to be valuable in indicating areas of increased moisture content and locations experiencing flow up or down adiabatic surfaces. However, in the early 1950s, this type of analysis faded out of use and not until the twenty-first century have some researchers started once again to examine the usefulness of isentropic analysis. One aspect in which isentropic analysis could be practical, based on prior research, is in severe weather situations, due to its ability to easily show adiabatic motion and moisture. As a result, I analyzed monthly climatological isentropic surfaces to identify distinct patterns associated with tornado occurrences for specific regions and months across the contiguous United States. I collected tornado reports from 1974 through 2009 to create tornado regions for each month across the contiguous United States and corresponding upper air data for the same time period. I then separated these upper air data into tornado and non-tornado days for specific regions and conducted synoptic and statistical analyses to establish differences between the two. Finally, I compared those results with analyses of individual case studies for each defined region using independent data from 2009 through 2010. On tornado days distinct patterns can be identified on the isentropic surface: (1) the average isentropic surface lowered on tornado days indicating a trough across the region, (2) a corresponding increase in moisture content occurred across the tornado region, and (3) wind shifted in such a manner to produce flow up the isentropic trough indicating uplift. When comparing the climatological results with the case studies, the isentropic pattern for the case studies in general was more pronounced compared to the climatological pattern; however, this would be expected as when creating the average the pattern/conditions will be smoothed. These findings begin to bridge the large gap in literature, show the usefulness of isentropic analysis in monthly and daily use and serve as catalysts to create a finer resolution database in isentropic coordinates.
ContributorsPace, Matthew Brandon (Author) / Cerveny, Randall S. (Thesis advisor) / Selover, Nancy J (Committee member) / Brazel, Anthony J. (Committee member) / Arizona State University (Publisher)
Created2012
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
This study considered the impact of grid resolution on wind velocity simulated by the Weather Research and Forecasting (WRF) model. The period simulated spanned November 2009 through January 2010, for which, multi-resolution nested domains were examined. Basic analysis was performed utilizing the data assimilation tools of NCEP/NCAR (National Center for Environmental Prediction/National Center for Atmospheric Research) to determine the ideal location to examine during the simulation was the Pacific Northwest portion of the United States, specifically the border between California and Oregon. The simulated mutli-resolution nested domains in this region indicated an increase in apparent wind speed as the resolution for the domain was increased. These findings were confirmed by statistical analysis which identified a positive bias for wind speed with respect to increased resolution as well as a correlation coefficient indicating the existence of a positive change in wind speed with increased resolution. An analysis of temperature change was performed in order to test the validity of the findings of the WRF simulation model. The statistical analysis performed on temperature change throughout the increased grid resolution did not indicate any change in temperature. In fact the correlation coefficient values between the domains were found in the 0.90 range, indicating the non-sensitivity of temperature across the increased resolutions. These results validate the findings of the WRF simulation: increased wind velocity can be observed at higher grid resolution. The study then considered the difference between wind velocity observed over the entire domains and the wind velocity observed solely over offshore locations. Wind velocity was observed to be significantly higher (an increase of 68.4%) in the offshore locations. The findings of this study suggest simulation tools should be utilized to examine domains at a higher resolution in order to identify potential locations for wind farms. The results go further to suggest the ideal location for these potential wind farms will be at offshore locations.
ContributorsBouey, Michael (Author) / Huang, Huei-Ping (Thesis advisor) / Trimble, Steve (Committee member) / Ronald, Ronald (Committee member) / Arizona State University (Publisher)
Created2012
Description
Severe weather affects many regions of the United States, and has potential to greatly impact many facets of society. This study provides a climatological spatial analysis by county of severe weather warnings issued by the National Weather Service (NWS) between January 1st, 1986 to December 31st, 2017 for the contiguous United States. The severe weather warnings were issued for county-based flash flood, severe thunderstorm, and tornado phenomena issued through the study period and region. Post 2002 severe weather warnings issued by storm warning area were included in this study in the form of county-based warnings simultaneously issued for each affected county. Past studies have researched severe weather warnings issued by the NWS, however these studies are limited in geographic representation, study period, and focused on population bias. A spatial analysis of severe weather warning occurrences by county identify that (a) highest occurrences of flash flood warnings are located in the desert Southwest and Texas, (b) severe thunderstorm warning occurrence is more frequent in Arizona, portions of the Midwest, the South, and the Mid and South Atlantic states, (c) the tornado activity regions of Tornado Alley and Dixie Alley (i.e. Colorado, Kansas, Oklahoma, Arkansas, Texas, Louisiana, Mississippi, Alabama, Tennessee, and Illinois) contained the highest occurrences of tornado warnings, and (d) the highest instances of aggregate warning occurrences are found in the desert Southwest, the Midwest, and the Southern regions of the United States. Generally, severe weather warning “hot spots” tend to be located in those same regions, with greater coverage. This study concludes with a comparison of local maxima and general hot spot regions to expected regions for each phenomenon. Implications of this study are far reaching, including emergency management, and has potential to reduce risk of life.
ContributorsLawhorn, Brandon (Author) / Cerveny, Randall S. (Thesis advisor) / Balling, Robert C. (Committee member) / Vose, Russel S (Committee member) / Krahenbuhl, Daniel (Committee member) / Arizona State University (Publisher)
Created2019
Description
Monsoon hazards routinely affect the community, economy, and environment of the American Southwest. A common link for hazard development during the North American Monsoon concerns the interplay between temperature, moisture, and wind in the vertical atmosphere controlled by an unstable monsoon circulation. This dissertation investigates vertical atmospheric patterns using in-situ sounding data, specifically, 1) environments favorable for severe hail on the Colorado Plateau, 2) significant parameters distinguishing unhealthy versus healthy ozone days in Phoenix, Arizona, and 3) vertical profile alignments associated with distinct ranges in ozone concentrations observed in Phoenix having defined health impacts.
The first study (published in the Journal of the Arizona-Nevada Academy of Science) determines significant variables on Flagstaff, Arizona 12Z rawinsonde data (1996-2009) found on severe hail days on the Colorado Plateau. Severe hail is related to greater sub-300 hectopascals (hPa) moisture, a warmer atmospheric column, lighter above surface wind speeds, more southerly to southeasterly oriented winds throughout the vertical (except at the 700 hPa pressure level), and higher geopotential heights.
The second study (published in Atmospheric Environment) employs principal component, linear discriminant, and synoptic composite analyses using Phoenix, Arizona rawinsonde data (2006-2016) to identify common monsoon patterns affecting ozone accumulation in the Phoenix metropolitan area. Unhealthy ozone occurs with amplified high-pressure ridging over the Four Corners region, 500 hPa heights often exceeding 5910 meters, surface afternoon temperatures typically over 40°C, lighter wind speeds in the planetary boundary layer under four ms-1, and persistent light easterly flow between 700-500 hPa countering the daytime mountain-valley circulation.
The final study (under revision in Weather and Forecasting) assesses composite atmospheric sounding analysis to forecast Air Quality Index ozone classifications of Good, Moderate, and collectively categories exceeding the U.S. EPA 2015 standard. The analysis, using Phoenix 12Z rawinsonde data (2006-2017), identifies the existence of “pollutant dispersion windows” for ozone accumulation and dispersal in Phoenix.
Ultimately, monsoon hazards result from a complex and evolving vertical atmosphere. This dissertation demonstrates the viability using available in-situ vertical upper-air data to anticipate recurring atmospheric states contributing to specific hazards. These results will improve monsoon hazard prediction in an effort to protect public and infrastructure.
The first study (published in the Journal of the Arizona-Nevada Academy of Science) determines significant variables on Flagstaff, Arizona 12Z rawinsonde data (1996-2009) found on severe hail days on the Colorado Plateau. Severe hail is related to greater sub-300 hectopascals (hPa) moisture, a warmer atmospheric column, lighter above surface wind speeds, more southerly to southeasterly oriented winds throughout the vertical (except at the 700 hPa pressure level), and higher geopotential heights.
The second study (published in Atmospheric Environment) employs principal component, linear discriminant, and synoptic composite analyses using Phoenix, Arizona rawinsonde data (2006-2016) to identify common monsoon patterns affecting ozone accumulation in the Phoenix metropolitan area. Unhealthy ozone occurs with amplified high-pressure ridging over the Four Corners region, 500 hPa heights often exceeding 5910 meters, surface afternoon temperatures typically over 40°C, lighter wind speeds in the planetary boundary layer under four ms-1, and persistent light easterly flow between 700-500 hPa countering the daytime mountain-valley circulation.
The final study (under revision in Weather and Forecasting) assesses composite atmospheric sounding analysis to forecast Air Quality Index ozone classifications of Good, Moderate, and collectively categories exceeding the U.S. EPA 2015 standard. The analysis, using Phoenix 12Z rawinsonde data (2006-2017), identifies the existence of “pollutant dispersion windows” for ozone accumulation and dispersal in Phoenix.
Ultimately, monsoon hazards result from a complex and evolving vertical atmosphere. This dissertation demonstrates the viability using available in-situ vertical upper-air data to anticipate recurring atmospheric states contributing to specific hazards. These results will improve monsoon hazard prediction in an effort to protect public and infrastructure.
ContributorsMalloy, Jonny William (Author) / Cerveny, Randall S. (Thesis advisor) / Selover, Nancy J (Committee member) / Brazel, Anthony J. (Committee member) / Balling, Robert C. (Committee member) / Arizona State University (Publisher)
Created2019