A numerical study into the effects of turbulent flows around full-scale buildings

This thesis describes the development and application of a numerical predictive procedure for turbulent flows around full-scale buildings. Two different turbulence models were considered: a complete Reynolds stress model with two alternative proposals for the pressure-strain correlations and a k-E model used in conjunction with both linear and nonlinear stress-strain relationships. The governing differential equations were discretized using finite-volume techniques and a co-located variable-storage arrangement. A multigrid method was introduced and was found to reduce the computational time by nearly a factor of ten. Both the Reynolds-stress transport model and the non-linear k-€ model were implemented in a form suitable for use with body-fitted coordinates on a co-located grid. When using the Reynolds-stress models, a number of techniques were utilized to stabilize the solution process and attain rapid convergence. The atmospheric boundary layer at inlet to the computation domain, traditionally specified from empirical correlations, was simulated here using a full Reynolds-stress model in conjunction with a marching integration procedure. Due account was taken of the terrain roughness which matched that for the full-scale tests. The outcome of those simulations consisted of profiles of mean velocity and turbulence quantities that were self sustaining and in close accord with the few full-scale measurements available. The turbulence models' performance was assessed first through detailed comparisons with various benchmark flows including the backward-facing step in both straight and divergent channel, the two-dimensional rib, the circular cylinder and the three-dimensional cube. Detailed model verification was then carried out by comparisons with full-scale measurements on various structures including a single-span low-rise building, a semicylindrical greenhouse and a multi-span glasshouse. It was found that the Reynolds-stress models consistently produced more accurate simulations than the k-E models. Moreover, it was demonstrated that a recently proposed model for the pressure-strain correlations yields very satisfactory results without the use of wall-reflection terms. Parametric studies were performed to determine the sensitivity of the average pressure loading to various design parameters such as the height and width of the building, the eaves geometry (sharp or curved) and the height and location of a solid windbreak placed upstream of the building. Finally, a method is proposed for representing the unsteady nature of the flow around full-scale buildings. The unsteady pressure loading is recovered and so is the peak loading which far exceeds the steady-state value. The method utilizes classical turbulence modelling techniques and is shown to yield results that are in qualitative accord with the field measurements

Long-term analysis of the asynchronicity between temperature and precipitation maxima in the United States Great Plains

Agriculture is a critical industry to the economy of the Great Plains (GP) region of North America and sensitive to change in weather and climate. Thus, improved knowledge of meteorological and climatological conditions during the growing season and associated variability across spatial and temporal scales is important. A distinct climate feature in the GP is the asynchronicity (AS) between the timing of temperature and precipitation maxima. This study investigated a long-term observational data set to quantify the AS and to address the impacts of climate variability and change. Global Historical Climate Network Daily (GHCN-Daily) data were utilized for this study; 352 GHCN-Daily stations were identified based on specific criteria and the dates of the precipitation and temperature maxima for each year were identified at daily and weekly intervals. An asynchronous difference index (ADI) was computed by determining the difference between these dates averaged over each decade. Analysis of daily and weekly ADI revealed two physically distinct regimes of ADI (positive and negative), with comparable shifts in the timing of both the maximum of precipitation and temperature over all six states within the GP examined when comparing the two different regimes. Time series analysis of decadal average ADI yielded moderate shifts (∼5 to 10 days from linear regression analysis) in ADI in several states with increased variability occurring over much of the study region

Primary Atmospheric Drivers of Pluvial Years in the United States Great Plains

Precipitation variability has increased in recent decades across the Great Plains (GP) of the United States. Drought and its associated drivers have been studied in the GP region; however, periods of excessive precipitation (pluvials) at seasonal to interannual scales have received less attention. This study narrows this knowledge gap with the overall goal of understanding GP precipitation variability during pluvial periods. Through composites of relevant atmospheric variables from the ECMWF twentieth-century reanalysis (ERA-20C), key differences between southern Great Plains (SGP) and northern Great Plains (NGP) pluvial periods are highlighted. The SGP pluvial pattern shows an area of negative height anomalies over the southwestern United States with wind anomalies consistent with frequent synoptic wave passages along a southward-shifted North Pacific jet. TheNGPpattern during pluvial periods, by contrast, depicts anomalously low heights in the northwestern United States and an anomalously extended Pacific jet. Analysis of daily heavy precipitation events reveals the key drivers for these pluvial events, namely, an east–west height gradient and associated stronger poleward moisture fluxes. Therefore, the results show that pluvial years over the GP are likely driven by synoptic-scale processes rather than by anomalous seasonal precipitation driven by longer time-scale features. Overall, the results present a possible pathway to predicting the occurrence of pluvial years over the GP and understanding the causes of GP precipitation variability, potentially mitigating the threats of water scarcity and excesses for the public and agricultural sectors

The Investigation of Effects of Quercetin and Its Combination with Cisplatin on Malignant Mesothelioma Cells In Vitro

Malignant Mesothelioma (MM) is an aggressive and lethal tumour of the serosal surfaces with poor prognosis. In this study, we have investigated the antiproliferative effect of Quercetin (QU) and its combination with Cisplatin (CIS) on SPC212 and SPC111 cell lines. Our experiments showed that QU significantly reduced the proliferation of cell lines, altered the cell cycle distribution, and increased the level of Caspase 9 (C9) and Caspase 3 (C3) in concentration and time-dependent manner. Additionally, the combination of QU + CIS was found more effective when compared with individual treatment of agents

The impact of the urban heat island during an intense heatwave

, an intense heat wave occurred in Oklahoma City. To quantify the impact of the urban heat island (UHI) in Oklahoma City on observed and apparent temperature conditions during the heat wave event, this study used observations from 46 locations in and around Oklahoma City. The methodology utilized composite values of atmospheric conditions for three primary categories defined by population and general land use: rural, suburban, and urban. The results of the analyses demonstrated that a consistent UHI existed during the study period whereby the composite temperature values within the urban core were approximately 0.5 • C warmer during the day than the rural areas and over 2 • C warmer at night. Further, when the warmer temperatures were combined with ambient humidity conditions, the composite values consistently revealed even warmer heat-related variables within the urban environment as compared with the rural zone

Primary Atmospheric Drivers of Dry and Wet Periods over the U.S. Great Plains within CMIP5 Models

Precipitation variability is critical to the economic and ecosystem health of the United States Great Plains (GP). Whether from wet or dry extremes, changes in annual precipitation can lead to impacts on the health of the ecosystem and overall crop yield in a given year. To this end, wet and dry extremes have been investigated using the ERA-20C and CMIP5 dataset on an annual timescale to determine the ability of climate-scale simulations to resolve atmospheric drivers of precipitation variability. Results from the ERA-20C analysis show that specific atmospheric circulation anomalies can be detected which relate eddy geopotential height (EGH) anomalies to dry or wet annual precipitation anomalies in the GP domain. Using a similar method of defining dry and wet years, CMIP5 model simulations were examined to determine their ability to resolve these drivers and the associated precipitation variability in the GP. After filtering the different models based on their depiction of GP precipitation variability, the model simulations were categorized as Tier 1 and Tier 2 models, where Tier 1 yielded overall strong similarities and Tier 2 with overall weaker similarities. Both the Tier 1 and Tier 2 models were subsequently analyzed using the same atmospheric fields investigated within the ERA-20C dataset. The results demonstrated that both the Tier 1 and Tier 2 model ensembles were able to resolve the atmospheric anomalies associated with dry and wet years over the GP. However, specific differences exist between the Tier 1 and Tier 2 ensembles, namely that the Tier 2 model composites show larger magnitude anomalies. This result likely means that the Tier 2 model composites produce too many years in which the atmospheric anomalies are the primary cause of the precipitation anomalies when compared with known observational cases of GP dry or wet years. Overall, however, the CMIP5 models were able to satisfactorily reproduce GP precipitation variability, while the root of the variability appears to be forced by processes that are not widely evident in reanalysis datasets

Atmospheric Contributors to Heavy Rainfall Events in the Arkansas-Red River Basin

This study analyzed the top 1% 24-hour rainfall events from 1994 to 2013 at eight climatological sites that represent the east to west precipitation gradient across the Arkansas-Red River Basin in North America. A total of 131 cases were identified and subsequently classified on the synoptic-scale, mesoscale, and local-scale to compile a climatological analysis of these extreme, heavy rainfall events based on atmospheric forcings. For each location, the prominent midtropospheric pattern, mesoscale feature, and predetermined thermodynamic variables were used to classify each 1% rainfall event. Individual events were then compared with other cases throughout the basin. The most profound results were that the magnitudes of the thermodynamic variables such as convective available potential energy and precipitable water values were poor predictors of the amount of rainfall produced in these extreme events. Further, the mesoscale forcings had more of an impact during the warm season and for the westernmost locations, whereas synoptic forcings were extremely prevalent during the cold season at the easternmost locations in the basin. The implications of this research are aimed at improving the forecasting of heavy precipitation at individual weather forecasts offices within the basin through the identified patterns at various scales

Role of Sea Surface Temperatures in Forcing Circulation Anomalies Driving U.S. Great Plains Pluvial Years

In the U.S. Great Plains (GP), diagnosing precipitation variability is key in developing an understanding of the present and future availability of water in the region. Building on previous work investigating U.S. GP pluvial years, this study usesERAtwentieth century (ERA-20C) reanalysis data to investigate key circulation anomalies driving GP precipitation anomalies during a subset of GP pluvial years (called in this paper Pattern pluvial years). With previous research showing links between tropical Pacific sea surface temperature (SST) anomalies and GP climate variability, this study diagnoses the key circulation anomalies through an analysis of SSTs and their influence on the atmosphere. Results show that during Pattern southern Great Plains (SGP) pluvial years, central tropical Pacific SST anomalies are coincident with key atmospheric anomalies across the Pacific basin and North America. During northern Great Plains (NGP) Pattern pluvial years, no specific pattern of oceanic anomalies emerges that forces the circulation anomaly feature inherent in specific NGP pluvial years. Utilizing the results for SGP pluvial years, a conceptual model is developed detailing the identified pathway for the occurrence of circulation patterns that are favorable for pluvial years over the SGP. Overall, results from this study show the importance of the identified SGP atmospheric anomaly signal and the potential for predictability of such events

Examining Rapid Onset Drought Development Using the Thermal Infrared–Based Evaporative Stress Index

Reliable indicators of rapid drought onset can help to improve the effectiveness of drought early warning systems. In this study, the evaporative stress index (ESI), which uses remotely sensed thermal infrared imagery to estimate evapotranspiration (ET), is compared to drought classifications in the U.S. Drought Monitor (USDM) and standard precipitation-based drought indicators for several cases of rapid drought development that have occurred across the United States in recent years. Analysis of meteorological time series from the North American Regional Reanalysis indicates that these events are typically characterized by warm air temperature and low cloud cover anomalies, often with high winds and dewpoint depressions that serve to hasten evaporative depletion of soil moisture reserves. Standardized change anomalies depicting the rate at which various multiweek ESI composites changed over different time intervals are computed to more easily identify areas experiencing rapid changes in ET. Overall, the results demonstrate that ESI change anomalies can provide early warning of incipient drought impacts on agricultural systems, as indicated in crop condition reports collected by the National Agricultural Statistics Service. In each case examined, large negative change anomalies indicative of rapidly drying conditions were either coincident with the introduction of drought in the USDM or lead the USDM drought depiction by several weeks, depending on which ESI composite and time-differencing interval was used. Incorporation of the ESI as a data layer used in the construction of the USDM may improve timely depictions of moisture conditions and vegetation stress associated with flash drought events

A Methodology for Flash Drought Identification: Application of Flash Drought Frequency across the United StatesJORDAN

With the increasing use of the term ‘‘flash drought’’ within the scientific community, Otkin et al. provide a general definition that identifies flash droughts based on their unusually rapid rate of intensi- fication. This study presents an objective percentile-based methodology that builds upon that work by identifying flash droughts using standardized evaporative stress ratio (SESR) values and changes in SESR over some period of time. Four criteria are specified to identify flash droughts: two that emphasize the vegetative impacts of flash drought and two that focus on the rapid rate of intensification. The method- ology was applied to the North American Regional Reanalysis (NARR) to develop a 38-yr flash drought climatology (1979–2016) across the United States. It was found that SESR derived from NARR data compared well with the satellite-based evaporative stress index for four previously identified flash drought events. Furthermore, four additional flash drought cases were compared with the U.S. Drought Monitor (USDM), and SESR rapidly declined 1–2 weeks before a response was evident with the USDM. From the climatological analysis, a hot spot of flash drought occurrence was revealed over the Great Plains, the Corn Belt, and the western Great Lakes region. Relatively few flash drought events occurred over mountainous and arid regions. Flash droughts were categorized based on their rate of intensification, and it was found that the most intense flash droughts occurred over the central Great Plains, Corn Belt, and western Great Lakes region