My sculptures, drawings, and installations deal with nature and weathering processes as metaphors for human experience.

Traditional stochastic approaches for synthetic generation of weather variables often assume a prior functional form for the stochastic process, are often not capable of reproducing the probabilistic structure present in the data, and may not be uniformly applicable across sites. In an attempt to find a general framework for stochastic generation of weather variables, this study marks a unique departure from the traditional approaches, and ushers in the use of data-driven nonparametric techniques and demonstrates their utility. Precipitation is one of the key variables that drive hydrologic systems and hence warrants more focus . In this regard, two major aspects of precipitation modeling were considered: (I) resampling traces under the assumption of stationarity in the process, or with some treatment of the seasonality, and (2) investigations into interannual and secular trends in precipitation and their likely implications. A nonparametric seasonal wet/dry spell model was developed for the generation of daily precipitation. In this the probability density functions of interest are estimated using non parametric kernel density estimators. In the course of development of this model, various nonparametric density estimators for discrete and continuous data were reviewed, tested, and documented, which resulted in the development of a nonparametric estimator for discrete probability estimation. Variations in seasonality of precipitation as a function of latitude and topographic factors were seen through the non parametric estimation of the time-varying occurrence frequency. Nonparametric spectral analysis, performed on monthly precipitation, revealed significant interannual frequencies and coherence with known atmospheric oscillations. Consequently, a non parametric, nonhomogeneous Markov chain for modeling daily precipitation was developed that obviated the need to divide the year into seasons. Multivariate nonparametric resampling technique from the nonparametrically fitted probability density functions, which can be likened to a smoothed bootstrap approach, was developed for the simulation of other weather variables (solar radiation, maximum and minimum temperature, average dew point temperature, and average wind speed). In this technique the vector of variables on a day is generated by conditioning on the vector of these variables on the preceding day and the precipitation amount on the current day generated from the wet/dry spell model.

The weather is an ever present and uncontrollable element in our lives. Only a handful of studies has addressed the relationship between weather and the behavior of children, although anecdotal and intuitive evidence of this relationship abounds. The purpose of this study was to observe the behavior of groups of elementary school-aged children in their classroom ecology during different phases of the weather cycle as observed by their teachers, observe any behavioral differences between girls and boys, and observe if any weather -related differences exist between the behavior of younger and older children. A model of the direct and indirect influence of the weather on children was introduced, and a comprehensive, systematic method of classifying weather data for analysis was presented. A significant relationship was found between day of week, grade, school, weather, and behavior.

Rain-induced sanitary sewer overflow due to high infiltration is a significant challenge for many utilities, including Pinellas County utilities. The main aim of this study is to develop a hydraulic model to analyze the performance of the existing sanitary sewer system, especially during intense rainfall events. To calculate the flow inputs for the model, a times series analysis was performed to separate the inflow and infiltration from the actual sewer flow. Using the Stevens-Schutzbach method, daily Base Infiltration (BI) was calculated and was subtracted from the total observed flow to give the Dry Weather Flow (DWF). Adjusting the DWF by the diurnal pattern, residual flows were calculated to test the flow variability in the system and compare to rain events (> 0.5 inches); the residual flow help deduced if there is a significant surface inflow into the system. Using PC SWMM as the hydraulic model, the average DWF was simulated using the average value and the diurnal daily and weekend pattern during the dry weather periods. The calculated BI was added to the model as a direct contribution from the statistical model. Both the average value of DWF and BI were distributed throughout the system for simulation. The simulated flow shows that few downstream manholes surcharges during extreme rainfall events and remained surcharge for over 48 hours. Cross-correlation analysis suggests the rainfall of the past seven days still impacts the BI, with the highest impact on days 1, 4 and 5. The correlogram results were used to develop a regression model, to predict the BI for different rainfall depths, which in turn was used for hydraulic performance analysis. Increasing the rainfall depths and routing the flow using PC SWMM, showed that the hydraulic grade line, number and hours of the surcharged manholes increases as total rainfall depths increases, but no sanitary sewer overflow. Sanitary sewer overflow occurred at the lift station with a design capacity of 200 GPM for all increased rainfall depths. Furthermore, the analysis results can help locate areas where overflow is more likely to occur, and can also help plan and implement a cost-effective rehabilitation program for the existing sewer network.

ABSTRACT Hail poses a substantial threat to life and property in the state of Florida. These losses could be minimized through better understanding of the relationships between atmospheric variables that impact hail formation in Florida. Improving hail forecasting in Florida requires analyzing a number of meteorological parameters and synoptic data related to hail formation. NOAA archive data was retrieved to create a database that was used to categorize text files of hail days. The text files were entered into the National Oceanic and Atmospheric Administration Earth System Research Laboratory website to create National Centers for Environmental Prediction/National Center for Atmospheric Research Reanalysis maps of atmospheric variables for Florida hail days as well as days leading to the hail event. These data were then analyzed to determine the relationship between variables that affect hail formation, in general, across different regions and seasons in Florida using Statistical Product and Service Solutions. The reasoning for the differing factors affecting hail formation between regions, seasons and hail sizes were discussed, as well as forecasting suggestions relating to region and month in Florida. The study found that the majority of all hail that occurs in Florida is during the wet season. A low Lifted Index, high Precipitable Water and lower than average Sea Level Pressure, in most cases, is present during hail days in Florida. Furthermore, results show that Vector Wind magnitude increases as hail size increases. Additionally, several atmospheric variables useful to studying hail events, such as Lifted Index, Precipitable Water, Sea Level Pressure, Vector Wind and Temperature have significant correlations with each other depending on the region and season being observed. Strong correlations between low Lifted Index, high Precipitable Water values and the occurrence of hail events are discussed, as well as the relationship between temperature anomalies at various pressure levels and the occurrence of hail events.

The purpose of this research was to create the longest possible, homogeneous, historical daily temperature dataset for Southern New Zealand, analyse the changes in extreme temperatures and investigate atmospheric circulation patterns that contributed to these changes. Daily minimum and maximum temperature data for Southern New Zealand were captured from paper records and extended to include all available archival data from the region. This dataset was digitised and contains temperatures from 26 stations that began operation sometime in the period between 1852 and 1953. Stations include the Chatham and Campbell islands. Adjustments for inhomogeneities in the dataset were made using a frequency distribution matching method. Dunedin has a record dating from 1852, the longest in the Southern Hemisphere south of 40�S latitude. Reconstruction of a homogeneous record for Dunedin was made by taking into account site changes from contemporaneous modem data logger measurements and from an analysis of overlapping period data. Temperatures showed no clear pattern of change in Southern New Zealand from the mid 1800s through to the early 1900s with the exception of a brief cold period that occurred around 1900. However, from the 1940s through to the 1970s both minimum and maximum extreme temperatures showed strong warming. These trends were duplicated over the shorter length period of record for other regions, especially in Eastern Canterbury. The warming trend was maintained over the period 1979 - 2003, but only in the colder ends of minimum and maximum distributions. Temperatures have become less cold due to the recent compression of the temperature distribution. There was a marked decrease in cold days at stations in the south and offshore islands. Atmospheric circulation pattems, and in particular ENSO, were shown to affect extreme temperatures recorded in Southern New Zealand. Anomalous southwesterlies associated with El Nino events produce cooler temperatures and increase the numbers of cold extreme temperatures, while anomalous northeasterlies typical of La Nina increase the numbers of warm extreme temperatures. Monthly frequencies of extreme temperatures were primarily affected by anomalous south/north meridional airflows to increase cold/warm extreme temperature frequencies. Zonal airflows have a lesser, but topographically influenced effect. Record hot and cold temperatures in Southern New Zealand were a product of the interaction between advective northerly and southerly airflows respectively, and local climatic effects caused by topography.

Risk management is a key component of aeronautical decision-making and one of the possible causes of pilot error (e.g., Jensen, Guilke, & Hunter, 1997). Risk management encompasses risk perception and risk tolerance. Risk perception involves the detection of risks associated with a situation, whereas risk tolerance is the willingness to accept a given degree of risk (Hunter, 2002). Previous studies using flight simulators have found that risk perception and risk tolerance differs between pilots who fly into adverse weather and those who do not (e.g., O�Hare, Owen, Jorgensen, Wiegmann, Hunter, & Mullen, 2007). The aim of this research was to assess risk perception and risk tolerance using scenario-based measures. The measure of risk perception was developed over three studies. Since risk perception is a skill which expert pilots exercise (Jensen et al., 1997), I used the Cochran-Weiss-Shanteau (CWS, Weiss & Shanteau, 2003) index to measure how good pilots were at perceiving aeronautical risks. Weiss and Shanteau assumed that an expert should be able to discriminate between two relevant stimuli, and do so consistently. Participants were presented with flight scenarios and rated the risk involved in each scenario from 0 (low risk) to 100 (high risk). If a valid measure of expertise in risk perception, those with experience in aeronautical decision-making should have been better at this task. In study one the qualified pilots had higher and more variable CWS scores than the non-pilots, suggesting that some pilots were expert at this task, whereas most non-pilots were poor at this task. The focus of study two was shifted to weather-related decision-making (WRDM). Geography students, student pilots, and qualified pilots did not differ in their mean CWS scores, although the qualified pilots were most discriminating, and the geography students were most consistent. To decrease the reliance of the task on memory, study three included a blocking task in between each scenario. While only a small scale study, the results suggested that the blocking task improved the qualified pilots� performance while the geography students� performance deteriorated. In study four, I used Lopes�s (1987) theory to measure risk tolerance in pilots. According to Lopes (1987), risk tolerant individuals are motivated by opportunity, or what they can gain from taking risks, whereas risk averse individuals are motivated by threat, or what they can lose from taking risks. Qualified pilots were presented with 36 flight scenarios, varying in the level of threat and opportunity. The pilots rated the likelihood of going on the flights. Multiple regression equations were calculated, measuring the influence of threat and opportunity on each pilot�s ratings. Pilots were largely risk averse, as their ratings were influenced by threat. The two pilots whose ratings were influenced by opportunity had experienced more aviation incidents compared to the pilots who were not influenced by opportunity. The aim of study five was to assess the relationship between risk management and in-flight WRDM. Qualified pilots completed a simulated flight into adverse weather, and four-computer based measures: the expertise in risk perception measure developed in study three, the risk tolerance measure developed in study four, and two implicit association tests assessing implicit risk perception and anxiousness towards adverse weather. Twelve pilots continued beyond the critical decision point, 18 pilots diverted, and 2 pilots crashed. There was no relationship between in-flight WRDM and expertise in weather-related risk perception. However, the pilots who diverted gave higher ratings of risk during the CWS task compared to the pilots who crashed. The pilots who diverted also tended to be more risk averse and implicitly perceived more risk in adverse weather, compared to the pilots who continued, suggesting a relationship between risk management and decision-making in a simulated flight into adverse weather. These five studies further highlight the role of risk management in pilot decision-making. The tools developed in these studies have potential for measuring risk management in pilots.

<p>Syftet med detta examensarbete är att titta på och eventuellt upptäcka vissa samband mellan de vanligaste klimatparametrarna (lufttemperatur, sol, vind, luftfuktighet och lufttryck) och inomhusklimatet. Inomhusklimatet är i detta arbete det samma som luftens temperatur inomhus.</p><p>Även en sammanställning av två studier kring NordIQ’s styrning av värmesystemet och tappvarmvattnet görs.</p><p> </p><p>En stor del av arbetet har varit att sammanställa och studera insamlad data från bland annat en väderstation.</p><p>Under den här perioden (våren) är det solen och utomhustemperaturen som har störst påverkan på temperaturen inomhus.</p><p> </p><p>En stor del inom energisektorn idag handlar om att använda energin effektivare och minska på utsläppen. Förhoppningen är att detta arbete ska kunna hjälpa till i den riktningen. Att utnyttja gratisenergin och dra ner på t.ex. fjärrvärmen är ett sätt, att inte kyla bort övertemperaturer utan att istället dra ner på den köpta energin.</p><p> </p><p>Ett annat sätt att utnyttja energin på ett effektivare sätt är att öka avkylningen och minska på flödet i uppvärmningssystemet. Det är något som NordIQ säger sig göra med sin styrning av värme och tappvarmvatten.</p><p>Sammanställningen visar att det stämmer.</p> / <p>The purpose of this thesis is to study and contingently discover some linkage between the most common climate parameters (air temperature, sun, wind, air humidity and air pressure) and the indoor climate. The indoor climate in this thesis is the same as the air-temperature indoor.</p><p>Also a compilation of two studies about NordIQ´s controlling of the heating system and hot water is done.</p><p> </p><p>A major portion of the work has been to compile and study collected data from among other things a weather station.</p><p>During this period (spring) the sun and the outdoor temperature have the greatest impact on the indoor temperature.</p><p> </p><p>A major portion of the energy sector today is about how to use the energy in a more effective way and decrease the emissions. Hopefully this thesis will help in that direction. To use the free energy and reduce for example district heating is one way, not cooling the high indoor temperatures, rather reduce the bought energy.</p><p> </p><p>Another way to take advantage of the energy in a more efficient approach is to increase annealing and reduce the flow in the heating system. That´s something with the aim of NordIQ`s controlling of the heat and hot water.</p><p>The compilation shows that it´s true.</p>

A circumferential slot In-line Virtual Impactor (IVI) has been designed using Computational Fluid Dynamics (CFD) simulation tools and experimentally characterized using monodispersed liquid aerosols to validate simulation results. The base design, IVI-100, has an application as a pre-separator for sampling inlets, where the device scalps large particles from the aerosol size distribution. The IVI-100 samples air in at 111 L/min and deliver the fine aerosol fraction in a 100 L/min flow and provide a cutpoint particle size of 10 µm, with a pressure drop of 45 Pa. An inverted dual cone configuration encased inside a tube provides the IVI-100 with a characteristic circumferential slot of width 0.254 mm (0.100 inches) and a slot length of 239 mm (9.42 inches) at the critical zone. The upper cone causes the flow to accelerate to an average throat velocity of 3.15 m/s, while the lower cone directs the major flow toward the exit port and minimizes recirculation zones that could cause flow instabilities in the major flow region. The cutpoint Stokes number is 0.73; however, the cutpoint can be adjusted by changing the geometrical spacing between the acceleration nozzle exit plane and a flow divider. Good agreement is obtained between numerically predicted and experimentally observed performance. An aerosol size selective inlet for bioaerosol and other air sampling applications using an upgraded prototype of IVI-100, mounted inside a BSI-100 inlet shell was tested in an aerosol wind tunnel over a speed range of 2 – 24 km/hr. The BSI-IVI-100 inlet has a cutpoint of 11 µm aerodynamic diameter and delivers the fine fraction at 100 L/m. The geometric standard deviation of the fractionation curve is 1.51 and the performance is not affected by wind speeds. An IVI-350, which is an adaptation of the IVI to be used as a powder fractionator, was designed based on computational simulations, and provides a cutpoint of 3 µm AD, while operating in a total flow rate of 350 L/min. Four Identical IVI -350 units will be operated in parallel to fractionate aerosolized powders in a 1400 L/min flow. An optimized inlet, with a contoured tear-drop shaped insert provides uniform flow to four identical IVI units and prevents powder accumulation in the system entrance.

This thesis addresses the issue of ground collision in poor weather conditions. As bad weather is an adverse factor when airplanes are taxiing, an obstacle detection system based on thermal vision is proposed to enhance the awareness of pilots during taxiing in poor weather conditions. Two infrared cameras are employed to detect the objects and estimate the distance of the obstacle. The distance is computed by stereo vision technology. A warning will be given if the distance is less than the safe distance predefined. To make the system independent, the proposed system is an on-board system which does not rely on airports or other airplanes. The type of obstacle is classified by the temperature of the object. Fuzzy logic is employed in the classification. Obstacles are classified into three main categories: aircraft, vehicle and people. Membership functions are built based on the temperature distribution of obstacles measured at the airport. In order to improve the accuracy of classification, a concept of using position information is proposed. Different types of obstacle are predefined according to different area at the airport. In the classification, obstacles are classified according to the types limited in that area. Due to the limitation of the thermal infrared camera borrowed, images were captured first and then processed offline. Experiments were carried out to evaluate the detecting distance error and the performance of system in poor weather conditions. The classification of obstacle is simulated with real thermal images and pseudo position information at the airport. The results suggest that the stereo vision system developed in this research was able to detect the obstacle and estimate the distance. The classification method classified the obstacles to a certain extent. Therefore, the proposed system can improve safety of aircraft and enhance situational awareness of pilots. The programming language of the system is Python 2.7. Computer graphic library OpenCV 2.3 is used in processing images. MATLAB is used in the simulation of obstacle classification.