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Numerical simulations using the Penn State University/NCAR MM4 model are performed to examine a stably stratified, zonal easterly flow past large scale three-dimensional mountain ranges in a rotating, initially barotropic, atmosphere. Upstream blocking by the mountain range diverts the flow primarily to the south and around the mountain. Conservation of potential vorticity results in the formation of a horizontal jet at low levels south of the mountain. This jet is barotropically unstable and leads to a continuous production of synoptic scale vorticity maxima which separate from the mountain and propagate downstream. Numerical simulations using topography representative of the Sierra Madre in Mexico imply that this mechanism may be important in providing some of the initial disturbances which grow into tropical cyclones in the eastern North Pacific Ocean. The wave train produced in the simulations corresponds to waves with 3-7 day periods which have been identified observationally in the eastern North Pacific region. The sensitivity of this effect to the stability of the basic state and the upstream wind speed is investigated. Simulations are also performed which show that the Hoggar and Atlas mountains of west-central Africa block the low-level easterlies resulting in a barotropically unstable jet and a train of vorticity maxima which separate from the mountain and propagate downstream. The spacing of these disturbances is roughly 1600 km and they propagate to the east with a period of about 2.5 days. These characteristics correspond to those of observed waves in the Africa/Atlantic region. It will also be shown that the unique topography of north-central Africa results in a mid-tropospheric easterly jet which has a maximum between 0-10°E and 15-20°N. The location and magnitude of this jet correspond to the so-called African easterly jet which is usually attributed to the strong surface temperature gradients over the continent of Africa. The numerical simulations presented in this work suggest that the mechanical effect of the topography may provide a constant source of energy for the maintenance of the African easterly jet.

The increasing frequency of sporadic weather patterns in the last decade, especially major winter storms, demands improvements in current weather forecasting techniques. Recently, there are growing interests in stratospheric forecasting because of its potential enhancements of weather forecasts. The dominating factors of northern hemisphere wintertime variation of the general circulation in the stratosphere is a phenomenon called stratospheric sudden warming (SSW) events. It is shown in multiple studies that SSW and cosmic ray muon flux variations are strongly correlated with the effective atmospheric temperature changes, which suggests that cosmic ray detectors could be potentially used as meteorological applications, especially for monitoring SSW events. A method for determining the effective temperature with cosmic ray flux measurements is studied in this work by using statistical modeling techniques, such as k-fold cross validation and partial least square regression. This method requires the measurement of the vertical profile of the atmospheric temperature, typically measured by radiosonde, for training the model. In this study, cosmic ray flux measured in Atlanta and Yakutsk are chosen for demonstrating this novel technique. The results of this study show the possibility of realtime monitoring on effective temperature by simultaneous measurement of cosmic ray muon and neutron flux. This technique can also be used for studying the historical SSW events using the past world wide cosmic ray data.

Canadian Prairie agriculture, in general, is expected to benefit under climate change with increasing mean temperatures projected for the immediate future. However, a number of knowledge gaps still exist. Foremost among these is the measurement of the effects of extreme climate events in a given year as well as their long-term impact on the supply of agricultural products, and also the financial situation of farms. In addition, the economic impacts of climate change on livestock operations are relatively under-studied. In particular, knowledge of the impacts on Prairie beef cattle remains more guesswork than research-based evidence. This dissertation assesses the impact of changes in the normal climate as well as the impact of climate extremes by including projected inter-annual climate variability. The economic impact of these changes on crops, beef cattle activities and the viability of farms in mixed operation settings is measured. Correspondingly, this work presents alternative adaptation measures and their likely use in managing mixed farm operations for future extreme weather events. For the analysis, two study sites are selected: (1) the Oldman River Basin of Alberta, called Pincher Creek, and (2) the Swift Current Creek Basin of Saskatchewan, called Swift Current. This study is a part of a larger project entitled “Vulnerability and Adaptation to Climate Extremes in the Americas” and the study sites are intended to represent the project catchment areas in the provinces of Alberta and Saskatchewan. I develop what I call a MF-CCE model (Mixed Farm model for the economic impact assessment of Climate Change and Extremes). The MF-CCE is a whole farm simulation model that integrates models of beef cattle production, crop production and climate changes into farm level economic decisions. Simulations are conducted over a 30-year period in each climate scenario: the first of these is a baseline climate scenario from 1971-2000, and I also simulate future climate change impacts for the 2041-2070 era. The modelled farms produce enough crops, hay and pasture to support the beef cattle feed demand. Pasture demand and supply are linked by specific pasture requirements and productivity. Beef herd feed grain demand and on-farm supply are linked by a linear programming optimization algorithm. Crop mix for the market is selected through the development of a multi-year linear programming problem that maximizes the present value of gross margins. Crop and hay productivity are estimated through the Food and Agriculture Organization’s (FAO’s) AquaCrop (version 3) modeling framework, while annual pasture productivity is estimated using the Forage Calculator for Native Rangeland obtained from the Saskatchewan Research Council (SRC). The AquaCrop is a water-driven crop simulation model, termed a crop water productivity (WP) model which simulates the yield response of herbaceous crops to water availability and use. The model is believed to be superior in simulating crop yield in the conditions where water is a key limiting factor in crop production (FAO, 2011). Summarizing the results of the simulation, prairie crop production is expected to benefit under the simulated climate change scenario. Increases in crop productivity generate about 60% higher profits in the Pincher Creek site and about 57% more for the Swift Current site. Due to increases in grain and hay productivity, more area is made available to produce grain for the market. This effectively doubles the crop net return at the Pincher Creek site and triples the crop return at the Swift Current site. A consideration of future pasture response to the climate change scenario is important in estimating climate change consequences for live beef production as well as on the economic return of a mixed farm. If the pasture productivity decreases, as assumed under the regular pasture yield scenario in the study, appropriate adaptation is necessary for the farm to benefit from future climate change. Under this scenario, beef production activities in the future are projected to gain by 50% in Pincher Creek and 40% in Swift Current compared to the baseline scenario. If pasture productivity under the future scenario increases in a manner similar to crop yield increases, existing pastureland will be enough to maintain beef herds into the future. In turn, this strategy will mitigate the cost of beef herd adaptation during climate extremes, and instead gains from beef cattle production would be 35% higher in Swift Current and 6% higher in Pincher Creek relative to gains under regular pasture yield conditions. At the farm level, with beef cattle and crop production combined, substantial gains are projected for both of the study sites. Farm net profit is estimated to increase by more than 35% at the Pincher Creek site and more than 140% at the Swift Current site under the future scenario. Income risk will also be lower in this scenario, as highlighted by a lower coefficient of variation of net farm profit. Farm financial indicators tracked in this study – farm cash flow, family cash flow, and farm net worth – all indicate that the farm’s financial position will be much better in the future climate scenario. At the Pincher Creek site, a few problematic liquidity events are forecasted under the future climate scenario, but in light of significant improvements in other economic indicators, overall, this effect is negligible. The appropriate choice of adaptation strategies for managing beef herds during extreme climate events plays an important role in determining the profitability of not only beef cattle activities, but also the financial position at the whole farm level. However, the choice of adaptations is contextual: the preference of adaptation strategy differs across activities, farms and period of study. For beef cattle activities, maintaining the beef herd without any compromise on herd size and implementing a regular feeding plan is preferred to other adaptation alternatives. At the whole farm level for the Pincher Creek site, culling the herd is preferred under the baseline scenario, while the purchasing feed option is preferred under the future climate scenario. At the Swift Current site, culling the herd is the preferred strategy under both scenarios. Commodity prices and the cost of farm inputs profoundly affect the economic position of the farm under the future climate change scenario. If commodity prices and cost of production remain the same as under the baseline scenario, future farm net profit is estimated to be 50% higher for the Pincher Creek site and about 25% higher for the Swift Current site, compared to profits under projected future prices. This result implies that the pure effect of climate change could be much higher if costs and prices do not change. Results of this dissertation indicate that average Prairie mixed farms, as represented by these study farms, remain economically viable under both the baseline and future scenarios. The results also suggest that the overall gain to these farms under a future climate change scenario would be positive. The potential severity of extreme climate events in the future, at least for the future scenario period simulated in this study, would not be significant enough to threaten the future economic viability of Prairie agriculture. However, the research also highlights the importance of policies that support farmers when they endure losses in years of extreme climate events. Further research on evaluating different Best Management Practices (BMPs) in dealing with droughts, for example, would be helpful in taking advantage of future climate change. Policy development to enhance the longer-term adaptive capacity of Prairie farmers, such as development of early warning systems for climate extremes, or the development of drought tolerant cultivars of crops and forages, would be most helpful in coping with climate extremes in the future.

published_or_final_version / Education / Master / Master of Science in Information Technology in Education

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The UK has highly ambitious targets for wind development, particularly offshore, where over 30GW of capacity is proposed for development. Integrating such a large amount of variable generation presents enormous challenges. Answering key questions depends on a detailed understanding of the wind resource and its temporal and spatial variability. However, sources of wind speed data, particularly offshore, are relatively sparse: satellite data has low temporal resolution; weather buoys and met stations have low spatial resolution; while the observations from ships and platforms are affected by the structures themselves. This work uses a state-of-the art mesoscale atmospheric model to produce a new high-resolution wind speed dataset over the British Isles and surrounding waters. This covers the whole region at a resolution of 3km for a period of eleven consecutive years, from 2000 to 2010 inclusive, and is thought to be the first high resolution re-analysis to represent a true historic time series, rather than a statistically averaged climatology. The results are validated against observations from met stations, weather buoys, offshore platforms and satellite-derived wind speeds, and model bias is reduced offshore using satellite derived wind speeds. The ability of the dataset to predict power outputs from current wind farms is demonstrated, and the expected patterns of power outputs from future onshore and offshore wind farms are predicted. Patterns of wind production are compared to patterns of electricity demand to provide the first conclusive combined assessment of the ability of future onshore and offshore wind generation meet electricity demand and contribute to secure energy supplies.

Scanning strategies for research and operational applications were developed for meteorological measurements with an experimental PAR, the MWR-05XP. A tornadic storm sampling strategy was developed with a 502.26 ms volumetric update and a resolution of 1.8 Az x 2 El x 150 m range. A sampling strategy for severe thunderstorm clusters was developed with a 10 second volumetric update and a resolution of 1.8 Az x 2 El x 300 m range. An operational weather scanning strategy was developed with an 81 second volumetric update and a resolution of 1.8 Az x 2 El x 150 m range. In general, for the acquisition of weather data, single frequency phased array radars offer only a slight sampling advantage over conventional scanning radars. This research verified that for meteorological sampling with the MWR-05XP, frequency diversity, coupled with electronic elevation scanning, offers a significant sampling advantage over conventional radars. The combination of electronic beam steering and frequency diversity produces a synergistic reduction in sampling time that increases the overall volumetric update rate. This research has also shown that, based on assumptions about the MWR-05XP operating parameters, it is possible to incorporate operational weather scanning into the radar's multifunction capability.

The increase in skill of numerical model guidance and the use of consensus forecast techniques have led to significant improvements in the accuracy of tropical cyclone track forecasts at ranges beyond 72 h. Identification of instances when the forecast track from an individual numerical model may be in error could lead to additional improvement in the accuracy of tropical cyclone track forecasts. An objective methodology is tested to characterize the spread among the three primary global numerical model forecast tracks used as guidance by the Joint Typhoon Warning Center. Statistically-significant principal components derived from empirical orthogonal functions of mid-tropospheric height and vorticity forecast fields identify cases of large spread among model forecasts. Cases in which the three-model average forecast track resulted in a large error were characterized by a distribution of principal components such that one component was significantly different from the other two. Removal of the forecast track associated with the outlying principal component resulted in a reduced forecast error. Therefore, the objective methodology may be utilized to define a selective consensus by removing forecast tracks from consideration based on the projection of forecast fields onto empirical orthogonal functions and inspecting the distribution of the resulting principal components.

We have developed metrics of the performance and operational impacts of METOC support to strike operations conducted on operational aircraft carriers (CVs). Our goal was to assess that support and make recommendations on improving it. We adapted an existing automated real time METOC metrics system, which was developed for land based training missions, for use on CVs by developing a new data collection form, new metrics, and new collection, analysis, and reporting architecture for the remote entering of sensitive mission data without compromise. The weather support element of a CV, the OA division, does not provide strike mission planning support, but does provide situational awareness to pilots. Our system allows that situational awareness to be measured and assessed using metrics that quantify the performance of the forecasts, the relationship of the forecasts to the mitigating actions taken by pilots due to adverse weather conditions, and the effects of individual weather phenomena on the execution of strike missions. A key element of the data collection, analysis, and reporting system developed in this study is the collection of METOC related data from pilots during their intelligence debriefings. This system is readily adaptable for the assessment of METOC support to other warfare areas.