Three weather sensitive multinomial logit models are estimated using the 2001 Transportation Tomorrow Survey in order explore the relationship between weather and home-based work trips within the City of Toronto, focusing on active modes of transportation. The data is restricted to non-captive commuters who have the option of alternating between all five basic modes of auto driver, auto passenger, transit, bike and walk with change in weather. Daily trip rates in various weather conditions are assessed. The combined effect of the daily trip rate and mode choice analysis is applied to several climate change scenarios. A 6oC increase in temperature can increase cycling trips by 17%, and reduce auto-passenger trips by 7%. A 20% increase or decrease in precipitation, however, is found to have much smaller impacts on all modes. Overall, the results confirm that impact of weather on active modes of transportation is significant enough to deserve attention at the research, data collection and planning levels.

Three weather sensitive multinomial logit models are estimated using the 2001 Transportation Tomorrow Survey in order explore the relationship between weather and home-based work trips within the City of Toronto, focusing on active modes of transportation. The data is restricted to non-captive commuters who have the option of alternating between all five basic modes of auto driver, auto passenger, transit, bike and walk with change in weather. Daily trip rates in various weather conditions are assessed. The combined effect of the daily trip rate and mode choice analysis is applied to several climate change scenarios. A 6oC increase in temperature can increase cycling trips by 17%, and reduce auto-passenger trips by 7%. A 20% increase or decrease in precipitation, however, is found to have much smaller impacts on all modes. Overall, the results confirm that impact of weather on active modes of transportation is significant enough to deserve attention at the research, data collection and planning levels.

Linkages between influenza prevalence and climate (e.g. precipitation, temperatures, El Nino Southern Oscillation ENSO) have been suspected, but definitive evidence remains elusive. This analysis investigated a climatic relationship between influenza mortality (measured by multiple caused pneumonia and influenza deaths) and influenza morbidity (measured by isolates tested for influenza). Influenza-climate linkages were analyzed at multiple spatial scales (e.g. local analysis, and regional analysis) and multiple temporal scales (e.g. annualized mortality counts, and mortality counts based on cumulative percentiles). Influenza mortality and morbidity were found to have significant correlations to seasonal temperatures, precipitation, and ENSO. Influenza-climate associations varied spatially and temporally, and underscore the importance of considering geographic scale in investigative analyses of disease. Evidence for an influenza-climate relationship provides a greater understanding of the enviro-climatic factors that can contribute to an influenza epidemic, and provides an impetus for further studies that incorporate climatic factors in influenza risk modeling.

The nature of electrical power requires specific infrastructure in order to operate adequately. Currently, the United States electricity grid contains a number of bottlenecking inefficiencies that arise from the aging infrastructure of the system. This paper examines the current state of the United States electricity grid, how potential changes in weather variables can affect the electricity consumption of residential consumers, and how implementation of Smart Grid technology can potentially mitigate these issues. It is determined through regression analysis that each weather variable that was tested proves significant for at least one of the consumers compared. This indicates that there is an enormous magnitude of individual variables that factor into residential electricity consumption and that more efficient and integrated electricity practices are necessary to optimize efficiency.

Traffic crashes tend to occur at relatively greater frequencies at particular locations, at particular time periods, and for particular subsets of drivers and vehicles. It is well recognized among the road safety community that crash-risk is highly elevated when inclement weather conditions occur in the winter. To present, most of the road safety studies focus on event-based analysis or seasonal analysis and give little attention to explore high-risk conditions at the daily temporal scale. The purpose of the study is to advance our understanding of high-risk crash conditions at the daily level and their occurrences in Southern Ontario, Canada. The study explores different definitions of high-crash days, and quantifies the influences of weather conditions, risk exposure, months and timing of precipitation on the likelihood of a high-crash day occurring using binary logistic regression model. Additionally, an approach for estimating the relative risk exposure using available traffic count data has also been developed. The results of the study show a small proportion of high-crash days are responsible for a considerable amount of traffic crashes during the winter. The risk of traffic crash is twice as high on high-crash days in comparison to non-high-crash days. The modeling approach well-fits the data and shows that winter weather conditions have significant influence on high-crash days with results being mostly consistent across the four study areas, Toronto, the Area Surrounding Toronto, London and the Area Surrounding London. Low temperature, heavy snowfalls, high wind speeds, high traffic volumes, early winter months, occurrence of precipitation in both morning and evening increase the odds of high-crash days to a large extent. The results of study could help to pre-schedule traffic operation and enforcement, to effectively distribute road safety resources and personnel, and to create situational awareness among road users and other stakeholders.

The spring reverse migration of landbirds (i.e., birds flying in the direction opposite to be expected), within the Great Lakes region is controversial because it is not understood if the extent or reversal of flight direction in spring is truly a change in migratory patterns or a brief anomaly. It is also not clear what the fitness and community level impacts are. My objective was to determine what and how weather influences reverse migration and to determine which species and families of birds participate the most frequently in this form of flight. I examined species which are participatory (and those that are not) as well as the impacts of specific weather covariates on the abundance of landbirds and focused explicitly on the putative reverse migration of landbirds. Field sites were located at the extreme southern tip of Fish Point, Pelee Island (2010-2012) and Point Pelee National Park (2012), where my field assistant and I visually recorded the total number of birds observed to be reverse migrating, while identifying all birds to species or family as best possible. This study was conducted over 97 days during April 26 – May 20, in 2010-2012. Information pertaining to potential reverse migration has only been formally documented twice in the Great Lakes region, most recently in 1951. I undertook a descriptive analysis to compare the numbers of individuals of bird species and families. Temperate and neotropical migrants were examined, compared, and divided into sub-sets based on their geographic ranges. I identified species at risk and vagrants which I observed during reverse migrations. Based on provincial population estimates, I determined the proportion of all reverse migrants where ≥200 individuals were observed. A descriptive analysis was undertaken to determine differences between sites (i.e., Point Pelee and Fish Point) in the final year of surveys (2012). Species and abundance were comparatively differentiated between each site and subsequently compared. While very few birds were observed flying anything but south, a total of 61,677 birds of 80 species was documented flying south. My results indicate temperate migrants vastly outnumbered neotropical migrants (as much as 4:1) and numbers of birds varied between study sites. Temperate migrants were noted to be more common (in the final study year) at Point Pelee compared to Fish Point, while neotropical migrants were more numerous at Fish Point than Point Pelee. Despite the fact that most migrant species participated in reverse migrations (i.e., of the species regularly occurring in the Pelee region at this time of year), complete absences were noted, most notably in Catharus thrushes, while species such as Rose-breasted Grosbeak and Scarlet Tanager, and families such as Tyrant Flycatchers, Vireos and Sparrows were observed to be less prevalent than anticipated. Species at risk and vagrants were noted relatively frequently during this study, suggesting that these surveys are an efficient and potentially important tool for migration monitoring in this region. Diurnal migrants, most notably Blackbirds, were observed to engage in reverse migration in higher numbers than nocturnal migrants, such as Wood Warblers. Seven weather covariates were measured and modeled with the total number of birds detected using R to determine which covariates explain the most amount of variation of the total number of birds during my surveys. I used an AICc approach to select the best model for each hypothesis. After selecting the top weather covariates with time lags according to the best (lowest) AICc values, I built general models by comparing all possible combinations of the covariates identified in the top models for each hypothesis. I included a random effect intercept for study site to discern any site difference or similarities between Point Pelee and Fish Point and specified a Poisson distribution (log-link function as implemented in the LMER package) because the data set was continuous (time-series) and count oriented. My adjusted time lag results show that most migrants tend to migrate during and ahead of inclement weather and/or periods of south winds. I also found that all identified covariates influence reverse migration to some degree. Wind direction and barometric pressure were the most significant of the covariates examined (β = 0.718 and -0.213, respectively). Specifically, wind direction is the most important covariate in explaining reverse migration, with days of south winds dramatically increasing the probability of higher numbers of birds during surveys. Low barometric pressure is also important for explaining the number of observed reverse migrants; therefore, days with lower barometric pressure have a greater likelihood of increased bird observations. Based on my observations and results I theorized that while reverse migration pertains to a distinct form of flight, it is likely not an actual form of migration. This form of flight at its simplest is likely a form of reorientation, whereby migratory birds take advantage of local weather conditions by flying south for extended distances. I anticipate that this form of flight must have serious consequences for the fitness levels and life-cycles of migratory birds. Studies looking at reverse migration provide a useful tool for migration monitoring, particularly as it is an underexplored phenomenon. Observations of thousands of birds, many of which are either species at risk or vagrants, collected in an efficient manner are vital for determining population trends related to migratory birds. Continuing this study would aid on-going monitoring programs assessing bird populations passing through the lower Great Lakes region. These studies will also help us understand the impacts of climate and climate change on migratory birds.

Weather radar has long been recognized as a potentially powerful tool for hydrological modelling. A single radar station is able to provide detailed precipitation information over entire watersheds. The operational use of radar in water resources applications, however, has been limited. Interpretation of raw radar data requires several rigorous analytical steps and a solid understanding of the technology. In general, hydrologists’ lack of meteorological background and the persistence of systematic errors within the data, has led to a common mistrust of radar-estimated precipitation values. As part of the Enhanced Nowcasting of Extreme Weather project, researchers at McGill University’s J.S. Marshall Radar Observatory in Montreal have been working to improve real-time quantitative precipitation estimates (QPEs). The aim is to create real-time radar precipitation products for the water resource community that are reliable and properly validated. The validation of QPEs is traditionally based on how well observed measurements agree with data from a precipitation gauge network. Comparisons between radar and precipitation gauge quantities, however, can be misleading. Data from a precipitation gauge network represents a series of single-point observations taken near ground surface. Radar, however, estimates the average rate of precipitation over a given area (i.e. a 1-km grid cell) based on the intensity of reflected microwaves at altitudes exceeding 1 km. Additionally, both measurement techniques are susceptible to a number of sources of error that further confound efforts to compare the two. One of the greatest challenges facing radar meteorologists is the variation in the vertical profile of reflectivity (VPR). A radar unit creates a volumetric scan of the atmosphere by emitting microwave beams at several elevation angles. As a beam travels away from the radar, its distance from ground surface increases. Different precipitation types are sampled at a number of heights (i.e. snow above the 0º C elevation and rain below it) that vary with range. The difficulty lies in estimating the intensity of precipitation at the Earth’s surface, based on measurements taken aloft. Scientists at McGill University have incorporated VPR correction techniques into algorithms used to automatically convert raw radar data into quantitative hydrological products. This thesis evaluates three real-time radar precipitation products from McGill University’s J.S. Marshall Radar Observatory in the context of hydrological modelling. The C0 radar product consists of radar precipitation estimates that are filtered for erroneous data, such as ground clutter and anomalous precipitation. The C2 and C3 radar products use different VPR correction techniques to improve upon the C0 product. The WATFLOOD hydrological model is used to assess the ability of each radar product to estimate precipitation over several watersheds within the McGill radar domain. It is proposed that using a watershed as sample area can reduce the error associated with sampling differences between radar and precipitation gauges and allow for the evaluation of a precipitation product over space and time. The WATFLOOD model is run continuously over a four-year period, using each radar product as precipitation input. Streamflow hydrographs are generated for 39 gauging stations within the radar domain, which includes parts of eastern Ontario, south-western Quebec and northern New York and Vermont, and compared to observed measurements. Streamflows are also modelled using distributed precipitation gauge data from 44 meteorological stations concentrated around the Montreal region. Analysis of select streamflow events reveals that despite the non-ideal placement of precipitation gauges throughout the study area, distributed precipitation gauge data are able to reproduce hydrological events with greater accuracy and consistency than any of the provided radar products. Precipitation estimates within the McGill radar domain are found to only be useful in areas within the Doppler range (120-km) where the radar beam is unobstructed by physiographic or man-made features. Among radar products, the C2 VPR-corrected product performed best during the greatest number of the flood events throughout the study area.

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. Även en sammanställning av två studier kring NordIQ’s styrning av värmesystemet och tappvarmvattnet görs.   En stor del av arbetet har varit att sammanställa och studera insamlad data från bland annat en väderstation. Under den här perioden (våren) är det solen och utomhustemperaturen som har störst påverkan på temperaturen inomhus.   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.   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. Sammanställningen visar att det stämmer. / 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. Also a compilation of two studies about NordIQ´s controlling of the heating system and hot water is done.   A major portion of the work has been to compile and study collected data from among other things a weather station. During this period (spring) the sun and the outdoor temperature have the greatest impact on the indoor temperature.   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.   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. The compilation shows that it´s true.

Weather radar has long been recognized as a potentially powerful tool for hydrological modelling. A single radar station is able to provide detailed precipitation information over entire watersheds. The operational use of radar in water resources applications, however, has been limited. Interpretation of raw radar data requires several rigorous analytical steps and a solid understanding of the technology. In general, hydrologists’ lack of meteorological background and the persistence of systematic errors within the data, has led to a common mistrust of radar-estimated precipitation values. As part of the Enhanced Nowcasting of Extreme Weather project, researchers at McGill University’s J.S. Marshall Radar Observatory in Montreal have been working to improve real-time quantitative precipitation estimates (QPEs). The aim is to create real-time radar precipitation products for the water resource community that are reliable and properly validated. The validation of QPEs is traditionally based on how well observed measurements agree with data from a precipitation gauge network. Comparisons between radar and precipitation gauge quantities, however, can be misleading. Data from a precipitation gauge network represents a series of single-point observations taken near ground surface. Radar, however, estimates the average rate of precipitation over a given area (i.e. a 1-km grid cell) based on the intensity of reflected microwaves at altitudes exceeding 1 km. Additionally, both measurement techniques are susceptible to a number of sources of error that further confound efforts to compare the two. One of the greatest challenges facing radar meteorologists is the variation in the vertical profile of reflectivity (VPR). A radar unit creates a volumetric scan of the atmosphere by emitting microwave beams at several elevation angles. As a beam travels away from the radar, its distance from ground surface increases. Different precipitation types are sampled at a number of heights (i.e. snow above the 0º C elevation and rain below it) that vary with range. The difficulty lies in estimating the intensity of precipitation at the Earth’s surface, based on measurements taken aloft. Scientists at McGill University have incorporated VPR correction techniques into algorithms used to automatically convert raw radar data into quantitative hydrological products. This thesis evaluates three real-time radar precipitation products from McGill University’s J.S. Marshall Radar Observatory in the context of hydrological modelling. The C0 radar product consists of radar precipitation estimates that are filtered for erroneous data, such as ground clutter and anomalous precipitation. The C2 and C3 radar products use different VPR correction techniques to improve upon the C0 product. The WATFLOOD hydrological model is used to assess the ability of each radar product to estimate precipitation over several watersheds within the McGill radar domain. It is proposed that using a watershed as sample area can reduce the error associated with sampling differences between radar and precipitation gauges and allow for the evaluation of a precipitation product over space and time. The WATFLOOD model is run continuously over a four-year period, using each radar product as precipitation input. Streamflow hydrographs are generated for 39 gauging stations within the radar domain, which includes parts of eastern Ontario, south-western Quebec and northern New York and Vermont, and compared to observed measurements. Streamflows are also modelled using distributed precipitation gauge data from 44 meteorological stations concentrated around the Montreal region. Analysis of select streamflow events reveals that despite the non-ideal placement of precipitation gauges throughout the study area, distributed precipitation gauge data are able to reproduce hydrological events with greater accuracy and consistency than any of the provided radar products. Precipitation estimates within the McGill radar domain are found to only be useful in areas within the Doppler range (120-km) where the radar beam is unobstructed by physiographic or man-made features. Among radar products, the C2 VPR-corrected product performed best during the greatest number of the flood events throughout the study area.

The location of the Inter-Tropical Convergence Zone plays an important role in the climatology of tropical regions. Yet, despite its importance, the basic physics that determine the location of the ITCZ are not fully understood. Observational analyses show that, where the cross-equatorial pressure gradient is strong, the maximum convection is not necessarily associated with the highest sea surface temperature,or correspondingly, the lowest sea level pressure. Tomas and Webster (1997) argue that if a strong enough cross-equatorial pressure gradient exists and the system is inertialy unstable, secondary ameliorating circulations will drive strong off-equatorial convection in regions where ITCZ location is determined by low tropospheric dynamics. The observational record is re-examined to test the inertial instability hypothesis using the new ECMWF reanalysis data set. Composite analyses are performed to study the structure of the summer meridional circulation for the tropical Eastern Pacific Ocean and Atlantic Ocean. In agreement with Tomas and Webster theory, we find that the magnitude of the cross-equatorial pressure difference appears to determine the intensity of convection with low values of outgoing longwave radiation always to the north of the zero absolute vorticity line, and the absolute vorticity advection equatorward of the this line. Also the observed oscillation period of the disturbance for the studied regions coincides with theoretical oscillation period of the inertial flow.