Ground-level ozone has long been recognized as an important health and ecosystem-related air qual... more Ground-level ozone has long been recognized as an important health and ecosystem-related air quality concern in Canada and the United States. In this work we seek to understand the characteristics of ground level ozone conditions for Canada and United States to support the Ozone Annex under the Canada-U.S. Air Quality Agreement. Our analyses are based upon the data collected by Canadian National Air Pollution Surveillance (NAPS, the NAPS database has also been expanded to include U.S. EPA ground level ozone data) network. Historical ozone data from 1974 to 2002 at a total of 538 stations (253 Canadian stations and 285 U.S. stations) were statistically analyzed using several methodologies including the Canada Wide Standard (CWS). A more detailed analysis including hourly, daily, monthly, seasonally and yearly ozone concentration distributions and trends was undertaken for 54 stations.
Using within-weather-group air pollution prediction models developed in Part I of this research, ... more Using within-weather-group air pollution prediction models developed in Part I of this research, this study estimates future air pollution levels for a variety of pollutants (specifically, carbon monoxide – CO, nitrogen dioxide – NO2, ozone – O3, sulphur dioxide – SO2, and suspended particles – SP) under future climate scenarios for four cities in south-central Canada. A statistical downscaling method was used to downscale five general circulation model (GCM) scenarios to selected weather stations. Downscaled GCM scenarios were used to compare respective characteristics of the weather groups developed in Part I; discriminant function analysis was used to allocate future days from two windows of time (2040–2059 and 2070–2089) into one of four weather groups. In Part I, the four weather groups were characterised as hot, cold, air pollution-related, and other (defined as relatively good air quality and comfortable weather conditions). In estimating future daily air pollution concentrations, three future pollutant emission scenarios were considered: Scenario I – emissions decreasing 20% by 2050, Scenario II – future emissions remaining at the same level as at the end of the twentieth century, and Scenario III – emissions increasing 20% by 2050. The results showed that, due to increased temperatures, the average annual number of days with high O3 levels in the four selected cities could increase by more than 40–100% by the 2050s and 70–200% by the 2080s (from the current areal average of 8 days) under the three pollutant emission scenarios. The corresponding number of low O3 days could decrease by 4–10% and 5–15% (from the current areal average of 312 days). For the rest of the pollutants, future air pollution levels will depend on future pollutant emission levels. Under emission Scenarios II and III, the average annual number of high pollution days could increase 20–40% and 80–180%, respectively, by the middle and late part of this century. In contrast, under Scenario I, the average annual number of high pollution days could decrease by 10–65%.
... The current study employs the synoptic weather typing and a number of linear and nonlinear re... more ... The current study employs the synoptic weather typing and a number of linear and nonlinear regression techniques to downscale future daily rainfall from large-scale GCM simulations to the ... The downscaling scheme is built upon the previous studies (ie, Cheng et al. ...
Hydrological Sciences Journal-journal Des Sciences Hydrologiques, 2011
Southern Ontario, Canada, has been impacted in recent years by many heavy rainfall and flooding e... more Southern Ontario, Canada, has been impacted in recent years by many heavy rainfall and flooding events that have exceeded existing historical estimates of infrastructure design rainfall intensity–duration–frequency (IDF) values. These recent events and the limited number of short-duration recording raingauges have prompted the need to research the climatology of heavy rainfall events within the study area, review the existing design IDF methodologies, and evaluate alternative approaches to traditional point-based heavy rainfall IDF curves, such as regional IDF design values. The use of additional data and the regional frequency analysis methodology were explored for the study area, with the objective of validating identified clusters or homogeneous regions of extreme rainfall amounts through Ward's method. As the results illustrate, nine homogeneous regions were identified in Southern Ontario using the annual maximum series (AMS) for daily and 24-h rainfall data from climate and rate-of-rainfall or tipping bucket raingauge (TBRG) stations, respectively. In most cases, the generalized extreme value and logistic distributions were identified as the statistical distributions that provide the best fit for the 24-h and sub-daily rainfall data in the study area. A connection was observed between extreme rainfall variability, temporal scale of heavy rainfall events and location of each homogeneous region. Moreover, the analysis indicated that scaling factors cannot be used reliably to estimate sub-daily and sub-hourly values from 24- and 1-h data in Southern Ontario. Citation Paixao, E., Auld, H., Mirza, M.M.Q., Klaassen, J. & Shephard, M.W. (2011) Regionalization of heavy rainfall to improve climatic design values for infrastructure: case study in Southern Ontario, Canada. Hydrol. Sci. J. 56(7), 1067–1089.Au cours des dernières années, le sud de l'Ontario (Canada), a subi les conséquences de nombreux épisodes de fortes pluies et d'inondations, qui ont dépassé les estimations historiques des valeurs des pluies de projet calculées par la méthode intensité–durée–fréquence (IDF). Ces épisodes récents, et le nombre limité de pluviographes enregistreurs à petit pas de temps, ont fait ressortir le besoin de revoir la climatologie des épisodes de fortes pluies dans la région étudiée, de revisiter les méthodologies IDF pour la conception, et d'envisager d'autres approches, comme des courbes IDF régionales, pouvant remplacer les courbes IDF ponctuelles traditionnelles. L'utilisation de la méthodologie d'analyse fréquentielle régionale a été évaluée pour le secteur d'étude, avec, comme objectif, la validation en termes de pluies extrêmes, des regroupements en régions homogènes déterminées par la méthode de Ward. L'analyse a permis d'identifier neuf régions homogènes pour le sud de l'Ontario au moyen de séries de maximums annuels pour les données quotidiennes et horaires de la pluie provenant de stations climatiques et de stations de pluviomètres à augets basculeurs. Dans la plupart des cas, la distribution des valeurs exrêmes généralisée et la distribution logistique généralisée se sont révélées fournir les meilleurs ajustements pour les données de précipitations de 24 h et moins dans la zone d'étude. Une relation a été observée entre la variabilité des précipitations extrêmes, l'échelle temporelle des événements de fortes précipitations et la localisation de chaque région homogène. En outre, l'analyse a indiqué que, dans le Sud de l'Ontario, les facteurs d'échelle ne peuvent pas être utilisés de manière fiable pour estimer les valeurs pour des durées inférieures à 1 ou 24 h à partir, respectivement, de données horaires ou journalières.
Synoptic weather typing and regression-based downscaling approaches have become popular in evalua... more Synoptic weather typing and regression-based downscaling approaches have become popular in evaluating the impacts of climate change on a variety of environmental problems, particularly those involving extreme impacts. One of the reasons for the popularity of these approaches is their ability to categorize a complex set of meteorological variables into a coherent index, facilitating the projection of changes in frequency and intensity of future daily extreme weather events and/or their impacts. This paper illustrated the capability of the synoptic weather typing and regression methods to analyze climatic change impacts on a number of extreme weather events and environmental problems for south-central Canada, such as freezing rain, heavy rainfall, high-/low-streamflow events, air pollution, and human health. These statistical approaches are helpful in analyzing extreme events and projecting their impacts into the future through three major steps or analysis procedures: (1) historical simulation modeling to identify extreme weather events or their impacts, (2) statistical downscaling to provide station-scale future hourly/daily climate data, and (3) projecting changes in the frequency and intensity of future extreme weather events and their impacts under a changing climate. To realize these steps, it is first necessary to conceptualize the modeling of the meteorology, hydrology and impacts model variables of significance and to apply a number of linear/nonlinear regression techniques. Because the climate/weather validation process is critical, a formal model result verification process has been built into each of these three steps. With carefully chosen physically consistent and relevant variables, the results of the verification, based on historical observations of the outcome variables simulated by the models, show a very good agreement in all applications and extremes tested to date. Overall, the modeled results from climate change studies indicate that the frequency and intensity of future extreme weather events and their impacts are generally projected to significantly increase late this century
Journal of Toxicology and Environmental Health-part A-current Issues, 2004
Recent research indicates that excessive rainfall has been a significant contributor to historica... more Recent research indicates that excessive rainfall has been a significant contributor to historical waterborne disease outbreaks. The Meteorological Service of Canada, Environment Canada, provided an analysis and testimony to the Walkerton Inquiry on the excessive rainfall events, including an assessment of the historical significance and expected return periods of the rainfall amounts. While the onset of the majority of the Walkerton, Ontario, Escherichia coli O157:H7 and Campylobacter outbreak occurred several days after a heavy rainfall on May 12, the accumulated 5-d rainfall amounts from 8–12 May were particularly significant. These 5-d accumulations could, on average, only be expected once every 60 yr or more in Walkerton and once every 100 yr or so in the heaviest rainfall area to the south of Walkerton. The significant link between excess rainfall and waterborne disease outbreaks, in conjunction with other multiple risk factors, indicates that meteorological and climatological conditions need to be considered by water managers, public health officials, and private citizens as a significant risk factor for water contamination. A system to identify and project the impacts of such challenging or extreme weather conditions on water supply systems could be developed using a combination of weather/climate monitoring information and weather prediction or quantitative precipitation forecast information. The use of weather monitoring and forecast information or a “wellhead alert system” could alert water system and water supply managers on the potential response of their systems to challenging weather conditions and additional requirements to protect health. Similar approaches have recently been used by beach managers in parts of the United States to predict day-to-day water quality for beach advisories.
Reducing societal vulnerability to weather related disasters under current and changing climate c... more Reducing societal vulnerability to weather related disasters under current and changing climate conditions will require a diverse and interconnected range of adaptive actions. Included among these actions are hazard identification and risk assessment, comprehensive emergency and disaster management, improved predictions of high impact weather, better land use planning, strategic environmental and ecosystem protection, continuously updated and improved climatic design values and changes to infrastructure codes and standards to support disaster resistant infrastructure. These actions will need to be undertaken by all levels of government, by individuals, planners, professional associations and investors. One critical disaster reduction response is that of emergency and disaster preparedness, which involves the development of an emergency response and management capability long before a disaster occurs. The provinces of Ontario and Quebec, in central Canada, have both passed provincial legislation requiring that all municipal and regional governments adopt emergency management planning. In support of these legislated measures in Ontario, Environment Canada along with its partner Emergency Management Ontario, have developed an atmospheric hazards publication and web site that supports municipalities in accessing climatological, extreme weather and air quality information, customizing atmospheric hazards maps for their localities and in linking hazards maps. Maps can be functionally linked through cumulative co-recognition software that allows the user to select specific thresholds per hazard map and to display the cumulative result of regional combinations of hazards. Information on climate trends for the hazards variables is presently available on the site, and future plans for the site include climate change trend projections, where appropriate.
This paper forms the second part of an introduction to a synoptic weather typing approach to asse... more This paper forms the second part of an introduction to a synoptic weather typing approach to assess differential and combined impacts of extreme temperatures and air pollution on human mortality, focusing on future estimates. A statistical downscaling approach was used to downscale daily five general circulation model (GCM) outputs (three Canadian and two US GCMs) and to derive six-hourly future climate information for the selected cities (Montreal, Ottawa, Toronto, and Windsor) in south–central Canada. Discriminant function analysis was then used to project the future weather types, based on historical analysis defined in a companion paper (Part I). Future air pollution concentrations were estimated using the within-weather-type historical simulation models applied to the downscaled future GCM climate data. Two independent approaches, based on (1) comparing future and historical frequencies of the weather groups and (2) applying within-weather-group elevated mortality prediction models, were used to assess climate change impacts on elevated mortality for two time windows (2040–2059 and 2070–2089). Averaging the five GCM scenarios, across the study area, heat-related mortality is projected to be more than double by the 2050s and triple by the 2080s from the current condition. Cold-related mortality could decrease by about 45–60% and 60–70% by the 2050s and the 2080s, respectively. Air pollution-related mortality could increase about 20–30% by the 2050s and 30–45% by the 2080s, due to increased air pollution levels projected with climate change. The increase in air pollution-related mortality would be largely driven by increases in ozone effects. The population acclimatization to increased heat was also assessed in this paper, which could reduce future heat-related mortality by 40%. It is most likely that the estimate of future extreme temperature- and air pollution-related mortality from this study could represent a bottom-line figure since many of the factors (e.g., population growth, age structure changes, and adaptation measures) were not directly taken into account in the analyses.
This paper forms the first part of an introduction to a synoptic weather typing approach to asses... more This paper forms the first part of an introduction to a synoptic weather typing approach to assess differential and combined impacts of extreme temperatures and air pollution on human mortality in south–central Canada, focusing on historical analysis (a companion paper—Part II focusing on future estimates). In this study, an automated synoptic weather typing procedure was used to identify weather types that have a marked association with high air pollution levels and temperature extremes, and facilitates assessments of the differential and combined health impacts of extreme temperatures and air pollution. Annual mean elevated mortality (when daily mortality exceeds the baseline) associated with extreme temperatures and acute exposures to air pollution, based on 1954–2000, was 1,082 [95% confidence interval (CI) of 1,017–1,147] for Montreal, 1,047 (CI 994–1,100) for Toronto, 462 (CI 438–486) for Ottawa, and 327 (CI 311–343) for Windsor. Of this annual mean elevated mortality, extreme temperatures are usually associated with roughly 20%, while air pollution is associated with the remaining 80%. Three pollutants (ozone, sulfur dioxide, and nitrogen dioxide) are associated with approximately 75% of total air pollution-related mortality across the study area. The remaining 25% is almost evenly associated with suspended particles and carbon monoxide, the other two pollutants addressed in this study. Of the five pollutants, ozone is most significantly associated with elevated mortality, making up one-third of the total air pollution-related mortality. PM2.5 and PM10 were not used as a measure of particulate in the study due to brief data records. The study results also suggest that, on the basis of daily mortality risks, extreme temperature-related weather presents a much greater risk to human health during heat waves and cold spells than air pollution. For example, in Montreal and Toronto, daily mean elevated mortality counts within the hottest weather type were twice as high as those within air pollution-related weather types.
A regression-based methodology was used to downscale hourly and daily station-scale meteorologica... more A regression-based methodology was used to downscale hourly and daily station-scale meteorological variables from outputs of large-scale general circulation models (GCMs). Meteorological variables include air temperature, dew point, and west–east and south–north wind velocities at the surface and three upper atmospheric levels (925, 850, and 500 hPa), as well as mean sea-level air pressure and total cloud cover. Different regression methods were used to construct downscaling transfer functions for different weather variables. Multiple stepwise regression analysis was used for all weather variables, except total cloud cover. Cumulative logit regression was employed for analysis of cloud cover, since cloud cover is an ordered categorical data format. For both regression procedures, to avoid multicollinearity between explanatory variables, principal components analysis was used to convert inter-correlated weather variables into uncorrelated principal components that were used as predictors. The results demonstrated that the downscaling method was able to capture the relationship between the premises and the response; for example, most hourly downscaling transfer functions could explain over 95% of the total variance for several variables (e.g. surface air temperature, dew point, and air pressure). Downscaling transfer functions were validated using a cross-validation scheme, and it was concluded that the functions for all weather variables used in the study are reliable. Performance of the downscaling method was also evaluated by comparing data distributions and extreme weather characteristics of downscaled GCM historical runs and observations during the period 1961–2000. The results showed that data distributions of downscaled GCM historical runs for all weather variables are significantly similar to those of observations. In addition, extreme characteristics of the downscaled meteorological variables (e.g. temperature, dew point, air pressure, and total cloud cover) were examined.
In the evening of August 2, 2006, a squall line moved across the southern Ontario cottage country... more In the evening of August 2, 2006, a squall line moved across the southern Ontario cottage country, Canada, from northwest to southeast, spawning at least 8 tornadoes, including two F2 confirmed touchdowns. The damage was extensive, cutting electricity power to more than 175,000 customers and flooding many homes. Some areas experienced more than 100 mm of rainfall. There was extensive wind damage from strong winds and wind gusts of 80 to over 100 km per hour. Using the Canadian operational weather forecast model, GEM-LAM (Global Environmental Multiscale - Limited Area Model), we have simulated the squall line event, in an attempt to highlight at least some of the major mechanisms that produced extreme winds and precipitation associated with the storm. For wind gusts, we employed the physically-based diagnostic parameterization scheme developed by Brasseur (2001), and following Goyette et al. (2003), that allows bringing down to the surface of high momentum air flow in the upper part of the planetary boundary layer. With this parameterization, the model produces results that are within 10-20% of the observed wind gusts. In spring of this year (2008), the cloud microphysical scheme in the model was replaced by the Milbrandt-Yau scheme. For the simulation of the August event, the model produces rainfall rates and accumulated amounts in a range consistent with the observation over the affected region.
Freezing rain is a major atmospheric hazard in mid-latitude nations of the globe. Among all Canad... more Freezing rain is a major atmospheric hazard in mid-latitude nations of the globe. Among all Canadian hydrometeorological hazards, freezing rain is associated with the highest damage costs per event. Using synoptic weather typing to identify the occurrence of freezing rain events, this study estimates changes in future freezing rain events under future climate scenarios for south-central Canada. Synoptic weather typing consists of principal components analysis, an average linkage clustering procedure (i.e., a hierarchical agglomerative cluster method), and discriminant function analysis (a nonhierarchical method). Meteorological data used in the analysis included hourly surface observations from 15 selected weather stations and six atmospheric levels of six-hourly National Centers for Environmental Prediction (NCEP) upper-air reanalysis weather variables for the winter months (November-April) of 1958/59-2000/01. A statistical downscaling method was used to downscale four general circulation model (GCM) scenarios to the selected weather stations. Using downscaled scenarios, discriminant function analysis was used to project the occurrence of future weather types. The within-type frequency of future freezing rain events is assumed to be directly proportional to the change in frequency of future freezing rain-related weather types
Synoptic climatological approaches were used in this study to determine the synergistic impacts o... more Synoptic climatological approaches were used in this study to determine the synergistic impacts of severe weather and air pollution on excess mortality risks in south-central Canada. The derived relationships based on the past and current conditions were then used to determine the potential impacts of climate change on human mortality risks. This study used principal components analysis, an average linkage clustering procedure, and discriminant function analysis to automatically classify distinctive synoptic categories based on the differentiations and similarities of meteorological characteristics between and within weather types. Meteorological data for 1953-2001 were used in the analyses. The data included hourly surface observations of air temperature, dew point temperature, sea-level air pressure, total cloud cover, wind speed and direction. Three atmospheric levels of 6-hourly NCEP-NCAR upper-air reanalysis weather variables (air and dew point temperatures, wind speed and direction) were used for the period 1958-2000. Air pollution data, including O3, SO2, NO2, CO and COH, was retrieved from the National Air Pollution Surveillance (NAPS) network for the period 1974-2000. Mortality data from Statistics Canada included the daily total non-traumatic mortality (e.g., ICD-9: 001-799) for the period 1950-1998. The study area included 3 cities in Ontario (Toronto, Ottawa and Windsor) and 1 city in Quebec (Montreal). Using the above procedures, 14-20 major synoptic types were identified for the selected weather stations during both warm (Apr.-Sep.) and cold seasons (Oct.-Mar.). The statistical procedure was able to successfully identify 8-12 weather types (depending upon location), that were associated with high mortality rates. Excess mortality within the identified synoptic weather types were shown to be associated with temperature extremes (heat and cold) and air pollution. Using GCM outputs and statistical downscaling methods, discriminant function analysis was then used to estimate the projected frequencies of excess mortality-related weather types for future climate scenarios. Climate change scenarios from the Canadian GCMs (CGCM1 and CGCM2) and the U.S. GCM (GFDL R30 Coupled Climate Model) for the periods 2040-2059 and 2070-89 were used in the analysis. For estimation of the future air pollution conditions, there are two methods: 1) discriminant function analysis is able to assess the projected frequencies of weather types associated with high air pollution concentrations for the future climate change scenarios; 2) the downscaled climate change scenarios were applied to the historical regression models to estimate the future projected concentrations. The expected mortality rates due to modeled global warming and pollutant effects for both warm and cold seasons can then be estimated for the selected cities.
The methods used in an earlier study focusing on the province of Ontario, Canada, were adapted fo... more The methods used in an earlier study focusing on the province of Ontario, Canada, were adapted for this current study to expand the study area over eastern Canada where the infrastructure is at risk of being impacted by freezing rain. To estimate possible impacts of climate change on future freezing rain events, a three-step process was used in the study: (1) statistical downscaling, (2) synoptic weather typing, and (3) future projections. A regression-based downscaling approach, constructed using different regression methods for different meteorological variables, was used to downscale the outputs of eight general circulation models to each of 42 hourly observing stations over eastern Canada. Using synoptic weather typing (principal components analysis, a clustering procedure, discriminant function analysis), the freezing rain-related weather types under historical climate (1958–2007) and future downscaled climate conditions (2016–2035, 2046–2065, 2081–2100) were identified for all selected stations. The potential changes in the frequency of future daily freezing rain events can be projected quantitatively by comparing future and historical frequencies of freezing rain-related weather types.The modelled results show that eastern Canada could experience more freezing rain events late this century during the coldest months (i.e., December to February) than the averaged historical conditions. Conversely, during the warmest months of the study season (i.e., November and April in the southern regions, October in the northern regions), eastern Canada could experience less freezing rain events late this century. The increase in the number of daily freezing rain events in the future for the coldest months is projected to be progressively greater from south to north or from southwest to northeast across eastern Canada. The relative decrease in magnitude of future daily freezing rain events in the warmest months is projected to be much less than the relative increase in magnitude in the coldest months. R ésumé [Traduit par la rédaction] Nous avons adapté pour la présente étude les méthodes utilisées dans une étude précédente concernant l'Ontario, au Canada, afin d'étendre la zone étudiée à l'est du Canada où l'infrastructure risque d'être touchée par la pluie verglaçante. Pour estimer les répercussions possibles du changement climatique sur les événements de pluie verglaçante futurs, nous avons adopté un processus en trois étapes dans cette étude : (1) la réduction statistique, (2) le typage des conditions synoptiques et (3) les projections dans le futur. Nous avons employé une méthode de réduction basée sur la régression, construite à l'aide de différentes techniques de régression pour différentes variables météorologiques, pour réduire les sorties de huit modèles de circulation générale à chacune de 42 stations d'observations horaires dans l'est du Canada. Au moyen du typage des conditions synoptiques (analyse des composantes principales, une procédure d'agrégation, analyse discriminante), nous avons identifié les types météorologiques liés à la pluie verglaçante dans le climat historique (1958–2007) et les conditions climatiques réduites futures (2016–2035, 2046–2065, 2081–2100) pour toutes les stations sélectionnées. Les changements potentiels dans la fréquence future des jours avec pluie verglaçante peuvent être projetés quantitativement en comparant les fréquences futures et historiques des types météorologiques liés à la pluie verglaçante.Les résultats modélisés montrent que l'est du Canada pourrait subir plus d'événements de pluie verglaçante dans la dernière partie du présent siècle durant les mois les plus froids (c.-à-d. de décembre à février) que ce qu'indiquent les conditions historiques moyennées. Réciproquement, durant les mois les plus chauds de la saison à l'étude (c.-à-d. novembre et avril dans les régions méridionales; octobre dans les régions septentrionales), l'est du Canada pourrait subir moins d'événements de pluie verglaçante dans la dernière partie du siècle. En se déplaçant du sud vers le nord ou du sud-ouest vers le nord-est dans l'est du Canada, il est prévu que l'accroissement du nombre d'événements de pluie verglaçante durant les mois les plus froids ira en grandissant. La diminution relative du nombre d'événements futurs de pluie verglaçante durant les mois les plus chauds devrait être beaucoup moins importante que son accroissement relatif durant les mois les plus froids.
Ground-level ozone has long been recognized as an important health and ecosystem-related air qual... more Ground-level ozone has long been recognized as an important health and ecosystem-related air quality concern in Canada and the United States. In this work we seek to understand the characteristics of ground level ozone conditions for Canada and United States to support the Ozone Annex under the Canada-U.S. Air Quality Agreement. Our analyses are based upon the data collected by Canadian National Air Pollution Surveillance (NAPS, the NAPS database has also been expanded to include U.S. EPA ground level ozone data) network. Historical ozone data from 1974 to 2002 at a total of 538 stations (253 Canadian stations and 285 U.S. stations) were statistically analyzed using several methodologies including the Canada Wide Standard (CWS). A more detailed analysis including hourly, daily, monthly, seasonally and yearly ozone concentration distributions and trends was undertaken for 54 stations.
Using within-weather-group air pollution prediction models developed in Part I of this research, ... more Using within-weather-group air pollution prediction models developed in Part I of this research, this study estimates future air pollution levels for a variety of pollutants (specifically, carbon monoxide – CO, nitrogen dioxide – NO2, ozone – O3, sulphur dioxide – SO2, and suspended particles – SP) under future climate scenarios for four cities in south-central Canada. A statistical downscaling method was used to downscale five general circulation model (GCM) scenarios to selected weather stations. Downscaled GCM scenarios were used to compare respective characteristics of the weather groups developed in Part I; discriminant function analysis was used to allocate future days from two windows of time (2040–2059 and 2070–2089) into one of four weather groups. In Part I, the four weather groups were characterised as hot, cold, air pollution-related, and other (defined as relatively good air quality and comfortable weather conditions). In estimating future daily air pollution concentrations, three future pollutant emission scenarios were considered: Scenario I – emissions decreasing 20% by 2050, Scenario II – future emissions remaining at the same level as at the end of the twentieth century, and Scenario III – emissions increasing 20% by 2050. The results showed that, due to increased temperatures, the average annual number of days with high O3 levels in the four selected cities could increase by more than 40–100% by the 2050s and 70–200% by the 2080s (from the current areal average of 8 days) under the three pollutant emission scenarios. The corresponding number of low O3 days could decrease by 4–10% and 5–15% (from the current areal average of 312 days). For the rest of the pollutants, future air pollution levels will depend on future pollutant emission levels. Under emission Scenarios II and III, the average annual number of high pollution days could increase 20–40% and 80–180%, respectively, by the middle and late part of this century. In contrast, under Scenario I, the average annual number of high pollution days could decrease by 10–65%.
... The current study employs the synoptic weather typing and a number of linear and nonlinear re... more ... The current study employs the synoptic weather typing and a number of linear and nonlinear regression techniques to downscale future daily rainfall from large-scale GCM simulations to the ... The downscaling scheme is built upon the previous studies (ie, Cheng et al. ...
Hydrological Sciences Journal-journal Des Sciences Hydrologiques, 2011
Southern Ontario, Canada, has been impacted in recent years by many heavy rainfall and flooding e... more Southern Ontario, Canada, has been impacted in recent years by many heavy rainfall and flooding events that have exceeded existing historical estimates of infrastructure design rainfall intensity–duration–frequency (IDF) values. These recent events and the limited number of short-duration recording raingauges have prompted the need to research the climatology of heavy rainfall events within the study area, review the existing design IDF methodologies, and evaluate alternative approaches to traditional point-based heavy rainfall IDF curves, such as regional IDF design values. The use of additional data and the regional frequency analysis methodology were explored for the study area, with the objective of validating identified clusters or homogeneous regions of extreme rainfall amounts through Ward's method. As the results illustrate, nine homogeneous regions were identified in Southern Ontario using the annual maximum series (AMS) for daily and 24-h rainfall data from climate and rate-of-rainfall or tipping bucket raingauge (TBRG) stations, respectively. In most cases, the generalized extreme value and logistic distributions were identified as the statistical distributions that provide the best fit for the 24-h and sub-daily rainfall data in the study area. A connection was observed between extreme rainfall variability, temporal scale of heavy rainfall events and location of each homogeneous region. Moreover, the analysis indicated that scaling factors cannot be used reliably to estimate sub-daily and sub-hourly values from 24- and 1-h data in Southern Ontario. Citation Paixao, E., Auld, H., Mirza, M.M.Q., Klaassen, J. & Shephard, M.W. (2011) Regionalization of heavy rainfall to improve climatic design values for infrastructure: case study in Southern Ontario, Canada. Hydrol. Sci. J. 56(7), 1067–1089.Au cours des dernières années, le sud de l'Ontario (Canada), a subi les conséquences de nombreux épisodes de fortes pluies et d'inondations, qui ont dépassé les estimations historiques des valeurs des pluies de projet calculées par la méthode intensité–durée–fréquence (IDF). Ces épisodes récents, et le nombre limité de pluviographes enregistreurs à petit pas de temps, ont fait ressortir le besoin de revoir la climatologie des épisodes de fortes pluies dans la région étudiée, de revisiter les méthodologies IDF pour la conception, et d'envisager d'autres approches, comme des courbes IDF régionales, pouvant remplacer les courbes IDF ponctuelles traditionnelles. L'utilisation de la méthodologie d'analyse fréquentielle régionale a été évaluée pour le secteur d'étude, avec, comme objectif, la validation en termes de pluies extrêmes, des regroupements en régions homogènes déterminées par la méthode de Ward. L'analyse a permis d'identifier neuf régions homogènes pour le sud de l'Ontario au moyen de séries de maximums annuels pour les données quotidiennes et horaires de la pluie provenant de stations climatiques et de stations de pluviomètres à augets basculeurs. Dans la plupart des cas, la distribution des valeurs exrêmes généralisée et la distribution logistique généralisée se sont révélées fournir les meilleurs ajustements pour les données de précipitations de 24 h et moins dans la zone d'étude. Une relation a été observée entre la variabilité des précipitations extrêmes, l'échelle temporelle des événements de fortes précipitations et la localisation de chaque région homogène. En outre, l'analyse a indiqué que, dans le Sud de l'Ontario, les facteurs d'échelle ne peuvent pas être utilisés de manière fiable pour estimer les valeurs pour des durées inférieures à 1 ou 24 h à partir, respectivement, de données horaires ou journalières.
Synoptic weather typing and regression-based downscaling approaches have become popular in evalua... more Synoptic weather typing and regression-based downscaling approaches have become popular in evaluating the impacts of climate change on a variety of environmental problems, particularly those involving extreme impacts. One of the reasons for the popularity of these approaches is their ability to categorize a complex set of meteorological variables into a coherent index, facilitating the projection of changes in frequency and intensity of future daily extreme weather events and/or their impacts. This paper illustrated the capability of the synoptic weather typing and regression methods to analyze climatic change impacts on a number of extreme weather events and environmental problems for south-central Canada, such as freezing rain, heavy rainfall, high-/low-streamflow events, air pollution, and human health. These statistical approaches are helpful in analyzing extreme events and projecting their impacts into the future through three major steps or analysis procedures: (1) historical simulation modeling to identify extreme weather events or their impacts, (2) statistical downscaling to provide station-scale future hourly/daily climate data, and (3) projecting changes in the frequency and intensity of future extreme weather events and their impacts under a changing climate. To realize these steps, it is first necessary to conceptualize the modeling of the meteorology, hydrology and impacts model variables of significance and to apply a number of linear/nonlinear regression techniques. Because the climate/weather validation process is critical, a formal model result verification process has been built into each of these three steps. With carefully chosen physically consistent and relevant variables, the results of the verification, based on historical observations of the outcome variables simulated by the models, show a very good agreement in all applications and extremes tested to date. Overall, the modeled results from climate change studies indicate that the frequency and intensity of future extreme weather events and their impacts are generally projected to significantly increase late this century
Journal of Toxicology and Environmental Health-part A-current Issues, 2004
Recent research indicates that excessive rainfall has been a significant contributor to historica... more Recent research indicates that excessive rainfall has been a significant contributor to historical waterborne disease outbreaks. The Meteorological Service of Canada, Environment Canada, provided an analysis and testimony to the Walkerton Inquiry on the excessive rainfall events, including an assessment of the historical significance and expected return periods of the rainfall amounts. While the onset of the majority of the Walkerton, Ontario, Escherichia coli O157:H7 and Campylobacter outbreak occurred several days after a heavy rainfall on May 12, the accumulated 5-d rainfall amounts from 8–12 May were particularly significant. These 5-d accumulations could, on average, only be expected once every 60 yr or more in Walkerton and once every 100 yr or so in the heaviest rainfall area to the south of Walkerton. The significant link between excess rainfall and waterborne disease outbreaks, in conjunction with other multiple risk factors, indicates that meteorological and climatological conditions need to be considered by water managers, public health officials, and private citizens as a significant risk factor for water contamination. A system to identify and project the impacts of such challenging or extreme weather conditions on water supply systems could be developed using a combination of weather/climate monitoring information and weather prediction or quantitative precipitation forecast information. The use of weather monitoring and forecast information or a “wellhead alert system” could alert water system and water supply managers on the potential response of their systems to challenging weather conditions and additional requirements to protect health. Similar approaches have recently been used by beach managers in parts of the United States to predict day-to-day water quality for beach advisories.
Reducing societal vulnerability to weather related disasters under current and changing climate c... more Reducing societal vulnerability to weather related disasters under current and changing climate conditions will require a diverse and interconnected range of adaptive actions. Included among these actions are hazard identification and risk assessment, comprehensive emergency and disaster management, improved predictions of high impact weather, better land use planning, strategic environmental and ecosystem protection, continuously updated and improved climatic design values and changes to infrastructure codes and standards to support disaster resistant infrastructure. These actions will need to be undertaken by all levels of government, by individuals, planners, professional associations and investors. One critical disaster reduction response is that of emergency and disaster preparedness, which involves the development of an emergency response and management capability long before a disaster occurs. The provinces of Ontario and Quebec, in central Canada, have both passed provincial legislation requiring that all municipal and regional governments adopt emergency management planning. In support of these legislated measures in Ontario, Environment Canada along with its partner Emergency Management Ontario, have developed an atmospheric hazards publication and web site that supports municipalities in accessing climatological, extreme weather and air quality information, customizing atmospheric hazards maps for their localities and in linking hazards maps. Maps can be functionally linked through cumulative co-recognition software that allows the user to select specific thresholds per hazard map and to display the cumulative result of regional combinations of hazards. Information on climate trends for the hazards variables is presently available on the site, and future plans for the site include climate change trend projections, where appropriate.
This paper forms the second part of an introduction to a synoptic weather typing approach to asse... more This paper forms the second part of an introduction to a synoptic weather typing approach to assess differential and combined impacts of extreme temperatures and air pollution on human mortality, focusing on future estimates. A statistical downscaling approach was used to downscale daily five general circulation model (GCM) outputs (three Canadian and two US GCMs) and to derive six-hourly future climate information for the selected cities (Montreal, Ottawa, Toronto, and Windsor) in south–central Canada. Discriminant function analysis was then used to project the future weather types, based on historical analysis defined in a companion paper (Part I). Future air pollution concentrations were estimated using the within-weather-type historical simulation models applied to the downscaled future GCM climate data. Two independent approaches, based on (1) comparing future and historical frequencies of the weather groups and (2) applying within-weather-group elevated mortality prediction models, were used to assess climate change impacts on elevated mortality for two time windows (2040–2059 and 2070–2089). Averaging the five GCM scenarios, across the study area, heat-related mortality is projected to be more than double by the 2050s and triple by the 2080s from the current condition. Cold-related mortality could decrease by about 45–60% and 60–70% by the 2050s and the 2080s, respectively. Air pollution-related mortality could increase about 20–30% by the 2050s and 30–45% by the 2080s, due to increased air pollution levels projected with climate change. The increase in air pollution-related mortality would be largely driven by increases in ozone effects. The population acclimatization to increased heat was also assessed in this paper, which could reduce future heat-related mortality by 40%. It is most likely that the estimate of future extreme temperature- and air pollution-related mortality from this study could represent a bottom-line figure since many of the factors (e.g., population growth, age structure changes, and adaptation measures) were not directly taken into account in the analyses.
This paper forms the first part of an introduction to a synoptic weather typing approach to asses... more This paper forms the first part of an introduction to a synoptic weather typing approach to assess differential and combined impacts of extreme temperatures and air pollution on human mortality in south–central Canada, focusing on historical analysis (a companion paper—Part II focusing on future estimates). In this study, an automated synoptic weather typing procedure was used to identify weather types that have a marked association with high air pollution levels and temperature extremes, and facilitates assessments of the differential and combined health impacts of extreme temperatures and air pollution. Annual mean elevated mortality (when daily mortality exceeds the baseline) associated with extreme temperatures and acute exposures to air pollution, based on 1954–2000, was 1,082 [95% confidence interval (CI) of 1,017–1,147] for Montreal, 1,047 (CI 994–1,100) for Toronto, 462 (CI 438–486) for Ottawa, and 327 (CI 311–343) for Windsor. Of this annual mean elevated mortality, extreme temperatures are usually associated with roughly 20%, while air pollution is associated with the remaining 80%. Three pollutants (ozone, sulfur dioxide, and nitrogen dioxide) are associated with approximately 75% of total air pollution-related mortality across the study area. The remaining 25% is almost evenly associated with suspended particles and carbon monoxide, the other two pollutants addressed in this study. Of the five pollutants, ozone is most significantly associated with elevated mortality, making up one-third of the total air pollution-related mortality. PM2.5 and PM10 were not used as a measure of particulate in the study due to brief data records. The study results also suggest that, on the basis of daily mortality risks, extreme temperature-related weather presents a much greater risk to human health during heat waves and cold spells than air pollution. For example, in Montreal and Toronto, daily mean elevated mortality counts within the hottest weather type were twice as high as those within air pollution-related weather types.
A regression-based methodology was used to downscale hourly and daily station-scale meteorologica... more A regression-based methodology was used to downscale hourly and daily station-scale meteorological variables from outputs of large-scale general circulation models (GCMs). Meteorological variables include air temperature, dew point, and west–east and south–north wind velocities at the surface and three upper atmospheric levels (925, 850, and 500 hPa), as well as mean sea-level air pressure and total cloud cover. Different regression methods were used to construct downscaling transfer functions for different weather variables. Multiple stepwise regression analysis was used for all weather variables, except total cloud cover. Cumulative logit regression was employed for analysis of cloud cover, since cloud cover is an ordered categorical data format. For both regression procedures, to avoid multicollinearity between explanatory variables, principal components analysis was used to convert inter-correlated weather variables into uncorrelated principal components that were used as predictors. The results demonstrated that the downscaling method was able to capture the relationship between the premises and the response; for example, most hourly downscaling transfer functions could explain over 95% of the total variance for several variables (e.g. surface air temperature, dew point, and air pressure). Downscaling transfer functions were validated using a cross-validation scheme, and it was concluded that the functions for all weather variables used in the study are reliable. Performance of the downscaling method was also evaluated by comparing data distributions and extreme weather characteristics of downscaled GCM historical runs and observations during the period 1961–2000. The results showed that data distributions of downscaled GCM historical runs for all weather variables are significantly similar to those of observations. In addition, extreme characteristics of the downscaled meteorological variables (e.g. temperature, dew point, air pressure, and total cloud cover) were examined.
In the evening of August 2, 2006, a squall line moved across the southern Ontario cottage country... more In the evening of August 2, 2006, a squall line moved across the southern Ontario cottage country, Canada, from northwest to southeast, spawning at least 8 tornadoes, including two F2 confirmed touchdowns. The damage was extensive, cutting electricity power to more than 175,000 customers and flooding many homes. Some areas experienced more than 100 mm of rainfall. There was extensive wind damage from strong winds and wind gusts of 80 to over 100 km per hour. Using the Canadian operational weather forecast model, GEM-LAM (Global Environmental Multiscale - Limited Area Model), we have simulated the squall line event, in an attempt to highlight at least some of the major mechanisms that produced extreme winds and precipitation associated with the storm. For wind gusts, we employed the physically-based diagnostic parameterization scheme developed by Brasseur (2001), and following Goyette et al. (2003), that allows bringing down to the surface of high momentum air flow in the upper part of the planetary boundary layer. With this parameterization, the model produces results that are within 10-20% of the observed wind gusts. In spring of this year (2008), the cloud microphysical scheme in the model was replaced by the Milbrandt-Yau scheme. For the simulation of the August event, the model produces rainfall rates and accumulated amounts in a range consistent with the observation over the affected region.
Freezing rain is a major atmospheric hazard in mid-latitude nations of the globe. Among all Canad... more Freezing rain is a major atmospheric hazard in mid-latitude nations of the globe. Among all Canadian hydrometeorological hazards, freezing rain is associated with the highest damage costs per event. Using synoptic weather typing to identify the occurrence of freezing rain events, this study estimates changes in future freezing rain events under future climate scenarios for south-central Canada. Synoptic weather typing consists of principal components analysis, an average linkage clustering procedure (i.e., a hierarchical agglomerative cluster method), and discriminant function analysis (a nonhierarchical method). Meteorological data used in the analysis included hourly surface observations from 15 selected weather stations and six atmospheric levels of six-hourly National Centers for Environmental Prediction (NCEP) upper-air reanalysis weather variables for the winter months (November-April) of 1958/59-2000/01. A statistical downscaling method was used to downscale four general circulation model (GCM) scenarios to the selected weather stations. Using downscaled scenarios, discriminant function analysis was used to project the occurrence of future weather types. The within-type frequency of future freezing rain events is assumed to be directly proportional to the change in frequency of future freezing rain-related weather types
Synoptic climatological approaches were used in this study to determine the synergistic impacts o... more Synoptic climatological approaches were used in this study to determine the synergistic impacts of severe weather and air pollution on excess mortality risks in south-central Canada. The derived relationships based on the past and current conditions were then used to determine the potential impacts of climate change on human mortality risks. This study used principal components analysis, an average linkage clustering procedure, and discriminant function analysis to automatically classify distinctive synoptic categories based on the differentiations and similarities of meteorological characteristics between and within weather types. Meteorological data for 1953-2001 were used in the analyses. The data included hourly surface observations of air temperature, dew point temperature, sea-level air pressure, total cloud cover, wind speed and direction. Three atmospheric levels of 6-hourly NCEP-NCAR upper-air reanalysis weather variables (air and dew point temperatures, wind speed and direction) were used for the period 1958-2000. Air pollution data, including O3, SO2, NO2, CO and COH, was retrieved from the National Air Pollution Surveillance (NAPS) network for the period 1974-2000. Mortality data from Statistics Canada included the daily total non-traumatic mortality (e.g., ICD-9: 001-799) for the period 1950-1998. The study area included 3 cities in Ontario (Toronto, Ottawa and Windsor) and 1 city in Quebec (Montreal). Using the above procedures, 14-20 major synoptic types were identified for the selected weather stations during both warm (Apr.-Sep.) and cold seasons (Oct.-Mar.). The statistical procedure was able to successfully identify 8-12 weather types (depending upon location), that were associated with high mortality rates. Excess mortality within the identified synoptic weather types were shown to be associated with temperature extremes (heat and cold) and air pollution. Using GCM outputs and statistical downscaling methods, discriminant function analysis was then used to estimate the projected frequencies of excess mortality-related weather types for future climate scenarios. Climate change scenarios from the Canadian GCMs (CGCM1 and CGCM2) and the U.S. GCM (GFDL R30 Coupled Climate Model) for the periods 2040-2059 and 2070-89 were used in the analysis. For estimation of the future air pollution conditions, there are two methods: 1) discriminant function analysis is able to assess the projected frequencies of weather types associated with high air pollution concentrations for the future climate change scenarios; 2) the downscaled climate change scenarios were applied to the historical regression models to estimate the future projected concentrations. The expected mortality rates due to modeled global warming and pollutant effects for both warm and cold seasons can then be estimated for the selected cities.
The methods used in an earlier study focusing on the province of Ontario, Canada, were adapted fo... more The methods used in an earlier study focusing on the province of Ontario, Canada, were adapted for this current study to expand the study area over eastern Canada where the infrastructure is at risk of being impacted by freezing rain. To estimate possible impacts of climate change on future freezing rain events, a three-step process was used in the study: (1) statistical downscaling, (2) synoptic weather typing, and (3) future projections. A regression-based downscaling approach, constructed using different regression methods for different meteorological variables, was used to downscale the outputs of eight general circulation models to each of 42 hourly observing stations over eastern Canada. Using synoptic weather typing (principal components analysis, a clustering procedure, discriminant function analysis), the freezing rain-related weather types under historical climate (1958–2007) and future downscaled climate conditions (2016–2035, 2046–2065, 2081–2100) were identified for all selected stations. The potential changes in the frequency of future daily freezing rain events can be projected quantitatively by comparing future and historical frequencies of freezing rain-related weather types.The modelled results show that eastern Canada could experience more freezing rain events late this century during the coldest months (i.e., December to February) than the averaged historical conditions. Conversely, during the warmest months of the study season (i.e., November and April in the southern regions, October in the northern regions), eastern Canada could experience less freezing rain events late this century. The increase in the number of daily freezing rain events in the future for the coldest months is projected to be progressively greater from south to north or from southwest to northeast across eastern Canada. The relative decrease in magnitude of future daily freezing rain events in the warmest months is projected to be much less than the relative increase in magnitude in the coldest months. R ésumé [Traduit par la rédaction] Nous avons adapté pour la présente étude les méthodes utilisées dans une étude précédente concernant l'Ontario, au Canada, afin d'étendre la zone étudiée à l'est du Canada où l'infrastructure risque d'être touchée par la pluie verglaçante. Pour estimer les répercussions possibles du changement climatique sur les événements de pluie verglaçante futurs, nous avons adopté un processus en trois étapes dans cette étude : (1) la réduction statistique, (2) le typage des conditions synoptiques et (3) les projections dans le futur. Nous avons employé une méthode de réduction basée sur la régression, construite à l'aide de différentes techniques de régression pour différentes variables météorologiques, pour réduire les sorties de huit modèles de circulation générale à chacune de 42 stations d'observations horaires dans l'est du Canada. Au moyen du typage des conditions synoptiques (analyse des composantes principales, une procédure d'agrégation, analyse discriminante), nous avons identifié les types météorologiques liés à la pluie verglaçante dans le climat historique (1958–2007) et les conditions climatiques réduites futures (2016–2035, 2046–2065, 2081–2100) pour toutes les stations sélectionnées. Les changements potentiels dans la fréquence future des jours avec pluie verglaçante peuvent être projetés quantitativement en comparant les fréquences futures et historiques des types météorologiques liés à la pluie verglaçante.Les résultats modélisés montrent que l'est du Canada pourrait subir plus d'événements de pluie verglaçante dans la dernière partie du présent siècle durant les mois les plus froids (c.-à-d. de décembre à février) que ce qu'indiquent les conditions historiques moyennées. Réciproquement, durant les mois les plus chauds de la saison à l'étude (c.-à-d. novembre et avril dans les régions méridionales; octobre dans les régions septentrionales), l'est du Canada pourrait subir moins d'événements de pluie verglaçante dans la dernière partie du siècle. En se déplaçant du sud vers le nord ou du sud-ouest vers le nord-est dans l'est du Canada, il est prévu que l'accroissement du nombre d'événements de pluie verglaçante durant les mois les plus froids ira en grandissant. La diminution relative du nombre d'événements futurs de pluie verglaçante durant les mois les plus chauds devrait être beaucoup moins importante que son accroissement relatif durant les mois les plus froids.
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