scholarly journals Analysis of the impacts of extreme weather events on Ontario’s electricity grid using agent-based modeling

2021 ◽  
Author(s):  
Ailiya Saeed

Extreme weather events have increased and are causing severe impacts on the electricity grid. Heat waves and ice storms are becoming more intense and frequent in Ontario, Canada. During an extreme weather event, the electricity demand fluctuates and the reliability of the electrical grid decreases due to equipment failure and shortage of electricity supply, which leads to blackouts. An initial stage simulation model is developed using the computational technique agent-based model. This thesis analyzed the impact of extreme weather events based on severity and frequency levels on two sector of Ontario’s electricity grid which are generation plants and distribution network. The simulation output showed multiple grid failures in different regions during extreme severity levels and increased frequencies of weather events. The model also showed heat waves and ice storms resulting differently depending on the month, extreme temperature months were more prone to failures than average temperature months.

2021 ◽  
Author(s):  
Ailiya Saeed

Extreme weather events have increased and are causing severe impacts on the electricity grid. Heat waves and ice storms are becoming more intense and frequent in Ontario, Canada. During an extreme weather event, the electricity demand fluctuates and the reliability of the electrical grid decreases due to equipment failure and shortage of electricity supply, which leads to blackouts. An initial stage simulation model is developed using the computational technique agent-based model. This thesis analyzed the impact of extreme weather events based on severity and frequency levels on two sector of Ontario’s electricity grid which are generation plants and distribution network. The simulation output showed multiple grid failures in different regions during extreme severity levels and increased frequencies of weather events. The model also showed heat waves and ice storms resulting differently depending on the month, extreme temperature months were more prone to failures than average temperature months.


Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 133 ◽  
Author(s):  
Lijun Liu ◽  
Yuanqiao Wen ◽  
Youjia Liang ◽  
Fan Zhang ◽  
Tiantian Yang

The impact of extreme weather events on the navigation environment in the inland waterways of the Yangtze River is an interdisciplinary hotspot in subjects of maritime traffic safety and maritime meteorology, and it is also a difficult point for the implementation of decision-making and management by maritime and meteorological departments in China. The objective of this study is to review the variation trends and distribution patterns in the periods of adverse and extreme weather events that are expected to impact on inland waterways transport (IWT) on the Yangtze River. The frequency of severe weather events, together with the changes in their spatial extension and intensity, is analyzed based on the ERA-Interim datasets (1979–2017) and the GHCNDEX dataset (1979–2017), as well as the research progresses and important events (2004–2016) affecting the navigation environment. The impacts of extreme weather events on IWT accidents and phenomena of extreme weather (e.g., thunderstorms, lightning, hail, and tornadoes) that affect the navigation environment are also analyzed and discussed. The results show that: (1) the sections located in the plain climate zone is affected by extreme weather in every season, especially strong winds and heat waves; (2) the sections located in the hilly mountain climate zone is affected particularly by spring extreme phenomena, especially heat waves; (3) the sections located in the Sichuan Basin climate zone is dominated by the extreme weather phenomena in autumn, except cold waves; (4) the occurrence frequency of potential flood risk events is relatively high under rainstorm conditions and wind gusts almost affect the navigation environment of the Jiangsu and Shanghai sections in every year; (5) the heat wave indices (TXx, TR, and WSDI) tend to increase and the temperature of the coldest day of the year gradually increases; (6) the high occurrences of IWT accidents need to be emphasized by relevant departments, caused by extreme weather during the dry season; and (7) the trends and the degree of attention of extreme weather events affecting IWT are ranked as: heat wave > heavy rainfall > wind gust > cold spell > storm. Understanding the seasonal and annual frequency of occurrence of extreme weather events has reference significance for regional management of the Yangtze River.


2011 ◽  
Vol 17 (2) ◽  
pp. 141 ◽  
Author(s):  
Denis A Saunders ◽  
Peter Mawson ◽  
Rick Dawson

Carnaby’s Black Cockatoo is an endangered species which has undergone a dramatic decline in range and abundance in southwestern Australia. Between October 2009 and March 2010 the species was subjected to a possible outbreak of disease in one of its major breeding areas and exposed to an extremely hot day and a severe localized hail storm. In addition, collisions with motor vehicles are becoming an increasing threat to the species. All of these stochastic events resulted in many fatalities. Species such as Carnaby’s Black Cockatoo which form large flocks are particularly susceptible to localized events such as hail storms, contagious disease and collisions with motor vehicles. Extreme temperatures may have major impacts on both flocking and non-flocking species. Predictions of climate change in the southwest of Western Australia are that there will be an increased frequency of extreme weather events such as heat waves and severe hail storms. The implications of more events of this nature on Carnaby’s Black Cockatoo are discussed.


2021 ◽  
Author(s):  
Sanaz Moghim ◽  
Mohammad Sina Jahangir

Abstract Extreme weather events such as heat waves and cold spells affect people’s lives. This study uses a probabilistic framework to evaluate heat waves and cold spells in different regions (Tehran in Iran and Vancouver in Canada). Average daily temperatures of meteorological stations of the two cities from 1995 to 2016 are used to identify four main indicators including intensity, average intensity, duration, and the rate of the occurrence. In addition, average intensities of the events are obtained from the MODIS Land Surface Temperature (LST) in each pixel of the two cities. To include possible uncertainties, the predictive probability distributions of the intensity and duration are derived using a Bayesian scheme and Monte-Carlo Markov Chain (MCMC) method. The probability distributions of the indicators show that the most extreme temperature (lowest temperature) occurs during the cold spell. Results indicate that although Tehran is more probable to experience heat waves than Vancouver, both cities are more likely to be affected by the cold spell than the heat wave. The developed approach can be used to characterize other extreme weather events in any location.


2018 ◽  
Vol 69 (7) ◽  
pp. 703 ◽  
Author(s):  
Robert Mangani ◽  
Eyob Tesfamariam ◽  
Gianni Bellocchi ◽  
Abubeker Hassen

This study assessed two versions of the crop model CropSyst (i.e. EMS, existing; MMS, modified) for their ability to simulate maize (Zea mays L.) yield in South Africa. MMS algorithms explicitly account for the impact of extreme weather events (droughts, heat waves, cold shocks, frost) on leaf development and yield formation. The case study of this research was at an experimental station near Johannesburg where both versions of the model were calibrated and validated by using field data collected from 2004 to 2008. The comparison of EMS and MMS showed considerable difference between the two model versions during extreme drought and heat events. MMS improved grain-yield prediction by ~30% compared with EMS, demonstrating a better ability to capture the behaviour of stressed crops under a range of conditions. MMS also showed a greater variability in response when both versions were forced with scenarios of projected climate change, with increased severity of drought and increased temperature conditions at the horizons 2030 and 2050, which could drive decreased maize yield. Yield was even lower with MMS (8 v. 11 t ha–1 for EMS) at the horizon 2050, relative to the baseline scenario (~13 t ha–1 at the horizon 2000). Modelling solutions accounting for the impact of extreme weather events can be seen as a promising tool for supporting agricultural management strategies and policy decisions in South Africa and globally.


2018 ◽  
Author(s):  
Junxi Zhang ◽  
Yang Gao ◽  
Kun Luo ◽  
L. Ruby Leung ◽  
Yang Zhang ◽  
...  

Abstract. The Weather Research and Forecasting model with Chemistry (WRF/Chem) was used to study the effect of extreme weather events on ozone in US for historical (2001–2010) and future (2046–2055) periods under RCP8.5 scenario. During extreme weather events, including heat waves, atmospheric stagnation, and their compound events, ozone concentration is much higher compared to non-extreme events period. A striking enhancement of effect during compound events is revealed when heat wave and stagnation occur simultaneously and both high temperature and low wind speed promote the production of high ozone concentrations. In regions with high emissions, compound extreme events can shift the high-end tails of the probability density functions (PDFs) of ozone to even higher values to generate extreme ozone episodes. In regions with low emissions, extreme events can still increase high ozone frequency but the high-end tails of the PDFs are constrained by the low emissions. Despite large anthropogenic emission reduction projected for the future, compound events increase ozone more than the single events by 10 % to 13 %, comparable to the present, and high ozone episodes are not eliminated. Using the CMIP5 multi-model ensemble, the frequency of compound events is found to increase more dominantly compared to the increased frequency of single events in the future over the US, Europe, and China. High ozone episodes will likely continue in the future due to increases in both frequency and intensity of extreme events, despite reductions in anthropogenic emissions of its precursors. However, the latter could reduce or eliminate extreme ozone episodes, so improving projections of compound events and their impacts on extreme ozone may better constrain future projections of extreme ozone episodes that have detrimental effects on human health.


2019 ◽  
Vol 32 (2) ◽  
pp. 244-266
Author(s):  
Edimilson Costa Lucas ◽  
Wesley Mendes-Da-Silva ◽  
Gustavo Silva Araujo

Purpose Managing the risks associated to world food production is an important challenge for governments. A range of factors, among them extreme weather events, has threatened food production in recent years. The purpose of this paper is to analyse the impact of extreme rainfall events on the food industry in Brazil, a prominent player in this industry. Design/methodology/approach The authors use the AR-GARCH-GPD hybrid methodology to identify whether extreme rainfall affects the stock price of food companies. To do so, the authors collected the daily closing price of the 16 food industry companies listed on the Brazilian stock exchange (B3), in January 2015. Findings The results indicate that these events have a significant impact on stock returns: on more than half of the days immediately following the heavy rain that fell between 28 February 2005 and 30 December 2014, returns were significantly low, leading to average daily losses of 1.97 per cent. These results point to the relevance of the need for instruments to hedge against weather risk, particularly in the food industry. Originality/value Given that extreme weather events have been occurring more and more frequently, financial literature has documented attempts at assessing the economic impacts of weather changes. There is little research, however, into assessing the impacts of these events at corporate level.


2020 ◽  
Author(s):  
Keh-Jian Shou

<p>Due to active tectonic activity, the rock formations are young and highly fractured in Taiwan area. The dynamic changing of river morphology makes the highly weathered formations or colluviums prone to landslide and debris flow. For the past decade, the effect of climate change is significant and creates more and more extreme weather events. The change of rainfall behavior significantly changes the landslide behavior, which makes the large-scale landslides, like the Shiaolin landslide, possible. Therefore, it is necessary to develop the new technologies for landslide investigation, monitoring, analysis, early warning, etc.</p><p>Since the landslide hazards in Taiwan area are mainly induced by heavy rainfall, due to climate change and the subsequent extreme weather events, the probability of landslides is also increased. Focusing on the upstreams of the watersheds in Central Taiwan, this project studied the behavior and hazard of shallow and deep-seated landslides. Different types of susceptibility models in different catchment scales were tested, in which the control factors were analyzed and discussed. This study also employs rainfall frequency analysis together with the atmospheric general circulation model (AGCM) downscaling estimation to predict the extreme rainfalls in the future. Such that the future hazard of the shallow and deep-seated landslide in the study area can be predicted. The results of predictive analysis can be applied for risk prevention and management in the study area.</p>


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