scholarly journals Impacts of compound extreme weather events on ozone in the present and future

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.

2018 ◽  
Vol 18 (13) ◽  
pp. 9861-9877 ◽  
Author(s):  
Junxi Zhang ◽  
Yang Gao ◽  
Kun Luo ◽  
L. Ruby Leung ◽  
Yang Zhang ◽  
...  

Abstract. The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) was used to study the effect of extreme weather events on ozone in the US for historical (2001–2010) and future (2046–2055) periods under the RCP8.5 scenario. During extreme weather events, including heat waves, atmospheric stagnation, and their compound events, ozone concentration is much higher compared to the non-extreme events period. A striking enhancement of effect during compound events is revealed when heat wave and stagnation occur simultaneously as 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 the 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 with a maximum daily 8 h average (MDA8) ozone concentration over 70 ppbv 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; thus 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.


2020 ◽  
Vol 12 (3) ◽  
pp. 435-452 ◽  
Author(s):  
Nadine Fleischhut ◽  
Stefan M. Herzog ◽  
Ralph Hertwig

AbstractAs climate change unfolds, extreme weather events are on the rise worldwide. According to experts, extreme weather risks already outrank those of terrorism and migration in likelihood and impact. But how well does the public understand weather risks and forecast uncertainty and thus grasp the amplified weather risks that climate change poses for the future? In a nationally representative survey (N = 1004; Germany), we tested the public’s weather literacy and awareness of climate change using 62 factual questions. Many respondents misjudged important weather risks (e.g., they were unaware that UV radiation can be higher under patchy cloud cover than on a cloudless day) and struggled to connect weather conditions to their impacts (e.g., they overestimated the distance to a thunderstorm). Most misinterpreted a probabilistic forecast deterministically, yet they strongly underestimated the uncertainty of deterministic forecasts. Respondents with higher weather literacy obtained weather information more often and spent more time outside but were not more educated. Those better informed about climate change were only slightly more weather literate. Overall, the public does not seem well equipped to anticipate weather risks in the here and now and may thus also fail to fully grasp what climate change implies for the future. These deficits in weather literacy highlight the need for impact forecasts that translate what the weather may be into what the weather may do and for transparent communication of uncertainty to the public. Boosting weather literacy may help to improve the public’s understanding of weather and climate change risks, thereby fostering informed decisions and mitigation support.


2021 ◽  
Author(s):  
Orestis Stavrakidis-Zachou ◽  
Konstadia Lika ◽  
Panagiotis Anastasiadis ◽  
Nikos Papandroulakis

Abstract Finfish aquaculture in the Mediterranean Sea faces increasing challenges due to climate change while potential adaptation requires a robust assessment of the arising threats and opportunities. This paper presents an approach developed to investigate effects of climate drivers on Greek aquaculture, a representative Mediterranean country with a leading role in the sector. Using a farm level approach, Dynamic Energy Budget models for European seabass and meagre were developed and environmental forcing was used to simulate changes in production and farm profitability under IPCC scenarios RCP45 and RCP85. The effects of temperature and extreme weather events at the individual and farm level were considered along with that of husbandry parameters such as stocking timing, market size, and farm location (inshore, offshore) for nine regions. The simulations suggest that at the individual level fish may benefit from warmer temperatures in the future in terms of growth, thus reaching commercial sizes faster, while the husbandry parameters may have as large an effect on growth as the projected shifts in climatic cues. However, this benefit will be largely offset by the adverse effects of extreme weather events at the population level. Such events will be more frequent in the future and, depending on the intensity one assigns to them, they could cause losses in biomass and farm profits that range from mild to detrimental for the industry. Overall, these results provide quantification of some of the potential threats for an important aquaculture sector while suggesting possibilities to benefit from emerging opportunities. Therefore, they could contribute to improving the sector’s readiness for tackling important challenges in the future.


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.


2018 ◽  
Vol 2 (1) ◽  
pp. 9-24
Author(s):  
Edoardo Bertone ◽  
Oz Sahin ◽  
Russell Richards ◽  
Anne Roiko

Abstract A decision support tool was created to estimate the treatment efficiency of an Australian drinking water treatment system based on different combinations of extreme weather events and long-term changes. To deal with uncertainties, missing data, and nonlinear behaviours, a Bayesian network (BN) was coupled with a system dynamics (SD) model. The preliminary conceptual structures of these models were developed through stakeholders' consultation. The BN model could rank extreme events, and combinations of them, based on the severity of their impact on health-related water quality. The SD model, in turn, was used to run a long-term estimation of extreme events' impacts by including temporal factors such as increased water demand and customer feedback. The integration of the two models was performed through a combined Monte Carlo–fuzzy logic approach which allowed to take the BN's outputs as inputs for the SD model. The final product is a participatory, multidisciplinary decision support system allowing for robust, sustainable long-term water resources management under uncertain conditions for a specific location.


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>


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):  
S Vijayakumar ◽  
A.K. Nayak ◽  
N. Manikandan ◽  
Suchismita Pattanaik ◽  
Rahul Tripathi ◽  
...  

Abstract The study investigates trend in extreme daily precipitation and temperature over coastal Odisha, India. 18 weather indices (8 related to temperature and 10 related to rainfall) were calculated using RClimDex software package for the period 1980–2010 . Trend analysis was carried out using linear regression and non-parametric Mann-Kendall test to find out the statistical significance of various indices. Results indicated, a strong and significant trend in temperature indices while the weak and non-significant trend in precipitation indices. The positive trend in Tmax mean, Tmin mean, TN90p (warm nights), TX90p (warm days), diurnal temperature range (DTR), warm spell duration indicator (WSDI), consecutive dry days (CDD) indicates increasing the frequency of warming events in coastal Odisha. Similarly, positive trend in highest maximum 1-day precipitation (RX1), highest maximum 2 consecutive day precipitation (RX2), highest maximum 3 consecutive day precipitation (RX3), highest maximum 5 consecutive day precipitation (RX5), number of heavy precipitation days (≥64.5mm), number of very heavy precipitation days (≥124.5mm) and negative trend in the number of rainy days (R2.5mm), consecutive wet days (CWD) indicate changes toward the more intense and poor distribution of precipitation in coastal Odisha. The combined effect of precipitation and temperature extreme events showed negative effects on rice grain yield. With the increasing number of extreme events there was sharp decline in rice grain yield was observed in the same year in all the coastal districts. This study emphasizes the need for new technology/management practice to minimize the impacts of extreme weather events on rice yield.


PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244512
Author(s):  
Luis Alexis Rodríguez-Cruz ◽  
Meredith T. Niles

Understanding how perceptions around motivation, capacity, and climate change’s impacts relate to the adoption of adaptation practices in light of experiences with extreme weather events is important in assessing farmers’ adaptive capacity. However, very little of this work has occurred in islands, which may have different vulnerabilities and capacities for adaptation. Data of surveyed farmers throughout Puerto Rico after Hurricane Maria (n = 405, 87% response rate) were used in a structural equation model to explore the extent to which their adoption of agricultural practices and management strategies was driven by perceptions of motivation, vulnerability, and capacity as a function of their psychological distance of climate change. Our results show that half of farmers did not adopt any practice or strategy, even though the majority perceived themselves capable and motivated to adapt to climate change, and understood their farms to be vulnerable to future extreme events. Furthermore, adoption was neither linked to these adaptation perceptions, nor to their psychological distance of climate change, which we found to be both near and far. Puerto Rican farmers’ showed a broad awareness of climate change’s impacts both locally and globally in different dimensions (temporal, spatial, and social), and climate distance was not linked to reported damages from Hurricane Maria or to previous extreme weather events. These results suggest that we may be reaching a tipping point for extreme events as a driver for climate belief and action, especially in places where there is a high level of climate change awareness and continued experience of compounded impacts. Further, high perceived capacity and motivation are not linked to actual adaptation behaviors, suggesting that broadening adaptation analyses beyond individual perceptions and capacities as drivers of climate adaptation may give us a better understanding of the determinants to strengthen farmers’ adaptive capacity.


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