Future Climate Projection and Zoning of Extreme Temperature Indices

2021 ◽  
Author(s):  
Mohammad Askari Zadeh ◽  
Gholamali Mozaffari ◽  
Mansoureh Kouhi ◽  
Younes Khosravi
Keyword(s):  
Carbon Dioxide Emissions ◽  
Extreme Temperature ◽  
Extreme Weather Events ◽  
Base Period ◽  
The Past ◽  
Temperature And Precipitation ◽  
Weather Events ◽  
The Future ◽  
Temperature Indices ◽  
Future Climate Projection

Abstract Global warming due to increasing carbon dioxide emissions over the past two centuries has had numerous climatic consequences. The change in the behavior and characteristics of extreme weather events such as temperature and precipitation is one of the consequences that have been of interest to researchers worldwide. In this study, the trend of 3 extreme indices of temperature: SU35, TR20, and DTR over two future periods have been studied using downscaled output of 3 GCMs in Razavi Khorasan province, Iran. The results show that the range of temperature diurnal variation (DTR) at three stations of Mashhad, Torbat-e-Heydarieh and Sabzevar during the base period has been reduced significantly. The trend of the number of summer days with temperatures above 35°C (SU35) in both Mashhad and Sabzevar stations was positive and no significant trend was found at Torbat-e-Heydarieh station. The number of tropical nights index (TR20) also showed a positive and significant increase in the three stations under study. The results showed highly significant changes in temperature extremes. The percentage of changes in SU35 index related to base period (1961–2014) for all three models (CNCM3, HadCM3 and NCCCSM) under A1B and A2 scenarios indicated a significant increase for the future periods of 2011–2030 and 2046–2065. TR20 is also expected to increase significantly during the two future periods. The percentage of changes of DTR into the future is negligible.

scholarly journals The occurrence of extreme monthly temperatures and precipitation in two global regions

2017 ◽  
Author(s):  
◽  
Max James Nunes
Keyword(s):  
Southern Oscillation ◽  
Strong Association ◽  
Extreme Temperature ◽  
Extreme Weather Events ◽  
Data Set ◽  
Temperature And Precipitation ◽  
Weather Events ◽  
Southwest Region ◽  
Regional Temperature ◽  
Central Usa

There has been a lot of focus on the occurrence of extreme weather events and their connection to climate change and variability. Much of this previous work has been related to individual events rather than for mean monthly conditions. This study examined the occurrence of extreme conditions in the monthly temperature and precipitation, and some correlations, for two geographically disparate regions of the Northern Hemisphere. These regions are the central USA (cUSA), and the southwest region of Russia (swRUS). For this research, an extreme temperature event was defined as a month that was three seasonal standard deviations from the period mean. Since precipitation is not normally distributed, the three (two) wettest and driest events of every month were chosen for the cUSA (swRUS) region in order to provide for a data set that was of similar size to the temperature data set for each region. The results demonstrate that in cUSA, there was preference for the occurrence of warm anomalies during periods of mean regional temperature increase and vice versa. For swRUS, there was a preference for the occurrence of cold anomalies early in the data set, and warm anomalies in the later part, although this period is one of steadily increasing mean temperatures for the region. There was a strong association at both locations between extreme months and the phase of the El Nino-Southern Oscillation (ENSO). In both regions, cold monthly anomalies were associated with persistent and strong upstream blocking events. Finally, two case studies are examined for the cUSA region.

scholarly journals Periodicity in Extreme Weather in the ‘Maritime Region’ of Eastern North America

2021 ◽  
Author(s):  
Carling Ruth Walsh ◽  
R. Timothy Patterson
Keyword(s):  
Solar Cycle ◽  
North America ◽  
Extreme Temperature ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Eastern North America ◽  
Quasi Biennial Oscillation ◽  
Temperature And Precipitation ◽  
Weather Events ◽  
Biennial Oscillation

Abstract Spectral and wavelet analysis were used to identify trends and cycles in extreme temperature and precipitation events based on historical data (~100-150 years) from six climate stations within the “Maritime Region” of eastern North America. Many statistically significant climate cycles were identified using both spectral and Morlet wavelet analyses at each of these locations for both extreme high and low temperature and precipitation (rain, snow) data, with periodicities typically ranging from ~ 2–30 years. To assess potential drivers of these cyclical extreme weather events, the records of these events were compared, using cross wavelet analysis, to the climate indices of several teleconnections, including the 11-year Schwabe solar cycle, Atlantic Multidecadal Oscillation, North Atlantic Oscillation, Arctic Oscillation, El Niño Southern Oscillation and the Quasi–Biennial Oscillation. It was found that the 11-year solar cycle had the strongest influence over extreme temperature and precipitation in this region, whereas the remaining oscillations, with the exception the Quasi–Biennial Oscillation, exhibited complex interactions with one another, characterized a variety of both positive and negative modulating effects. The Quasi–Biennial Oscillation was found to drive high–frequency oscillations in extreme weather, particularly extreme precipitation. Overall, the findings of this study indicate that extreme weather events in this region have not substantially increased or decreased in number over time, but have been predominantly influenced by several cyclic climate phenomena.

scholarly journals Evaluating the Dependence between Temperature and Precipitation to Better Estimate the Risks of Concurrent Extreme Weather Events

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Hussein Wazneh ◽  
M. Altaf Arain ◽  
Paulin Coulibaly ◽  
Philippe Gachon
Keyword(s):  
Winter Season ◽  
Extreme Temperature ◽  
Extreme Weather ◽  
Climatic Variables ◽  
Urban Systems ◽  
Extreme Weather Events ◽  
Copula Functions ◽  
Temperature And Precipitation ◽  
Weather Events ◽  
Precipitation And Temperature

Precipitation and temperature are among major climatic variables that are used to characterize extreme weather events, which can have profound impacts on ecosystems and society. Accurate simulation of these variables at the local scale is essential to adapt urban systems and policies to future climatic changes. However, accurate simulation of these climatic variables is difficult due to possible interdependence and feedbacks among them. In this paper, the concept of copulas was used to model seasonal interdependence between precipitation and temperature. Five copula functions were fitted to grid (approximately 10 km × 10 km) climate data from 1960 to 2013 in southern Ontario, Canada. Theoretical and empirical copulas were then compared with each other to select the most appropriate copula family for this region. Results showed that, of the tested copulas, none of them consistently performed the best over the entire region during all seasons. However, Gumbel copula was the best performer during the winter season, and Clayton performed best in the summer. More variability in terms of best copula was found in spring and fall seasons. By examining the likelihoods of concurrent extreme temperature and precipitation periods including wet/cool in the winter and dry/hot in the summer, we found that ignoring the joint distribution and confounding impacts of precipitation and temperature lead to the underestimation of occurrence of probabilities for these two concurrent extreme modes. This underestimation can also lead to incorrect conclusions and flawed decisions in terms of the severity of these extreme events.

scholarly journals Change in mean and extreme temperature at Yingkou station in Northeast China from 1904 to 2017

2021 ◽  
Vol 164 (3-4) ◽  
Author(s):  
Xiaoying Xue ◽  
Guoyu Ren ◽  
Xiubao Sun ◽  
Panfeng Zhang ◽  
Yuyu Ren ◽  
...  
Keyword(s):  
Northeast China ◽  
Extreme Temperature ◽  
Maximum Temperature ◽  
Data Set ◽  
The Past ◽  
Significant Downward Trend ◽  
Cold Events ◽  
Temperature Indices ◽  
Increasing Trends ◽  
Change In Mean

AbstractThe understanding of centennial trends of extreme temperature has been impeded due to the lack of early-year observations. In this paper, we collect and digitize the daily temperature data set of Northeast China Yingkou meteorological station since 1904. After quality control and homogenization, we analyze the changes of mean and extreme temperature in the past 114 years. The results show that mean temperature (Tmean), maximum temperature (Tmax), and minimum temperature (Tmin) all have increasing trends during 1904–2017. The increase of Tmin is the most obvious with the rate of 0.34 °C/decade. The most significant warming occurs in spring and winter with the rate of Tmean reaching 0.32 °C/decade and 0.31 °C/decade, respectively. Most of the extreme temperature indices as defined using absolute and relative thresholds of Tmax and Tmin also show significant changes, with cold events witnessing a more significant downward trend. The change is similar to that reported for global land and China for the past six decades. It is also found that the extreme highest temperature (1958) and lowest temperature (1920) records all occurred in the first half of the whole period, and the change of extreme temperature indices before 1950 is different from that of the recent decades, in particular for diurnal temperature range (DTR), which shows an opposite trend in the two time periods.

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 ◽  
...  
Keyword(s):  
Extreme Events ◽  
Heat Waves ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Low Wind Speed ◽  
Weather Events ◽  
The Us ◽  
The Future ◽  
Compound Events ◽  
Ozone Episodes

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.

scholarly journals Weather Literacy in Times of Climate Change

2020 ◽  
Vol 12 (3) ◽  
pp. 435-452 ◽  
Author(s):  
Nadine Fleischhut ◽  
Stefan M. Herzog ◽  
Ralph Hertwig
Keyword(s):  
Climate Change ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
The Public ◽  
Weather Events ◽  
The Future ◽  
Nationally Representative ◽  
And Migration ◽  
Weather Risks

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.

scholarly journals Projecting Climate Change Impacts on Mediterranean Finfish Production: A Case Study in Greece.

2021 ◽  
Author(s):  
Orestis Stavrakidis-Zachou ◽  
Konstadia Lika ◽  
Panagiotis Anastasiadis ◽  
Nikos Papandroulakis
Keyword(s):  
Climate Change ◽  
Climate Change Impacts ◽  
Population Level ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Mediterranean Country ◽  
Farm Level ◽  
Weather Events ◽  
The Future ◽  
The Individual

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.

scholarly journals Future Temperature Extremes Will Be More Harmful: A New Critical Factor for Improved Forecasts

2019 ◽  
Vol 16 (20) ◽  
pp. 4015 ◽  
Author(s):  
Costas A. Varotsos ◽  
Yuri A. Mazei
Keyword(s):  
Climate Change ◽  
Temperature Change ◽  
Heat Waves ◽  
Extreme Temperature ◽  
Well Being ◽  
Early Warning Systems ◽  
Extreme Weather Events ◽  
Anthropogenic Activity ◽  
Extreme Temperature Events ◽  
The Past

There is increasing evidence that extreme weather events such as frequent and intense cold spells and heat waves cause unprecedented deaths and diseases in both developed and developing countries. Thus, they require extensive and immediate research to limit the risks involved. Average temperatures in Europe in June–July 2019 were the hottest ever measured and attributed to climate change. The problem, however, of a thorough study of natural climate change is the lack of experimental data from the long past, where anthropogenic activity was then very limited. Today, this problem can be successfully resolved using, inter alia, biological indicators that have provided reliable environmental information for thousands of years in the past. The present study used high-resolution quantitative reconstruction data derived from biological records of Lake Silvaplana sediments covering the period 1181–1945. The purpose of this study was to determine whether a slight temperature change in the past could trigger current or future intense temperature change or changes. Modern analytical tools were used for this purpose, which eventually showed that temperature fluctuations were persistent. That is, they exhibit long memory with scaling behavior, which means that an increase (decrease) in temperature in the past was always followed by another increase (decrease) in the future with multiple amplitudes. Therefore, the increase in the frequency, intensity, and duration of extreme temperature events due to climate change will be more pronounced than expected. This will affect human well-being and mortality more than that estimated in today’s modeling scenarios. The scaling property detected here can be used for more accurate monthly to decadal forecasting of extreme temperature events. Thus, it is possible to develop improved early warning systems that will reduce the public health risk at local, national, and international levels.

scholarly journals Evolution of Rhonegletscher, Switzerland, over the past 125 years and in the future: application of an improved flowline model

2007 ◽  
Vol 46 ◽  
pp. 268-274 ◽  
Author(s):  
Shin Sugiyama ◽  
Andreas Bauder ◽  
Conradin Zahno ◽  
Martin Funk
Keyword(s):  
Mass Balance ◽  
Aerial Photographs ◽  
Future Application ◽  
Equilibrium Line Altitude ◽  
Future Evolution ◽  
The Past ◽  
Temperature And Precipitation ◽  
The Future ◽  
Shape Effects ◽  
Precipitation Records

AbstractTo study the past and future evolution of Rhonegletscher, Switzerland, a flowline model was developed to include valley shape effects more accurately than conventional flowband models. In the model, the ice flux at a gridpoint was computed by a two-dimensional ice-flow model applied to the valley cross-section. The results suggested the underestimation of the accumulation area, which seems to be a general problem of flowline modelling arising from the model’s one-dimensional nature. The corrected mass balance was coupled with the equilibrium-line altitude (ELA) change, which was reconstructed for the period 1878–2003 from temperature and precipitation records, to run the model for the past 125 years. The model satisfactorily reproduced both changes in the terminus position and the total ice volume derived from digital elevation models of the surface obtained by analyses of old maps and aerial photographs. This showed the model’s potential to simulate glacier evolution when an accurate mass balance could be determined. The future evolution of Rhonegletscher was evaluated with three mass-balance conditions: the mean for the period 1994–2003, and the most negative (2003) and positive (1978) mass-balance values for the past 50 years. The model predicted volume changes of –18%, –58% and +38% after 50 years for the three conditions, respectively.

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