scholarly journals An Independent Assessment of Anthropogenic Attribution Statements for Recent Extreme Temperature and Rainfall Events

2017 ◽  
Vol 30 (1) ◽  
pp. 5-16 ◽  
Author(s):  
Oliver Angélil ◽  
Dáithí Stone ◽  
Michael Wehner ◽  
Christopher J. Paciorek ◽  
Harinarayan Krishnan ◽  
...  
Keyword(s):  
Climate Model ◽  
Extreme Temperature ◽  
Extreme Weather ◽  
Data Sources ◽  
Extreme Weather Events ◽  
Systematic Bias ◽  
American Meteorological Society ◽  
Extreme Precipitation Events ◽  
Weather Events ◽  
Event Attribution

The annual “State of the Climate” report, published in the Bulletin of the American Meteorological Society (BAMS), has included a supplement since 2011 composed of brief analyses of the human influence on recent major extreme weather events. There are now several dozen extreme weather events examined in these supplements, but these studies have all differed in their data sources as well as their approaches to defining the events, analyzing the events, and the consideration of the role of anthropogenic emissions. This study reexamines most of these events using a single analytical approach and a single set of climate model and observational data sources. In response to recent studies recommending the importance of using multiple methods for extreme weather event attribution, results are compared from these analyses to those reported in the BAMS supplements collectively, with the aim of characterizing the degree to which the lack of a common methodological framework may or may not influence overall conclusions. Results are broadly similar to those reported earlier for extreme temperature events but disagree for a number of extreme precipitation events. Based on this, it is advised that the lack of comprehensive uncertainty analysis in recent extreme weather attribution studies is important and should be considered when interpreting results, but as yet it has not introduced a systematic bias across these studies.

scholarly journals On the attribution of the impacts of extreme weather events to anthropogenic climate change

2021 ◽  
Author(s):  
Sarah E Perkins-Kirkpatrick ◽  
Daithi Stone ◽  
Dann M. Mitchell ◽  
Suzanne M. Rosier ◽  
Andrew David King ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Anthropogenic Impacts ◽  
Extreme Weather ◽  
Anthropogenic Climate Change ◽  
Extreme Weather Events ◽  
Climate Change Signal ◽  
Care Needs ◽  
Weather Events ◽  
The Impact

Abstract Investigations into the role of anthropogenic climate change in extreme weather events are now starting to extend into analysis of anthropogenic impacts on non-climate (e.g. socio-economic) systems. However, care needs to be taken when making this extension, because methodological choices regarding extreme weather attribution can become crucial when considering the events’ impacts. The fraction of attributable risk (FAR) method, useful in extreme weather attribution research, has a very specific interpretation concerning a class of events, and there is potential to misinterpret results from weather event analyses as being applicable to specific events and their impact outcomes. Using two case studies of meteorological extremes and their impacts, we argue that FAR is not generally appropriate when estimating the magnitude of the anthropogenic signal behind a specific impact. Attribution assessments on impacts should always be carried out in addition to assessment of the associated meteorological event, since it cannot be assumed that the anthropogenic signal behind the weather is equivalent to the signal behind the impact because of lags and nonlinearities in the processes through which the impact system reacts to weather. Whilst there are situations where employing FAR to understand the climate change signal behind a class of impacts is useful (e.g. “system breaking” events), more useful results will generally be produced if attribution questions on specific impacts are reframed to focus on changes in the impact return value and magnitude across large samples of factual and counterfactual climate model and impact simulations. We advocate for constant interdisciplinary collaboration as essential for effective and robust impact attribution assessments.

scholarly journals Reliability Framework for Characterizing Heat Wave and Cold Spell Events

2021 ◽  
Author(s):  
Sanaz Moghim ◽  
Mohammad Sina Jahangir
Keyword(s):  
Heat Wave ◽  
Heat Waves ◽  
Probability Distributions ◽  
Extreme Temperature ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Average Intensity ◽  
Cold Spell ◽  
Weather Events ◽  
Two Cities

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.

Measuring the Impact of Insurance on Recovery after Extreme Weather Events Using Nightlights

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Sally Owen ◽  
Ilan Noy ◽  
Jacob Pástor-Paz ◽  
David Fleming
Keyword(s):  
Extreme Rainfall ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Property Damage ◽  
Night Time ◽  
Extreme Precipitation Events ◽  
Weather Events ◽  
Using Data ◽  
The Impact ◽  
Precipitation Events

Abstract Climate change is predicted to make extreme weather events worse and more frequent in many places around the world. In New Zealand, the Earthquake Commission (EQC) was created to provide insurance for earthquakes. In some circumstances, however, homeowners affected by extreme weather events can also make claims to the EQC – for landslip, storm or flood events. In this paper, we explore the impact of this public natural hazard insurance on recovery from weather-related events. We do this by using a proxy for short-term economic recovery: satellite imagery of average monthly night-time radiance. Linking these night-time light data to precipitation data records, we compare areas which experienced damage from extreme rainfall episodes to those that suffered no damage even though they experienced extreme rainfall. Using data from three recent intense storms, we find that areas that experienced property damage, and were paid in a timely manner by EQC, did not fare any worse than areas that suffered no property damage but were exposed to these extreme precipitation events. This finding suggests that EQC insurance is serving its stated purpose by protecting claimants from the adverse impact of extreme weather events.

scholarly journals Stakeholder Perspectives on the Attribution of Extreme Weather Events: An Explorative Enquiry

2015 ◽  
Vol 7 (3) ◽  
pp. 224-237 ◽  
Author(s):  
Sebastian Sippel ◽  
Peter Walton ◽  
Friederike E. L. Otto
Keyword(s):  
Extreme Weather ◽  
Extreme Weather Events ◽  
Southeast Europe ◽  
Stakeholder Perspectives ◽  
Weather Events ◽  
Event Attribution ◽  
Potential Applications ◽  
Key Aspects ◽  
Depth Interviews

Abstract Recent extreme weather events and their impacts on societies have highlighted the need for timely adaptation to the changing odds of their occurrence. Such measures require appropriate information about likely changes in event frequency and magnitude on relevant spatiotemporal scales. However, to support robust climate information for decision-making, an effective communication between scientists and stakeholders is crucial. In this context, weather event attribution studies are increasingly raising attention beyond academic circles, although the understanding of how to take it beyond academia is still evolving. This paper presents the results of a study that involved in-depth interviews with stakeholders from a range of sectors about potential applications and the general usefulness of event attribution studies. A case study of the hot and dry summer 2012 in southeast Europe is used as a concrete example, with a focus on the applicability of attribution results across sectors. An analysis of the interviews reveals an abundant interest among the interviewed stakeholders and highlights the need for information on the causes and odds of extreme events, in particular on regional scales. From this data key aspects of stakeholder engagement are emerging, which could productively feed back into how probabilistic event attribution studies are designed and communicated to ensure practical relevance and usefulness for the stakeholder community.

scholarly journals Multi-thousand member ensemble atmospheric simulations with global 60km resolution using climateprediction.net

2020 ◽  
Author(s):  
Peter Watson ◽  
Sarah Sparrow ◽  
William Ingram ◽  
Simon Wilson ◽  
Drouard Marie ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Atmospheric Model ◽  
Computing System ◽  
Extreme Weather ◽  
Global Climate Models ◽  
Extreme Weather Events ◽  
Weather Events ◽  
The Impact

<p>Multi-thousand member climate model simulations are highly valuable for showing how extreme weather events will change as the climate changes, using a physically-based approach. However, until now, studies using such an approach have been limited to using models with a resolution much coarser than the most modern systems. We have developed a global atmospheric model with 5/6°x5/9° resolution (~60km in middle latitudes) that can be run in the climateprediction.net distributed computing system to produce such large datasets. This resolution is finer than that of many current global climate models and sufficient for good simulation of extratropical synoptic features such as storms. It will also allow many extratropical extreme weather events to be simulated without requiring regional downscaling. We will show that this model's simulation of extratropical weather is competitive with that in other current models. We will also present results from the first multi-thousand member ensembles produced at this resolution, showing the impact of 1.5°C and 2°C global warming on extreme winter rainfall and extratropical cyclones in Europe.</p>

scholarly journals Impacts of climatic variables on cyclone in the coastal regions of Bangladesh

2016 ◽  
Vol 27 (3) ◽  
pp. 272-284
Author(s):  
MAM Hossen ◽  
MA Farukh ◽  
MS Hossen ◽  
MA Badhan ◽  
S Biswas ◽  
...  
Keyword(s):  
Monsoon Season ◽  
Extreme Temperature ◽  
Extreme Weather ◽  
Coastal Areas ◽  
Climatic Variables ◽  
Extreme Weather Events ◽  
Statistical Tool ◽  
Profound Influence ◽  
Weather Events ◽  
Study Results

Geographical position of Bangladesh makes it vulnerable to several extreme weather events like cyclone in the southern part due to extreme climatological events. Therefore, in this study, we had mainly tried to study on the variations of temperature, relative humidity (RH) and sunshine hours (SH) in the coastal areas to find out its effect on the formation of cyclone. Data from 1975-2014 of these climatic variables was provided by the Bangladesh Meteorological Department (BMD) and analyzed with the statistical tool MS Excel 2010 as per objective of the study. Results showed that in the16 stations, temperature has shown homogenous trend where it has seen that in all the stations the Tmean and Tmax were ranging from 180C to 300C and 280C to 420C respectively. In maximum stations, the Tmax and extreme Tmean has found in the months of April and May which is a cyclone occurring month. Again RHmax has mostly found in the post monsoon season where RHmean is ranging 84~88% mainly in the Khulna, Mongla, Khepupara and Barisal areas, may have profound influence on the formation of cyclone especially in this area. SHmax has found in the month April where the highest was about 12.08 hr. These higher amounts of temperature play profound influence in increasing temperature in the studied areas which have direct consequences on cyclone events. So, extreme temperature, RH and SH in these months may had profound influence on the formation of cyclone. These information could be very useful to the related scientists to study on several extreme weather events due to variation of temperature especially on cyclogenesis which are a most common devastating phenomenon for the coastal areas like Bangladesh.Progressive Agriculture 27 (3): 272-284, 2016

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 Projected changes in persistent extreme summer weather events: The role of quasi-resonant amplification

2018 ◽  
Vol 4 (10) ◽  
pp. eaat3272 ◽  
Author(s):  
Michael E. Mann ◽  
Stefan Rahmstorf ◽  
Kai Kornhuber ◽  
Byron A. Steinman ◽  
Sonya K. Miller ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Coupled Model ◽  
High Amplitude ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Anthropogenic Aerosols ◽  
Pronounced Increase ◽  
Weather Events

Persistent episodes of extreme weather in the Northern Hemisphere summer have been associated with high-amplitude quasi-stationary atmospheric Rossby waves, with zonal wave numbers 6 to 8 resulting from the phenomenon of quasi-resonant amplification (QRA). A fingerprint for the occurrence of QRA can be defined in terms of the zonally averaged surface temperature field. Examining state-of-the-art [Coupled Model Intercomparison Project Phase 5 (CMIP5)] climate model projections, we find that QRA events are likely to increase by ~50% this century under business-as-usual carbon emissions, but there is considerable variation among climate models. Some predict a near tripling of QRA events by the end of the century, while others predict a potential decrease. Models with amplified Arctic warming yield the most pronounced increase in QRA events. The projections are strongly dependent on assumptions regarding the nature of changes in radiative forcing associated with anthropogenic aerosols over the next century. One implication of our findings is that a reduction in midlatitude aerosol loading could actually lead to Arctic de-amplification this century, ameliorating potential increases in persistent extreme weather events.

scholarly journals Interpreting climate model projections of extreme weather events

2015 ◽  
Vol 10 ◽  
pp. 10-28 ◽  
Author(s):  
Stephen J. Vavrus ◽  
Michael Notaro ◽  
David J. Lorenz
Keyword(s):  
Climate Model ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Weather Events

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.

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