Description: Publication date: Available online 5 April 2018 Source: Weather and Climate Extremes Author(s): N. Herold, M. Ekström, J. Kala, J. Goldie, J.P. Evans The negative impacts of climate extremes on socioeconomic sectors in Australia makes understanding their behaviour under future climate change necessary for regional planning. Providing robust and actionable climate information at regional scales relies on the downscaling of global climate model data and its translation into impact-relevant information. The New South Wales/Australian Capital Territory Regional Climate Modelling (NARCliM) project contains downscaled climate data over all of Australia at a 50 km resolution, with ensembles of simulations for the recent past (1990–2009), near future (2020–2039) and far future (2060–2079). Here we calculate and examine sector-relevant indices of climate extremes recommended by the Expert Team on Sector-specific Climate Indices (ET-SCI). We demonstrate the utility of NARCliM and the ET-SCI indices in understanding how future changes in climate extremes could impact aspects of the health and agricultural sectors in Australia. Consistent with previous climate projections, our results indicate that increases in heat and drought related extremes throughout the 21st century will occur. In the far future, maximum day time temperatures are projected to increase by up to 3.5 °C depending on season and location. The number of heatwaves and the duration of the most intense heatwaves will increase significantly in the near and far future, with greater increases in the north than south. All capital cities are projected to experience at least a tripling of heatwave days each year by the far future, compared to the recent past. Applying published heat-health relationships to projected changes in temperature shows that increases in mortality due to high temperatures for all cities examined would occur if projected future climates occurred today. Drought and the number of days above 30 °C are also projected to increase over the major wheat-growing regions of the country, particularly during spring when sensitivity of wheat to heat stress is greatest. Assuming no adaptation or acclimatisation, published statistical relationships between drought and national wheat yield suggest that national yields will have a less than one quarter chance of exceeding the annual historical average under far future precipitation change (excluding impacts of future temperature change and CO 2 fertilization). The NARCliM data examined here, along with the ET-SCI indices calculated, provide a powerful and publicly available dataset for regional planning against future changes in climate extremes.

Description: Publication date: Available online 4 April 2018 Source: Weather and Climate Extremes Author(s): Michael Wehner, Dáithí Stone, Hideo Shiogama, Piotr Wolski, Andrew Ciavarella, Nikolaos Christidis, Harinarayan Krishnan We examine the effect of the 20th and recent 21st century anthropogenic climate change on high temperature extremes as simulated by four global atmospheric general circulation models submitted to the Climate of the 20th Century Plus Detection and Attribution project. This coordinated experiment is based upon two large ensembles simulations for each participating model. The “world that was” simulations are externally forced as realistically as possible. The “world that might have been” is identical except that the influence of human forcing is removed but natural forcing agents and variations in ocean and sea ice are retained. We apply a stationary generalized extreme value analysis to the annual maxima of the three day average of the daily maximum surface air temperature, finding that long period return values have been increased by human activities between 1 and 3 °C over most land areas. Corresponding changes in the probability of achieving long period non-industrial return values in the industrialized world are also presented. We find that most regions experience increases in the frequency and intensity of extremely hot three day periods, but anthropogenic sulfate aerosol forcing changes locally can decrease these measures of heat waves in some models.

Description: Publication date: Available online 3 April 2018 Source: Weather and Climate Extremes Author(s): Yeon-Hee Kim, Seung-Ki Min, Dáithí A. Stone, Hideo Shiogama, Piotr Wolski To assess the anthropogenic influence on the summer 2013 heat wave in Korea, this study employed a fraction of attributable risk (FAR) approach to three Atmospheric General Circulation Models (AGCMs) with a large ensemble simulation, participating in the C20C+ Detection and Attribution Project. Monthly and daily temperatures were compared between two experiments. The real world (ALL) experiments were simulated under the observed variations in sea surface temperature, sea ice, greenhouse gas, and aerosol concentrations, while the counterfactual world (NAT) experiments were performed under adjusted boundary conditions by removing anthropogenic warming and with preindustrial levels of greenhouse gases and aerosols. Results from the three AGCMs consistently show that anthropogenic influences had an important role in the extreme heat event over Korea, increasing the chance of the occurrence of extreme warming in summer mean temperature as observed in 2013 by at least 20 times, which supports results from the Coupled Model Intercomparison Project Phase 5 (CMIP5) coupled GCMs (CGCMs). A comparison of individual CMIP5 CGCMs suggests that inter-model difference in FAR values is highly correlated with the amplitude of surface warming centered over Korea, which is also supported by the three AGCMs. Further analysis of individual forcing experiments suggests that the inter-model difference in the regional surface warming is closely linked to the model's response to the aerosol forcing, with stronger influence than that of greenhouse gas forcing. Anthropogenic influences also result in a 5–6 times greater likelihood of extreme daily heat events as observed in 2013, which supports a robust mean-extreme relation in the attribution of extreme heat waves. Generally good agreement between AGCM and CGCM results increases the robustness of the conclusion of anthropogenic influences on the summer 2013 Korean heat wave.

Description: Publication date: Available online 29 March 2018 Source: Weather and Climate Extremes Author(s): Ana Lopez, Erin Coughlan de Perez, Juan Bazo, Pablo Suarez, Bart van den Hurk, Marteen van Aalst Empirical evidence shows that acting on early warnings can help humanitarian organizations reduce losses, damages and suffering while reducing costs. Available forecasts of extreme events can provide the information required to automatically trigger preparedness measures, while ‘value of information’ approaches can, in principle, guide the selection of forecast thresholds that make early action preferable to inaction. We acknowledge here that, for real-world humanitarian situations, the value of information approach accurately estimates the value of forecasts only if key factors relevant for the humanitarian sector are taken into account. First, the negative consequences of acting in vain are significant and must be factored in. Secondly, the “most valuable” forecast thresholds depend on criteria beyond expenses reduction, and this choice must be explicitly considered in funding mechanisms for early warning products and services. Two options to guide this selection are examined: a maximizing criterion for cost effectiveness, and a satisficing criterion for loss avoidance. Third, decision-makers must be able to confidently assess whether the forecast threshold they are selecting is robust to all possible cost/loss structures for the action in question. Based on these considerations, we explore the application of the valuation approach to select which forecasts (magnitude, probability and lead time) should trigger humanitarian actions. Using a basic example of ensemble precipitation forecast to prepare for potential floods, we discuss how the valuation approach can be used to select probability thresholds that trigger early action, and some of the generalisations required to make this applicable to a wider range of humanitarian situations.

Description: Publication date: Available online 22 March 2018 Source: Weather and Climate Extremes Author(s): Sourav Mukherjee, Saran Aadhar, Daithi Stone, Vimal Mishra India has witnessed some of the most devastating extreme precipitation events, which have affected urban transportation, agriculture, and infrastructure. Despite the profound implications and damage due to extreme precipitation events, the influence of anthropogenic warming on the intensity and frequency of extreme precipitation events over India remains poorly constrained. Here using the gridded observations and simulations from the Coupled model intercomparison project 5 (CMIP5) and Climate of 20th century plus (C20C+) detection and attribution (D&A) project, we show that the frequency and intensity of extreme precipitation events have increased in India during the last few decades. Along with the extreme precipitation, dew point temperature has also increased during 1979–2015. The scaling relationship between extreme precipitation and dew point temperature shows a super (more than 7% increase per unit rise in dew point temperature) Clausius-Clapeyron (C-C) relationship for the majority of south India. Moreover, southern and central India show a higher (10%/°C) scaling relationship than north India (3.5%/°C). Our analysis using the Hist (historic) and HistNat (historic natural) simulations from the CMIP5 and C20C+ projects confirms an increase in the frequency of extreme precipitation events under the anthropogenic warming. Moreover, we show that 1–5 day precipitation maxima at 5–500 year return period increases (10–30%) under the anthropogenic warming. The frequency of precipitation extremes is projected to rise more prominently in southern and central India in the mid and end of the 21st century under the representative concentration pathway (RCP) 8.5. Our results show a significant contribution of anthropogenic warming in the rise of the frequency of extreme precipitation, which has implications for infrastructure, agriculture, and water resources in India.

Description: Publication date: Available online 21 March 2018 Source: Weather and Climate Extremes Author(s): John A. Long, Paul C. Stoy, Tobias Gerken Tornadoes are among the most destructive natural events and occur most frequently in the United States. It is difficult to ascertain if the frequency of tornadoes in the U.S. is increasing because our ability to observe and report tornado occurrence has increased over time. Previous studies have demonstrated that tornado likelihood has shifted toward earlier dates across the south-central United States over the past seven decades, the region sometimes called “Tornado Alley”, if it can be assumed that seasonal observation effort has not shifted over time. It is unclear if such shifts in tornado seasonality have also occurred elsewhere, including the region of the southeastern United States where tornado likelihood has a bimodal annual distribution. We use circular methods to demonstrate that the date of observed peak tornado occurrence during the early tornado season has not changed in the past seven decades. However, the date of peak tornado occurrence during the later tornado season has shifted toward earlier dates by more than a week. The influence of tropical storms had no effect on changes in late-season tornado seasonality. The conclusions are robust with respect to whether tornado counts or tornado days are used as the response variable. Results demonstrate the ongoing need to encourage tornado preparedness in the southeastern U.S., where tornadoes tend to have a higher impact on humans, and to understand the mechanisms that underlie trends in tornado seasonality.

Description: Publication date: March 2018 Source: Weather and Climate Extremes, Volume 19

Description: Publication date: March 2018 Source: Weather and Climate Extremes, Volume 19 Author(s): Sajad Zare, Naser Hasheminejad, Hossein Elahi Shirvan, Rasoul Hemmatjo, Keyvan Sarebanzadeh, Saeid Ahmadi Heat stress negatively influences human health and performance, and leading to lower efficiency in daily activities. The present study sought to examine the relationship between UTCI, other heat indices (SET, PET, PMV, PPD, and WBGT), and environmental parameters. Daily data, encompassing a 12 month period in 2016 (from 6 a.m. to 9 p.m. for each day), were retrieved from the Meteorological Organization of Kerman. The data were fed into SPSS 20, followed by conducting Pearson product moment correlation and linear regression to find the association between UTCI and other heat indices/environmental parameters. Excel 2016 was also utilized to draw the relevant diagrams. Significant correlations were detected between UTCI and other heat indices (SET, PET, PMV, and WBGT). UTCI also was measurably correlated with environmental parameters like dry temperature (P 〈 0.0001). The highest correlation coefficient was observed between UTCI and PET (r = 0.96). UTCI also had strong correlations with WBGT (r = 0.88), SET (r = 0.87), and dry temperature (r = 0.90). Thus, indices that are calculated based on body thermal equation (i.e. SET and PET) are more strongly connected with UTCI, registering a better slope. On the other hand, WBGT is more similar to UTCI (than other indices) in terms of thermal perception.

Description: Publication date: Available online 1 March 2018 Source: Weather and Climate Extremes Author(s): Nelson B. Villoria, Bowen Chen Simultaneous worldwide crop failures stemming from a more unstable climate may reduce the scope for international trade to compensate food shortages and stabilize food prices across the various regions of the world. Understanding the effects of changes in crop productivity on global markets requires knowledge about the extent to which crop yields may be systematically related across producing and consuming centers. This short communication contributes to this knowledge by investigating the potential changes in the strength of two key sources of supply risks in global maize markets: yield variance and cross-country yield correlation. We focus on the largest producing and consuming countries of the world. We capitalize on yield projections from the Global Gridded Crop Model Intercomparison project. Exploratory analysis of the skill of the underlying GGCMI models in reproducing key moments of the distribution of observed yields reveals that they overstate observed variances but faithfully reproduce observed patterns of cross-country correlations. We find no evidence of an increase in the degree of cross-country dependency of maize yields. We also find a higher incidence of what would be considered extremely low maize yields by present-time standards stemming from the projected downward trend in yields levels toward mid-century. The weak dependency of maize yields across countries, an the possibility of reducing the higher incidence of extremes through policies aimed to reverse the climate-induced downward trends in yields, suggest that international trade can become a valuable tool to ameliorate the effects of more unstable crop yields.

Description: Publication date: Available online 13 February 2018 Source: Weather and Climate Extremes Author(s): Dáithí A. Stone, Mark D. Risser, Oliver M. Angélil, Michael F. Wehner, Shreyas Cholia, Noel Keen, Harinarayan Krishnan, Travis A. O'Brien, William D. Collins This paper presents two contributions for research into better understanding the role of anthropogenic warming in extreme weather. The first contribution is the generation of a large number of multi-decadal simulations using a medium-resolution atmospheric climate model, CAM5.1-1degree, under two scenarios of historical climate following the protocols of the C20C+ Detection and Attribution project: the one we have experienced (All-Hist), and one that might have been experienced in the absence of human interference with the climate system (Nat-Hist). These simulations are specifically designed for understanding extreme weather and atmospheric variability in the context of anthropogenic climate change. The second contribution takes advantage of the duration and size of these simulations in order to identify features of variability in the prescribed ocean conditions that may strongly influence calculated estimates of the role of anthropogenic emissions on extreme weather frequency (event attribution). There is a large amount of uncertainty in how much anthropogenic emissions should warm regional ocean surface temperatures, yet contributions to the C20C+ Detection and Attribution project and similar efforts so far use only one or a limited number of possible estimates of the ocean warming attributable to anthropogenic emissions when generating their Nat-Hist simulations. Thus, the importance of the uncertainty in regional attributable warming estimates to the results of event attribution studies is poorly understood. The identification of features of the anomalous ocean state that seem to strongly influence event attribution estimates should therefore be able to serve as a basis set for effective sampling of other plausible attributable warming patterns. The identification performed in this paper examines monthly temperature and precipitation output from the CAM5.1-1degree simulations averaged over 237 land regions, and compares interannual anomalous variations in the ratio between the frequencies of extremes in the All-Hist and Nat-Hist simulations against variations in ocean temperatures.