extreme heat
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Author(s):  
Ethan David Coffel ◽  
Corey Lesk ◽  
Jonathan M Winter ◽  
Erich C Osterberg ◽  
Justin Staller Mankin

Abstract U.S. maize and soy production have increased rapidly since the mid-20th century. While global warming has raised temperatures in most regions over this time period, trends in extreme heat have been smaller over U.S. croplands, reducing crop-damaging high temperatures and benefiting maize and soy yields. Here we show that agricultural intensification has created a crop-climate feedback in which increased crop production cools local climate, further raising crop yields. We find that maize and soy production trends have driven cooling effects approximately as large as greenhouse gas induced warming trends in extreme heat over the central U.S. and substantially reduce them over the southern U.S., benefiting crops in all regions. This reduced warming has boosted maize and soy yields by 3.3 (2.7 – 3.9; 13.7 – 20.0%) and 0.6 (0.4 – 0.7; 7.5 – 13.7%) bu/ac/decade, respectively, between 1981 and 2019. Our results suggest that if maize and soy production growth were to stagnate, the ability of the crop-climate feedback to mask warming would fade, exposing U.S. crops to more harmful heat extremes.


2022 ◽  
Author(s):  
Duarte F. Costa ◽  
Helber B. Gomes ◽  
Maria Cristina L. Silva ◽  
Liming Zhou
Keyword(s):  

Elem Sci Anth ◽  
2022 ◽  
Vol 10 (1) ◽  
Author(s):  
Rachel Licker ◽  
Kristina Dahl ◽  
John T. Abatzoglou

Outdoor workers perform critical societal functions, often despite higher-than-average on-the-job risks and below-average pay. Climate change is expected to increase the frequency of days when it is too hot to safely work outdoors, compounding risks to workers and placing new stressors on the personal, local, state, and federal economies that depend on them. After quantifying the number of outdoor workers in the contiguous United States and their median earnings, we couple heat-based work reduction recommendations from the U.S. Centers for Disease Control and Prevention with an analysis of hourly weather station data to develop novel algorithms for calculating the annual number of unsafe workdays due to extreme heat. We apply these algorithms to projections of the frequency of extreme heat days to quantify the exposure of the outdoor workforce to extreme heat and the associated earnings at risk under different emissions scenarios and, for the first time, different adaptation measures. With a trajectory of modest greenhouse gas emissions reductions, outdoor worker exposure to extreme heat would triple that of the late 20th-century baseline by mid-century, and earnings at risk would reach an estimated $39.3 billion annually. By the late century with that same trajectory, exposure would increase four-fold compared to the baseline with an estimated $49.2 billion in annual earnings at risk. Losses are considerably higher with a limited-mitigation trajectory. While universal adoption of 2 specific adaptation measures in conjunction could reduce mid-century and late-century economic risks by roughly 90% and 93%, respectively, practical limitations to their adoption suggest that emissions mitigation policies will be critical for ensuring the well-being and livelihoods of outdoor workers in a warming climate.


2022 ◽  
Vol 158 ◽  
pp. 106902
Author(s):  
Sara McElroy ◽  
Sindana Ilango ◽  
Anna Dimitrova ◽  
Alexander Gershunov ◽  
Tarik Benmarhnia

Author(s):  
Ana C. Cebrián ◽  
Jesús Asín ◽  
Alan E. Gelfand ◽  
Erin M. Schliep ◽  
Jorge Castillo-Mateo ◽  
...  

AbstractEvidence of global warming induced from the increasing concentration of greenhouse gases in the atmosphere suggests more frequent warm days and heat waves. The concept of an extreme heat event (EHE), defined locally based on exceedance of a suitable local threshold, enables us to capture the notion of a period of persistent extremely high temperatures. Modeling for extreme heat events is customarily implemented using time series of temperatures collected at a set of locations. Since spatial dependence is anticipated in the occurrence of EHE’s, a joint model for the time series, incorporating spatial dependence is needed. Recent work by Schliep et al. (J R Stat Soc Ser A Stat Soc 184(3):1070–1092, 2021) develops a space-time model based on a point-referenced collection of temperature time series that enables the prediction of both the incidence and characteristics of EHE’s occurring at any location in a study region. The contribution here is to introduce a formal definition of the notion of the spatial extent of an extreme heat event and then to employ output from the Schliep et al. (J R Stat Soc Ser A Stat Soc 184(3):1070–1092, 2021) modeling work to illustrate the notion. For a specified region and a given day, the definition takes the form of a block average of indicator functions over the region. Our risk assessment examines extents for the Comunidad Autónoma de Aragón in northeastern Spain. We calculate daily, seasonal and decadal averages of the extents for two subregions in this comunidad. We generalize our definition to capture extents of persistence of extreme heat and make comparisons across decades to reveal evidence of increasing extent over time.


Author(s):  
Suresh Kumar Rathi ◽  
Soham Chakraborty ◽  
Saswat Kishore Mishra ◽  
Ambarish Dutta ◽  
Lipika Nanda

Extreme heat and heat waves have been established as disasters which can lead to a great loss of life. Several studies over the years, both within and outside of India, have shown how extreme heat events lead to an overall increase in mortality. However, the impact of extreme heat, similar to other disasters, depends upon the vulnerability of the population. This study aims to assess the extreme heat vulnerability of the population of four cities with different characteristics across India. This cross-sectional study included 500 households from each city across the urban localities (both slum and non-slum) of Ongole in Andhra Pradesh, Karimnagar in Telangana, Kolkata in West Bengal and Angul in Odisha. Twenty-one indicators were used to construct a household vulnerability index to understand the vulnerability of the cities. The results have shown that the majority of the households fell under moderate to high vulnerability level across all the cities. Angul and Kolkata were found to be more highly vulnerable as compared to Ongole and Karimnagar. Further analysis also revealed that household vulnerability is more significantly related to adaptive capacity than sensitivity and exposure. Heat Vulnerability Index can help in identifying the vulnerable population and scaling up adaptive practices.


Abstract Extreme heat events pose a threat to human health. Forecasting and warning strategies have been developed to mitigate heat-health hazards. Yet, studies have found that the public lacks knowledge about their heat-health risks and preventive actions to take to reduce risks. Local governmental websites are an important means to communicate preparedness to the public. The purpose of this study is to examine information provided to the public on municipal government webpages of the 10 most populous U.S. cities. A two-level document and content analyses were conducted. A direct content analysis was conducted using federal government websites and documents to create the Extreme Heat Event Public Response Rubric. The Rubric contains two broad categories of populations and actions that are further specified. The Rubric was then used to examine local government extreme heat event websites for the 10 most populous cities in the U.S. The examination of the local government sites found that information included on the websites failed to identify the breadth of populations at greater risk for adverse heat-health outcomes and omitted some recommended actions designed to prevent adverse heat-health events. Local governments often communicated concrete and simple content to the public but more complex information was not included on their websites.


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