Increasing probability of mortality during Indian heat waves

Mazdiyasni, Omid; AghaKouchak, Amir; Davis, Steven J.; Madadgar, Shahrbanou; Mehran, Ali; Ragno, Elisa; Sadegh, Mojtaba; Sengupta, Abhronil; Ghosh, Subimal; Dhanya, C. T.; Niknejad, M.

doi:10.1126/sciadv.1700066

Cited by 267 publications

(176 citation statements)

References 26 publications

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“…In this study, we are interested in conditional probability of crop production exceeding a certain amount ( Y > y ) at different climatic conditions ( X = x ); i.e., F Y ∣ X ( Y > y | X = x ). The conditional probability density function of f Y ∣ X ( y | x ) is expressed as follows [ Madadgar and Moradkhani , ; Mazdiyasni et al , ]:

f_{Y true∣ X} (()|, y, x) = c ([],, F_{X} ((), x), F_{Y} ((), y)) . f_{Y} ((), y)

where c is the probability density function (PDF) of the continuous copula function and f Y ( y ) is the PDF of marginal distribution for crop yield. Once the conditional PDF for a particular drought condition is obtained from equation , the probability of crop yield exceeding a certain amount, i.e., F Y ∣ X ( Y > y | X = x ), is calculated as the area under f Y ∣ X ( y | x ) for Y > y .…”

Section: Methodsmentioning

confidence: 99%

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Probabilistic estimates of drought impacts on agricultural production

Madadgar

AghaKouchak

Farahmand

et al. 2017

Geophysical Research Letters

Self Cite

148

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Increases in the severity and frequency of drought in a warming climate may negatively impact agricultural production and food security. Unlike previous studies that have estimated agricultural impacts of climate condition using single‐crop yield distributions, we develop a multivariate probabilistic model that uses projected climatic conditions (e.g., precipitation amount or soil moisture) throughout a growing season to estimate the probability distribution of crop yields. We demonstrate the model by an analysis of the historical period 1980–2012, including the Millennium Drought in Australia (2001–2009). We find that precipitation and soil moisture deficit in dry growing seasons reduced the average annual yield of the five largest crops in Australia (wheat, broad beans, canola, lupine, and barley) by 25–45% relative to the wet growing seasons. Our model can thus produce region‐ and crop‐specific agricultural sensitivities to climate conditions and variability. Probabilistic estimates of yield may help decision‐makers in government and business to quantitatively assess the vulnerability of agriculture to climate variations. We develop a multivariate probabilistic model that uses precipitation to estimate the probability distribution of crop yields. The proposed model shows how the probability distribution of crop yield changes in response to droughts. During Australia's Millennium Drought precipitation and soil moisture deficit reduced the average annual yield of the five largest crops.

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f_{Y true∣ X} (()|, y, x) = c ([],, F_{X} ((), x), F_{Y} ((), y)) . f_{Y} ((), y)

Section: Methodsmentioning

confidence: 99%

“…In this study, we are interested in conditional probability of crop production exceeding a certain amount (Y > y) at different climatic conditions (X = x); i.e., F Y|X (Y > y | X = x). The conditional probability density function of f Y|X (y | x) is expressed as follows [Madadgar and Moradkhani, 2013;Mazdiyasni et al, 2017]:…”

Section: Copula-based Modelmentioning

confidence: 99%

Probabilistic estimates of drought impacts on agricultural production

Madadgar

AghaKouchak

Farahmand

et al. 2017

Geophysical Research Letters

Self Cite

148

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“…The climatic changes are expected to adversely influence the economy, ecosystems, and humans that are exposed to it [Watts et al, 2015;Revi et al, 2014;Seto et al, 2012]. Heat waves particularly result in excessive mortality rates [Mora et al, 2017;Mazdiyasni et al, 2017;Mitchell et al, 2016;Green et al, 2016;Cox et al, 2016;Xu et al, 2016;Tong et al, 2015;Huang et al, 2012], higher hospital admissions [Linares et al, 2017;Iñiguez et al, 2016;Díaz et al, 2015], preterm delivery [Cox et al, 2016], economic and labor productivity loss [Estrada et al, 2017;Zander et al, 2015], damage to infrastructure, and higher energy usage [Revi et al, 2014]. The total death toll by extreme temperatures hitting Europe in Summer 2003 and the Russian Federation in Summer 2010 makes heat waves the second deadliest kind of disaster related to weather extremes during the period 2001 to 2010 [World Meteorological Organization (WMO), 2014].…”

Section: Introductionmentioning

confidence: 99%

Heat stress increase under climate change twice as large in cities as in rural areas: A study for a densely populated midlatitude maritime region

Wouters

Ridder

Poelmans

et al. 2017

Geophysical Research Letters

143

104

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Urban areas are usually warmer than their surrounding natural areas, an effect known as the urban heat island effect. As such, they are particularly vulnerable to global warming and associated increases in extreme temperatures. Yet ensemble climate‐model projections are generally performed on a scale that is too coarse to represent the evolution of temperatures in cities. Here, for the first time, we combine unprecedented long‐term (35 years) urban climate model integrations at the convection‐permitting scale (2.8 km resolution) with information from an ensemble of general circulation models to assess temperature‐based heat stress for Belgium, a densely populated midlatitude maritime region. We discover that the heat stress increase toward the mid‐21st century is twice as large in cities compared to their surrounding rural areas. The exacerbation is driven by the urban heat island itself, its concurrence with heat waves, and urban expansion. Cities experience a heat stress multiplication by a factor 1.4 and 15 depending on the scenario. Remarkably, the future heat stress surpasses everywhere the urban hot spots of today. Our results demonstrate the need to combine information from climate models, acting on different scales, for climate change risk assessment in heterogeneous regions. Moreover, these results highlight the necessity for adaptation to increasing heat stress, especially in urban areas.

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“…Temperatures in already hot regions approach and may eventually exceed the limits of physiological adaptation [88]. For example, the 0.5 • C rise in mean temperatures in India between 1960 and 2009 resulted in a 146% increase in high mortality events (>100 mortalities) associated with heat [89]. Residential buildings are a strategic context in which to reduce health risks from rising temperatures [90,91].…”

Section: Climate Change Heat Impacts On Health and Residential Buildmentioning

confidence: 99%

The Impact of Subsidies on the Prevalence of Climate-Sensitive Residential Buildings in Malaysia

2017

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Dependence on air-conditioning (AC) for residential cooling and ventilation is a health and sustainability challenge. In hot temperatures, climate-sensitive buildings (CSB) can complement and/or substitute for AC usage in achieving thermal comfort. Many countries facing such conditions-particularly in tropical climates-are developing quickly, with rising populations and income creating demand for new housing and AC. This presents a window for adoption of CSB but could also result in long term lock-in of AC-dependent buildings. Here, a simple system dynamics model is used to explore the potential and limitations of subsidies to affect futures of housing stock and night-time AC usage in Malaysia. The effectiveness of subsidies in achieving high uptake of CSB and resulting health benefits is highly dependent on homebuyer willingness to pay (WTP). A detailed understanding of WTP in the Malaysian context and factors that can shift WTP is necessary to determine if CSB subsidies can be a good policy mechanism for achieving CSB uptake.

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Increasing probability of mortality during Indian heat waves

Abstract: An increase of 0.5°C in summer mean temperatures increases the probability of mass heat-related mortality in India by 146%.

Cited by 267 publications

References 26 publications

Probabilistic estimates of drought impacts on agricultural production

Probabilistic estimates of drought impacts on agricultural production

Heat stress increase under climate change twice as large in cities as in rural areas: A study for a densely populated midlatitude maritime region

The Impact of Subsidies on the Prevalence of Climate-Sensitive Residential Buildings in Malaysia

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