Climate Change Driving Surge in ‘Day-Night Hot Extremes’ in Northern Hemisphere
By Daisy Dunne
Deadly "day-night hot extremes" are increasing across the northern hemisphere due to climate change, a new study finds.
And the number of people exposed to such events, also known as "compound hot extremes," is likely to increase "several-fold" as temperatures continue to climb in the coming decades, the study authors tell Carbon Brief.
If global temperatures reach 2 C — the upper limit set by countries in the Paris agreement — the frequency of compound hot extremes could more than double across the northern hemisphere, when compared to 2012, the research finds.
However, if greenhouse gas emissions are not curbed, compound hot extremes could become eight times more frequent by the end of the century.
The study sets out "clear evidence" that human-caused climate change is leaving its mark on extreme heat events, another scientist tells Carbon Brief.
Day and Night
The new study, published in Nature Communications, looks specifically at "compound hot extremes" — a 24-hour period in summer where hot daytime temperatures are followed by similar nightime temperatures. (Temperatures are considered "hot" if they are in the top 10% of temperatures experienced by a region from 1960-2012.)
These kinds of events pose a particularly high danger to human health, explain study authors Dr Yang Chen, a climate extremes scientist from the Chinese Academy of Meteorological Sciences, and Dr Jun Wang, a climate and meteorological scientist from the Institute of Atmospheric Physics in China. In a joint interview, they tell Carbon Brief:
Simply put, compound hot extremes deprive humans of the valuable chance of relief, which could have been provided by the 'cooling-off' effects of a nighttime low.
Such conditions occurred during the 2003 summer heatwave in Europe, which saw 70,000 deaths across 16 countries, the authors say. Another example is the 1995 Chicago heatwave, which led to more than 700 heat-related deaths in just five days.
The study is the first to present "a complete storyline on compound hot extremes" — investigating how they have changed, the role of climate change in this and how they might increase in the future, the authors say.
The results show that compound hot extremes "are significantly increasing and will continue to increase in frequency and intensity" across the northern hemisphere, say Chen and Wang:
These increases in heat hazards will translate into several-fold increases in population exposure to them. The rise of anthropogenic emission of greenhouse gas emissions is to blame for these increases.
For the first part of their study, the authors analysed the "fingerprint" of human-caused climate change on compound hot extremes to date. To do this, they conducted an "attribution" analysis.
This involves using climate models to produce two sets of simulations: one including all the factors that affect the climate, including human-caused greenhouse gas emissions, volcanic eruptions and solar variability, and one including all of these factors except for greenhouse gas emissions.
The researchers then compared the frequency and intensity of compound hot extremes in both of these scenarios.
They found that only the scenario including human-caused greenhouse gas emissions could closely reproduce the pattern of compound hot extremes observed from 1960 to 2012. In their research paper, the authors write:
We find that the summer-mean warming over 1960-2012 largely dictates the past increases in frequency and intensity of compound hot extremes during that period in both observations and simulations.
The maps below show observed changes in summertime compound hot extreme frequency (left) and intensity (right) across the northern hemisphere from 1960-2012.
The left-hand map shows changes in the number of compound hot extreme days per decade (yellow to red for increases; light to dark blue for decreases), while the right-hand map shows changes in the average temperature of compound hot extremes per decade (same color scale).
Contributions from changing temperature mean and variability. Wang et al. (2020)
The map shows that increases in the frequency and intensity of compound hot extremes are widespread across the northern hemisphere, with parts of continental Europe and China particularly affected.
(Gaps in the data prevented the researchers from analysing changes in the most southern parts of the northern hemisphere, the authors say in their research paper.)
While the global pattern of increases is best explained by human-caused global warming, it is possible that some regional differences may be explained by other factors, the authors say.
For example, the drying of soils could help to explain local variation of heat extremes, the authors say in their research paper.
This is because dry soils accumulate heat during the day and release it at night, Wang and Chen say, making night hot extremes and, therefore, compound hot extremes, more likely.
The authors also used climate models to project possible future changes to compound hot extremes until 2100. They investigated two scenarios: one "intermediate mitigation" pathway with moderately high greenhouse gas emissions ("RCP4.5") and one with very high greenhouse gas emissions ("RCP8.5").
Within each emissions scenario, they also looked at the changes to compound hot extremes expected if the world reaches 1.5 C and 2 C of global warming, which are the temperature limits set by the Paris agreement.
The charts below show the average expected change in the number of summertime compound hot extreme days (purple line), as well as independent hot days (blue line) and independent hot nights (turquoise line) across the northern hemisphere under RCP4.5 (top) and RCP8.5 (bottom) until 2100. (Compound extremes are where a hot day is followed by a hot night, whereas an "independent hot day" is when a hot day is not followed by a hot night.)
On the charts, red circles point out when the temperature limits of 1.5 C and 2 C will be breached in each scenario. The bottom chart also highlights when 4C could be breached. The various data points represent results from different climate models.
(It is worth noting that events are considered to be compound or independent. So, a 24-hour period where a hot day is followed by a hot night would be considered a compound extreme, but not an independent hot day or hot night.)
Constrained projections of summertime hot extremes. Wang et al. (2020)
The results show that the average number of compound hot extreme days across the northern hemisphere in summer would more than double if temperatures reach 2 C, when compared to 2012.
Keeping temperatures at 1.5 C could see five fewer compound hot extreme days across the northern hemisphere, on average, when compared to 2 C, the research adds.
If greenhouse gas emissions are extremely high (RCP8.5), the number of summertime compound hot extremes could increase eight-fold by 2100, when compared to 2012, the results show.
The charts also show that compound hot events are expected to increase at a much more rapid rate than independent hot day or hot night events.
This is chiefly because climate change is known to have a larger effect on nightime temperatures than daytime temperatures, the authors say.
Therefore, as the chances of hot nights become higher, the chances of compound hot events also increase — and, so, the chances of a hot day or night occurring independently decreases, explain Chen and Wang.
The findings reinforce "the urgency in reducing emission of greenhouse gases" for policymakers, say Chen and Wang:
We should keep the point in mind that as the globe warms, future summers are increasingly dominated by compound hot extremes and become more uncomfortable. Namely, a hot day accompanied by a hot night without a relief window for humans might become a 'new norm'. As a result, vigilance against excess heat should be kept through day and night.
I think the main take home message from this study is that we should use consecutive day-night hot extremes as a major heat-health indicator for policymaking, as compound hot extremes are projected to have larger future increases in frequency and intensity then hot days or nights.
The findings produce "clear evidence" that human-caused climate change is leaving its mark on extreme heat events, says Prof Peter Stott, who leads on climate monitoring and attribution at the Met Office Hadley Centre. Stott, who was also not involved in the research, tells Carbon Brief:
I don't find the conclusions of the study very surprising, but I do like the way the authors have comprehensively set out the implications – the clear evidence that the changes to date are driven by human emissions and the clear evidence that future changes will result in significant increases in the frequency and intensity of these compound extremes worldwide.
Reposted with permission from Carbon Brief.
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By Eric Tate and Christopher Emrich
Disasters stemming from hazards like floods, wildfires, and disease often garner attention because of their extreme conditions and heavy societal impacts. Although the nature of the damage may vary, major disasters are alike in that socially vulnerable populations often experience the worst repercussions. For example, we saw this following Hurricanes Katrina and Harvey, each of which generated widespread physical damage and outsized impacts to low-income and minority survivors.
Mapping Social Vulnerability<p>Figure 1a is a typical map of social vulnerability across the United States at the census tract level based on the Social Vulnerability Index (SoVI) algorithm of <a href="https://onlinelibrary.wiley.com/doi/abs/10.1111/1540-6237.8402002" target="_blank"><em>Cutter et al.</em></a> . Spatial representation of the index depicts high social vulnerability regionally in the Southwest, upper Great Plains, eastern Oklahoma, southern Texas, and southern Appalachia, among other places. With such a map, users can focus attention on select places and identify population characteristics associated with elevated vulnerabilities.</p>
Fig. 1. (a) Social vulnerability across the United States at the census tract scale is mapped here following the Social Vulnerability Index (SoVI). Red and pink hues indicate high social vulnerability. (b) This bivariate map depicts social vulnerability (blue hues) and annualized per capita hazard losses (pink hues) for U.S. counties from 2010 to 2019.<p>Many current indexes in the United States and abroad are direct or conceptual offshoots of SoVI, which has been widely replicated [e.g., <a href="https://link.springer.com/article/10.1007/s13753-016-0090-9" target="_blank"><em>de Loyola Hummell et al.</em></a>, 2016]. The U.S. Centers for Disease Control and Prevention (CDC) <a href="https://www.atsdr.cdc.gov/placeandhealth/svi/index.html" target="_blank">has also developed</a> a commonly used social vulnerability index intended to help local officials identify communities that may need support before, during, and after disasters.</p><p>The first modeling and mapping efforts, starting around the mid-2000s, largely focused on describing spatial distributions of social vulnerability at varying geographic scales. Over time, research in this area came to emphasize spatial comparisons between social vulnerability and physical hazards [<a href="https://doi.org/10.1007/s11069-009-9376-1" target="_blank"><em>Wood et al.</em></a>, 2010], modeling population dynamics following disasters [<a href="https://link.springer.com/article/10.1007%2Fs11111-008-0072-y" target="_blank" rel="noopener noreferrer"><em>Myers et al.</em></a>, 2008], and quantifying the robustness of social vulnerability measures [<a href="https://doi.org/10.1007/s11069-012-0152-2" target="_blank" rel="noopener noreferrer"><em>Tate</em></a>, 2012].</p><p>More recent work is beginning to dissolve barriers between social vulnerability and environmental justice scholarship [<a href="https://doi.org/10.2105/AJPH.2018.304846" target="_blank" rel="noopener noreferrer"><em>Chakraborty et al.</em></a>, 2019], which has traditionally focused on root causes of exposure to pollution hazards. Another prominent new research direction involves deeper interrogation of social vulnerability drivers in specific hazard contexts and disaster phases (e.g., before, during, after). Such work has revealed that interactions among drivers are important, but existing case studies are ill suited to guiding development of new indicators [<a href="https://doi.org/10.1016/j.ijdrr.2015.09.013" target="_blank" rel="noopener noreferrer"><em>Rufat et al.</em></a>, 2015].</p><p>Advances in geostatistical analyses have enabled researchers to characterize interactions more accurately among social vulnerability and hazard outcomes. Figure 1b depicts social vulnerability and annualized per capita hazard losses for U.S. counties from 2010 to 2019, facilitating visualization of the spatial coincidence of pre‑event susceptibilities and hazard impacts. Places ranked high in both dimensions may be priority locations for management interventions. Further, such analysis provides invaluable comparisons between places as well as information summarizing state and regional conditions.</p><p>In Figure 2, we take the analysis of interactions a step further, dividing counties into two categories: those experiencing annual per capita losses above or below the national average from 2010 to 2019. The differences among individual race, ethnicity, and poverty variables between the two county groups are small. But expressing race together with poverty (poverty attenuated by race) produces quite different results: Counties with high hazard losses have higher percentages of both impoverished Black populations and impoverished white populations than counties with low hazard losses. These county differences are most pronounced for impoverished Black populations.</p>
Fig. 2. Differences in population percentages between counties experiencing annual per capita losses above or below the national average from 2010 to 2019 for individual and compound social vulnerability indicators (race and poverty).<p>Our current work focuses on social vulnerability to floods using geostatistical modeling and mapping. The research directions are twofold. The first is to develop hazard-specific indicators of social vulnerability to aid in mitigation planning [<a href="https://doi.org/10.1007/s11069-020-04470-2" target="_blank" rel="noopener noreferrer"><em>Tate et al.</em></a>, 2021]. Because natural hazards differ in their innate characteristics (e.g., rate of onset, spatial extent), causal processes (e.g., urbanization, meteorology), and programmatic responses by government, manifestations of social vulnerability vary across hazards.</p><p>The second is to assess the degree to which socially vulnerable populations benefit from the leading disaster recovery programs [<a href="https://doi.org/10.1080/17477891.2019.1675578" target="_blank" rel="noopener noreferrer"><em>Emrich et al.</em></a>, 2020], such as the Federal Emergency Management Agency's (FEMA) <a href="https://www.fema.gov/individual-disaster-assistance" target="_blank" rel="noopener noreferrer">Individual Assistance</a> program and the U.S. Department of Housing and Urban Development's Community Development Block Grant (CDBG) <a href="https://www.hudexchange.info/programs/cdbg-dr/" target="_blank" rel="noopener noreferrer">Disaster Recovery</a> program. Both research directions posit social vulnerability indicators as potential measures of social equity.</p>
Social Vulnerability as a Measure of Equity<p>Given their focus on social marginalization and economic barriers, social vulnerability indicators are attracting growing scientific interest as measures of inequity resulting from disasters. Indeed, social vulnerability and inequity are related concepts. Social vulnerability research explores the differential susceptibilities and capacities of disaster-affected populations, whereas social equity analyses tend to focus on population disparities in the allocation of resources for hazard mitigation and disaster recovery. Interventions with an equity focus emphasize full and equal resource access for all people with unmet disaster needs.</p><p>Yet newer studies of inequity in disaster programs have documented troubling disparities in income, race, and home ownership among those who <a href="https://eos.org/articles/equity-concerns-raised-in-federal-flood-property-buyouts" target="_blank">participate in flood buyout programs</a>, are <a href="https://www.eenews.net/stories/1063477407" target="_blank" rel="noopener noreferrer">eligible for postdisaster loans</a>, receive short-term recovery assistance [<a href="https://doi.org/10.1016/j.ijdrr.2020.102010" target="_blank" rel="noopener noreferrer"><em>Drakes et al.</em></a>, 2021], and have <a href="https://www.texastribune.org/2020/08/25/texas-natural-disasters--mental-health/" target="_blank" rel="noopener noreferrer">access to mental health services</a>. For example, a recent analysis of federal flood buyouts found racial privilege to be infused at multiple program stages and geographic scales, resulting in resources that disproportionately benefit whiter and more urban counties and neighborhoods [<a href="https://doi.org/10.1177/2378023120905439" target="_blank" rel="noopener noreferrer"><em>Elliott et al.</em></a>, 2020].</p><p>Investments in disaster risk reduction are largely prioritized on the basis of hazard modeling, historical impacts, and economic risk. Social equity, meanwhile, has been far less integrated into the considerations of public agencies for hazard and disaster management. But this situation may be beginning to shift. Following the adage of "what gets measured gets managed," social equity metrics are increasingly being inserted into disaster management.</p><p>At the national level, FEMA has <a href="https://www.fema.gov/news-release/20200220/fema-releases-affordability-framework-national-flood-insurance-program" target="_blank">developed options</a> to increase the affordability of flood insurance [Federal Emergency Management Agency, 2018]. At the subnational scale, Puerto Rico has integrated social vulnerability into its CDBG Mitigation Action Plan, expanding its considerations of risk beyond only economic factors. At the local level, Harris County, Texas, has begun using social vulnerability indicators alongside traditional measures of flood risk to introduce equity into the prioritization of flood mitigation projects [<a href="https://www.hcfcd.org/Portals/62/Resilience/Bond-Program/Prioritization-Framework/final_prioritization-framework-report_20190827.pdf?ver=2019-09-19-092535-743" target="_blank" rel="noopener noreferrer"><em>Harris County Flood Control District</em></a>, 2019].</p><p>Unfortunately, many existing measures of disaster equity fall short. They may be unidimensional, using single indicators such as income in places where underlying vulnerability processes suggest that a multidimensional measure like racialized poverty (Figure 2) would be more valid. And criteria presumed to be objective and neutral for determining resource allocation, such as economic loss and cost-benefit ratios, prioritize asset value over social equity. For example, following the <a href="http://www.cedar-rapids.org/discover_cedar_rapids/flood_of_2008/2008_flood_facts.php" target="_blank" rel="noopener noreferrer">2008 flooding</a> in Cedar Rapids, Iowa, cost-benefit criteria supported new flood protections for the city's central business district on the east side of the Cedar River but not for vulnerable populations and workforce housing on the west side.</p><p>Furthermore, many equity measures are aspatial or ahistorical, even though the roots of marginalization may lie in systemic and spatially explicit processes that originated long ago like redlining and urban renewal. More research is thus needed to understand which measures are most suitable for which social equity analyses.</p>
Challenges for Disaster Equity Analysis<p>Across studies that quantify, map, and analyze social vulnerability to natural hazards, modelers have faced recurrent measurement challenges, many of which also apply in measuring disaster equity (Table 1). The first is clearly establishing the purpose of an equity analysis by defining characteristics such as the end user and intended use, the type of hazard, and the disaster stage (i.e., mitigation, response, or recovery). Analyses using generalized indicators like the CDC Social Vulnerability Index may be appropriate for identifying broad areas of concern, whereas more detailed analyses are ideal for high-stakes decisions about budget allocations and project prioritization.</p>
By Jessica Corbett
Sen. Bernie Sanders on Tuesday was the lone progressive to vote against Tom Vilsack reprising his role as secretary of agriculture, citing concerns that progressive advocacy groups have been raising since even before President Joe Biden officially nominated the former Obama administration appointee.