A Review of Recent Advances in Research on Extreme Heat Events

Horton, Radley M.; Mankin, Justin S.; Lesk, Corey; Coffel, Ethan; Raymond, Colin

doi:10.1007/s40641-016-0042-x

Cited by 343 publications

(269 citation statements)

References 181 publications

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“…The possible mechanisms governing heat waves are reasonably summarized by a recent review article by Horton et al [32]. They pointed out that the underlying drivers for heat waves are atmospheric blocking, which is commonly associated with clear skies with increasing solar insulation on surface, adiabatic warming accompanied by sinking motion, and warm air advection.…”

Section: Linkage Of Blocking To Southeastern Heatwave Of 2007mentioning

confidence: 99%

The Dynamical Linkage of Atmospheric Blocking to Drought, Heatwave and Urban Heat Island in Southeastern US: A Multi-Scale Case Study

et al. 2018

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Atmospheric blocking is a long standing structure stalled in the mid-troposphere which is often associated with extreme weather events such as droughts, heatwaves, flood and cold air outbreak. A striking atmospheric blocking is identified to persist over the US during 13-17 August 2007, exacerbating the existing drought over the Southeastern US. This pronounced blocking event not only intensified the concurrent drought conditions, but also led to a record-breaking heatwave over the Southeast of the US. The excessive heat observed during this heatwave is attributable to the subsidence-associated adiabatic warming as well as the dry-and-warm air advection over Alabama and the neighboring states. At the local scale, we choose Birmingham, AL, as the study area for exploring the blocking influence on urban heat island. Based on the remote sensing data, the surface (skin) urban heat island is found to be 8 • C in this area on the block-onset day. This provides partial evidences that the surface urban heat island intensity is likely amplified by the blocking-induced heat waves. The present work provides a unique case study in which blocking, drought, heatwave and urban heat island all occur concurrently, and interplay across a spectrum of spatial scales. We conclude that atmospheric blocking is capable of reinforcing droughts, initiating heatwaves, and probably amplifying the urban heat island intensity during the concurrent period.

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Section: Linkage Of Blocking To Southeastern Heatwave Of 2007mentioning

confidence: 99%

The Dynamical Linkage of Atmospheric Blocking to Drought, Heatwave and Urban Heat Island in Southeastern US: A Multi-Scale Case Study

et al. 2018

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“…Fouillet et al [21] used receptor model which comprises of chemical mass balance (CMB), principal component analysis (PCA) and factor analysis (FA) to examine the level of particulate matter concentration in Nigeria. Horton et al [22] used independent t test to determine the association between vehicle emission and incidences of asthma, cardiovascular and bronchitis in Jos plateau state Kalkstein and Valimont [23] went further to combine the used of independent t test and chi square test to test for strength of association between ventilator pattern and the presence of chronic bronchitis. Direct logistic regression model was also employed to assess the impact of age, gender, educational attainment, exposure to firewood smoke, and cigarette smoking on chronic bronchitis.…”

Section: Methodsmentioning

confidence: 99%

Heat Waves Research and Impacts on Human Health: The Need for Studies in Nigeria: A Review

Agan¹

2017

J Earth Sci Clim Change

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“…Observed tendencies in T , q and θ e are naturally a product of a combination of these drivers (Horton et al, 2016). The expression of internal climates modes (e.g., ENSO, PNA and NAO) influences the frequency and intensity of different synoptic-scale phenomena (Sheridan, 2003;Weaver, 2013) and has been found to be partly responsible for an increase in the number of oppressively hot days in many urban areas across the USA over recent decades (Sheridan et al, 2009).…”

Section: Motivation and Objectivesmentioning

confidence: 99%

Modeling the contributions of global air temperature, synoptic-scale phenomena and soil moisture to near-surface static energy variability using artificial neural networks

2017

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Abstract. The static energy content of the atmosphere is increasing on a global scale, but exhibits important subglobal and subregional scales of variability and is a useful parameter for integrating the net effect of changes in the partitioning of energy at the surface and for improving understanding of the causes of so-called "warming holes" (i.e., locations with decreasing daily maximum air temperatures (T ) or increasing trends of lower magnitude than the global mean). Further, measures of the static energy content (herein the equivalent potential temperature, θ e ) are more strongly linked to excess human mortality and morbidity than air temperature alone, and have great relevance in understanding causes of past heat-related excess mortality and making projections of possible future events that are likely to be associated with negative human health and economic consequences. New nonlinear statistical models for summertime daily maximum and minimum θ e are developed and used to advance understanding of drivers of historical change and variability over the eastern USA. The predictor variables are an index of the daily global mean temperature, daily indices of the synoptic-scale meteorology derived from T and specific humidity (Q) at 850 and 500 hPa geopotential heights (Z), and spatiotemporally averaged soil moisture (SM). SM is particularly important in determining the magnitude of θ e over regions that have previously been identified as exhibiting warming holes, confirming the key importance of SM in dictating the partitioning of net radiation into sensible and latent heat and dictating trends in near-surface T and θ e . Consistent with our a priori expectations, models built using artificial neural networks (ANNs) out-perform linear models that do not permit interaction of the predictor variables (global T , synoptic-scale meteorological conditions and SM). This is particularly marked in regions with high variability in minimum and maximum θ e , where more complex models built using ANN with multiple hidden layers are better able to capture the day-to-day variability in θ e and the occurrence of extreme maximum θ e . Over the entire domain, the ANN with three hidden layers exhibits high accuracy in predicting maximum θ e > 347 K. The median hit rate for maximum θ e > 347 K is > 0.60, while the median false alarm rate is ≈ 0.08.

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A Review of Recent Advances in Research on Extreme Heat Events

Cited by 343 publications

References 181 publications

The Dynamical Linkage of Atmospheric Blocking to Drought, Heatwave and Urban Heat Island in Southeastern US: A Multi-Scale Case Study

The Dynamical Linkage of Atmospheric Blocking to Drought, Heatwave and Urban Heat Island in Southeastern US: A Multi-Scale Case Study

Heat Waves Research and Impacts on Human Health: The Need for Studies in Nigeria: A Review

Modeling the contributions of global air temperature, synoptic-scale phenomena and soil moisture to near-surface static energy variability using artificial neural networks

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