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"Weather effects"
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Human health and physical activity during heat exposure
This book provides fundamental concepts in human thermal physiology and their applications in general public, occupational, military, and athletics settings from the biometeorological perspective. The book includes a section on human physiology, epidemiology and special considerations in aforementioned populations, and behavioral and technological adjustments people may take to combat thermal environmental stress and safeguard their health. The book is the first of its kind to compile multiple disciplines--human physiology, climatology, and medicine--in one to provide fundamental concepts in human thermal physiology and their applications in general public, occupational, military, and athletics settings from the biometeorological perspective; Developed by experts, scientists, and physicians from exercise physiology, climatology, public health, sports medicine, and military medicine; Highlights special considerations and applications of thermal physiology to general public, occupational, military, and athletics settings.
Book
Development of a data-driven weather index for beach parks tourism
The complexity of the human-environment interface predicates the need for tools and techniques that can enable the effective translation of weather and climate products into decision-relevant information. Indices are a category of such tools that may be used to simplify multi-faceted climate information for economic and other decision-making. Climate indices for tourism have been popularized in the literature over the past three decades, but despite their prevalence, these indices have a number of limitations, including coarse temporal resolution, subjective rating and weighting schemes, and lack of empirical validation. This paper critically assesses the design of the tourism climate index, the holiday climate index-beach, and a new, mathematically optimized index developed for the unique contextual realities of Great Lakes beach tourism. This new methodology combines the use of expert knowledge, stated visitor preferences, and mathematical optimization to develop an index that assigns daily weather scores based on four weather sub-indices (thermal comfort, wind speed, precipitation, and cloud cover). These daily scores are then averaged to the monthly level and correlated to visitation data at two beach parks in Ontario (Canada). This optimized index demonstrates a strong fit (R2 = 0.734, 0.657) with observed visitation at Pinery Provincial Park and Sandbanks Provincial Park, outperforming both the tourism climate index (R2 = 0.474, 0.018) and the holiday climate index-beach (R2 = 0.668, 0.427). This study advances our understanding of the magnitude and seasonality of weather impact on beach tourist visitation and can inform decision-making of tourism marketers and destination managers.
Journal Article
Space Weather Effects on Transportation Systems: A Review of Current Understanding and Future Outlook
Space weather events, including solar flares, coronal mass ejections, and geomagnetic storms, have significant effects on various transportation systems. This review provides a comprehensive examination of the current understanding and future outlook of space weather effects on air, maritime, railway, and ground transportation. It explores the mechanisms through which space weather causes communication blackouts, satellite navigation failure, elevated cosmic radiation, and geomagnetically induced currents, leading to disruptions in transportation operations. Historical events are analyzed to underscore the diversity and severity of these impacts. Additionally, this review discusses the anticipated challenges posed by the upcoming solar maximum of Solar Cycle 25 and highlights the need for improved forecasting, mitigation strategies, and resilient infrastructure to safeguard transportation systems against space weather threats. By integrating findings from recent studies and historical data, this review aims to enhance the preparedness and response strategies of the transportation sector in the face of evolving space weather risks.
Journal Article
Revealing the association between cerebrovascular accidents and ambient temperature: a meta-analysis
The association between cerebrovascular accidents (CVA) and weather has been described across several studies showing multiple conflicting results. In this paper, we aim to conduct a meta-analysis to further clarify this association, as well as to find the potential sources of heterogeneity. PubMed, EMBASE, and Google Scholar were searched from inception through 2015, for articles analyzing the correlation between the incidence of CVA and temperature. A pooled effect size (ES) was estimated using random effects model and expressed as absolute values. Subgroup analyses by type of CVA were also performed. Heterogeneity and influence of covariates—including geographic latitude of the study site, male percentage, average temperature, and time interval—were assessed by meta-regression analysis. Twenty-six articles underwent full data extraction and scoring. A total of 19,736 subjects with CVA from 12 different countries were included and grouped as ischemic strokes (IS;
n
= 14,199), intracerebral hemorrhages (ICH;
n
= 3798), and subarachnoid hemorrhages (SAH;
n
= 1739). Lower ambient temperature was significantly associated with increase in incidence of overall CVA when using unadjusted (pooled ES = 0.23,
P
< 0.001) and adjusted data (pooled ES = 0.03,
P
= 0.003). Subgroup analyses showed that lower temperature has higher impact on the incidence of ICH (pooled ES = 0.34,
P
< 0.001), than that of IS (pooled ES = 0.22,
P
< 0.001) and SAH (pooled ES = 0.11,
P
= 0.012). In meta-regression analysis, the geographic latitude of the study site was the most influencing factor on this association (
Z
-score = 8.68). Synthesis of the existing data provides evidence supporting that a lower ambient temperature increases the incidence of CVA. Further population-based studies conducted at negative latitudes are needed to clarify the influence of this factor.
Journal Article
Integrating Social and Behavioral Sciences Within the Weather Enterprise
Our ability to observe and forecast severe weather events has improved markedly over the past few decades. Forecasts of snow and ice storms, hurricanes and storm surge, extreme heat, and other severe weather events are made with greater accuracy, geographic specificity, and lead time to allow people and communities to take appropriate protective measures. Yet hazardous weather continues to cause loss of life and result in other preventable social costs.
There is growing recognition that a host of social and behavioral factors affect how we prepare for, observe, predict, respond to, and are impacted by weather hazards. For example, an individual's response to a severe weather event may depend on their understanding of the forecast, prior experience with severe weather, concerns about their other family members or property, their capacity to take the recommended protective actions, and numerous other factors. Indeed, it is these factors that can determine whether or not a potential hazard becomes an actual disaster. Thus, it is essential to bring to bear expertise in the social and behavioral sciences (SBS)-including disciplines such as anthropology, communication, demography, economics, geography, political science, psychology, and sociology-to understand how people's knowledge, experiences, perceptions, and attitudes shape their responses to weather risks and to understand how human cognitive and social dynamics affect the forecast process itself.
Integrating Social and Behavioral Sciences Within the Weather Enterprise explores and provides guidance on the challenges of integrating social and behavioral sciences within the weather enterprise. It assesses current SBS activities, describes the potential value of improved integration of SBS and barriers that impede this integration, develops a research agenda, and identifies infrastructural and institutional arrangements for successfully pursuing SBS-weather research and the transfer of relevant findings to operational settings.
eBook
Synergistic effects of synoptic weather patterns and topography on air quality: a case of the Sichuan Basin of China
Heavy air pollution is strongly influenced by weather conditions and is thus sensitive to climate change. Especially, for the areas with complex topography such as the Sichuan Basin (SB), one of the most polluted areas of China, the synergistic effects of synoptic weather patterns and topography on air quality are unclear and warrant investigation. This study examined the typical synoptic patterns of SB in winter days of 2013–2017 and revealed their synergistic effects with topography on air quality. Three categories of synoptic patterns including dry low-trough, high-pressure, and wet low-vortex patterns accompanying heavy, medium, and slight air pollution, respectively, were identified. In particular, the dry low-trough patterns occur most frequently, accounting for around 62% of the total days. In the case of this pattern, westerly wind prevails over the SB and the aloft atmosphere is warmer than the Tibetan Plateau (TP) at the same height, which induces the cold air over TP moving eastward to the SB. Under the synergistic effects of the cold air eastward movement and TP, a strong descending motion (known as foehn) is observed on the leeward slope of the towering TP. This foehn warming causes a stable layer above the planetary boundary layer (PBL), which suppresses secondary circulation and PBL. These features restrict atmospheric pollutant dispersion, resulting in poor air quality. In contrast, for the high-pressure and wet low-vortex patterns, cold air masses from the north invade southward and cover the northwest SB. This invasion remarkably decreases the atmospheric stability of the lower troposphere, deepens the PBL, and enhances the height of secondary circulation, thereby facilitating air pollutant dispersion. Moreover, the wet low-vortex pattern is accompanied by frequent precipitation events (with 80% rainy days), further bringing down air pollution levels. These findings provide an insight for improving air pollution forecast in the complex terrain areas under global warming.
Journal Article
Anthropogenic climate change has slowed global agricultural productivity growth
Agricultural research has fostered productivity growth, but the historical influence of anthropogenic climate change (ACC) on that growth has not been quantified. We develop a robust econometric model of weather effects on global agricultural total factor productivity (TFP) and combine this model with counterfactual climate scenarios to evaluate impacts of past climate trends on TFP. Our baseline model indicates that ACC has reduced global agricultural TFP by about 21% since 1961, a slowdown that is equivalent to losing the last 7 years of productivity growth. The effect is substantially more severe (a reduction of ~26–34%) in warmer regions such as Africa and Latin America and the Caribbean. We also find that global agriculture has grown more vulnerable to ongoing climate change.Agricultural productivity has increased historically, but the impact of climate change on productivity growth is not clear. In the last 60 years, anthropogenic climate change has reduced agricultural total factor production globally by 21%, with stronger impacts in warmer regions.
Journal Article
Summer weather becomes more persistent in a 2 °C world
Heat and rainfall extremes have intensified over the past few decades and this trend is projected to continue with future global warming1–3. A long persistence of extreme events often leads to societal impacts with warm-and-dry conditions severely affecting agriculture and consecutive days of heavy rainfall leading to flooding. Here we report systematic increases in the persistence of boreal summer weather in a multi-model analysis of a world 2 °C above pre-industrial compared to present-day climate. Averaged over the Northern Hemisphere mid-latitude land area, the probability of warm periods lasting longer than two weeks is projected to increase by 4% (2–6% full uncertainty range) after removing seasonal-mean warming. Compound dry–warm persistence increases at a similar magnitude on average but regionally up to 20% (11–42%) in eastern North America. The probability of at least seven consecutive days of strong precipitation increases by 26% (15–37%) for the mid-latitudes. We present evidence that weakening storm track activity contributes to the projected increase in warm and dry persistence. These changes in persistence are largely avoided when warming is limited to 1.5 °C. In conjunction with the projected intensification of heat and rainfall extremes, an increase in persistence can substantially worsen the effects of future weather extremes.
Journal Article
Understanding the variability of Australian fire weather between 1973 and 2017
Australian fire weather shows spatiotemporal variability on interannual and multi-decadal time scales. We investigate the climate factors that drive this variability using 39 station-based historical time series of the seasonal 90th-percentile of the McArthur Forest Fire Danger Index (FFDI) extending from 1973 through 2017. Using correlation analyses, we examine the relationship of these time series to the El Niño Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and the Indian Ocean Dipole (IOD), considering both concurrent and time-lagged relationships. Additionally, longer term behaviour of the time series using linear trend analysis is discussed in the context of the climate drivers, Interdecadal Pacific Oscillation (IPO) and anthropogenic climate change. The results show that ENSO is the main driver for interannual variability of fire weather, as defined by FFDI in this study, for most of Australia. In general, El Niño-like conditions lead to more extreme fire weather, with this effect stronger in eastern Australia. However, there are significant regional variations to this general rule. In NSW, particularly along the central coast, negative SAM is a primary influence for elevated fire weather in late-winter and spring. In the southeast (VIC and TAS), the El Niño-like impact is exacerbated when positive IOD conditions are simultaneously observed. The spring conditions are key, and strongly influence what is observed during the following summer. On longer time scales (45 years), linear trends are upward at most stations; this trend is strongest in the southeast and during the spring. The positive trends are not driven by the trends in the climate drivers and they are not consistent with hypothesized impacts of the IPO, either before or after its late-1990s shift to the cold phase. We propose that anthropogenic climate change is the primary driver of the trend, through both higher mean temperatures and potentially through associated shifts in large-scale rainfall patterns. Variations from interannual factors are generally larger in magnitude than the trend effects observed to date.
Journal Article
Impact of low-pressure systems on winter heavy air pollution in the northwest Sichuan Basin, China
The cities of Chengdu, Deyang, and Mianyang in the northwest Sichuan Basin are part of a rapidly developing urban agglomeration adjoining the eastern slopes of the Tibetan Plateau. Heavy air pollution events have frequently occurred over these cities in recent decades, but the effects of meteorological conditions on these pollution events are unclear. We explored the effects of weather systems on winter heavy air pollution from 1 January 2006 to 31 December 2012 and from 1 January 2014 to 28 February 2017. A total of 10 heavy air pollution events occurred during the research period and 8 of these took place while the region was affected by a dry low-pressure system at 700 hPa. When the urban agglomeration was in front of the low-pressure system and the weather conditions were controlled by a warm southerly air flow, a strong temperature inversion appeared above the atmospheric boundary layer acting as a lid. Forced by this strong inversion layer, the local secondary circulation was confined to the atmospheric boundary layer, and the horizontal wind speed in the lower troposphere was low. As a result, vertical mixing and horizontal dispersion in the atmosphere were poor, favoring the formation of heavy air pollution events. After the low-pressure system had transited over the region, the weather conditions in the urban agglomeration were controlled by a dry and cold air flow from the northwest at 700 hPa. The strong inversion layer gradually dissipated, the secondary circulation enhanced and uplifted, and the horizontal wind speed in the lower troposphere also increased, resulting in a sharp decrease in the concentration of air pollutants. The strong inversion layer above the atmospheric boundary layer induced by the low-pressure system at 700 hPa thus played a key role in the formation of heavy air pollution during the winter months in this urban agglomeration. This study provides scientific insights for forecasting heavy air pollution in this region of China.
Journal Article