Browse

You are looking at 1 - 10 of 118,680 items for

  • Refine by Access: All Content x
Clear All
Zeke Baker

Abstract

A major implication of climate change is the declining capacity for communities to anticipate future conditions and scenarios. In the Bering Sea region of western Alaska, this situation is acute and holds manifold consequences, particularly for the region’s primarily Indigenous residents. Based upon interviews and fieldwork in two Bering Sea communities and among regional weather forecasters, this paper explores the intertwined temporalities of weather, climate, and social life. I demonstrate that anticipatory culture, which otherwise structures anticipatory practices with regard to climate, local weather, and social life, is beset by temporal dissonance across three time scales. First, dramatic climatic and ecosystem shifts reshape how Indigenous Peoples envision themselves as culturally inhabiting a long-range history and future. Second, changes in weather patterns, ecological cycles, and sea ice dynamics upset evaluations of seasonality, leading to a pervasive sense of unpredictability. Third, on the everyday time scale, social and technological change complicates mariners’ evaluations of risk and economic (commercial and subsistence) decision-making. I conclude by connecting these three socioenvironmental temporalities to the temporal frames that primarily characterize weather and climate services, with an emphasis on the U.S. National Weather Service. The paper discusses how such services may further orient toward engaging socially embedded practices of anticipation in addition to formal prediction. Such an orientation can help to shape an anticipatory culture that more closely aligns meteorological and social patterns.

Restricted access
Yu-Wen Su

Abstract

The continuously increasing temperatures worldwide indicate that the frequently extreme heat in summer will become a new normal. The extreme high temperature (EHT) could be dangerous to human health, especially for outdoor workers or commuters, and could increase the risk of grid collapse. Thus, the possibility of a day off due to EHT has started to be discussed in Taiwan, based on the experience of typhoon day off, but discussions have not yet concluded. In this study, the effects of the EHT day off on electricity consumption in the industrial, service, and residential sectors were investigated through two determinants: First, high temperature would increase the electricity consumption in space cooling. Second, a day off would change people’s behavior of electricity consumption from workday to nonworkday modes. Combining the effects of cooling hours and nonworkdays, the net influence of the EHT day off on electricity consumption can be evaluated. Estimated results indicated that an EHT day off can reduce aggregate electricity consumption by between 0.41% and 1.08%. The reduction of electricity consumption due to the off day offsets the increase driven by high temperatures. Thus, an EHT day off will mitigate the pressure on the power grid and benefit electricity conservation.

Restricted access
Zhiming Yang, Bo Yang, Pengfei Liu, Yunquan Zhang, and Xiao-Chen Yuan

Abstract

Climate may significantly affect human society. Few studies have focused on the temperature impact on residents’ health, especially mental health status. This paper uses 98 423 observations in China to study the relationship between temperature and health, based on the China Family Panel Studies survey during 2010–16. We analyze the health effects of extreme hot and cold weather and compare the effects under different social demographic factors including gender, age, and income. We find that temperature and health status exhibit a nonlinear relationship. Women and low-income households are more likely to be impacted by extreme cold, whereas men, the elderly, and high-income households are more sensitive to extreme heat. Our results highlight the potential effects of extreme temperatures on physical and mental health and provide implications for future policy decisions to protect human health under a changing climate.

Restricted access
Siqin Wang, Yan Liu, and Jonathan Corcoran

Abstract

Both the built environment and the natural environment have a physiological and psychological effect on human behavior, which potentially affects people’s sensitivity and tolerance to surrounding noise and leads to annoyance, nuisance, distress, or overt actions and aggressive behaviors such as noise complaints to people living nearby. This study aims to explore the extent to which weather conditions affect the prevalence of noise complaints between neighbors mediated through the neighborhood’s built environment. Using Brisbane, Australia, as a study case, we draw on a large-scale administrative dataset from 2016 to explore the monthly and seasonal variations of noise complaints between neighbors and employ a stepwise multiple regression to analyze the extent to which weather factors affect noise complaints. Our findings show that neighbors largely complain about noise made by animals, and such complaints most frequently appear in March–May, the autumn season in the Southern Hemisphere. Built environment plays a primary role in noise complaints, and culturally diverse suburbs with less green space tend to have a higher likelihood of neighbor complaints in spring and summer; such a likelihood is further increased by a higher level of wind, humidity, and temperature in a yearly time frame. However, the effect of weather on animal- and non-animal-related noise complaints in different seasons is less consistent. Our findings, to a certain degree, reveal that weather conditions may serve as a psychological moderator to change people’s tolerance and sensitivity to noise, alter their routine activities and exposure to noise sources, and further affect the likelihood of noise complaints between neighbors.

Restricted access
Victoria A. Johnson, Kimberly E. Klockow-McClain, Randy A. Peppler, and Angela M. Person

Abstract

Residents of the Oklahoma City metropolitan area are frequently threatened by tornadoes. Previous research indicates that perceptions of tornado threat affect behavioral choices when severe weather threatens and, as such, are important to study. In this paper, we examine the potential influence of tornado climatology on risk perception. Residents across central Oklahoma were surveyed about their perceptions of tornado proneness for their home location, and this was compared with the local tornado climatology. Mapping and programming tools were then used to identify relationships between respondents’ perceptions and actual tornado events. Research found that some dimensions of the climatology, such as tornado frequency, nearness, and intensity, have complex effects on risk perception. In particular, tornadoes that were intense, close, and recent had the strongest positive influence on risk perception, but weaker tornadoes appeared to produce an “inoculating” effect. Additional factors were influential, including sharp spatial discontinuities between neighboring places that were not tied to any obvious physical feature or the tornado climatology. Respondents holding lower perceptions of risk also reported lower rates of intention to prepare during tornado watches. By studying place-based perceptions, this research aims to provide a scientific basis for improved communication efforts before and during tornado events and for identifying vulnerable populations.

Open access
Jen Henderson, Lisa Dilling, Rebecca Morss, Olga Wilhelmi, and Ursula Rick

Abstract

Unintended consequences from decisions made in one part of a social–ecological system in response to climate hazards can magnify vulnerabilities for others in the same system. Yet anticipating or identifying these cascades and spillovers in real time is difficult. Social learning is an important component of adaptation that has the ability to facilitate adaptive capacity by mobilizing multiple actors around a common resource to manage collectively in ways that build local knowledge, reflective practices, and a broader understanding of contexts for decisions. While the foundations of social learning in resource management have been theorized in the literature, empirical examples of unintended consequences that trigger social learning are few. This article analyzes two cases of drought decisions made along the Arkansas River basin in Colorado; in each, social learning occurred after actors experienced unanticipated impacts from others’ decisions. Methods include interviews with actors, both individual and institutional representatives of different sectors (recreation, agriculture, etc.), and a review of relevant historical and policy documents. The study identifies four features of social learning that aided actors’ responses to unanticipated consequences: governance structures that facilitated more holistic river management; relationship boundaries that expanded beyond small-scale decisions to capture interactions and emergent problems; knowledge of others’ previous experience, whether direct or indirect; and creation of spaces for safer experimentation with adaptation changes. Results identify empirical examples of actors who successfully learned to adapt together to unexpected consequences and thus may provide insight for others collectively managing drought extremes.

Restricted access
Jiwoo Lee, Kenneth R. Sperber, Peter J. Gleckler, Karl E. Taylor, and Céline J. W. Bonfils

Abstract

We evaluate extratropical modes of variability in the three most recent phases of the Coupled Model Intercomparison Project (CMIP3, CMIP5, and CMIP6) to gauge improvement of climate models over time. A suite of high-level metrics is employed to objectively evaluate how well climate models simulate the observed northern annular mode (NAM), North Atlantic Oscillation (NAO), Pacific–North America pattern (PNA), southern annular mode (SAM), Pacific decadal oscillation (PDO), North Pacific Oscillation (NPO), and North Pacific Gyre Oscillation (NPGO). We apply a common basis function (CBF) approach that projects model anomalies onto observed empirical orthogonal functions (EOFs), together with the traditional EOF approach, to CMIP Historical and AMIP models. We find simulated spatial patterns of those modes have been significantly improved in the newer models, although the skill improvement is sensitive to the mode and season considered. We identify some potential contributions to the pattern improvement of certain modes (e.g., the Southern Hemisphere jet and high-top vertical coordinate); however, the performance changes are likely attributed to gradual improvement of the base climate and multiple relevant processes. Less performance improvement is evident in the mode amplitude of these modes and systematic overestimation of the mode amplitude in spring remains in the newer climate models. We find that the postdominant season amplitude errors in atmospheric modes are not limited to coupled runs but are often already evident in AMIP simulations. This suggests that rectifying the egregious postdominant season amplitude errors found in many models can be addressed in an atmospheric-only framework, making it more tractable to address in the model development process.

Restricted access
Minghao Yang, Chongyin Li, Xiong Chen, Yanke Tan, Xin Li, Chao Zhang, and Guiwan Chen

Abstract

The reproducibility of climatology and the midwinter suppression of the cold-season North Pacific storm track (NPST) in historical runs of 18 CMIP6 models is evaluated against the NCEP reanalysis data. The results show that the position of the climatological peak area of 850-hPa meridional eddy heat flux (υT850) is well captured by these models. The spatial patterns of climatological υT850 are basically consistent with the NCEP reanalysis. Generally, NorESM2-LM and CESM2-WACCM present a relatively strong capability to reproduce the climatological amplitude of υT850 with lower RMSE than the other models. Compared with CMIP5 models, the intermodel spread of υT850 climatology among the CMIP6 models is smaller, and their multimodel ensemble is closer to the NCEP reanalysis. The geographical distribution in more than half of the selected models is farther south and east. For the subseasonal variability of υT850, nearly half of the models exhibit a double-peak structure. In contrast, the apparent midwinter suppression in the NPST represented by the 250-hPa filtered meridional wind variance (υυ250) is reproduced by all the selected models. In addition, the present study investigates the possible reasons for simulation biases regarding climatological NPST amplitude. It is found that a higher model horizontal resolution significantly intensifies the climatological υυ250. There is a significant in-phase relationship between climatological υυ250 and the intensity of the East Asian winter monsoon (EAWM). However, the climatological υT850 is not sensitive to the model grid spacing. Additionally, the climatological low-tropospheric atmospheric baroclinicity is uncorrelated with climatological υυ250. The stronger climatological baroclinic energy conversion is associated with the stronger climatological υT850.

Open access
Wenjun Cui, Xiquan Dong, Baike Xi, and Zhe Feng

Abstract

This study uses machine-learning methods, specifically the random-forests (RF) method, on a radar-based mesoscale convective system (MCS) tracking dataset to classify the five types of linear MCS morphology in the contiguous United States during the period 2004–16. The algorithm is trained using radar- and satellite-derived spatial and morphological parameters, along with reanalysis environmental information from a 5-yr manually identified nonlinear mode and five linear MCS modes. The algorithm is then used to automate the classification of linear MCSs over 8 years with high accuracy, providing a systematic, long-term climatology of linear MCSs. Results reveal that nearly 40% of MCSs are classified as linear MCSs, of which one-half of the linear events belong to the type of system having a leading convective line. The occurrence of linear MCSs shows large annual and seasonal variations. On average, 113 linear MCSs occur annually during the warm season (March–October), with most of these events clustered from May through August in the central eastern Great Plains. MCS characteristics, including duration, propagation speed, orientation, and system cloud size, have large variability among the different linear modes. The systems having a trailing convective line and the systems having a back-building area of convection typically move more slowly and have higher precipitation rate, and thus they have higher potential for producing extreme rainfall and flash flooding. Analysis of the environmental conditions associated with linear MCSs show that the storm-relative flow is of most importance in determining the organization mode of linear MCSs.

Restricted access
Kyle Chudler and Steven A. Rutledge

Abstract

The Propagation of Intraseasonal Oscillations (PISTON) field campaign took place in the waters of the western tropical North Pacific during the late summer and early fall of 2018 and 2019. During both research cruises, the Colorado State University SEA-POL polarimetric C-band weather radar obtained continuous 3D measurements of oceanic precipitation systems. This study provides an overview of the variability in convection observed during the PISTON cruises, and relates this variability to large-scale atmospheric conditions. Using an objective classification algorithm, precipitation features are identified and labeled by their size (isolated, sub-MCS, MCS) and degree of convective organization (nonlinear, linear). It is shown that although large mesoscale convective systems (MCSs) occurred infrequently (present in 13% of radar scans), they contributed a disproportionately large portion (56%) of the total rain volume. Conversely, small isolated features were present in 91% of scans, yet these features contributed just 11% of the total rain volume, with the bulk of the rainfall owing to warm rain production. Convective rain rates and 30-dBZ echo-top heights increased with feature size and degree of organization. MCSs occurred more frequently in periods of low-level southwesterly winds, and when low-level wind shear was enhanced. By compositing radar and sounding data by phases of easterly waves (of which there were several in 2018), troughs are shown to be associated with increased precipitation and a higher relative frequency of MCS feature occurrence, while ridges are shown to be associated with decreased precipitation and a higher relative frequency of isolated convective features.

Restricted access