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Job Ad: Climate Modeling/Climate and Human Health-Associate Professor/Professor

12/3/2019

The University of Alabama, Department of Geography seeks a new colleague with research expertise in Climate Modeling or Climate and Human Health, starting August 16, 2020, at the rank of Associate Professor or Professor, with tenure.

This search is part of an effort to elevate the University of Alabama’s visibility and impact in climate research including the analysis and interpretation of climate data, particularly concerning hydroclimatology, climate-health relationships, environmental health sciences, environmental epidemiology, climate-related food security, or climate modeling more broadly. The ideal candidate’s professional accomplishments include sustained success securing external funding, a nationally/internationally recognized profile, and a solid track record of successful graduate student recruitment and mentoring.

We seek a scholar who can take advantage of the collaborative opportunities on the Tuscaloosa campus, including those at the newly–formed Alabama Water Institute (http://ovpred.ua.edu/alabama-water-institute/) and Alabama Life Research Institute (http://ovpred.ua.edu/alabama-life-research-institute/), and the NOAA National Water Center (http://www.nws.noaa.gov/oh/nwc/). Candidates with research interests that also complement one or more of the department’s broader research foci, including water resources, human-environment systems, environmental management and change, or geographic information analysis (see http://geography.ua.edu/), are particularly encouraged to apply. A Ph.D. in Geography or closely related discipline is required. It is expected that the successful candidate will transfer an active research program to the University of Alabama.

For more information, please visit the job site.

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Our new paper has been published in Climatic Change

10/27/2019

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Our new paper, entitled "Approval of Political Leaders can Slant Evaluation of Political Issues: Evidence from Public Concern for Climate Change in the U.S." has been published in Climatic Change. You can find the abstract below:

"Climate change has become one of the signature issues that divides the American public. Numerous empirical studies of the past two decades have identified the politicization of this issue. In recent years, the concurrence of rising extreme weather events and uptick in public concern for climate change has led to common speculation that the former may drive up the latter. Using a nationally representative survey dataset combined with climate extremes data including extreme heat, extreme precipitation, and mild drought or worse, we use Structural Equation Modeling to examine how politics and climate extremes altogether shape American public concern for climate change. In addition to confirming politicization of climate change, we find that approval of President Trump not only promotes skeptical climate change perceptions but also serve as an intervening amplifier of these perceptions for Republicans and conservatives. Thus, one’s concern for climate change is partially explained by their political identification and partially explained by their levels of approval of Trump. With the 2020 presidential election underway, it remains to be seen how attitudes toward presidential candidates can affect climate change perceptions and support for climate policies. The widely speculated role of climate extremes however fails to show significant effects in views towards climate change. We provide explanations for this insignificant finding. The study ends by calling for more studies to further investigate into the drivers of formation of opinions towards climate change."

The following figure is from the accepted manuscript (Shao and Hao 2019)

Figure 1. Structural Equation Modeling Diagram (Shao and Hao 2019)

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Our new paper is published in the International Journal of Environmental Health Research

9/16/2019

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A new paper I co-authored with Dr. Hoehun Ha is published in the International Journal of Environmental Health Research. In this paper, we examined potential factors that could affect community-level mental health across the United States. Here is the the summary:

"Mental health studies have underscored the hazardous conditions of each phase of life, from youth and pre-adulthood through adulthood in the United States. This situation calls for increased public awareness of the mental health issue and better understanding of the significant factors associated with mental health hazard. The main objective of this spatial epidemiological research is to gain greater insights into the geographic dimension displayed by the different duration of mentally unhealthy days (MUDs) across U.S. counties. Using Behavioural Risk Factor Surveillance System (BRFSS) data in 2014, we examine main factors of mental health hazard including health behaviour, clinical care, socioeconomic and physical environment, demographic, community resilience, and extreme climatic conditions. In this study, we take complex design factors such as clustering, stratification and sample weight in the BRFSS data into account by using Complex Samples General Linear Model (CSGLM). Then, spatial regression models, spatial lag and error models, are applied to examine spatial dependencies and heteroscedasticity. Econometric analysis underscores that all categories of air pollution, community resilience, and sunlight variables tested are significant push factors of mentally unhealthy days (MUDs) duration. Results of the geographic analyses indicate that counties with lower air pollution (PM2.5), higher community resilience (social, economic, infrastructure, and institutional resilience), and higher sunlight exposure had significantly lower average number of MUDs reported in the past 30 days. These findings suggest that policy makers should take air pollution, community resilience, and sunlight exposure into account when designing environmental and health policies and allocating resources to more effectively manage mental health problems."
The following figure is from this paper (Ha and Shao 2019)

Figure 1. County-level annual average number of age-adjusted mentally unhealthy days (MUDs) reported in the past 30 days, 2014 (source: Ha and Shao, forthcoming)

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National Socio-Environmental Synthesis Center (SYSYNC) Postdoctoral Fellowship in 2020

9/16/2019

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The National Socio-Environmental Synthesis Center (SESYNC), located in Annapolis, Maryland, invites applications from early-career scholars (≤ 4 years post Ph.D.) for two-year postdoctoral fellowships that begin June 1, 2020. This postdoctoral fellow is expected to work with a Collaborating Mentor on "projects that have the potential to advance understanding of socio-environmental systems."

I am interested in serving as a Collaborating Mentor, working with a postdoc fellow on a range of topics that would fall within the socio-environmental systems. Specific topics could include:

1. social response to climate extremes
2. climate adaptation decision making
3. community resilience to environmental hazards in an urban setting or at a regional scale

To learn more about this opportunity, please visit the SESYNC webiste.

If you are interested in working with me, please send an email to me at wshao1@ua.edu.

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The website of my lab Environmental Decision Making at UA is up and running

9/13/2019

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The website of my lab Environmental Decision Making at UA is up and running. Please check it out.
We encourage inquires from prospective Master of Science or Ph.D students with research interests in environmental decision making within a geographic context. In particular, we seek students with training in statistics, data analysis, quantitative methods, and Geographic Information System (GIS). Students' specific research interests can include:

1. environmental risk perceptions
2. individual adaptive behavior/intention
3. community vulnerability and resilience
4. environmental planning/policy
5. environmental hazards and public health

If you are interested in joining us, please send your inquiry along with your CV., unofficial transcripts, test scores to Dr. Wanyun Shao at wshao1@ua.edu.

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I am now an associate editor of Palgrave Communications

8/28/2019

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I have joined the International Editorial Board of Palgrave Communications (a Nature journal). I am an associate editor in the subject area of Geography and Demography.

Palgrave Communications is a fully open-access, online journal publishing peer-reviewed research across the full spectrum of the humanities and social sciences. Palgrave Communications welcomes the submission of in-depth interdisciplinary studies.

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A new paper in Palgrave Communications

8/20/2019

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In a new paper I co-authored with Dr. Jonghun Kam and his Ph.D student Soon-Yoon Kim at the Department of Civil and Environmental Engineering, we used Google Trends to reveal the spatiotemporal patterns of US drought awareness. This paper has been published in Palgrave Communications (a Nature journal). Here is more information about this paper:

Article Title: Spatiotemporal Patterns of US Drought Awareness

Summary:
Drought is a creeping climatological phenomenon with persistent precipitation deficits. The intangible and gradual characteristics of drought cause a lack of social response during the onset. The level of awareness of a local drought increases rapidly through mass media reports and online information searching activities when the drought reaches its peak severity. This high level of local drought awareness drives concerns for water shortage and support for water policy. However, spatiotemporal patterns of national-scale drought awareness have never been studied due to constraints imposed by time-consuming and costly survey data collection and surveys' limited sample sizes.
Here, we present the national-scale study to reveal the spatiotemporal patterns of drought awareness over the contiguous United States (CONUS) using Google Trends data and an advanced statistical technique, Principal Component Analysis (PCA). Results show that the first two PC modes can explain 48% (38% for PC1 and 10% for PC2; see Figures below) of the total variance of state-level drought awareness. We find that the PC1 mode relates to a national pattern of drought awareness across the CONUS. The spatiotemporal patterns further imply that residents in the Northeastern US region are the most aware of the emergence of drought, regardless of the geographic location of the occurrence. The results illustrate how search engine queries and social media data can help develop an effective and efficient plan for drought mitigation in the future.

The following Figure comes from Kim et al. (2019):

Figure 1: Major principle components of state-level drought awareness and state-level drought risk over the contiguous United States. Temporal correlations of Drought Awareness from the first two major modes with individual state-level drought awareness ((c) and (d), respectively) and individual state-level drought risk ((e) and (f), respectively). White colored states depict the states with insignificant temporal correlation at the 99% confident level.

Figure 2: State-level correlation analysis of drought awareness and drought risk. Colors in the grid cells depict temporal correlation coefficients of state-level drought awareness (left triangle) and state-level drought risk (right triangle) of one state with those of the rest 48 states. To assist interpretation, areas that depict interstate relationships within the region (green colored boundaries) and across regions (blue colored boundaries) are shown in the legend box at upper-left corner.

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A new paper in Disasters

6/28/2019

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Our new paper was published in Disasters (impact factor: 1.797). Here is the abstract:

"It is of significance to assess and depict community vulnerability to floods and hurricanes. Over the past several decades, flooding and hurricanes have affected millions of people and caused massive economic losses. Despite efforts to reduce risks, these natural hazards remain to be a considerable challenge to coastal communities. In this paper, Geographic Information Systems (GIS) methods are used to analyze coastal communities’ vulnerability to hurricanes and flooding along the U.S. Gulf coast, which is prone to these two hazards. Specifically, two types of quantitative indicators are developed: exposure to hurricanes and flooding, based on data from multiple sources such as National Climate Data Center and National Flood Insurance Program among others, and a social vulnerability index, constructed on census data at census tract level. These indices are combined to depict the spatial patterns of overall community vulnerability to flooding and hurricane hazards along the U.S. Gulf Coast. Results of this study can potentially inform disaster management agencies, county governments and municipalities of areas with heightened community vulnerabilities. The demonstration of geographic distribution of community vulnerability can assist decision makers in prioritizing to‐do items and designing policies/plans for more effective allocation of resources. We end this paper by discussing the limitations to the present study and the practical implications of the assessment."
The following two figures are from this article (Shao et al. forthcoming).

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A new paper in Environmental Research Letters

4/15/2019

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Our paper on public support for flood mitigation was just published on Environmental Research Letters (impact factor: 6.192). Here is the abstract:

"What is the decision-making mechanism people rely upon to mitigate flood risk? Applying Bayesian Network modelling to a comprehensive survey dataset for the U.S. Gulf Coast, we find that the overall support for flood mitigation can be inferred from flood insurance purchase behavior (i.e., without insurance vs. with insurance purchased mandatorily, voluntarily, or both). Therefore, we propose a theoretical decision-making mechanism composed of two dimensions including informed flood risk and sense of insecurity. The informed flood risk is the primary determinant on one's overall support for flood mitigation. Risk mitigation decisions are largely contingent on the level of risk that is effectively conveyed to individuals. Additionally, sense of insecurity plays a moderate role in determining individuals' overall support for flood mitigation. The sense of insecurity can move people toward overall support for mitigation, but the effect is not as large as the informed risk. Results of this study have fundamental policy implications. The flood risk informed by Federal Emergency Management Agency's flood maps not only provides the compulsory basis for flood insurance purchase but also determines individuals' overall support for flood mitigation. Flood map inaccuracy can immensely mislead individuals' overall risk mitigation decision. Meanwhile, this flood risk mitigation decision-making mechanism inferred from a survey data in the U.S. Gulf Coast needs to be tested and validated elsewhere."

In this paper, we proposed a flood mitigation decision-making mechanism (please see below). One implication of this study is that "the importance of risk information in overall flood mitigation decisions. Although the flood premiums do not reflect real risks due to discounts, flood hazard zones have effectively conveyed the risk to homeowners. Risk signals can thus be delivered to homeowners through various means."