Jon, Ihnji; Huang, Shih-Kai; Lindell, Michael K. (2019). Perceptions and Expected Immediate Reactions to Severe Storm Displays. Risk Analysis, 39(1), 274 – 290.
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Abstract
The National Weather Service has adopted warning polygons that more specifically indicate the risk area than its previous county-wide warnings. However, these polygons are not defined in terms of numerical strike probabilities (p(s)). To better understand people's interpretations of warning polygons, 167 participants were shown 23 hypothetical scenarios in one of three information conditions-polygon-only (Condition A), polygon + tornadic storm cell (Condition B), and polygon + tornadic storm cell + flanking nontornadic storm cells (Condition C). Participants judged each polygon's p(s) and reported the likelihood of taking nine different response actions. The polygon-only condition replicated the results of previous studies; p(s) was highest at the polygon's centroid and declined in all directions from there. The two conditions displaying storm cells differed from the polygon-only condition only in having p(s) just as high at the polygon's edge nearest the storm cell as at its centroid. Overall, p(s) values were positively correlated with expectations of continuing normal activities, seeking information from social sources, seeking shelter, and evacuating by car. These results indicate that participants make more appropriate p(s) judgments when polygons are presented in their natural context of radar displays than when they are presented in isolation. However, the fact that p(s) judgments had moderately positive correlations with both sheltering (a generally appropriate response) and evacuation (a generally inappropriate response) suggests that experiment participants experience the same ambivalence about these two protective actions as people threatened by actual tornadoes.
Keywords
Decision-making; Tornado; Risk; Communication; Numeracy; Residents; Shelter; Events; Protective Actions; Risk Perceptions; Tornado Warning Polygons; Judgments; Tornadoes; Meteorological Services; Storms; Lymphocytes B; Polygons; Emergency Warning Programs; Evacuation; Displays; Inappropriateness; Weather; Warnings; Conditions; Ambivalence
Wang, Kaiwen; Liu, Xiaomang; Li, Yuqi; Yang, Xiaohua; Bai, Peng; Liu, Changming; Chen, Fei. (2019). Deriving a Long-Term Pan Evaporation Reanalysis Dataset for Two Chinese Pan Types. Journal Of Hydrology, 579.
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Abstract
A long-term continuous and consistent pan evaporation (E-pan) reanalysis dataset will augment the analysis of E-pan distributions when the observation network is discontinuous or inconsistent, and assist in the evaluation of the outputs of General Circulation Models (GCMs) and Land Surface Models (LSMs). From the 1950s to early 2000s, China had a continuous observation of the D20 pan, but this was replaced by the 601B pan across China around 2002, and thus the E-pan observation network became discontinuous and inconsistent. This study developed a long-term monthly, 0.05 degrees, continuous and consistent reanalysis dataset for both D20 and 6018 pans covering mainland China throughout 1960-2014, based on meteorological data homogenization and interpolation and E-pan assimilation. The PenPan-V3 model used inE(pan) assimilation was successfully validated by observations at 767 and 591 stations for D20 and 601B pans, respectively. Comprehensively considering the physical influence of elevation, radiation, wind speed, humidity, and air temperature, the average annual and seasonal gridded E-pan reanalyses show significant spatial dependent on proximity to the ocean and latitude, consistent with previous studies. The reanalysis dataset can be used to analyze E-pan distributions across China, including the areas without observations, and to estimate the representativeness of E-pan to atmospheric evaporative demand. The dataset has been released in two cloud servers in China and the United States, and it will continue to be maintained and updated.
Keywords
General Circulation Model; Evaporation (meteorology); Atmospheric Temperature; Wind Speed; China; Long-term Continuous And Consistent Dataset; Pan Evaporation Reanalysis Dataset; Representativeness To Atmospheric Evaporative Demand; Maximal T-test; Reference Evapotranspiration; Climate Data; Energy-balance; Reference Crop; Trends; Water; Model; Demand; General Circulation Models; Air Temperature; Data Collection; Evaporation; Evaporative Demand; Humidity; Latitude; Meteorological Data; United States
Kim, Taehoon; Kim, Yong-Woo; Cho, Hunhee. (2020). Dynamic Production Scheduling Model Under Due Date Uncertainty in Precast Concrete Construction. Journal Of Cleaner Production, 257.
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Abstract
Precast concrete structures (PCs) are widely used in the construction industry to reduce project delivery times and improve quality. On-time delivery of PCs is critical for successful project completion because the processes involving precast concrete are the critical paths in most cases. However, existing models for scheduling PC production are not adequate for use in dynamic environments where construction projects have uncertain construction schedules because of various reasons such as poor labor productivity, inadequate equipment, and poor weather. This research proposes a dynamic model for PC production scheduling by adopting a discrete-time simulation method to respond to due date changes in real time and by using a new dispatching rule that considers the uncertainty of the due dates to minimize tardiness. The model is validated by simulation experiments based on various scenarios with different levels of tightness and due date uncertainty. The results of this research will contribute to construction project productivity with a reliable and economic precast concrete supply chain. (C) 2020 Elsevier Ltd. All rights reserved.
Keywords
Multiple Production; Demand Variability; Supply Chain; Shop; Management; Minimize; Lines; Precast Concrete Production; Dynamic Simulation; Uncertainty; Production Scheduling; Dispatching Rule
Lindell, Michael K.; Sorensen, John H.; Baker, Earl J.; Lehman, William P. (2020). Community Response to Hurricane Threat: Estimates of Household Evacuation Preparation Time Distributions. Transportation Research Part D-transport And Environment, 85.
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Abstract
Household evacuation preparation time distributions are essential when computing evacuation time estimates (ETEs) for hurricanes with late intensification or late changing tracks. Although evacuation preparation times have been assessed by expected task completion times, actual task completion times, and departure delays, it is unknown if these methods produce similar results. Consequently, this study compares data from one survey assessing expected task completion times, three surveys assessing actual task completion times, and three surveys assessing departure delays after receiving a warning. In addition, this study seeks to identify variables that predict household evacuation preparation times. These analyses show that the three methods of assessing evacuation preparation times produce results that are somewhat different, but the differences have plausible explanations. Household evacuation preparation times are poorly predicted by demographic variables, but are better predicted by variables that predict evacuation decisions-perceived storm characteristics, expected personal impacts, and evacuation facilitators.
Keywords
Travel Demand Model; Decision-making; Communication; Prediction; Simulation; Hurricane Evacuation Models; Preparation Time Distributions; Mobilization Time Distributions; Departure Delay Time Distributions; Social Milling
Peers, Justin B.; Lindell, Michael K.; Gregg, Christopher E.; Reeves, Ashleigh K.; Joyner, Andrew T.; Johnston, David M. (2021). Multi-Hazard Perceptions at Long Valley Caldera, California, USA. International Journal Of Disaster Risk Reduction, 52.
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Abstract
Caldera systems such as Long Valley Caldera, California; Taupo, New Zealand; and Campi Flegrei, Italy, experience centuries to millennia without eruption, but have the potential for large eruptions. This raises questions about how local residents' behavioral responses to these low-probability high-consequence events differ from their responses to events, such as wildfires and earthquakes, that have higher probabilities. To examine this issue, a multi-hazard mail survey of 229 households explored perceptions of-and responses to-volcano, earthquake and wildfire hazards in the Long Valley Volcanic Region. Response efficacy was the only significant predictor of emergency preparedness, which suggests that hazard managers can increase household emergency preparedness by emphasizing this attribute of protective actions. In addition to response efficacy, expected personal consequences, hazard intrusiveness, and affective responses were all significantly related to information seeking. This indicates that hazard managers can also increase households' information seeking about local hazards and appropriate protective actions by communicating the certainty and severity of hazard impacts (thus increasing expected personal consequences) and that they communicate this information repeatedly (thus increasing hazard intrusiveness) to produce significant emotional involvement (thus increasing affective response).
Keywords
Households Expected Responses; Risk Information-seeking; Volcanic Risk; Earthquake; Model; Adjustment; Mitigation; Communication; Preparedness; Predictors; Volcano Hazard Perception; Earthquake Hazard Perception; Wildfire Hazard Perception; Emergency Preparedness; Information Seeking
I am interested in developing analysis methods and metrics for accurate daylight analysis. More concretely, I would like to work on developing color accurate sky models through analyzing HDR photographs, and to integrate it to annual daylight simulation method. Additionally, I am also interested in integration of daylight simulation in environmental design.
The SHARE Lab (Safety and Health Advancement through Research and Education) has produced two ergonomics best practice booklets and two training videos on the use of 4-wheel carts in the roofing trade. Housed in the Department of Construction Management, the mission of the SHARE Lab is to promote construction safety and health through evidence-based innovative research, education, and practices. For more information, please contact Contact Dr. Ken-Yu Lin, Associate Professor, if you’d like access to the guide book or the…
On February 9, Lever for Change announced that the College of Built Environment’s Carbon Leadership Forum (CLF) and four other finalist teams will advance to the next stage of the 2030 Climate Challenge, a $10 million award launched last year to reduce greenhouse gas emissions in the U.S. by 2030. The Challenge, sponsored by an anonymous donor, will fund proven, data-driven solutions tackling greenhouse gas emissions in the buildings, industry, and/or transportation sectors in communities across the country. Sixty-eight proposals…
Urban ecology, simulation modeling, scenario planning, enhancing ecosystem functions in coupled human-natural systems
The Urban Ecology Research Laboratory (UERL) is an interdisciplinary team of University of Washington researchers and Ph.D. students studying cities as urban ecosystems. The lab studies urban landscapes as hybrid phenomena that emerge from the interactions between human and ecological processes, and the interactions between urban development and ecosystem dynamics.
As part of the University of Washington’s innovative leadership in urban ecology research and education, the UERL transcends traditional disciplinary boundaries to address some of society’s most challenging problems. UERL research interests include: complexity and resilience in coupled natural and human systems, urban landscape patterns and ecosystem function, urban ecosystem management, modeling land cover change, adaptation and scenario planning. The UERL assists planners, decision makers and non-governmental organizations in making informed decisions about urban development in a rapidly changing environment.
The Urban Ecology Research Laboratory is directed by Professor Marina Alberti, and includes interdisciplinary PhD students, post-doctoral research associates, research scientists, and affiliate faculty from diverse disciplines who collaborate to study coupled natural and human systems.