More Like this

1. Forest Management and Adaptation Strategies in Response to Climate Change by the Taiwanese Public

   https://doi.org/10.3390/atmos12081056  

   Wan-Yu Liu, Chien-Chen Wu (August 2021, Atmosphere)

   null (Ed.)

   Forests account for 60% of lands in Taiwan. Climate change impacts forests in many aspects and is increasingly likely to undermine the ability of forests to provide basic ecosystem services. To help reduce the impact of climate change on Taiwan’s forests, people must be made aware of the relationship between climate change and forests. Based on questionnaires collected from 17 cities in Taiwan, this study applied spatial analysis to assess the respondents’ understanding of climate change and adaptation strategies for forest management. A total of 650 questionnaires were distributed and 488 valid ones were collected. The results show that (1) Most respondents believe that climate change is true and more than half of the respondents have experienced extreme weather events, especially extreme rainfall; (2) Most respondents believe that climate change will affect Taiwan’s forests with the majority recognizing the increasing impact of extreme events being the primary cause, followed by changes in the composition of tree species and the deterioration of forest adaptability due to climate change; (3) Most respondents expressed that forest management should be adjusted for climate change and called for measures being taken to establish mixed forests as well as monitoring forest damage; (4) In order to address the difficulties faced by forest owners on the impact of climate change, the majority of respondents felt that the government should raise forest owners’ understanding on climate change and adaptation policies, while the subsidy incentives must also be adjusted. The results of this study show that the respondents do realize the importance of climate change and forest management so much so their awareness in this matter led to their support for forest adaptation measures and policies. 

   more » « less
2. Revealing the Statistics of Extreme Events Hidden in Short Weather Forecast Data

   https://doi.org/10.1029/2023AV000881  

   Finkel, Justin; Gerber, Edwin P.; Abbot, Dorian S.; Weare, Jonathan (March 2023, AGU Advances)

   Abstract Extreme weather events have significant consequences, dominating the impact of climate on society. While high‐resolution weather models can forecast many types of extreme events on synoptic timescales, long‐term climatological risk assessment is an altogether different problem. A once‐in‐a‐century event takes, on average, 100 years of simulation time to appear just once, far beyond the typical integration length of a weather forecast model. Therefore, this task is left to cheaper, but less accurate, low‐resolution or statistical models. But there is untapped potential in weather model output: despite being short in duration, weather forecast ensembles are produced multiple times a week. Integrations are launched with independent perturbations, causing them to spread apart over time and broadly sample phase space. Collectively, these integrations add up to thousands of years of data. We establish methods to extract climatological information from these short weather simulations. Using ensemble hindcasts by the European Center for Medium‐range Weather Forecasting archived in the subseasonal‐to‐seasonal (S2S) database, we characterize sudden stratospheric warming (SSW) events with multi‐centennial return times. Consistent results are found between alternative methods, including basic counting strategies and Markov state modeling. By carefully combining trajectories together, we obtain estimates of SSW frequencies and their seasonal distributions that are consistent with reanalysis‐derived estimates for moderately rare events, but with much tighter uncertainty bounds, and which can be extended to events of unprecedented severity that have not yet been observed historically. These methods hold potential for assessing extreme events throughout the climate system, beyond this example of stratospheric extremes. 

   more » « less
3. How will climate change shape climate opinion?

   https://doi.org/10.1088/1748-9326/ab466a  

   Howe, Peter D.; Marlon, Jennifer R.; Mildenberger, Matto; Shield, Brittany S. (October 2019, Environmental Research Letters)

   Abstract As climate change intensifies, global publics will experience more unusual weather and extreme weather events. How will individual experiences with these weather trends shape climate change beliefs, attitudes, and behaviors? In this article, we review 73 papers that have studied the relationship between climate change experiences and public opinion. Overall, we find mixed evidence that weather shapes climate opinions. Although there is some support for a weak effect of local temperature and extreme weather events on climate opinion, the heterogeneity of independent variables, dependent variables, study populations, and research designs complicate systematic comparison. To advance research on this critical topic, we suggest that future studies pay careful attention to differences between self-reported and objective weather data, causal identification, and the presence of spatial autocorrelation in weather and climate data. Refining research designs and methods in future studies will help us understand the discrepancies in results, and allow better detection of effects, which have important practical implications for climate communication. As the global population increasingly experiences weather conditions outside the range of historical experience, researchers, communicators, and policymakers need to understand how these experiences shape-and are shaped by-public opinions and behaviors. 

   more » « less
4. Winter Weather Whiplash: Impacts of Meteorological Events Misaligned With Natural and Human Systems in Seasonally Snow‐Covered Regions

   https://doi.org/10.1029/2019EF001224  

   Casson, N_J; Contosta, A_R; Burakowski, E_A; Campbell, J_L; Crandall, M_S; Creed, I_F; Eimers, M_C; Garlick, S.; Lutz, D_A; Morison, M_Q; et al (December 2019, Earth's Future)

   Abstract “Weather whiplash” is a colloquial phrase for describing an extreme event that includes shifts between two opposing weather conditions. Prior media coverage and research on these types of extremes have largely ignored winter weather events. However, rapid swings in winter weather can result in crossing from frozen to unfrozen conditions, or vice versa; thus, the potential impact of these types of events on coupled human and natural systems may be large. Given rapidly changing winter conditions in seasonally snow‐covered regions, there is a pressing need for a deeper understanding of such events and the extent of their impacts to minimize their risks. Here we introduce the concept of winter weather whiplash, defined as a class of extreme event in which a collision of unexpected conditions produces a forceful, rapid, back‐and‐forth change in winter weather that induces an outsized impact on coupled human and natural systems. Using a series of case studies, we demonstrate that the effects of winter weather whiplash events depend on the natural and human context in which they occur, and discuss how these events may result in the restructuring of social and ecological systems. We use the long‐term hydrometeorological record at the Hubbard Brook Experimental Forest in New Hampshire, USA to demonstrate quantitative methods for delineating winter weather whiplash events and their biophysical impacts. Ultimately, we argue that robust conceptual and quantitative frameworks for understanding winter weather whiplash events will contribute to the ways in which we mitigate and adapt to winter climate change in vulnerable regions. 

   more » « less
5. Extreme Weather Events and the Performance of Critical Utility Infrastructures: A Case Study of Hurricane Harvey

   https://doi.org/10.1007/s41885-023-00139-9  

   Rafi, Shahnawaz; Meng, Sisi; Santos, Joost; Mozumder, Pallab (December 2023, Economics of Disasters and Climate Change)

   Extreme weather events have significant economic and social impacts, disrupting essential public services like electricity, phone communication, and transportation. This study seeks to understand the performance and resilience of critical infrastructure systems in Houston, Texas, using Hurricane Harvey (2017) as a case study. We surveyed 500 Houston Metropolitan Statistical Area residents after Hurricane Harvey’s landfall about disruption experience in electricity, water, phone/cellphone, internet, public transportation, workplace, and grocery stores. Our household survey data revealed the proportion and duration of disruption in each system. Approximately 70% of respondents reported experiencing electricity outages, while half (51%) had no access to water for up to six days. Two-thirds of surveyed households lacked internet access, and 50% had their phone services disconnected. Additionally, around 71% of respondents were unable to commute to work, and 73% were unable to purchase groceries for their families during this period. We incorporated the household survey responses into the Dynamic Inoperability Input-Output Model (DIIM) to estimate inoperability and economic losses across interconnected sectors. The projected economic loss was estimated to be in the range of $6.7- $9.7 billion when sensitivity analysis is performed with respect to the number of working days. Understanding the resilience of each sector and the inherent interdependencies among them can provide beneficial insight to policymakers for disaster risk management, notably preparedness and recovery planning for future events. 

   more » « less