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Henry P. Huntington and Gary M. Lackmann
Open access
Corey Davis, Heather Aldridge, Ryan Boyles, Karen S. McNeal, Lindsay Maudlin, and Rachel Atkins

Abstract

While there is growing demand for use of climate model projections to understand the potential impacts of future climate on resources, there is a lack of effective visuals that convey the range of possible climates across spatial scales and with uncertainties that potential users need to inform their impact assessments and studies. We use usability testing including eye tracking to explore how a group of resource professionals (foresters) interpret and understand a series of graphical representations of future climate change, housed within a web-based decision support system (DSS), that address limitations identified in other tools. We find that a three-map layout effectively communicates the spread of future climate projections spatially, that location-specific information is effectively communicated if depicted both spatially on a map and temporally on a time series plot, and that model error metrics may be useful for communicating uncertainty and in demonstrating the utility of these future climate datasets.

Open access
John Y. N. Cho and James M. Kurdzo

Abstract

An econometric geospatial benefit model for nontornadic thunderstorm wind casualty reduction is developed for meteorological radar network planning. Regression analyses on 22 years (1998–2019) of storm event and warning data show, likely for the first time, a clear dependence of nontornadic severe thunderstorm warning performance on radar coverage. Furthermore, nontornadic thunderstorm wind casualty rates are observed to be negatively correlated with better warning performance. In combination, these statistical relationships form the basis of a cost model that can be differenced between radar network configurations to generate geospatial benefit density maps. This model, applied to the current contiguous U.S. weather radar network, yields a benefit estimate of $207 million (M) yr−1 relative to no radar coverage at all. The remaining benefit pool with respect to enhanced radar coverage and scan update rate is about $36M yr−1. Aggregating these nontornadic thunderstorm wind results with estimates from earlier tornado and flash flood cost reduction models yields a total benefit of $1.12 billion yr−1 for the present-day radars and a remaining radar-based benefit pool of $778M yr−1.

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Amy Savage, Lisa Schubert, Corey Huber, Hilary Bambrick, Nina Hall, and Bill Bellotti

Abstract

Climate change, malnutrition, and noncommunicable diseases (NCDs) are three of the most significant health challenges of this century, and they share fundamental underlying drivers. Pacific Island countries (PICs) are at the forefront of the impacts of climate change, which is likely to affect food and nutrition security (FNS) directly and indirectly, and many countries have existing high NCD burdens. This paper surveys the climate change adaptation (CCA) landscape in one PIC, Vanuatu. It explores the extent to which FNS and diet-related NCDs are considered and addressed within CCA initiatives. A comprehensive review of the literature related to CCA, FNS, and NCDs in Vanuatu was combined with 32 semistructured interviews with key experts and stakeholders. This study found that some promising groundwork has been laid for tackling the effects of climate change on FNS in policy and governance, agriculture, coastal management, and nutrition. However, several opportunities for strengthening CCA were identified: targeting urban populations; complementary integration of disaster risk reduction and CCA; incorporating local knowledge; applying a systems-based framing of NCDs as climate-sensitive health risks; and emphasizing human-centered, community-led CCA. Vanuatu will continue to be affected by accelerating climate change. A strong foundation for CCA presents clear opportunities for further development. As food and nutrition insecurity and diet-related NCD risk factors are increasingly exacerbated by climate change, alongside other socioeconomic drivers, it is crucial to find new and innovative ways to increase transformational resilience and adaptive capacity that also improve nutrition and health outcomes.

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Jessica N. Burgeno and Susan L. Joslyn

Abstract

For high-impact weather events, forecasts often start days in advance. Forecasters believe that consistency among subsequent forecasts is important to user trust and can be reluctant to make changes when newer, potentially more accurate information becomes available. However, to date, there is little empirical evidence for an effect of inconsistency among weather forecasts on user trust, although the reduction in trust due to inaccuracy is well documented. The experimental studies reported here compared the effects of forecast inconsistency and inaccuracy on user trust. Participants made several school closure decisions based on snow accumulation forecasts for one and two days prior to the target event. Consistency and accuracy were varied systematically. Although inconsistency reduced user trust, the effect of the reduction due to inaccuracy was greater in most cases suggesting that it is inadvisable for forecasters to sacrifice accuracy in favor of consistency.

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I. Martínez-Zarzoso

Abstract

This paper investigates the extent to which international migration can be explained by climate change and whether this relationship varies systematically between groups of countries. The primary focus is to further investigate the heterogeneous effect found for countries with different income levels using a yearly migration dataset and allowing the country grouping to be data driven. For this purpose, a recently proposed statistical technique is used, the grouped fixed-effects (GFE) estimator, which groups the countries of origin according to the data generating process. The results indicate that, on average, increasing population-weighted temperatures are associated with an increase in emigration rates but that the pattern differs between groups. The relationship is driven by a group of countries mainly located in Africa and central Asia. No statistically robust association is found between population-weighted precipitation and emigration.

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Mikhail Varentsov, Natalia Shartova, Mikhail Grischenko, and Pavel Konstantinov

Abstract

The assessment of bioclimatic conditions at the national scale remains a highly relevant task. It might be one of the main parts of the national strategy for the sustainable development of different regions under changing climatic conditions. This study evaluated the thermal comfort conditions and their changes in Russia according to gridded meteorological data from ERA-Interim reanalysis with a spatial resolution of 0.75° × 0.75° using the two most popular bioclimatic indices based on the human energy balance: physiologically equivalent temperature (PET) and universal thermal comfort index (UTCI). We analyzed the summer and winter means of these indices as well as the repeatability of different thermal stress grades for the current climatological standard normal period (1981–2010) and the trends of these parameters over the 1979–2018 period. We revealed the high diversity of the analyzed parameters in Russia as well as significant differences between the contemporary climate conditions and their changes in terms of mean temperature, mean values of bioclimatic indices, and thermal stress repeatability. Within the country, all degrees of thermal stress were possible; however, severe summer heat stress was rare, and in winter nearly the whole country experienced severe cold stress. Multidirectional changes in bioclimatic conditions were observed in Russia against the general background of climate warming. The European part of the country was most susceptible to climate change because it experiences significant changes both in summer and winter thermal stress repeatability. Intense Arctic warming was not reflected in significant changes in thermal stress repeatability.

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Rachel Dryden, M. Granger Morgan, and Stephen Broomell

Abstract

An increase in the severity of extreme weather is arguably one of the most important consequences of climate change with immediate and potentially devastating impacts. Recent events, like Hurricane Harvey, stimulated public discourse surrounding the role of climate change in amplifying, or otherwise modifying, the patterns of such events. Within the scientific community, recent years have witnessed considerable progress on “climate attribution”—the use of statistical techniques to assess the probability that climate change is influencing the character of some extreme weather events. Using a novel application of signal detection theory, this article assesses when, and to what extent, laypeople attribute changes in hurricanes to climate change and whether and how certain characteristics predict this decision. The results show that people attribute hurricanes to climate change based on their preexisting climate beliefs and numeracy. Respondents who were more dubious about the existence of climate change (and more numerate) required a greater degree of evidence (i.e., a more extreme world) before they were willing to suggest that an unusual hurricane season might be influenced by climate change. However, those who have doubts were still willing to make these attributions when hurricane behavior becomes sufficiently extreme. In general, members of the public who hold different prior views about climate change are not in complete disagreement about the evidence they perceive, which leaves the possibility for future work to explore ways to bring such judgments back into alignment.

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Samuel J. Childs, Russ S. Schumacher, and Stephen M. Strader

Abstract

Severe convective storms along the Front Range and eastern plains of Colorado frequently produce tornadoes and hail, leading to substantial damage and crop losses annually. Determination of future human exposure from these events must consider both changes in meteorological conditions and population dynamics. Projections of EF0 + tornadoes (on the enhanced Fujita scale) and severe [1.0+ in. (25.4+ mm)] hail reports out to the year 2100 are computed using convective parameter proxies generated from dynamically downscaled GFDL Climate Model, version 3 (GFDL CM3), output by the WRF Model for control and future climate scenarios. The proxies suggest that tornado and hail days in the region may increase by up to one tornado day and three hail days per year by 2100, with the greatest increases across northeastern Colorado. Using a spatially explicit Monte Carlo model, projected future frequency and spatial changes in tornadoes and hail are superimposed with population projections from the shared socioeconomic pathways (SSPs) to provide a range of possible scenarios for end-of-century human exposure to tornadoes and hailstorms. Changes in hazard frequency and spatial distribution may amplify human exposure up to 117% for tornadoes and 178% for hail in the region by 2100, although specific results are sensitive to uncertain combinations of future overlaps between hazard spatial distribution and population. Findings presented herein not only will provide the public, insurers, policy makers, land-use planners, and researchers with estimates of potential future tornado and hail impacts in the Front Range region, they also will allow the weather enterprise to better understand, prepare for, and communicate tornado and hail risk to eastern Colorado communities.

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Tyler A. Beeton and Shannon M. McNeeley

Abstract

Although drought is a natural part of climate across the north-central United States, how drought is experienced and responded to is the result of complex biophysical and social processes. Climate change assessments indicate drought impacts will likely worsen in the future, which will further challenge decision-making. Here, a drought management decision typology is empirically developed from synthesis of three in-depth case studies using a modified grounded-theory approach. The typology highlights 1) the entity or entities involved, 2) management sectors, 3) decision types, 4) spatial and temporal scale(s) of decision-making, and 5) barriers that inhibit decision-making. Findings indicate similarities in decision types and barriers across cases. Changes in operations, practices, or behaviors; information and technology; and legal or policy changes were the most common decision types, while commonly cited barriers were institutional constraints, fragmented decision-making, and limited personnel and financial resources. Yet barriers and responses also differed within and between sectors and jurisdictions. Several barriers inhibited anticipatory, regional, and interagency drought response, such as limited institutional support, competing mandates, limited resources, lack of usable information, limits to interagency fund transfers, and historical context and distrust among entities. Findings underscore the importance of documenting nuanced decision-making in local places and broader generalizations in decision-making across scales. This contributes to the goal of developing drought science that is actionable for decision-making.

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