Erin Towler

Investigating the Use of a Genesis Potential Index for Tropical Cyclones in the North Atlantic Basin

Large-scale environmental variables known to be linked to the formation of tropical cyclones have previously been used to develop empirical indices as proxies for assessing cyclone frequency from large-scale analyses or model simulations. Here the authors examine the ability of two recent indices, the genesis potential (GP) and the genesis potential index, to reproduce observed North Atlantic cyclone annual frequency variations and trends. These skillfully estimate the mean seasonal variation of observed cyclones, but they struggle with reproducing interannual frequency variability and change. Examination of the independent contributions by the four terms that make up the indices finds that potential intensity and shear have significant skill, while moisture and vorticity either do not contribute to or degrade the indices’ capacity to reproduce observed interannual variability. It is also found that for assessing basinwide cyclone frequency, averaging indices over the whole basin is less skillful than its application to the general area off the coast of Africa broadly covering the main development region (MDR). These results point to a revised index, the cyclone genesis index (CGI), which comprises only potential intensity and vertical shear. Application of the CGI averaged over the MDR demonstrates high and significant skill at reproducing interannual variations and trends in all-basin cyclones across both reanalyses. The CGI also provides a more accurate reproduction of seasonal variations than the original GP. Future work applying the CGI to other tropical cyclone basins and to the downscaling of relatively course climate simulations is briefly addressed.

A framework for investigating large-scale patterns as an alternative to precipitation for downscaling to local drought

Global Climate Model (GCM) projections suggest that drought will increase across large areas of the globe, but lack skill at simulating climate variations at local-scales where adaptation decisions are made. As such, GCMs are often downscaled using statistical methods. This study develops a 3-step framework to assess the use of large-scale environmental patterns to assess local precipitation in statistically downscaling to local drought. In Step 1, two statistical downscaling models are developed: one based on temperature and precipitation and another based on temperature and a large-scale predictor that serves as a proxy for precipitation. A key component is identifying the large-scale predictor, which is customized for the location of interest. In Step 2, the statistical models are evaluated using NCEP/NCAR Reanalysis data. In Step 3, we apply a large ensemble of future GCM projections to the statistical models. The technique is demonstrated for predicting drought, as measured by the Palmer Drought Severity Index, in South-central Oklahoma, but the framework is general and applicable to other locations. Case study results using the Reanalysis show that the large-scale predictor explains slightly more variance than precipitation when predicting local drought. Applying future GCM projections to both statistical models indicates similar drying trends, but demonstrates notable internal variability. The case study demonstrates: (1) where a large-scale predictor performs comparably (or better) than precipitation directly, then it is an appealing predictor choice to use with future projections, (2) when statistically downscaling to local scales, it is critical to consider internal variability, as it may be more important than predictor selection.

Engaging Communities and Climate Change Futures with Multi-Scale, Iterative Scenario Building (MISB) in the Western United States

Current projections of future climate change foretell potentially transformative ecological changes that threaten communities globally. Using two case studies from the United States Intermountain West, this article highlights the ways in which a better articulation between theory and methods in research design can generate proactive applied tools that enable locally grounded dialogue about the future, including key vulnerabilities and potential adaptive pathways. Moreover, anthropological knowledge and methods, we find, are well-suited to the complexities and uncertainties that surround future climate change. In this article, we outline a narrative-driven assessment methodology we call multi-scale, iterative scenario building (MISB) that adheres to four key principles: (1) meaningful integration of socioecological interactions, (2) engagement with uncertainty, (3) awareness and incorporation of dynamic spatial and temporal scales, and (4) inclusion of diverse knowledge(s) from both social and natural sciences as well as from communities, including skeptics and deniers. The research found that MISB illuminated the complex, relational nature of vulnerability and adaptation and provided significant insight into potential, and sometimes surprising, future conflicts, synergies, and opportunities. We also found that MISB engendered a deep appreciation among participants, even skeptics and deniers, about the numerous, multi-scaled feedbacks and path dependencies generated by interacting drivers of social and ecological change. In conclusion, we argue this approach provides substantial space for the reflexive learning needed to create the “critical emancipatory knowledge” required in the face of transformational threats like climate change, and as such, we suggest potential avenues to support planning and decision making in the face of uncertain futures.

A risk-based approach to evaluating wildlife demographics for management in a changing climate: a case study of the Lewis's Woodpecker.

Given the projected threat that climate change poses to biodiversity, the need for proactive response efforts is clear. However, integrating uncertain climate change information into conservation planning is challenging, and more explicit guidance is needed. To this end, this article provides a specific example of how a risk-based approach can be used to incorporate a species’ response to climate into conservation decisions. This is shown by taking advantage of species’ response (i.e., impact) models that have been developed for a well-studied bird species of conservation concern. Specifically, we examine the current and potential impact of climate on nest survival of the Lewis’s Woodpecker (Melanerpes lewis) in two different habitats. To address climate uncertainty, climate scenarios are developed by manipulating historical weather observations to create ensembles (i.e., multiple sequences of daily weather) that reflect historical variability and potential climate change. These ensembles allow for a probabilistic evaluation of the risk posed to Lewis’s Woodpecker nest survival and are used in two demographic analyses. First, the relative value of each habitat is compared in terms of nest survival, and second, the likelihood of exceeding a critical population threshold is examined. By embedding the analyses in a risk framework, we show how management choices can be made to be commensurate with a defined level of acceptable risk. The results can be used to inform habitat prioritization and are discussed in the context of an economic framework for evaluating trade-offs between management alternatives.

Incorporating Climate Uncertainty in a Cost Assessment for New Municipal Source Water

AbstractThough new water supply source development has always required planning under many forms of uncertainty, climate change presents an added dimension that may exacerbate supply and water quality challenges. Hence, new decision-support tools are needed, and in this paper an approach that incorporates the uncertainty of climate variability and change into a cost assessment framework for a municipal drinking water provider in Colorado is developed and applied. The water utility provider is developing a new source of water supply, but treatment costs are relatively high because of the advanced processes needed to treat the water to desired standards. Furthermore, the new water source has variable salinity concentrations that are not removed by any of the implemented treatment processes, requiring blending with an existing lower salinity water source. This results in an increase in the finished water salinity (as compared with the existing water source), which can have negative impacts on customer satisf...

Characterizing drought risks and implications for water management under climate change

Drought risks arise from the intersection of climate hazards and social vulnerability. To characterize drought risks, we develop and demonstrate a new Combined Drought Risk Index (CDRI). We link a Global Climate Model-driven top-down approach to drought hazard prediction under lower and higher emission scenarios with a bottom-up component that investigates a facet of vulnerability. For the latter, we use stakeholder interviews to investigate how important stakeholders believe that water is for various local uses and measure their cultural worldviews. The CDRI is demonstrated for a study site in south-central Oklahoma, where water availability is highly influenced by drought and management of water resources is contested by local stakeholders. For this region, following the higher emissions scenario leads to more frequent droughts, particularly at higher magnitudes. Stakeholder interviews reveal that people perceive the importance of water differently for various uses. The CDRI combines the drought projections and stakeholder perceptions to show that for water uses where values are diverse, perceived differences are exacerbated in the future, especially under higher emissions. We also investigate why stakeholder perceptions differ by examining cultural worldviews, which can help to diagnose why disagreement may arise over water management. For some water uses, the importance people attribute to water can be partially explained by worldview, pointing to some implications for water management policy. We discuss how the results can be used to reduce potential disagreement among stakeholders and promote sustainable water management, which is particularly important for planning under potentially increasing drought.

Toward the Application of Decadal Climate Predictions

AbstractDecadal prediction is a relatively new branch of climate science that bridges the gap between seasonal climate forecasts and multidecadal-to-century projections of climate change. This paper develops a three-step framework toward the potential application of decadal temperature predictions using the Community Climate System Model, version 4 (CCSM4). In step 1, the predictions are evaluated and it is found that the temperature hindcasts show skill over some regions of the United States and Canada. In step 2, the predictions are manipulated using two methods: a deterministic-anomaly approach (like climate change projections) and a probabilistic tercile-based approach (like seasonal forecasts). In step 3, the predictions are translated by adding a delta (for the anomaly manipulation) and conducting a weighted resample (for the probabilistic manipulation), as well as using a new hybrid method. Using the 2010 initialized hindcast, the framework is demonstrated for predicting 2011–15 over two case-study...