Atzori, R., Fyall, A., & Miller, G. (2018). Tourist responses to climate change: Potential impacts and adaptation in Florida's coastal destinations. Tourism Management, 69.
Abstract: Florida, one of the world's most visited tourist destinations, holds one of the most vulnerable positions as a result of climate change. Through a quantitative survey, this study gathered the responses of 432 tourists who had previously visited Florida, with a hypothetical scenario of changed climatic conditions. The examination of the tourist perspective showed the presence of ample sunshine and factors related to beach comfort as the reasons for choosing the destination. In a scenario were beaches disappear and tropical diseases become more widespread, the majority of respondents stated they would choose a different destination. However, respondents would reconsider their intentions if adaptation measures such as reduced prices, coastal habitat conservation and measures to protect beaches from erosion and coastal areas from inundation were in place. The findings suggest that seasonal and geographic shifts in tourism demand could be mitigated by the implementation of adaptation measures at the destination level.
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Burke, A., Present, T. M., Paris, G., Rae, E. C. M., Sandilands, B. H., Gaillardet, J., et al. (2018). Sulfur isotopes in rivers: Insights into global weathering budgets, pyrite oxidation, and the modern sulfur cycle. Earth and Planetary Science Letters, 496, 168–177.
Abstract: The biogeochemical sulfur cycle is intimately linked to the cycles of carbon, iron, and oxygen, and plays an important role in global climate via weathering reactions and aerosols. However, many aspects of the modern budget of the global sulfur cycle are not fully understood. We present new S measurements on sulfate from more than 160 river samples from different geographical and climatic regions—more than 46% of the world's freshwater flux to the ocean is accounted for in this estimate of the global riverine sulfur isotope budget. These measurements include major rivers and their tributaries, as well as time series, and are combined with previously published data to estimate the modern flux-weighted global riverine S as 4.4 ± 4.5‰ (V-CDT), and 4.8 ± 4.9‰ when the most polluted rivers are excluded. The sulfur isotope data, when combined with major anion and cation concentrations, allow us to tease apart the relative contributions of different processes to the modern riverine sulfur budget, resulting in new estimates of the flux of riverine sulfate due to the oxidative weathering of pyrites (1.3 ± 0.2 Tmol S/y) and the weathering of sedimentary sulfate minerals (1.5 ± 0.2 Tmol S/y). These data indicate that previous estimates of the global oxidative weathering of pyrite have been too low by a factor of two. As pyrite oxidation coupled to carbonate weathering can act as a source of CO2 to the atmosphere, this global pyrite weathering budget implies that the global CO2 weathering sink is overestimated. Furthermore, the large range of sulfur isotope ratios in modern rivers indicates that secular changes in the lithologies exposed to weathering through time could play a major role in driving past variations in the S value of seawater.
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Collins, J. M., Paxton, C. H., Wahl, T., & Emrich, C. T. (2017). Climate and weather extremes. In E. P. Chassignet, J. W. Jones, V. Misra, & J. Obeysekera (Eds.), Florida's climate: Changes, variations, & impacts (pp. 579–615). Gainesville, FL: Florida Climate Institute.
Abstract: This chapter examines Florida’s extreme weather hazards: 1) why they happen, 2) their relation to interannual to multidecadal climate variability, and 3) the potential of each hazard and spatial variability across the state. The weather hazards indicated are under these broad categories: precipitation (rainfall, flooding, droughts), thunderstorms (lightning, hail, convective wind, tornadoes), tropical weather (tropical storms and hurricanes), and temperatures (extreme highs and lows). The conclusions section mainly addresses the challenge of attributing extreme events to human-induced climate change.
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Downing, J., Borrero, H., Liu, H., & Boucek, R. (2016). Differential impacts from an extreme cold spell on subtropical vs. tropical specialist bees in southern Florida. Ecosphere, 7(5), e01302.
Abstract: Gradual warming and changes in extreme weather patterns associated with human induced climate change are altering the range distributions of species. However, species responses to climate change are predicted to be more strongly affected by extreme events than by changes in mean values. As a result, measuring species' responses to extreme events in addition to the mean changes in climate are necessary to predict species range limits under future conditions. This study examines the impacts of a cold spell in southern Florida on native and an introduced oil-collecting bees by examining the bees' interactions with two native plants species. Our results provide evidence of differential impacts from an extreme cold event on a native, subtropical bee vs. an introduced, tropical bee. Specifically, the cold spell had little impact on the abundance of the native bee, while the abundance of the introduced, tropical bee was negatively impacted. Our findings demonstrate that extreme cold spells are important climate change-related phenomena that can have strong impacts on tropical species distributions and abundances, especially at the threshold of their thermal tolerances. Our approach also provided a rare opportunity to examine these impacts on multiple interacting species, which provides a more realistic assessment of the potential impacts of climate change.
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Erb, V., Lolavar, A., & Wyneken, J. (2019). The Role of Sand Moisture in Shaping Loggerhead Sea Turtle (Caretta Caretta) Neonate Growth in Southeast Florida. Chelonian Conservation and Biology, 17(2), 245–251.
Abstract: Many environmental variables that affect incubating turtle eggs in the nest may also affect hatchling development, following hatchling emergence. However, these effects may be subtle and are largely unexamined. In this study, we analyzed the effect of sand moisture content during incubation on the postemergence growth rates of loggerhead sea turtles (Caretta caretta) in southeastern Florida. We divided 10 clutches in halves, reburied them, and exposed them to 1 of 2 treatments. At emergence, 7 clutches met minimum criteria for inclusion in the study. One halfclutch received only ambient rainfall ("dry" treatment) while the other half-clutch received ambient rainfall plus daily watering ("wet" treatment). Data loggers were used to record incubation temperatures in both groups. Hatchlings were captured at emergence and laboratoryreared over a period of similar to 3 mo. Mass, straight carapace length (SCL), and straight carapace width (SCW) were measured weekly to track growth. Initial measurements were larger for turtles from the wet nests in all metrics. Turtles from wet nests grew more in SCW than turtles from dry nests. Turtle growth from the 2 treatments did not differ in SCL or mass measurements. Larger initial sizes and faster SCW growth may enable the turtles to more quickly achieve a refuge size from their gape-limited predators. Moisture availability during nesting season is projected to decrease based on climate change models. If that change materializes, it could negatively affect hatchling sizes and neonate growth rates, survival, and hence the recovery of this imperiled species.
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Hightower, J. N., Carlisle, J. D., & Chalfoun, A. D. (2018). Nest mortality of sagebrush songbirds due to a severe hailstorm. The Wilson Journal of Ornithology, 130(2), 561–567.
Abstract: Demographic assessments of nesting birds typically focus on failures due to nest predation or brood parasitism. Extreme weather events such as hailstorms, however, can also destroy eggs and injure or kill juvenile and adult birds at the nest. We documented the effects of a severe hailstorm on 3 species of sagebrush-associated songbirds: Sage Thrasher (Oreoscoptes montanus), Brewer's Sparrow (Spizella breweri), and Vesper Sparrow (Pooecetes gramineus), nesting at eight 24 ha study plots in central Wyoming, USA. Across all plots, 17% of 128 nests failed due to the hailstorm; however, all failed nests were located at a subset of study plots (n = 3) where the hailstorm was most intense, and 45% of all nests on those plots failed due to hail. Mortality rates varied by species, nest architecture, and nest placement. Nests with more robust architecture and those sited more deeply under the shrub canopy were more likely to survive the hailstorm, suggesting that natural history traits may modulate mortality risk due to hailstorms. While sporadic in nature, hailstorms may represent a significant source of nest failure to songbirds in certain locations, especially with increasing storm frequency and severity forecasted in some regions with ongoing climate change. Received 7 July 2017. Accepted 20 September 2017.
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Hong, S. - Y., Park, H., Cheong, H. - B., Kim, J. - E. E., Koo, M. - S., Jang, J., et al. (2013). The Global/Regional Integrated Model system (GRIMs). Asia-Pacific J Atmos Sci, 49(2), 219–243.
Abstract: A multiscale atmospheric/oceanic model system with unified physics, the Global/Regional Integrated Model system (GRIMs) has been created for use in numerical weather prediction, seasonal simulations, and climate research projects, from global to regional scales. It includes not only the model code, but also the test cases and scripts. The model system is developed and practiced by taking advantage of both operational and research applications. This article outlines the history of GRIMs, its current applications, and plans for future development, providing a summary useful to present and future users.
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Jones, J. W., Hansen, J. W., Royce, F. S., & Messina, C. D. (2000). Potential benefits of climate forecasting to agriculture. Agriculture, Ecosystems & Environment, 82, 169–184.
Abstract: Climate variability leads to economic and food security risks throughout the world because of its major influences on agriculture. Accurate forecasts of climate 3-6 months ahead of time can potentially allow farmers and others in agriculture to make decisions to reduce unwanted impacts or take advantage of expected favorable climate. However, potential benefits of climate forecasts vary considerably because of many physical, biological, economic, social, and political factors. The purpose of this study was to estimate the potential economic value of climate forecasts for farm scale management decisions in one location in the Southeast USA (Tifton, GA; 31 degrees 23'N; 83 degrees 31'W) for comparison with previously-derived results for the Pampas region of Argentina. The same crops are grown in both regions but at different times of the year. First, the expected value of tailoring crop mix to El Nino-Southern Oscillation (ENSO) phases for a typical farm in Tifton was estimated using crop models and historical daily weather data. Secondly, the potential values for adjusting management of maize (Zea maize L.) to different types of climate forecasts (perfect knowledge of (a) ENSO phase, (b) growing season rainfall categories, and (c) daily weather) were estimated for Tifton and Pergamino, Argentina (33 degrees 55'S; 60 degrees 33'W). Predicted benefits to the farm of adjusting crop mix to ENSO phase averaged from US$ 3 to 6 ha-1 over all years, depending on the farmer's initial wealth and aversion to risk. Values calculated for Argentina were US$ 9-15 for Pergamino and up to US$ 35 for other locations in the Pampas. Varying maize management by ENSO phase resulted in predicted forecast values of US$ 13 and 15 for Tifton and Pergamino, respectively. The potential value of perfect seasonal forecasts of rainfall tercile on maize profit was higher than for ENSO-based forecasts in both regions (by 28% in Tifton and 70% in Pergamino). Perfect knowledge of daily weather over the next season provided an upper limit on expected value of about US$ 190 ha-1 for both regions. Considering the large areas of field crop production in these regions, the estimated economic potential is very high. However, there are a number of challenges to realize these benefits. These challenges are generally related to the uncertainly of climate forecasts and to the complexities of agricultural systems.
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Kirtman, B. P., Schneider, E. K., Straus, D. M., Min, D., & Burgman, R. (2011). How weather impacts the forced climate response. Clim Dyn, 37(11-12), 2389–2416.
Abstract: The new interactive ensemble modeling strategy is used to diagnose how noise due to internal atmospheric dynamics impacts the forced climate response during the twentieth century (i.e., 1870–1999). The interactive ensemble uses multiple realizations of the atmospheric component model coupled to a single realization of the land, ocean and ice component models in order to reduce the noise due to internal atmospheric dynamics in the flux exchange at the interface of the component models. A control ensemble of so-called climate of the twentieth century simulations of the Community Climate Simulation Model version 3 (CCSM3) are compared with a similar simulation with the interactive ensemble version of CCSM3. Despite substantial differences in the overall mean climate, the global mean trends in surface temperature, 500 mb geopotential and precipitation are largely indistinguishable between the control ensemble and the interactive ensemble. Large differences in the forced response; however, are detected particularly in the surface temperature of the North Atlantic. Associated with the forced North Atlantic surface temperature differences are local differences in the forced precipitation and a substantial remote rainfall response in the deep tropical Pacific. We also introduce a simple variance analysis to separately compare the variance due to noise and the forced response. We find that the noise variance is decreased when external forcing is included. In terms of the forced variance, we find that the interactive ensemble increases this variance relative to the control.
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Kren,, Cucurull,, & Wang,. (2018). Impact of UAS Global Hawk Dropsonde Data on Tropical and Extratropical Cyclone Forecasts in 2016. Wea. Forecasting, 33(5), 1121–1141.
Abstract: A preliminary investigation into the impact of dropsonde observations from the Global Hawk (GH) on tropical and extratropical forecasts is performed using the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS). Experiments are performed during high-impact weather events that were sampled as part of the NOAA Unmanned Aerial Systems (UAS) Sensing Hazards with Operational Unmanned Technology (SHOUT) field campaigns in 2016: 1) three extratropical systems in February 2016 and 2) Hurricanes Matthew and Nicole in the western Atlantic. For these events, the benefits of GH observations under a satellite data gap scenario are also investigated. It is found that the assimilation of GH dropsondes reduces the track error for both Matthew and Nicole; the improvements are as high as 20% beyond 60 h. Additionally, the localized dropsondes reduce global forecast track error for four tropical cyclones by up to 9%. Results are mixed under a satellite gap scenario, where only Hurricane Matthew is improved from assimilated dropsondes. The improved storm track is attributed to a better representation of the steering flow and atmospheric midlevel pattern. For all cases, dropsondes reduce the root-mean-square error in temperature, relative humidity, wind, and sea level pressure by 3%-8% out to 96 h. Additional benefits from GH dropsondes are obtained for precipitation, with higher skill scores over the southeastern United States versus control forecasts of up to 8%, as well as for low-level parameters important for severe weather prediction. The findings from this study are preliminary and, therefore, more cases are needed for statistical significance.
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Liu, Q., Tan, Z. - M., Sun, J., Hou, Y., Fu, C., & Wu, Z. (2020). Changing rapid weather variability increases influenza epidemic risk in a warming climate. Environ. Res. Lett., 15(4).
Abstract: It is believed that the continuing change in the Earth's climate will affect the viral activity and transmission of influenza over the coming decades. However, a consensus of the severity of the risk of an influenza epidemic in a warming climate has not been reached. It was previously reported that the warmer winter can reduce influenza epidemic caused mortality, but this relation cannot explain the deadly influenza epidemic in many countries over northern mid-latitudes in the winter of 2017-2018, one of the warmest winters in recent decades. Here, we reveal that the widely spread 2017-2018 influenza epidemic can be attributed to the abnormally strong rapid weather variability. We demonstrate, from historical data, that the large rapid weather variability in autumn can precondition the deadly influenza epidemic in the subsequent months in highly populated northern mid-latitudes; and the influenza epidemic season of 2017-2018 was a typical case. We further show that climate model projections reach a consensus that the rapid weather variability in autumn will continue to strengthen in some regions of northern mid-latitudes in a warming climate, implying that the risk of an influenza epidemic may increase 20% to 50% in some highly populated regions in the later 21st century.
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Liu, Z., Macpherson,, Groves, C., Martin, J. B., Yuan, D., & Zeng, S. (2018). Large and active CO2 uptake by coupled carbonate weathering. Earth-Science Reviews, 182, 42–49.
Abstract: Carbonate mineral weathering coupled with aquatic photosynthesis on the continents, herein termed coupled carbonate weathering (CCW), represents a current atmospheric CO2 sink of about 0.5 Pg C/a. Because silicate mineral weathering has been considered the primary geological CO2 sink, CCW's role in the present carbon cycle has been neglected. However, CCW may be helping to offset anthropogenic atmospheric CO2 increases as carbonate minerals weather more rapidly than silicates. Here we provide an overview of atmospheric CO2 uptake by CCW and its impact on global carbon cycling. This overview shows that CCW is linked to climate and land-use change through changes in the water cycle and water-born carbon fluxes. Projections of future changes in carbon cycling should therefore include CCW as linked to the global water cycle and land-use change.
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Lolavar, A., & Wyneken, J. (2015). Effect of rainfall on loggerhead turtle nest temperatures, sand temperatures and hatchling sex. Endang. Species. Res., 28(3), 235–247.
Abstract: Marine turtles deposit their eggs in underground nests where they develop unattended and without parental care. Incubation temperature varies with environmental conditions, including rainfall, sun/shade and sand type, and affects developmental rates, hatch and emergence success, and embryonic sex. We documented (1) rainfall and sand temperature relationships and (2) rainfall, nest temperatures and hatchling sex ratios at a loggerhead turtle (Caretta caretta) nesting beach in Boca Raton, Florida, USA, across the 2010 to 2013 nesting seasons. Rainfall data collected concurrently with sand temperatures at different depths showed that light rainfall affected surface sand; effects of the heaviest rainfall events tended to lower sand temperatures but the temperature fluctuations were small once upper nest depths were reached. This is important in understanding the potential impacts of rainfall as a modifier of nest temperatures, as such changes can be quite small. Nest temperature profiles were synchronized with rainfall data from weather services to identify relationships with hatchling sex ratios. The sex of each turtle was verified laparoscopically to provide empirical measures of sex ratio for the nest and nesting beach. The majority of hatchlings in the samples were female, suggesting that across the 4 seasons most nest temperatures were not sufficiently cool to produce males. However, in the early portion of the nesting season and in wet years, nest temperatures were cooler, and significantly more males hatched.
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Perondi, D., Fraisse, C. W., Staub, C. G., Cerbaro, V. A., Barreto, D. D., Pequeno, D. N. L., et al. (2019). Crop season planning tool: Adjusting sowing decisions to reduce the risk of extreme weather events. Computers and Electronics in Agriculture, 156, 62–70.
Abstract: Frost, extreme high temperatures, dry spells, and other weather extremes influence crop development, often causing major variations in yield from one season to the next. Selected growth stages such as flowering and grain filling are particularly sensitive to temperature and/or precipitation extremes and farmers are often unable to manage this risk. Crop simulation models have matured into powerful tools for identifying strategies in fully utilizing scarce natural resources under variable climate conditions. However, the use of crop models often requires expert knowledge and an extensive number of input datasets. Combining the power of Internet, computing technology, and web-based decision-support tools is becoming increasingly popular in situations where these requirements cannot be met. The objective of this study is to develop a simple decision-support tool that combines freely available information with the functionality of complex crop models in a user friendly interface for real-time assessment of soil, plant, and weather information. The resulting tool is intended to be used ahead of the growing season by producers, and it enables the estimation and minimization of the likelihood of extreme weather events during critical stages of crop development.
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Royce, F. S., Jones, J. W., & Hansen, J. W. (2001). Model-based optimization of crop management for climate forecast applications. Transactions of the ASAE, 44, 1319–1327.
Abstract: Recent improvements in climate forecast technology have led to new uses of crop models for exploring potential benefits of tailoring crop management to expected weather conditions. However, conventional use of crop models limits each simulation experiment to a small, predetermined subset of the possible combinations of variables. Unfortunately, much of the potential contribution of dynamic models is untapped when seeking optimal management parameters under varying environmental and/or economic scenarios. This research linked a widely used crop model, CERES-Maize, to a simulated annealing algorithm and a partial budget calculator, to permit optimizing economic results by varying crop management. Management was optimized by El Nino-Southern Oscillation (ENSO) phase using a 67-year series of daily weather data from Pergamino, Argentina. The per-hectare value of the ENSO-optimized management was calculated. Nine management variables were included in the optimizations, at two levels of resolution (increments or step size) for each variable. The optimization algorithm, Adaptive Simulated Annealing (ASA), required tuning to achieve reasonable reliability and efficiency. Although the optimizer did not consistently find the precise optimal combination at either resolution, it did consistently find the optimal "region", with small differences in some management variables. A "quenching" variation of simulated annealing was found to be much faster but considerably less reliable. Optimization by ENSO phase leads to phase-differentiated management: earlier planting date, higher N applications, and increased plant density lead to higher yields during El Nino, as compared to neutral and especially La Nina years. The CERES-Maize to ASA linkage is useful for investigating optimal combinations of management practices using validated crop simulation models.
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Senkbeil, J. C., Saunders, M. E., & Taylor, B. (2017). Changes in Summer Weather Type Frequency in Eastern North America. Annals of the American Association of Geographers, 107(5), 1229–1245.
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Silva, J. A., Matyas, C. J., & Cunguara, B. (2015). Regional inequality and polarization in the context of concurrent extreme weather and economic shocks. Applied Geography, 61, 105–116.
Abstract: This study examines how extreme weather influences regional inequality and polarization within Mozambique in the context of on-going economic shocks. Utilizing satellite-based estimates of rainfall spatially analyzed within a GIS, we establish a 16-year rainfall climatology and calculate monthly rainfall anomalies for 665 villages. We approximate storm-total rainfall from all tropical cyclones entering the Mozambique Channel, as well as the extent of damaging winds for those making landfall, between 2005 and 2008. We group villages according to tropical cyclone impacts and use hierarchical cluster analysis to group the remaining villages according to shared patterns of monthly rainfall anomalies. Using economic data from the 2005 and 2008 National Agricultural Surveys of Mozambique, we relate weather patterns associated with near normal rainfall, tropical cyclones, flooding, and drought to changes in inequality and polarization by conducting decomposition analyses of the Gini index and Duclos-Esteban-Ray (DER) polarization index. Our findings mainly correspond to the generally accepted view that weather shocks exacerbate existing income and power disparities within societies. However, in some cases we find evidence that inequality and polarization can decline in the aftermath of an extreme event, and increase even where the weather is relatively good. By identifying varying effects of extreme events on inequality and polarization at subnational level, our study enables a more detailed understanding of weather-related effects on socio-economic outcomes in rural societies rapidly integrating into the global economy.
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Tang, J., & Matyas, C. (2018). A Nowcasting Model for Tropical Cyclone Precipitation Regions Based on the TREC Motion Vector Retrieval with a Semi-Lagrangian Scheme for Doppler Weather Radar. Atmosphere, 9(5), 200.
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Verdin, A., Rajagopalan, B., Kleiber, W., Podestá, G., & Bert, F. (2018). A conditional stochastic weather generator for seasonal to multi-decadal simulations. Journal of Hydrology, 556, 835–846.
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Wong, K. V. (2016). Planning and Engineering Strategies to Mitigate Effects of Climate Change. J. Energy Resour. Technol, 138(1), 014701.
Abstract: Extreme weather events seem to have become more frequent with climate change. These anomalies throughout the world may generally be categorized as drought, heavy rain storms, landslides, heavy snow storms, sea level rise, ice melts from the polar regions, tornadoes and hurricanes. The environmental and real property damage caused may be minimized if proper planning and best practices are engineered into place before the catastrophic events occur. The management of vulnerable areas should definitely include such plans and strategies. The purpose of the current work is to point to the best practices already being carried out in some areas, and to draw attention to some of the knowledge embodied in the indigenous populations in particular regions, which have come by this knowledge via generations of survival through adverse climate/ environmental changes. The integration of this indigenous knowledge where applicable, with modern engineering tools and techniques will help the world better to face the climatic challenges ahead.
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