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What comprises climate? It can be considered loosely but succinctly as the study of air: its properties, movement, and composition. Such major elements of study as temperature, precipitation, clouds, wind, radiation, and air pollution all fall under this definition. Rephrased, climate science consists of the study of anything that occurs in the atmosphere or is directly connected with or affected by the atmosphere, and on timescales long enough for meaningful statistics (typically at least several years). But there are some additional atmospheric phenomena not traditionally studied as such that nonetheless have bearing on subjects that are in the more traditional climate purview. In fact, they are so common as to be absolutely mundane: light and sound. Sound is the main casualty of simplification in the primary set of equations used in atmospheric science and particularly in modeling, for the reason that otherwise models would have to simulate energy moving very rapidly between gridcells and this would require very short timesteps, making the whole modeling enterprise considerably more computationally intensive. As they bear little energy compared with other wavelengths, they are routinely neglected. But that's not to say that they are inconsequential: sound is a critical medium for many animals as well as humans, affecting their ability to do everything from attracting mates to finding food. Animals that use sonar, of course, are particularly vulnerable. For these reasons and others, the European Environment Agency has set a goal of reducing sound pollution 'significantly', while acknowledging attainment of this goal in the near future is highly unlikely. That is mostly because the major sources of anthropogenic sound pollution, vehicle and air traffic, are increasing or remaining constant. It is also worth noting that natural environments can be quite noisy as well -- tropical forests, for instance -- but that the key is that organisms there have adapted to the noise, whereas those in other biomes generally have not.  Noise-pollution map of New York City and vicinity. Major highways, avenues, and flight paths show up particularly well. Source: https://www.6sqft.com/noise-map-of-the-u-s-reveals-noise-pollution-is-worse-jersey-than-nyc/ Likewise, while visible light is of course an essential component of radiation, and its effects on atmospheric temperature are well-characterized by observations and models, its effects on ecosystems (and thus indirect effects on climate) are very rarely considered. A study from 2014 makes the point that tropical bats avoid areas with even small amounts of light pollution, and that this avoidance spells trouble for plants in fragmented forests that rely on bats' seed-dispersal proclivities. The resultant potential change in forest cover further implies an impact on traditional climate metrics like temperature and precipitation, given the strong positive-feedback relationship between deforestation and future drying. A direct effect of light pollution on plants has been observed (at least in terms of correlations) regarding springtime budding in the UK. It's not hard to imagine other similarly complex but very real linkages connecting changes in animal or plant behavior due to artificial-light exposure with aspects of local or regional climate.  The lights of Chicago, USA. Source: National Geographic, Jun 2016. On the non-traditional impacts side, many of the studies that have been produced concern temperature. There are several reasons for this focus: it's easily measured, constantly affects us (unlike, say, precipitation), varies widely across the globe, and not infrequently reaches values that we find uncomfortable, if not outright dangerous. Indoors, high nighttime temperatures are closely linked to sleep disruption in the U.S., despite the widespread availability of electricity and air conditioning. The effects are particularly strong among the impoverished and the elderly, and cannot help but be read in the context of the extensive medical literature implicating poor sleep in a host of maladies. Indoors, warm wintertime indoor temperatures are perhaps too comfortable, suggests a study pointing to lower caloric loss through metabolic heating than in decades and centuries past. Pleasant temperatures and sunshine, on the other hand, have been shown to improve cognitive performance.
While traditional ways of measuring climate and its impacts are deservedly predominant, it's often instructive to at least consider the other ways in which the atmosphere and life on the surface of the Earth interact. These are often more complex than they would seem at first glance, which is part of the joy of this field of study. And just as health and environmental impacts are maximized in urban areas as measured by traditional metrics, so too are they maximized there by non-traditional ones, making consideration of the factors behind them worthy of at least occasional consideration in an era when our ability to understand and consciously work to modify the interconnectedness of climate, economics, health, and the environment is increasing year by year.
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Resettlement, like migration, is a product of fragility. Unlike migration, it's typically coordinated and forced, rather than sporadic and voluntary. The fragility that spurs it can be sociopolitical (as with harried minority groups), economic (as with smallholder farms during the Great Depression), climatic (as along the Louisiana coast), or any combination of these. Where climatic fragility leads to economic fragility, making climatic and economic incentives consonant, self-initiated movement is most likely, even in the absence of a disaster per se. But typically, it takes a disaster, and even then few people want to leave their homes and neighborhoods if at all possible. This post examines resettlement in the 20th century United States and its implications for the future we all face, which includes the challenges of extreme heat, sea-level rise, and stronger storms (among others). To start, it's important to put resettlement in context. In a previous post, I explored the issue of climate-induced migration and resettlement in comparison with the adaptation measures that are more conventionally favored by planners. 'Adaptation' encompasses everything from human behavior to upgraded electrical grids and taller seawalls, and this will be sufficient for most of the population. The risks and costs of climate change are of course unevenly distributed geographically, but such is the raison d'etre of government -- to smooth out expenses and revenues across the full population, so that projects can be undertaken that are too complex, expensive, time-consuming, or unmarketable to fall within the province of private-sector activity. But of course government redistribution has its discontents, and particularly pertinent in the climate context is the disconnect between behaviors generated by current incentives and optimal behaviors from a utilitarian point of view. The basis of the objection is a simple economic axiom: the lower the cost of a good, the more of it is demanded, a prototypical example being taxpayer subsidy of the National Flood Insurance Program incentivizing the development of flood-prone areas. For the foreseeable future, much of this shared risk will probably remain politically and financially tolerable. But consider the most extreme cases: the sinking island, the isolated canyon community... these are the margins where serious public conversations need to be had about whether and how governments should provide an avenue (and perhaps additional incentives) for residents to relocate to less-fragile locations. The government thumb is already on the scales affecting where people live, in ways as varied as the infamous mortgage-interest deduction, the aforementioned NFIP, and the commitment to footing the entire bill for wildfire suppression without passing on any of the costs to homeowners. In the best case, climate-related challenges force a clear-eyed look at the purpose and consequences of these kinds of subsidies. If the major externalities are not internalized, market distortions and the resulting inefficiencies will continue indefinitely.  1935 poster advertising Resettlement Administration farmer-assistance programs. Source: Bernarda Bryson. Library of Congress Prints and Photographs Division Washington, D.C. 20540 USA CARD #: 97520475 Although inexact, the closest parallel to the present-day issues posed by ongoing climate trends is probably the 1930s Dust Bowl and Great Depression. There was in fact a short-lived "Resettlement Administration", under the umbrella of the New Deal, whose aim was to resettle farmers as a response to rural poverty brought on by a combination of antiquated agricultural practices and adverse environmental conditions (heat and drought). As the former program administrator described it, the driving force of the program was explicitly economic, with the aim of addressing the suboptimal productivity of labor and land that the small struggling Great Plains farms represented. Buyouts were extensive, but the new suburban communities for the displaced that were envisioned were never realized on any consequential scale. Despite support from many small farmers, these new developments faced ultimately crippling opposition on both financial and sociocultural fronts. This provides a valuable lesson for the present, in that it highlights the importance of considering where people will go and how they will be assimilated into a new community, beyond simply getting them out of harm's way. An alternative is to move a group of people wholesale from one place to another, as happened with both Native Americans and African Americans. That neither example was terribly successful points to the critical role of economics, in addition to community cohesion.  An idealized 1920s vision of the progressive optimization of land use in New York State, with substantial implied movement of people from the less-productive to the more-productive areas. The report argued for government-managed resettlement to speed along this process and improve the economic fortunes of the poor in the less-productive areas, even without the motive force of climate-related disasters. Source: Jacobs 1989, quoting Mumford 1925. At the same time, state initiatives were begun to alleviate the primarily economic hardship being suffered by smallholder farmers in the Northeast. With advances in technology and transportation stemming from the Industrial Revolution, their farms were no longer economically viable due to inherent climate and topographic factors, but many were trapped by debt. A decades-long political debate ensued between the 'social Darwinists' (advocating resettlement of the affected) and the 'repopulationists' (advocating investments allowing them to adapt to the changing times). The former group prevailed and buyouts began in earnest in the early 1930s in New York State under the governorship of FDR, who saw them as efficient ways to manage growing rural malaise. This is one of the few examples where a potential humanitarian disaster was foreseen and successfully avoided. However, they lasted just a few years before funding was cut back to skeleton levels. A humbling lesson from these past efforts is that even in an era of substantial climatic stress and economic upheaval, these programs' achievements were ultimately narrower than their original visions. Key elements that seem necessary for long-term success are the preservation of some kind of social fabric, a plan for economic integration into the new community, and having community buy-in from the outset. A reliable and continuing revenue stream is also necessary from a programmatic point of view. Looking to the future, the social-fabric issue seems particularly pertinent given rising inequality, especially in urban areas. Exacerbating it is the fact that, even without climate stressors, the wealthy and highly educated are much more mobile and have more transferable skills, so that the economic and social shock of resettlement is smaller for them. This means that the poor are often forced to make larger changes in response to climatic threats, despite not having the resources to comfortably do so. Subsistence farmers are arguably the worst off, being highly vulnerable to climatic whims, having the fewest resources, and having a livelihood which depends on the scarce resource of land (as opposed to practicing a trade or service-based skill). Fortunately, some efforts are underway in the international-policy sphere to smooth out the expected necessary transitions -- in fact, there's even a non-profit organization expressly dedicated to facilitating climate-related displacements. Climate and social-science researchers are brainstorming solutions, and localized efforts have been implemented and largely proven successful, though in all likelihood large-scale initiatives will only begin when the true scale of the issue comes into focus. While not something that's likely to affect most of us, the exigencies of resettlement will have a large-enough impact on those who do experience them that we all should be interested in finding efficacious and cost-effective solutions. While climate change exists on a bigger scale than anything seen before in human history, no disaster has ever been purely natural (including the Dust Bowl), which should give us heart that the answers are not out of the realm of experience either.  Recent examples of resettlement (a.k.a. managed retreat) along coastlines following damaging storms. Source: Hino et al. 2017, "Managed Retreat as a Response to Natural Hazard Risk." I recently attended the Rutgers Climate Symposium, where this year's theme was 'cities and climate' — especially appropriate for an event situated in the USA's finest megalopolis. A key takeaway from the day was the degree to which -- due to their high concentration of people, money, and physical assets -- cities are at the front lines of climate- and environment-related issues, more so than rural areas, provinces, or countries. One speaker, Bill Solecki, listed a number of unique challenges cities have faced in the last few centuries, which have been encountered and dealt with largely in serial fashion: fire, sanitation, air pollution, open space, and urban decay. From this perspective, sea-level rise or extreme heat is just another challenge that will mainly be felt first in cities, and that will strain the resources of some, but likely fail to change the larger arc of history that bends toward urbanization. The speaker Julie Pullen noted that this trend represents an opportunity across much of the globe to effect major change in urban form and lifestyles as the century progresses.
In fact, this positioning of cities on the front lines of global issues has been the case for about as long as cities themselves have existed, if for no reason other than that local governments are typically and of necessity concerned with more-prosaic matters than national leaders, who have more of a tendency to helicopter in, make a pronouncement, and helicopter out (hence Fiorello LaGuardia's quip that 'There's no Democratic or Republican way to pick up the garbage'). The greater complexity of cities than suburban or rural areas inspires and motivates a greater complexity of governance, and this fact is largely implicated in the strikingly complete sorting of the US (and many other places) into liberal urban and conservative rural halves. Whatever their political leanings or economic status, another emergent theme was the need for municipalities to work together to tackle problems too big for any one of them to face alone. Not every city can afford an office of environment or climate, nor is there always the political will for it. Leveraging existing knowledge, financial, and political networks brings down the cost associated with addressing climate-related problems through economies of scale, and consequently reduces the potency of the argument that a given solution is too expensive or cumbersome to implement. For example, the various cities in a metropolitan area could all use information from the same study to assess their vulnerability to sea-level rise; could all finance seawall improvements through the same pooling they use to fund transportation infrastructure; could all coordinate these actions through the same conference of mayors they all belong to; etc. Organizations like the Global Covenant of Mayors and the Urban Climate Change Research Network also serve as conduits for resources and information while still allowing cities to take their own individualistic problem-solving approaches. As a result, one of the main lessons of the symposium and of the most-recent Urban Climate Change Research Network report was that the most effective climate-related consortia all consider their programs as elements of larger programs or strategies, rather than being viewed ipso facto. Another aspect concerns disadvantaged populations: in environment-related issues as in political and financial ones, and in the developed world as in the developing, these communities are where there is the most room for improvement in terms of communication and implementation of cost-effective measures to address problems (whether done proactively or reactionarily). Thus, these populations must be explicitly focused on for substantial equity strides to be made. Lastly, integrated and participatory decision-making around urban climatology is crucial for making decisions that are good (as these require the input of various leaders and organizations) and also decisions that are actually implemented (as this only happens when the aforementioned people consider the decisions legitimate and accurate). As speaker Cynthia Rosenzweig emphasized, this is exemplified by, essentially, keeping an open mind rather than letting pure science dictate the decisions. Risk reduction, reaction, and long-term planning should be considered hand-in-hand. It's doubly important to keep this integrated framework in mind in the frenzied weeks and months after an extreme event, which is when much of the political energy and financial muscle are available to enact changes. More broadly, Bill Solecki stressed that the intersection of extreme events, climate change, and urban areas is where there's the motivation and wherewithal for society-wide adaptation measures, and where these measures would have the biggest impact. And yet, they also illustrate one of the most fundamental challenges in applying the results of urban-climatological studies: that while we have lots of data on roughly what's expected in terms of climate in the next 100 years, we don't know what to do about it -- that is to say, we don't know how to react viscerally, and certainly not how to plan in an organized and effective manner. Which is exactly why these kinds of mutual brainstorming sessions between urban climatologists and everyone else with a stake in the future of cities in the 21st century are so important. Note: this text was written for the website of the Consortium for Climate Risk in the Urban Northeast, where it will also be published by and by. The subject matter complements nicely many of the previous posts on this site, in the general sense of linking climate and social topics and particularly in exposing their deep interconnectedness. Global sea level is trending inexorably upward, and at an increasing rate (Figure 1). This acceleration is expected to continue over the course of the 21st century, though with wide uncertainty (Figure 2) — an uncertainty proportionally much wider than that for global-average temperature, on which it’s loosely dependent. In this post we explore some of the reasons for the large uncertainty in projected sea-level rise [SLR], and CCRUN’s contribution to the scientific effort aimed at understanding and whittling away at it.  Figure 1: Increase in global-average sea level since 1700, estimated from salt marshes across the world (light purple), various tide gauges (dark purple, green, and orange), and satellite altimetry (light blue). These sea-level changes are calculated with respect to the geoid, i.e. local effects of uplift and glacial isostatic adjustment have been corrected for so the time series can be meaningfully compared across regions. Source: Church et al. 2013.  Figure 2: A timeseries of estimated global-average sea level, encompassing projections with a central range (dark gray shading) and wider uncertainty bounds (light gray shading) as well as a simplified time series starting in the year 1800. Source: Melillo et al. 2014 and Parris et al. 2012, via the National Centers for Environmental Information web portal (https://statesummaries.ncics.org/ny). There are three primary contributors to SLR: ice melting, thermal expansion, and changes in land height. The first two are mostly global in nature, whereas the last depends on local geological forces. Global-average sea level is rising about 3-4 mm/yr, and the majority of this is due to thermal expansion — as water gets warmer, it gets less dense, i.e. the same mass takes up more space. Increases in ocean volume due to melting ice account for another 1 mm/yr or so. In CCRUN’s focus area of the Northeast US, additional local SLR of about 1 mm/yr is attributable to the continuing readjustment of the land to the freeing of the burden that the North American ice sheet imposed on it until about 15,000 years ago (Figure 3). This “glacial isostatic adjustment” means that Canada and the northernmost tier of the United States are rebounding, while areas on the periphery of the glacier, such as most of the US East Coast, are compensating by sinking. And the ice-weighting effect is not trivial: bedrock under the Antarctic Ice Sheet is currently depressed 500-1000 m by the weight of the ice (Anderson 1999). Like a bathtub being warped, this results in apparent sea-level changes independent of increases in the total volume of the oceans.  Figure 3: Current apparent rate of change of sea level (mm/yr) resulting only from global isostatic adjustment, as averaged over 160 model simulations based on observations. Dark blue areas indicate post-glacial rebound, while dark red indicates peripheral subsidence. Source: Hay et al. 2015. So what does the future hold? We know for certain that thermal expansion will continue apace, considering that it takes at least 1000 years for the ocean to come into thermal equilibrium with the atmosphere (Goodwin et al. 2015) – in other words, if we stopped emitting greenhouse gases today, the ocean would keep heating up for centuries. ocean volume will undoubtedly continue increasing in a warmer world -- but how much? The question is a thorny one because it’s not only the amount of melted ice that will determine future SLR, but the source: ice sheets are massive enough to have an appreciable gravitational effect on the oceans, so taking them away means a decrease in sea level nearby. Currently, Greenland is contributing somewhat more to SLR than Antarctica (Velicogna et al. 2014). As a consequence, North Atlantic SLR is slower than the global average (Figure 4). Projections that Greenland will continue to rapidly melt mean this regional dynamic could persist, so long as there are no big surprises from West Antarctica. Another Greenland-related factor also contributes to the Northeast US being a global hotspot of SLR uncertainty: the effect of its melting on the Atlantic Meridional Overturning Circulation (Little et al. 2015b). A slowdown in AMOC, resulting for example from a meltwater pulse, would tend to increase sea level in the North Atlantic (Goddard et al. 2015). Another significant dynamical factor is the North Atlantic Oscillation, which in its positive phase has southwesterly winds along the Northeast coast and consequent marginally lower sea level – any long-term changes in the NAO could thus have an impact on the local average rate of SLR as well.
However, these regional variations pale in comparison to the potential global increases stemming from Antarctic melting. The total amount of ice on Earth is enough to raise sea level about 80 m, with East Antarctica accounting for about 65 m of this. Most research suggests East Antarctica will experience little melting as far as we can predict, and that West Antarctica and Greenland will retain ice for at least several hundred years. But these are suggestions rather than guarantees. While our species and many others have proven on the whole able to adapt to the continental-scale changes in coast locations, vegetation, and temperatures associated with glacial-interglacial cycles (Grant et al. 2014), these last occurred when humans were few in number, nomadic, and nearly possessionless, rather than having $1.5 trillion in immobile housing investments on the glacial moraine of Long Island alone (U.S. Census Bureau 2016). With all these social, ecological, and economic motivations in mind, CCRUN-affiliated scientists are working to estimate SLR on varying timescales. Radley Horton helped develop a model to predict the likelihood that a given coastal area will likely be able to adapt (by ecologic, depositional, or anthropogenic means) to seas as they rise, or whether the coastal ecosystem will simply become submerged (Lentz et al. 2016). For example, for a variety of reasons a marsh accrete sediment and remain marshy, or may “fall behind” SLR and disappear under the waves. The authors found that some locations are much more dynamic than others, allowing them more leeway to effectively maintain their ecosystem status quo (e.g. actively depositional barrier islands and beaches), whereas those that are more passive (e.g. marshes and impermeable surfaces) are most likely to be inundated (Figure 5). With relatively modest amounts of SLR, it’s presumed there will be successful anthropogenic efforts to keep most developed areas dry.  Figure 5: Predicted effect of sea-level rise on the coastline of Plum Island, MA, including the coast’s feedback response, in the 2080s relative to the present-day. Red areas are most likely to be functionally the same, while dark blue areas are currently above mean sea level but are likely to be flooded in the future. Source: Lentz et al. 2016. The Lentz et al. study, however, did not take into account the possible effect of stronger storms lashing the beaches and eroding away any progress they might have made in keeping pace with SLR. However, two earlier CCRUN papers did just that (Horton et al. 2015; Little et al. 2015b). As it turns out, SLR and tropical-cyclone intensity are highly correlated in climate models, and including this correlation results in a longer tail of future flooding extremes than would otherwise be predicted (Figure 6). A large fraction of this correlation can be attributed to the underlying factor of upper-ocean warming. While tropical cyclones are more powerful, “Nor’easters” occur more frequently and often move more slowly, increasing their overall flooding potential (Horton et al. 2015). Many storm-specific factors affect the location and extent of flooding from a given storm, including wind speed, wind direction, storm speed, storm direction (i.e. a storm coming from the east will pile up more water on an eastward-facing coast), precipitation intensity, total precipitation, and storm timing relative to the daily and bimonthly tidal cycles. Because coastal inundation is a function of storm flooding overlaid on mean SLR, long-term changes in any combination of these factors can ‘stack the deck’ in terms of exacerbating or counterbalancing the effects of mean SLR. Recent trends have been upward for both frequency and intensity in recent decades, with the majority of evidence suggesting the strongest storms will get even stronger (Horton and Liu 2014).  Figure 6: Comparison of a comprehensive flood index — accounting for frequency, duration, and intensity of coastal flooding — at end of century for the modest RCP 2.6 emissions scenario and the business-as-usual RCP 8.5 scenario against the observed record (inset). Source: Little et al. 2015a. CCRUN researchers are looking not just at the regional scale — using regional and global climate models, and leveraging correlations and other statistical tools — but at the level of the individual street. In this vein, a new nested model was designed specifically for New York Harbor (Blumberg et al. 2015). This enables questions to be answered about the very local impact of a given storm, sediment-dredging project, etc., and thus to make recommendations as to the most cost-effective measures to dampen waves and storm surges along complex coastlines. Such models are critical tools for assessing the local impact of a regional or global trigger such as accelerated ice-sheet melting. As one might expect from the highly varied times of tides even within a single short stretch of coastline, near-shore dynamics are inordinately complex and can result in feedbacks both positive and negative stemming from an initial perturbation. This is doubly true where humans have so highly modified the coastline, as in the Northeast US. Lack of awareness of this kind of nonlinear response was part of the reason for the unexpected severity of the flooding during Hurricane Katrina in New Orleans after some of the levees broke. In any system that evolves dynamically, projections inherently get more uncertain further and further out into the future. In the case of SLR, there’s not only the atmosphere, ocean, and cryosphere changes to consider, but also the iterative human response to these changes. And in addition to the mean, storm surges, storm tides, and large waves are additional complicating factors. While the 90th-percentile estimate of SLR by 2100 in New York City is about 75” (Horton et al. 2015), the analogy with insurance purchased in case of a devastating but rare event should be kept in sight. And this is particularly so for a region where finance and insurance have long been a pillar of economic success, alongside maritime industries like shipping and whaling, and where property values are among the highest in the country (Figure 7).  Figure 7: US states mapped according to land area (left) and according to total residential property value (right), with shading indicating property value per square mile in each state. Source: Spiser 2015. To extend the finance analogy, in stocks the volatility index reflects investor sentiment about upcoming uncertainty in the markets. If such an index existed for the climate, it would surely be increasing, due largely to anthropogenic influences which are making it harder to predict the future even as understanding of the climate per se continues to get better and better. The most common investor response to expectations of high volatility is to pull out and wait for conditions to improve, but the Earth is a market that can’t be pulled out of, and that won’t recover naturally from an unnatural forcing. Thus CCRUN’s philosophy is to face such problems and their uncertainty head-on, with all the tools and information that can be mustered. Understanding issues of this magnitude, whether climatic or otherwise, is always a strong value proposition. References:
Anderson, J., (1999), Antarctic marine geology. Cambridge University Press, ISBN 0-521-59317-4. Blumberg, A. F., N. Georgas, L. Yin, T. O. Herrington, and P. M. Orton (2015), Street-scale modeling of storm surge inundation along the New Jersey Hudson River waterfront. J. Atmos. Ocean. Tech., 32, 1486-1497, doi:10.1175/jtech-d-14-00213.1. Church, J. A., et al. (2013), Sea-level change. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press. Goddard, P. B., J. Yin, S. M. Griffies, and S. Zhang (2015), An extreme event of sea-level rise along the Northeast coast of North America in 2009-10. N. Commun., 6:6346, doi:10.1038/ncomms7346. Goodwin, P., R. G. Williams, and A. Ridgwell (2015), Sensitivity of climate to cumulative carbon emissions due to compensation of ocean heat and carbon uptake. Nat. Geosci., 8, 29-34, doi:10.1038/ngeo2304. Grant, K. M., et al. (2014), Sea-level variability over five glacial cycles. Nat. Commun., 5 (5076), doi:10.1038/ncomms6076. Hay, C. C., E. Morrow, R. E. Kopp, and J. X. Mitrovica (2015), Probabilistic reanalysis of twentieth-century sea-level rise. Nature, 517, 481-492, doi:10.1038/nature14093. Horton, R. M., and J. Liu (2014), Beyond Hurricane Sandy: What might the future hold for tropical cyclones in the North Atlantic? J. Extr. Even. 01, 1450007, 30 pp., doi:10.1142/s2345737614500079. Horton, R. M., C. Little, V. Gornitz, D. Bader, and M. Oppenheimer (2015), New York City Panel on Climate Change 2015 Report Chapter 2: Sea-Level Rise and Coastal Storms. Ann. N.Y. Acad. Sci., 1336, 36-44, doi:10.1111/nyas.12593. Lentz, E. E., E. R. Thieler, N. G. Plant, S. R. Stippa, R. M. Horton, and D. B. Gesch (2016), Evaluation of dynamic coastal response to sea-level rise modifies inundation likelihood. Nat. Clim. Change, 6, 696-701, doi:10.1038/nclimate2957. Little, C. M., R. M. Horton, R. E. Kopp, M. Oppenheimer, G. A. Vecchi, and G. Villarini (2015), Joint projections of US East Coast sea level and storm surge. Nat. Clim. Change, 5, 1114-1121, doi:10.1038/nclimate2801. Little, C. M., R. M. Horton, R. E. Kopp, M. Oppenheimer, and S. Yip (2015), Uncertainty in twenty-first-century CMIP5 sea-level projections. J. Clim., 28, 838-852, doi:10.1175/jcli-d-14-00453.1. Melillo, J. M., T. C. Richmond, and G. W. Yohe, Eds. (2014), Climate change impacts in the United States: The Third National Climate Assessment. U.S. Global Change Research Program, 841 pp., doi: 10.7930/J0Z31WJ2. Parris, A., P. Bromirski, V. Burkett, D. Cayan, M. Culver, J. Hall, R. Horton, K. Knutti, R. Moss, J. Obeysekera, A. Sallenger, and J. Weiss (2012), Global Sea-Level-Rise Scenarios for the US National Climate Assessment. NOAA Tech Memo OAR CPO-1. 37 pp. Spiser, M. (2015), Resizing America based on property values. Business Insider. http://www.businessinsider.com/resizing-america-based-on-property-values-2015-7. U.S. Census Bureau (2016), 2011-2015 American Community Survey 5-Year Estimates. https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?src=CF. Velicogna, I., T. C. Sutterley, and M. R. van den Broeke (2014), Regional acceleration in ice mass loss from Greenland and Antarctica using GRACE time-variable gravity data. J. Geophys. Res. Space Physics, 41, 8130-8137, doi:10.1002/2014gl061052. |
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