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. 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). 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). 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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Back in July 2016 I first laid out the logic and methodology for computing "comfort scores" based on the deviation of temperatures on each day from the range considered ideal for human comfort, and I expanded upon this more practically in June 2017. (Charts for the most-recent periods are found in the Recent Weather section.) The true discomfort of low temperatures is estimated from the wind chill, and of high temperatures from the heat index. I've since made several refinements to the calculation. These include introducing a diurnal cycle to the range of ideal temperatures, so that now 64-70 F is considered ideal at night, and 70-80 F is considered ideal during the day. I also have run the calculation for North American Regional Reanalysis data to get higher-resolution results for the United States. The most-substantial change, however, is the inclusion of precipitation rate as an additional variable, along with the original ones of temperature, humidity, and wind speed. This means the discomfort is calculated as a sum of contributions from heat, cold, and wetness. From experience we all know that the effect of precipitation on comfort varies with temperature — cold rain is much more unpleasant than warm rain, and at very hot temperatures rain is welcome, as long as it's not very heavy. These relationships are captured in the below diagram illustrating the bivariate nature of the precipitation component of the discomfort score. With this new definition, I recalculated the scores for the entire world using NCEP reanalysis, and for the continental US using NARR reanalysis. In the galleries below are the new climatologies for discomfort scores (red being most uncomfortable, blue most comfortable), encompassing the annual average as well as seasonal averages for winter, spring, summer, and fall, for the world (top) and the US (bottom). Key features include the complete unsuitability of Antarctica for human comfort, the appeal (climatologically speaking) of the subtropical ocean gyres, and the relative comfort of much of the tropics, especially those areas at several thousand feet elevation such as southern Africa, Central America, and Southeast Asia. Nonetheless, the hottest and most-humid areas (the northern Indian Ocean, western Pacific, and coastal Arabia) see summertime discomfort levels much greater than those elsewhere in the tropics, and in fact they approach those of Antarctica in austral summer (but are nothing like those in austral winter). Due to the inclusion of precipitation as discomfort-score factor, there is a greater value placed on dryness, resulting in the improved performance of the western US relative to the eastern. This makes the Southwest and Central Valley the most comfortable places on an annual-average basis, and even in summer they are much more comfortable than the humid Gulf of Mexico and Gulf of California. I also used the revised discomfort-score climatology to compute time series over the period of available reanalysis data, 1979-2016. The next figure shows the trend in contributions to globally averaged discomfort for heat and cold. As the world has gotten warmer, discomfort has come more and more from heat rather than cold. Individual hot years also stand out, such as the El Ninos of 1983, 1998, and 2016. Note that discomfort is a nonlinear function of temperature due to the compounding effects of humidity and wind speed, as well as the threshold effects introduced by the calculation methodology. Regardless, a clear change is evident since about 1995, and these trends will likely continue as more locations experience uncomfortable heat while simultaneously experiencing less uncomfortable cold. The last figure shows the same information, but broken down into latitudinal averages. Shown are percentiles relative to the 1979-2016 average for that latitudinal band; for example, a year falling in the 90th percentile means it was more uncomfortable overall than 90% of years in that location. Discomfort in the tropics and subtropics is primarily a function of heat, whereas in the mid-latitudes and polar regions it is a function of cold. Therefore, a trend toward greater comfort is expected poleward of 30 deg and toward less comfort equatorward of that — and that's exactly what is shown here. The last two years have exhibited record discomfort in the tropics and record comfort at the poles, which is again a trend very likely to continue.
For our entire history as a species we’ve largely conceptualized ourselves as acting in opposition to Nature — improving it, bending it to our will — and yet (in a sense, paradoxically) there was always the assumption that this was a near-Sisyphean task, because Nature was so vast, its bounties so immeasurable, and its threats (disease, predation, exposure, etc) so omnipresent. Thus the frequent 19th-century references to the desirability of "improving the land", to the point of equating it with civilization itself, and the infamous stacks of bison bones, the dogged hunting of the right whale, and the heedless dumping of waste that, while ubiquitous, were recognized early on, by none other than Thoreau, as leading in an unsavory direction. The world was seen as a endless buffet open for feasting on industrial scales. In many ways, it is still that way now, more than ever before, due to the hugely greater population and associated demand for consumption that the planet now sustains. A simple perusal of satellite imagery confirms that as ground truth. In fact, the very concept of wilderness reserves (and even those are somewhat rare) would have been completely foreign to our ancestors only a few generations ago. Essentially, our species has become so numerous and technologically savvy that we've won the upper hand in the timeless struggle to survive in an indifferent environment. Along with that advantage come many implications, among them the realization that weather and climate are not just things that ‘happen’, à la Zeus, but things that can be shaped — to minimize the unintentional damage we've inflicted, of course, but also to achieve desirable outcomes for us (e.g. cloud seeding). An analogous realization happened long ago for the Dutch with their polders, where they succeeded in not only preventing their land from being further eroded, but managed to reclaim large tracts from the sea with technological advances and investments. This success represents a power and an opportunity, somewhat like a teenage parent overwhelmed by feeling like they have barely learned how to take care of themselves but have been entrusted with the cosmic duty of taking care of someone else as well. With this increasing awareness of responsibility come the first glimmerings of a strategy to address the underlying problem of the uncontrolled experimentation of pumping large quantities of greenhouse gases and other pollutants into the atmosphere and oceans — hence the Paris climate accords, among other actions. These have been accompanied, naturally, by reports of the many challenges such agreements need to overcome: political, social, financial, etc. Less reported on than some of the others is the effect of an inextricable linkage of development patterns with technology, which at a very fundamental level acts as a huge drag on the ability of society to 'decarbonize' (i.e. become more energy-efficient) at anything approaching a rapid rate. [The below figure provides a compelling illustration.] A recent paper stresses the point that making changes too quickly means 'stranding' assets, since for example a power plant that's only 10 years old has decades' worth of profitability left, profit that would be lost if it were to be mothballed. So, in addition to the direct effect of the long lifetime of carbon dioxide in the atmosphere, this social/financial "lock-in" is another way that choices made now have ripple effects far into the future. In fact, it's difficult to imagine how the world might warm less than 2 C when the lock-in effect is estimated at being in the neighborhood of 1.8 C. In other words, if every choice from now on was made in the most environmentally sustainable way possible, but we continue to use the roads, buildings, power sources, vehicles, airplanes, etc. that we already have until they reach the end of their normal lifetimes, their combined emissions will cause something like 1.8 C of warming.
This large lock-in effect is only beginning to be appreciated and understood in detail, but it's clearly of the highest relevance for the climate of the coming decades. The situation could even be viewed as a version of the "Tragedy of the Commons", in that it'd be best in the long term if everyone who was capable of minimizing their emissions did so immediately, but it's in no one's financial interests to do so in the short term (at any particular moment) given the huge opportunity cost of losing out on the dividends of their current lifestyle. That's where strong, probably government-based, incentives would need to come in. On the analogy of nurturing 'infant industries' with financial assistance until they are strong enough to compete in the open marketplace, redevelopment could be heavily incentivized on larger and larger swaths of land until it had gained enough momentum to no longer need the artificial incentivization. This strategy could reduce the lock-in effect, but even so, it's a formidable adversary. Rather than battling pure Nature, as in the past, we're battling the jacked-up version of it that we've created. The present is the integral of the past, and in the realm of development patterns and their interactions with climate, that's true in very tangible and sobering ways. Making yourself scarce is in vogue — identifying and reducing carbon footprints, leaving no trace when visiting parks, restoring various natural environments, etc. This trend is in response to a long history of conspicuous consumption and attendant environmental damages. The imperative of economic development results in most every country having a clear pattern emerge as the arc of development progresses: build {buildings, infrastructure, industries, wealth} first, consider the consequences later. This applies equally to lives (safety regulations) and finances (consumer protections) as it does to the environment. Then, as people get more stuff, they get more conservative and have a greater desire to protect what they have versus acquiring even more. In Europe & North America, the development pendulum began swinging back from indiscriminate and cheap to expensive and more-carefully-considered around the third quarter of the 20th century, and there is some indication that it’s begun swinging back in places like China as well (somewhat ahead of expectations), but it’s still on its initial ramp-up in places like Sub-Saharan Africa and South Asia. In a sense, then, environmentalism in the real world is discretionary – desirable to everyone, but always decidedly in a mediocre position (at best) in the public’s list of priorities. As the environment improves, as it has in the US since the mid-20th century (whose unprecedented pollution and unfettered industrial activities prompted the first major environmental movement), the marginal value of additional investment and attention decreases. Concern for 'naturalness' has come in multiple waves, though, and it's interesting to note that the animating conservationist spirit of the 19th century in fact preceded large-scale industrialization, and how the modern emphasis on clean air, water, etc. is echoed in the ethos of that era, despite the interlude of a century of faith in the all-curative power of technology to liberate people from their surroundings. Whatever the exact reason, there is now a growing awareness of more-nuanced effects than burning rivers and black smog -- things like cardiac stress from increased heat, economic impacts of heat extremes (plus another paper on heat extremes), and greater infant mortality from air pollution. Below are three examples of cities that are experimenting with different ways of consciously shaping their urban form to reduce its impact on the surrounding environment, with the aim of making their economies stronger and citizens healthier. In essence, all three are bargaining that -- given the costs of environmental degradation -- doing something is not only morally preferable but in fact cheaper in the long run than doing nothing. In Los Angeles, concern centers on the effect of the urban heat island on human health. Scientists working with city planners are aiming to reduce extreme summertime heat by 1.5 deg K by 2040, which is comparable with the projected increase in temperature in the same timespan. There are theoretically well-founded methods of doing this -- whitening roofs, planting more vegetation, rounding off building corners to facilitate airflow -- but the sheer quantity and variety of built structures across Southern California, combined with the region's many microclimates, make it an especially challenging task. New technology, such as permeable and/or more-reflective asphalt, may come into play. The exact cooling strategy will likely differ from neighborhood to neighborhood, based on the current situation. For example, a canyon already has sufficient airflow, but a mid-valley spot may not; reflective asphalt will be less effective in an area where the streets are already shady. There is also the inherent push-pull between water conservation and temperature limitation, because water (via evaporative cooling) is the single most effective way to cool the air. And of course Los Angeles has a particularly tangled history with using water from other places for its own purposes. With the attendant complications, overcoming financial, technical, climatological, and political obstacles to reach the city's goal will be a demonstration of the feasibility of this cooling program just about anywhere that has the resources to invest in itself in this upfront manner, and that then need only watch the dividends slowly accrue over the following decades. In Barcelona, the aim is cultural as much as it is climatological. With the vision of recreating the vibrant pedestrian-oriented urban patchwork that was ubiquitous before motor vehicles came to dominate just about every block across the globe (not to mention the reshaping of cities to their specifications), streets in parts of the city are being eliminated to form 'superblocks' -- nearly-carless cities-within-cities. Public opinion is conflicted, naturally, but transportation officials are adamant that the idea is a net positive, in terms of traffic pollution as well as noise reduction, space for play, and more social interactions. These positives seem quite straightforward. But part of the trouble is that while Barcelona is known for its compactness, that same factor also restricts airflow, magnifying the effect of whatever traffic pollution there is. Further, there is the traffic-engineering maxim of 'latent demand', which posits that traffic will always swell to fill whatever space you allot it -- and by not banning traffic altogether (which would be very difficult indeed), critics fear the creation of traffic-choked boulevards that are disruptive but no improvement over distributed side streets. Lastly, there are concerns about accessibility, longer commutes, etc. that have yet to be fully addressed. In any case, if the experiment is deemed a success it is sure to be replicated many times over elsewhere, providing a new template for modern urban design.
And in New York, plans rely primarily on vegetation and its ability to cool the surrounding air by evapotranspiration as well as through direct shading of the surface. Some roof-whitening is also in the mix. There is an unmistakable socioeconomic dimension to this program, given the strong correlation between vegetation cover and household income that is present in New York as it is in most other cities. This correlation is compounded by another one, that between air conditioning and knowledge of/access to social & medical services on the one hand, and household income on the other. City officials have some additional metrics with which to decide how to direct their investment: the economic benefits of existing trees, in terms of stormwater interception, energy conservation (through cooling from shading and evapotranspiration), air-pollution reduction, and CO2 absorption, have been calculated and mapped (using US Forest Service formulas) for every street tree in the entire city. Then, weather observations can show the hottest areas, and, in combination with climate and tree-benefit models, allow precise estimates of the efficacy of placing trees and/or white roofs on a given city block, ultimately yielding a ranked list of the most-cost-effective sites. While there are other issues for which income and climate vulnerability are closely linked, in New York as elsewhere, addressing the longstanding problem of urban heat is certainly a defensible place to start. |
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