New York City Panel on Climate Change 2019 Report Chapter 5: Mapping Climate Risk

New York City Panel on Climate Change 2015 Report. Chapter 3: Static coastal flood mapping.

Appendix II: NPCC 2015 technical details.

Implications, Planning, and Design Considerations for Rising Sea Levels at the Coast

Radley Horton,1,a Daniel Bader,1,a Yochanan Kushnir,2 Christopher Little,3 Reginald Blake,4 and Cynthia Rosenzweig5 1Columbia University Center for Climate Systems Research, New York, NY. 2Ocean and Climate Physics Department, Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY. 3Atmospheric and Environmental Research, Lexington, MA. 4Physics Department, New York City College of Technology, CUNY, Brooklyn, NY. 5Climate Impacts Group, NASA Goddard Institute for Space Studies; Center for Climate Systems Research, Columbia University Earth Institute, New York, NY

Sea-level rise: towards understanding local vulnerability

Coastal flooding from storm surge is one of the most dangerous and damaging natural hazards that societies face. It was responsible for half of all hurricane-related mortalities in the United States from 1963 to 2012, far more than any other factor (Rappaport, 2014). Coastal extreme water levels are increasing globally, mainly driven by rises in mean sea level (MSL; e.g., Marcos et al., 2015; Marcos and Woodworth, 2017; Menéndez and Woodworth, 2010). Sea level rise is also causing rapid increases in the annual number of shallow "nuisance floods" for low-lying neighborhoods (e.g., Strauss et al., 2016; Sweet and Marra, 2014). The objectives of this chapter are to review the latest knowledge on New York City flood risk from storms and tides, and to evaluate how climate change will affect this risk between now and the end of the century. Methods used by NPCC (2015) for assessing storm-driven extreme floods are generally repeated here, including the use of the Federal Emergency Management Agency (FEMA, 2013) baseline flood hazards (e.g., the 100-year flood1) and the methods for adding sea level rise and mapping the resulting hazard (Horton et al., 2015b; Patrick et al., 2015). New advancements include an innovative analysis of monthly tidal flooding based on a dynamic model, a broadened set of sea level rise scenarios supplemented with the Antarctic Rapid Ice Melt (ARIM) scenario (see Chapter 3), and sensitivity analyses that show how differing methods would affect our results. Wind is a primary factor for coastal storm surge, and a brief review is given in Appendix 4.A, with the latest scientific knowledge on what drives extreme wind events in the New York City area and how they may change in the future. Coastal storms have historically flooded New York City's lowest lying neighborhoods many times, and even a water level 5 ft below that of record-setting Hurricane Sandy is sufficient to begin flooding several neighborhoods (Fig. 4.1). The worst four known coastal floods were all caused by tropical cyclones (1788, 1821, 1960, and 2012), whereas the fifth worst was caused by an extratropical cyclone in 1992 (Orton et al., 2016b). Sandy in 2012 was a "hybrid" storm type, in that it was transitioning from a tropical to an extratropical cyclone while approaching landfall. It generated the highest recorded water level at New York Harbor in at least 300 years, due to sustained strong easterly winds and a storm surge maximum coinciding with high tide (Colle et al., 2015; Orton et al., 2016b). Wind is the primary factor governing storm surge, through its speed and the distance over which it blows, the wind fetch. The height and timing of high tide relative to the peak storm surge is also an important factor for New York City coastal flooding (e.g., Colle et al., 2015; Colle et al., 2008; Georgas et al., 2014; Kemp and Horton, 2013). Storm tide can be defined as the combination of tide level and storm surge, measured as a value above a given year's MSL. The total water level is the storm tide plus MSL and can be measured with respect to the geodetic North American Vertical Datum of 1988 (NAVD88). In addition to storm surge and tide, waves can also raise water levels at some coastal neighborhoods of New York City (e.g., Van Verseveld et al., 2015), and are incorporated into FEMA's "base flood elevation" (FEMA, 2013). This section hereafter refers to storm tide and total water level (called "still water elevation" by FEMA), neither of which includes the oscillations caused by waves. Rainfall typically has a negligible effect on storm-maximum coastal and estuarine water levels surrounding New York City (Orton et al., 2012), though it can directly cause street and neighborhood flooding (e.g., NYC-DEP, 2010). Of the top 22 known historical storm tide events in New York City history, 15 have been caused by extratropical cyclones, which impact the region far more often than hurricanes (Booth et al., 2015; Catalano and Broccoli, 2018). However, extratropical cyclones appear to have a lower maximum storm tide potential because their maximum wind speeds (based on observations) are much lower than those for hurricanes or hybrids (Orton et al. 2016b). In storm tide data going back to 1844 (Talke et al., 2014) and news reports back to the 1700s (Orton et al., 2016b), no extratropical cyclone-driven storm tide has exceeded 7.2 ft MSL and the 1000-year return period extratropical storm tide was recently estimated to be only 8.5 ft MSL (Orton et al., 2016b). For comparison, Sandy's storm tide was 11.1 ft MSL (relative to the 2012 MSL). Climate change is an increasingly important factor for storm-driven floods and "sunny-day" nuisance floods worldwide. It has increased the height of New York City coastal floods by causing sea levels to rise (Kemp and Horton, 2013; Talke et al., 2014), and this effect is expected to worsen in future decades (e.g., Garner et al., 2017; Orton et al., 2015). Although intensities of tropical and perhaps extratropical cyclones are expected to strengthen in this region, cyclone track changes are difficult to project, and studies have shown mixed results for the effects on New York City storm tides. Uncertainty in this area of research is still high (Garner et al., 2017; Lin et al., 2012; Roberts et al., 2016). "Present-day" flood risk studies typically use past storm events or analysis of their characteristics to represent the present-day hazard, assuming no change to storm climatology. Several academic and governmental studies have found 100-year storm tide estimates in New York City ranging from 6.7 to 11.3 ft (Table 4.1). FEMA's standard map products show contours of the 100- and 500-year return period flood zones, among other metrics, and these return periods have been a common focus of past NPCC flood mapping assessments of sea level rise impacts (Orton et al., 2015; Patrick et al., 2015). These can be referred to as the 1% and 0.2% annual chance floods, respectively, corresponding to the percentage chance of each occurring in a given year. The most recent FEMA (2013) estimates of 100- and 500-year floods are 11.3 and 14.8 ft NAVD88, respectively, and are presently used for planning and building codes but not for insurance purposes because of a successful appeal by New York City (FEMA, 2016). One source of differences between studies in Table 4.1 involves the use of historical storm tide data versus model-based data. Model-based studies can include synthetic tropical cyclones that have never occurred, with the goal of representing all possible events and surge–tide combinations beyond those observed in the limited historical record (Lin et al., 2014). Additional reasons for differences can include the particular choice of models, probability distributions, and probabilistic frameworks used to derive storm sets (see discussion in Orton et al., 2016b; Wahl et al., 2017). The Monte Carlo approaches of Lopeman et al. (2015) and Nadal-Caraballo et al. (2016) are based on historical storm tide data, but also show strong differences for the 100-year event, likely due to their use of different methods for synthesizing water-level time series from storm surge and tide data. Considering the very wide range of storm tide estimates at all return periods shown in Table 4.1, flood hazard assessments should be evaluated using comparisons of both observed and model-based estimates (Orton et al., 2016b). Coastal flooding for the New York City region has already been worsened by sea level rise. For example, Sandy's peak water level rose higher, and its return period decreased by a factor of three because of the historic sea level rise of 1.64 ft between 1800 and 2000 (Lin et al., 2016). An early sign of sea level rise readily experienced by the public is an increasing frequency of nuisance flooding, which increased substantially in the United States between 1950 and 2013 (Sweet and Marra, 2014; Sweet et al., 2014). Strauss et al. (2016) attribute two-thirds of U.S. nuisance flood days since 1950 to global warming.2 Nationwide, the number of such flood days has increased by over 80% for the period 1985–2014 relative to 1955–1984. In New York City, the total number of flood days has grown from 32 to 63 over these two 30-year periods. Thirty-four of the 63 flood days can be linked to anthropogenic sea level rise over the study period (Strauss et al., 2016).3 The increasing incidence of coastal flooding creates a growing public inconvenience because of potential damages to low-lying infrastructure and private homes, which would face more frequent street, driveway, and basement flooding without adaptive measures. Already affected New York City areas include several neighborhoods around Jamaica Bay, including parts of Old Howard Beach (Fig. 4.1) and nearby Hamilton Beach, Broad Channel, and Rockaway Peninsula (Fig. 4.2). New York City flood risk may also have risen due to climate change–related influences on storms (e.g., intensity, frequency, or storm track), as well as changes in the water flow behavior in New York Harbor caused by dredging of ship channels and filling of wetlands. The latter has been shown to have raised the 100-year flood for the Jamaica Bay region of New York City by 1.44 ft since the late 1800s (Orton et al., 2016a). Since the mid-1800s, the 10-year flood height at The Battery has risen by 2.36 ± 0.82 ft, 1.44 ft of this resulting from sea level rise and the remaining 0.92 ft from other sources, such as storm changes or anthropogenic harbor modifications (Talke et al., 2014). Studies of historical data have not found significant evidence in this region for larger storm tides due to the effect of climate change on storms (e.g., Marcos and Woodworth, 2017; Wahl and Chambers, 2016). Moreover, no quantitative evidence has been presented demonstrating that Hurricane Sandy was intensified or its storm tide was increased or made more likely by climate change (Lackmann, 2015; Mattingly et al., 2015). Sandy had hybrid cyclone characteristics as it approached the region and therefore represents a relatively complex case study (Galarneau et al., 2013; Zambon et al., 2014). In this section, we assess how sea level rise will affect storm-driven and tidally driven coastal flooding over the 21st century. The assessment and mapping of storm-driven floods with the NPCC (2015) high-estimate (90th percentile) scenarios conservatively4 captures the possible future extreme event contribution to coastal flood risk (Horton et al., 2015b; Patrick et al., 2015). These results are repeated here, as they are now being used for planning purposes by New York City (e.g., NYC-DCP, 2018a, 2018b, 2018c). The assessment of tidal flooding is an important advancement over NPCC (2015), as more frequently recurring nuisance floods are one of the earliest manifestations of sea level rise and can be a more important driver of flood adaptation (Moftakhari et al., 2017; Sweet and Park, 2014). The water levels and flood mapping of ARIM, a higher impact, lower probability sea level rise scenario, are included for both storm- and tide-driven flooding to raise awareness, but not for planning purposes. Static mapping approaches simply superimpose sea level rise on water levels for various return period floods and extrapolate ("bathtub") the water level horizontally over the floodplain (Patrick et al., 2015). On the other hand, dynamic flood modeling explicitly accounts for all the forces acting on the water and the resulting water movement, yet is computationally expensive (Orton et al., 2015). Static mapping is used here for the storm-driven flood assessment, and a hybrid dynamic/static approach is used for tidally driven flooding, as described and discussed below. All flood mapping in this report uses the static approach to project water levels onto inland flood zones, and these static mapping methods are given in Chapter 5 of this report. The flood hazard assessments and mapping assume no future changes in the shoreline due to either coastal erosion or coastal flood protection, for example, and therefore may over- or underestimate flood area. New York City is implementing a $20 billion adaptation plan developed after Hurricane Sandy (City of New York, 2013). Moreover, recent work has demonstrated that while extreme water levels around the United Kingdom have increased due to sea level rise, this has not led to a corresponding increase in coastal flooding, due to improved coastal protection measures, forecasts, and emergency planning (Haigh and Nicholls, 2017; Stevens et al., 2016). NPCC (2015) research compared the results of static and dynamic flood modeling of sea level rise using FEMA (2013) storm tide scenarios as a present-day baseline, and found that they were similar for most locations. Differences were usually within ±0.5 ft, and therefore using static mapping leads to a relatively small additional uncertainty compared to the large uncertainty in storm tide probabilities and sea level rise projections (Orton et al., 2015). Section 4.3.2 uses dynamic modeling to address possible changes to tides with sea level rise, and shows these are also relatively small. Due to these findings and the high expense of performing hundreds of storm simulations for each sea level rise scenario, here we utilize static methods to assess future storm-driven flooding. We also follow NPCC (2015) precedent by not including the possible effects of storm climatology changes on flooding, but this is partially addressed with a sensitivity analysis (see "Sensitivity tests" section). Studies have shown that atmospheric warming will likely intensify tropical cyclones in the future (Emanuel, 2005; Garner et al., 2017; Knutson et al., 2010; Lin et al., 2012). However, changes in storm tracks could offset the intensity increase, resulting in little change in storm tides at The Battery (Garner et al., 2017). Most studies suggest there will be a future decrease in the frequency of extratropical cyclones over the North Atlantic (Bengtsson et al., 2006; Chang, 2013; Zappa et al., 2013), although little decrease near the coast (Colle et al., 2013). Some studies have shown an increase in intensity for extratropical cyclones over the next 100 years (Marciano et al., 2015; Michaelis et al., 2017) resulting from additional condensational heating in a warmer (and more moist) climate; however, not all models agree with this change (Seiler and Zwiers, 2016). There is currently little understanding of how hybrid storms like Sandy will change in the future, and more work is needed looking at tropical and extratropical cyclone changes as well. The NPCC (2015) coastal flood scenarios took the FEMA (2013) study as a baseline, focused only on the 90th percentile sea level rise scenario, and used static methods for the primary map and flood-level products (Horton et al., 2015b; Patrick et al., 2015). Those results are now being used for planning purposes by New York City (e.g., NYC-DCP, 2018a, 2018b, 2018c). The sea level rise projections were based on an ensemble of 24 global climate models and two emissions scenarios (RCP4.5 and RCP8.5), along with literature review and expert judgement (see Chapter 3) to reflect uncertainty in future emissions as well as in the ocean, cryosphere, and climate system. The sea level rise projections were presented for the 10th, 25th, 75th, and 90th percentiles, for the 2020s, 2050s, and (Table We the static flood scenario the of sea level rise on the 100- and 500-year storm tide of the FEMA (2013) In we the to include this projections that are for the and (see Chapter Section Table for 100- and 500-year flood water levels for a range of sea level rise scenarios and time are shown in Table For example, the 100-year water level for the from to ft for the percentile sea level rise This rises to ft in the Table shows estimated future return periods for the baseline 100- and 500-year floods of 11.3 and 14.8 ft NAVD88, 100-year flood will more occurring on years in the 2050s, and years in the (90th and the is at 500-year flood of 14.8 ft will have a return period below 5 for a range of return periods are in Appendix 100-year flood map with the 90th percentile and sea level rise for the Jamaica Bay and areas of the is shown in similar map is presented in Chapter 5 of this report Climate but here we in on this region due to its a significant of the total floodplain area. The the of the area at risk of flooding for each sea level rise scenario, into the future. However, only and show the range of uncertainty the sea level rise The 100-year flood baseline of FEMA (2013) a similar area to that which was flooded Hurricane Sandy (Orton et al., 2015), and this is compared with future tidal flooding at the end of Section of the 100-year return period floodplain over time in the Jamaica Bay and areas of New York City for the NPCC (2015) 90th percentile sea level rise and assume no future changes in the shoreline due to either coastal erosion or coastal flood protection, for example, and therefore may over- or underestimate flood area. represents a probability than of scenario for the late 21st from recent modeling of behavior to the sea level rise It is included to raise but not for planning purposes. analyses of the sensitivity of these results to three are given below. we evaluate the sensitivity to on future which can cause large differences in sea level rise the choice of a sea level rise percentile is as for it may be more to the probability of sea level rise through (Lin et al., 2016; Lin and 2017; et al., 2017). In the sensitivity we the possible of storm characteristics due to climate for which there The results presented in and are based on NPCC (2015) sea level rise projections Section that projections for both the lower and higher (Horton et al., a higher scenario would in higher flood For example, the 90th percentile sea level rise for an et al., 2017) that rapid and leads to an estimated 100-year flood by the that is ft higher than that based on the NPCC (2015) 90th percentile sea level rise On the other hand, a lower scenario would in lower flood flood levels based on the of and sea level rise projections from et al. are shown in The approach of a sea level rise with the storm tide through leads to a 100-year flood in the of ft the case the 8.5 sea level rise et al., 2017) is to the FEMA This approach estimates the flood level all sea level rise Lin et al., in this the estimated flood level is above the from with the percentile of the sea level rise for various sea level rise are compared in In the the sea level rise is the sea level rise such as with the high emissions scenarios for the of the sea level rise can be well above the from with the projections of the effect of sea level rise on coastal floods may sea level rise distributions, in addition to with percentiles, to a more of the in sea level rise the above results changes to which could also increase future flood sensitivity to tropical cyclones, we estimated future tropical cyclone storm tide probabilities using storm projections based on four climate models (Lin et al., 2012). show a increase of in the storm tides in the relative to the assessment only sea level rise and no storm Additional of this analysis are given in using these climate models suggest that tropical cyclone changes will to higher storm tides, yet similar studies using (2013) climate models found no changes in tropical (Garner et al., 2017) and extratropical cyclone et al., storm tides. The among different climate models in these studies is often and some models that could (Lin et al., 2012). research on this should be One important additional factor that more study is the possible between future sea level rise and storm changes et al., 2015). are far more than storm and modeling their potential flooding therefore a much number of simulations and expense than a we use dynamic simulations with sea level projections to the future of tides, though we use static mapping to map these water levels onto monthly tidal flooding the lowest lying in a neighborhoods (e.g., Hamilton NPCC has not evaluated how sea level rise will affect tidally driven nuisance flooding. However, tidal flooding can to a in the advancement of to at a of perhaps nuisance floods (Sweet and Park, 2014). a the has in projections of future tidal flooding (see Chapter for of flooding An here is that we map monthly tidal flooding, which can be a of repeated flooding that is sufficient to adaptation we and map the which is the of all monthly in tide is not a standard tidal used by such as MSL or It is typically exceeded by observed water levels at New York City, based on of observed water levels at The and Jamaica Bay the of floods (Sweet and Park, 2014). dynamic simulations of tides are using the Stevens of and Coastal using the New York Harbor and and and 2010; Orton et al., 2016b). a period tide and water-level time series at all are to tidal analysis et al., to tide time series that all the and monthly are and tide estimates are using estimates from several around New York City mean of for was only The for this sea level rise case are to all results for sea level rise This approach for modeling tides with sea level rise was used recently by this in studies of and Jamaica Bay et al., Kemp et al., 2017). Static mapping methods for using these tide data to map monthly tidal are described in Chapter 5 Climate the map of monthly tidal flooding for the Jamaica Bay area of New York City, based on projections of 90th percentile and sea level rise. similar monthly tidal flood map is presented in the Climate chapter the 90th percentile sea level rise scenario, monthly tidal flooding by the is including large of low-lying areas like Rockaway this 90th percentile scenario, flooding is very all neighborhoods around the and includes of (Fig. top In the more extreme scenario, the flooding is at of area affected by monthly tidal flooding for Jamaica Bay and areas of New York City for NPCC (2015) 90th percentile sea level rise and assume no future changes in the shoreline due to either coastal erosion or coastal flood protection, for example, and therefore may over- or underestimate flood area. represents a than of scenario for the late 21st from recent modeling of behavior to the sea level rise It is included to raise but not for planning purposes. The of a monthly tidal flood is presented here as a of flooding. the effect of sea level rise on monthly tidal flooding has several compared with mapping tidal flooding which has common (e.g., Climate NYC-DCP, on around New York City, by ft (Fig. and therefore is a substantially higher of tidal flooding, a larger area of the as sea level is exceeded hundreds of has only and is more as a for sea level rise will affect neighborhood and adaptation (e.g., tidal flooding is already occurring on some low-lying of New York City, and with are the modeling and mapping (e.g., 4.2). Moreover, mapping the relatively frequent and monthly tidal flooding may be more than mapping the 100-year for flood risk and its advancement with sea level rise. of dynamic modeling results to of tides and sea level rise (Fig. that the is relatively small around New York Harbor and for and adding and of the of sea level rise to to results dynamic and static storm tide modeling were compared (Orton et al., 2015), the differences between here are within ±0.5 the 90th percentile sea level rise as an example, the additional increase in monthly high tides at The Battery is ft, and at is ft (Fig. sea level rise ft, while the dynamic of the tides ft to The sea level rise at has a very than but into the impacts of extreme sea level rise that may in beyond (see Chapter Sea In the sea level rise could raise tidal flooding to levels even more than those that Hurricane For example, with the scenario of ft of sea level rise at even the maximum tidal water levels are than the maximum water levels Sandy (Fig. In this to the NPCC (2015) coastal flood projections for New York City, has historical and present-day flood and how sea level rise will affect storm- and tide-driven future flooding. dynamic/static analysis shows that monthly flooding will not be a the or but by late in the it could impact most of the neighborhoods surrounding Jamaica Bay, as well as several other low-lying neighborhoods of the to this monthly tidal flooding include Rockaway Howard Beach, and and areas to the the sea level rise by the end of this could raise tidal flooding to levels even more than that which Hurricane static assessment of storm-driven flooding shows how extreme events such as the 100- and 500-year floods will rise with a of sea level rise ranging from to 90th for the 2020s, 2050s, and and including the scenarios for the and on future emissions are shown to cause large differences in the sea level rise and as a the flood differences can also from differing methods for probabilities of storm tides and sea level rise. An improved understanding of and future flood risk should be to New York City for therefore the for research to address coastal flooding in the New York Orton is by a and Lin and Colle are by the United States of Climate and with from for and The 4.1 map was a with New York City of City of the in this report address the of extreme wind events and how they may change the region in the future, here we review the latest on this winds at New York City and the New York are with nearby extratropical cyclones, and and tropical cyclones storms and winds the can be in and strong near a coastal storm and Colle (2015) that and peak in while peak in and the there can be wind (Colle et al., 2012), and and and tropical cyclones extratropical such as Sandy Colle et al., and to extratropical cyclones, most studies suggest there will be a future decrease in their frequency over the North Atlantic (Bengtsson et al., 2006; Chang, 2013; Zappa et al., 2013), although little decrease near the coast (Colle et al., 2013). Some studies have found that there will be an increase in intensity for extratropical cyclones over the next 100 years over the Atlantic (Marciano et al., 2015; Michaelis et al., 2017) resulting from additional condensational heating in a warmer (and more moist) climate; however, not all models agree with this change (Seiler and Zwiers, 2016). cyclones that cause wind to follow a track (Booth et al., 2015), and climate models suggest that there has been an increase in the of cyclones along this track (Colle et al., 2013). However, these two studies were not focused on the of and more work is in tropical cyclones, and are even because climate models storm approaches have been by using future changes in the from models to future storm For example, and Colle (2015) that there will be a increase in the number of storm days for the New York region by the end of the from which one can a significant increase in the number of wind However, higher models will to be used in future studies to these results. Several studies have shown that atmospheric warming will likely intensify tropical cyclones in the future (Emanuel, 2005; Garner et al., 2017; Knutson et al., 2010; Lin et al., 2012). There is currently little understanding of how hybrid storms like Sandy will change in the future, and more work is needed to both tropical and extratropical cyclone

Future sea level change in the Mediterranean Sea is one of the major climate hazards for populations living in low-elevation coastal zones (≤10 m above mean sea level). In this study, we analyze projections of mean sea level rise in the Mediterranean Sea by the end of the 21st century. To address this, we use a set of multi-decadal simulations from three pairs of regional climate system models (RCSMs) of the Med-CORDEX initiative together with the simulations of their driving global climate models (GCMs). For the first time, we analyze the mean relative sea level simulated by a set of high-resolution and fully coupled regional models to provide a detailed characterization of regional and local patterns of future Mediterranean sea level change. By 2100, under the high-emission SSP5-8.5 scenario, the basin-averaged total sea level is projected to rise by +71 cm from RCSMs and +76 cm from GCMs (central estimates). Among the sea level components, the sterodynamic term (dynamic sea level + global mean thermosteric sea level) is the largest contributor to total sea level rise, with 91% of its contribution driven by global thermal expansion. The sterodynamic term and the vertical land motion drive local sea level adjustments in regions such as the Balearic Sea and the Ionian islands, leading to the highest sea level rise in the Mediterranean. We find that sea level rise in the Mediterranean is expected to be slower than the nearby Atlantic due to a dynamic adjustment within the basin. Furthermore, compared to the GCMs, the RCSMs show a higher spread (extremes) of the sea level response without a mean regional effect.

Chapter 6: Insurance industry

Chapter 5: Law and regulation

Sea-Level Rise (SLR) Projections from the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Army Corp of Engineers (USACE) indicate increasing, and imminent, risk to coastal communities from tidal flooding and hurricane storm surge. Building on recent research related to the potential demographic impacts of such changes (Hauer et al. 2016, in Nat Clim Chang 3:802–806, 2017; Neumann et al. 2015; Curtis and Schneider in Popul Environ 33:28–54, 2011), localized flooding projections in the Miami Beach area (Wdowinski et al. in Ocean Coast Manag 126:1–8, 2016) and projected economic losses associated with this rise in projected SLR (Fu et al. Ocean Coast Manag 133:11–17, 2016); this research investigates the accrued current cost, in terms of real-estate dollars lost, due to recurrent tidal flooding and projected increases of flooding in Miami-Dade County. Most directly related to this line of research, Keenan et al. (2018) have recently produced results indicating that Climate Gentrification is taking place in Miami, FL with higher elevations in flood prone areas appreciating at a higher rate. In that vein of thinking, we seek to answer a question posed by such research: What is the actual accrued loss to sea-level rise over the recent past? To answer this question, we replicate well-documented estimation methods by combining publicly available sea-level rise projections, tide gauge trends, and property lot elevation data to identify areas regularly at risk of flooding. Combining recent patterns of flooding inundation with future forecasts, we find that properties projected to be inundated with tidal flooding in 2032 have lost $3.08 each year on each square foot of living area, and properties near roads that will be inundated with tidal flooding in 2032 have lost $3.71 each year on each square foot of living area. These effects total over $465 million in lost real-estate market value between 2005 and 2016 in the Miami-Dade area.

Accuracy assessment of global DEMs for the mapping of coastal flooding on a low-lying sandy environment: Cassino Beach, Brazil

Projections of climate change are inherently uncertain, leading to considerable debate over suitable allowances for future changes such as sea-level rise (an ‘allowance’ is, in this context, the amount by which something, such as the height of coastal infrastructure, needs to be altered to cope with climate change). Words such as ‘plausible’ and ‘high-end’ abound, with little objective or statistically valid support. It is firstly shown that, in cases in which extreme events are modified by an uncertain change in the average (e.g. flooding caused by a rise in mean sea level), it is preferable to base future allowances on estimates of the expected frequency of exceedances rather than on the probability of at least one exceedance. A simple method of determining a future sea-level rise allowance is then derived, based on the projected rise in mean sea level and its uncertainty, and on the variability of present tides and storm surges (‘storm tides’). The method preserves the expected frequency of flooding events under a given projection of sea-level rise. It is assumed that the statistics of storm tides relative to mean sea level are unchanged. The method is demonstrated using the GESLA (Global Extreme Sea-Level Analysis) data set of roughly hourly sea levels, covering 198 sites over much of the globe. Two possible projections of sea-level rise are assumed for the 21st century: one based on the Third and Fourth Assessment Reports of the Intergovernmental Panel on Climate Change and a larger one based on research since the Fourth Assessment Report.

As global mean sea level continues to rise, thresholds corresponding to coastal inundation impacts are exceeded more frequently. This paper aims to relate sea level rise (SLR) observations and projections to their physical on‐the‐ground impacts. Using a large coastal city as an example, we show that in Sydney, Australia, frequencies of minor coastal inundation have increased from 1.6 to 7.8 days per year between 1914 and present day. We attribute over 80% of the observed coastal inundation events between 1970 and 2015 to the predominantly anthropogenic increases in global mean sea level. Further, we find that impact‐producing coastal inundation will occur weekly by 2050 under high‐ and medium‐emission/SLR scenarios and daily by 2100 under high emissions. The proportion of tide‐only coastal inundation events (i.e., where no storm surge is required to exceed flood thresholds) will increase with SLR, such that most coastal inundation events, including those considered historically severe, will become a predictable consequence of SLR and astronomical tides. These findings are important for coastal managers as frequency, severity, and predictability of inundation impacts can all now be related to the amount of SLR (e.g., a planning allowance or SLR projection). By incorporating known historical inundation events, this allows contextualization, visualization, and localization of global SLR and the changing nature of future coastal inundation risk.

New York City Panel on Climate Change 2015 Report. Conclusions and recommendations.

Sea level rise is one of the main risk factors for the preservation of cultural heritage sites located along the coasts of the Mediterranean basin. Coastal retreat, erosion, and storm surges are posing serious threats to archaeological and historical structures built along the coastal zones of this region. In order to assess the coastal changes by the end of 2100 under the expected sea level rise of about 1 m, we need a detailed determination of the current coastline position based on high resolution Digital Surface Models (DSM). This paper focuses on the use of very high-resolution Unmanned Aerial Vehicles (UAV) imagery for the generation of ultra-high-resolution mapping of the coastal archaeological area of Pyrgi, Italy, which is located near Rome. The processing of the UAV imagery resulted in the generation of a DSM and an orthophoto with an accuracy of 1.94 cm/pixel. The integration of topographic data with two sea level rise projections in the Intergovernmental Panel on Climate Change (IPCC) AR5 2.6 and 8.5 climatic scenarios for this area of the Mediterranean are used to map sea level rise scenarios for 2050 and 2100. The effects of the Vertical Land Motion (VLM) as estimated from two nearby continuous Global Navigation Satellite System (GNSS) stations located as close as possible to the coastline are included in the analysis. Relative sea level rise projections provide values at 0.30 ± 0.15 cm by 2050 and 0.56 ± 0.22 cm by 2100 for the IPCC AR5 8.5 scenarios and at 0.13 ± 0.05 cm by 2050 and 0.17 ± 0.22 cm by 2100, for the IPCC Fifth Assessment Report (AR5) 2.6 scenario. These values of rise correspond to a potential beach loss between 12.6% and 23.5% in 2100 for Representative Concentration Pathway (RCP) 2.6 and 8.5 scenarios, respectively, while, during the highest tides, the beach will be provisionally reduced by up to 46.4%. In higher sea level positions and storm surge conditions, the expected maximum wave run up for return time of 1 and 100 years is at 3.37 m and 5.76 m, respectively, which is capable to exceed the local dune system. With these sea level rise scenarios, Pyrgi with its nearby Etruscan temples and the medieval castle of Santa Severa will be exposed to high risk of marine flooding, especially during storm surges. Our scenarios show that suitable adaptation and protection strategies are required.