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Sea level changes near coastlines include tides, a kind of wave caused by the gravitational effects of the sun and moon, along with the Earth’s rotation.
Tidal changes across various time scales, though cyclic, can be superimposed upon the background rise in global sea level; add regional rise driven by ocean circulation, and the highest tides can begin to cause flooding in coastal zones that were previously unaffected, or that experienced such flooding at lower frequencies.
An instructive example comes from the Italian city of Venice, which became iconic for its canals and gondolas as sea level rose gradually over the centuries. Its founding settlements in the fifth century were intended to offer protection against barbarian raids. Built on a marshy lagoon and numerous islands, the city has adapted to gradual immersion, tracking sea level closely by the stains left on buildings and, starting in the 20th century, by tide gauges.
A 2009 modeling study [Carbognin et al.], however, found that rising relative sea level caused by modern day climate change might be pushing the maritime city toward an unsustainably high frequency of flood threat, as high tide levels increase. The study showed that, while the city itself is sinking due to natural processes at 0.05 centimeters per year, relative sea level could rise between 17 and 53 centimeters by the end of the century. This could push high tides above 110 centimeters, the point at which lagoon gates are shut to protect the city from flooding, at a far higher frequency—from the present four instances each year to a range of 20 to 250, depending on assumptions in different modeling scenarios. In this case, cyclic “high water events” caused by astronomical high tides, low-pressure systems, winds from the southeast and other factors are driven even higher by global sea-level rise induced by climate change, hovering in the background.
Storm surge is a higher-than-normal rise of coastal waters, above the astronomical high tide. Its main causes are strong winds within a tropical storm or hurricane, both literally pushing seawater and creating huge waves that travel to the coast and break there. Low atmospheric pressure also induces a dome of water near the storm center. Precipitation and the Coriolis effect may also play a role.
While making direct causal connections between globally averaged climate change and individual storms remains very difficult, improved modeling techniques offer a rare chance to forecast the potential imprint of the global climate signal on short-term, localized meteorological events as the next few decades unfold.
One modeling study [Tebaldi et al., 2012] examined long-term data from 55 tide gauges along the coasts of the contiguous United States. The study’s authors also used more detailed data from the gauges, from 1979 to 2008, to derive historic patterns of “extreme high water events.” They combined those data with sea-level-rise projections to estimate potential storm surge effects through the middle of the 21st century.
By 2050, the authors reported, their modeling showed some of the gauge locations would see high-water events yearly that, today, are considered likely to occur once a century (having a one percent chance of occurring in any given year). Once-a-century events, meanwhile, would become decadal (a 10 percent chance of occurring in any given year). Most locations would experience a higher frequency of storm surge events once considered rare, the study says.
While European tide-gauge records can be found as early as the 1670s [Woppelmann et al., 2006], long-term records began in earnest only in the late 18th century, and not until the late 19th century in the southern hemisphere. Large gaps in time as well as geographical spread, however, complicate efforts to make tide-gauge-based determinations of global sea level rise for the 19th and even for the 20th century [Mitchum et al. 2010].
Still, researchers have devised a variety of methods to overcome these gaps and identify trends in global mean sea-level rise during the 20th century. The result: substantial agreement on the long-term trend but differences in assessment of variations over years and decades [Rhein et al., 2013].
Perhaps the best-known tide gauge reconstruction, and the first of its kind, combined modern satellite altimetry with historical tide-gauge measurements to fill in the gaps for the 1950 to 2000 period [Church et al. 2004]. This led to a globally averaged sea level rise of 1.8 millimeters per year, plus or minus 0.3. A recent extension of this method [Watson et al., 2015] compensated for vertical land motion using GPS estimates and found an increased rate of sea level rise over the previous 20 years—contrasting with previous work suggesting a slowing [Cazenave et al. 2014].
Another approach limits analysis to very long-term records with few discontinuities. Holgate [Holgate, 2007], for example, chose nine long and largely uninterrupted records from the Permanent Service for Mean Sea Level to create a global mosaic: New York from 1856 to 2003, Key West 1913-2003, San Diego 1906-2003, Balboa 1908-1996, Honolulu 1905-2003, Cascais 1882-1993, Newlyn 1915-2004, Trieste 1905-2004, and Auckland 1903-2000. Each record has at least 11 months of data per year and fewer than 15 days missing.
A third relies upon many shorter-term records that are then filtered, removing short-term variations to reveal longer-term trends. One research effort [Jevrejeva et al., 2006] also drew from the PSMSL to examine 12 large-scale ocean regions, removing biennial to decadal oscillations to derive a century-long global sea level trend. Their trend was comparable, for the 1993 to 2000 timeframe, to that yielded by TOPEX/Poseidon altimeter measurements.
A recent reconstruction averaged regional measurements across latitudinal bands to produce a global trend [Merrifield et al., 2009]. And a more recent effort [Thompson and Merrifield, 2014] employed satellite altimeter and tide-gauge data to reveal a faster rate of sea level rise in the southern hemisphere than in the northern.
One novel approach employed a “neural network,” a type of computer model that simulates the action of neurons arranged in interconnected layers. The model’s output again extrapolates tide gauge data to connect coastal to regional and global-mean sea-level readings, thus eliminating potential problems with vertical land motion, and to fill gaps in tide-gauge records [Wenzel and Schroter, 2010].