# On Sea-Level Change in Coastal Areas

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## Abstract

**:**

**GSLTG**) and on combining tide gauges and satellite data (

**GSLl**), are subjected to singular spectrum analysis (

**SSA**) to determine their trends and periodic or quasi-periodic components.

**GLSTG**increases by 90 mm from 1860 to 2020, a contribution of 0.56 mm/yr to the mean rise rate. Annual to multi-decadal periods of ∼90/80, 60, 30, 20, 10/11, and 4/5 years are found in both

**GSLTG**and

**GSLl**. These periods are commensurable periods of the Jovian planets, combinations of the periods of Neptune (165 yr), Uranus (84 yr), Saturn (29 yr) and Jupiter (12 yr). These same periods are encountered in sea-level changes, the motion of the rotation pole

**RP**and evolution of global pressure

**GP**, suggesting physical links. The first SSA components comprise most of the signal variance: 95% for

**GSLTG**, 89% for

**GSLl**, 98% for

**GP**and 75% for

**RP**. Laplace derived the Liouville–Euler equations that govern the rotation and translation of the rotation axis of any celestial body. He emphasized that one must consider the orbital kinetic moments of all planets in addition to gravitational attractions and concluded that the Earth’s rotation axis should undergo motions that carry the combinations of periods of the Sun, Moon and planets. Almost all the periods found in the

**SSA**components of sea-level (

**GSLl**and

**GSLTG**), global pressure (

**GP**) and polar motion (

**RP**), of their modulations and their derivatives can be associated with the Jovian planets. The trends themselves could be segments of components with still longer periodicities (e.g., 175 yr Jose cycle).

## 1. Introduction

**SL**(P,t) as the difference between (1) the distance from the center of mass of the Earth to the sea surface, at time t and location P, and (2), the distance from the center of mass of the Earth to the sea bottom (solid Earth), which is the water depth, at the same time t and location P:

**SL**variations in the Sea of Japan to variations in density and atmospheric pressure. Marmer [12] noted an annual oscillation at the tide gauges of Seattle and San Francisco that he also linked to meteorological phenomena. After a decade of additional observations, Jabobs [13] and LaFond [14] concluded that there was indeed a general rise in sea-level. Several explanations were considered: insulation from the Sun, meteorological tides, water density, changes in geography and geology of ocean basins. None was found to be completely satisfactory. McEwen [15] envisioned a complex mechanism with evaporation in the summer and precipitation in winter affecting the global sea-level. Further study showed that these annual variations were in fact in the phase in all observation stations, and the idea had to be dropped. Only the pressure patterns and hence the winds remained as a potential cause of periodic

**SL**variations.

**SL**[18,19,20,21,22,23,24,25].

**SSA**). The first

**SSA**components of both series, i.e., the trends, are very similar, with a major acceleration event near 1900 and a sea-level lagging pole motion by 5–10 years.

**SSA**components with periods 1 yr, ∼11 yr and 5.4 yr are common to the two series. An important feature is a 0.5 yr component that is present in sea-level but absent from pole motion. The remarkable similarity of the two trends and their phase lag suggests a causal relationship opposite to what is generally accepted.

**PSMSL**, https://www.psmsl.org/data/obtaining/complete.php (accessed on 5 July, 2020). Measurements of coastal sea level are available at 1548 sites; the raw data at all sites are shown in Figure 1.

**VLM**= $[{R}_{se}(\mathrm{P},\mathrm{t})-{R}_{se}{(\mathrm{P},\mathrm{t}}_{r})]$, can be accessed through GPS measurements. These allow far better coverage of Earth surface but cover a much shorter span of time, generally 30 yr at most. For that reason, only “recent” trends covering that period can be accessed. A very thorough analysis of these data has recently been published by [8]. The database is maintained by the Nevada Geodetic Laboratory, with 19286 sites scattered throughout the globe, and is called Median Interannual Difference Adjusted for Skewness (

**MIDAS**, http://geodesy.unr.edu/velocities/ (accessed on 5 July 2020).

**GSL**) curves (e.g., [8,27]). Interest in these

**GSL**curves has focused on their trends, acceleration, annual and inter-annual variations, and on the mechanisms responsible for these variations.

**SSA**method (see Golyandina and Zhigljavsky [28], Lemmerling and Van Huffel [29], Golub and Reinsch [30]) to a number of geophysical and heliophysical time series.

**SSA**decomposes any time series into a sum of components, a trend (that may or may not be present) and stationary quasi-periodic components. We have explained the method in a number of papers [31,32]. For instance, oscillations (pseudo-cycles) of ∼160, ∼90, ∼60, ∼22 and ∼11 yr are found in a series of sunspot numbers (e.g., Refs. [33,34,35,36,37,38,39]) as well as in a number of terrestrial phenomena [31,32,40,41,42,43,44,45,46,47,48,49,50,51,52,53], particularly sea level [26,54,55,56,57]. These particular periods (or periodicities) are of special interest, as they are members of the family of commensurable periods of the Jovian planets acting on the Earth and Sun [39,41,49,51,58]. These values are indeed close to the revolution periods of Neptune (165 yr), Uranus (84 yr), Saturn (29 yr) and Jupiter (12 yr) and several of their commensurable periods (see Table 1 in [51]).

**SSA**of these. In Section 3, we discuss and analyze the time series of vertical land motion (

**VLM**) based on GPS measurements. In Section 4, we submit some global sea-level (

**GSL**) curves that include satellite observations to

**SSA**. We compare and discuss the results of these analyses in Section 5 and conclude in Section 6.

## 2. SSA of Tide Gauge Records Time Series (i.e., $[{\mathit{R}}_{\mathit{ss}}(\mathrm{P},\mathrm{t})-{\mathit{R}}_{\mathit{ss}}{(\mathrm{P},\mathrm{t}}_{\mathbf{r}})]$

**GSLTG**). We are aware of the uncertainties due to geography and tectonics but are interested in subjecting the original data to as little manipulation as possible.

**SL**are displayed (Figure 3).

**GSLTG**. The

**GSLTG**curve is then analyzed using

**SSA**. The analysis yields a sum of components with (pseudo-) periods of 1 yr, 90 yr, 60 yr, 80 yr, 0.5 yr and 20 yr (in order of decreasing amplitudes). These are shown (in order of decreasing period) in Figure 5 (see also Table 2). The leading annual component has an amplitude (peak to trough) of 80 mm and undergoes a (longer than centennial) modulation with 10 mm amplitude. The next two components (90 and 80 yr) both have an amplitude of 40 mm, and the next three of approximately 15 mm. Taken together, they capture 95% of the total variance. The trend itself can be modeled with only three sine functions with periods 90, 60 and 20 yr.

## 3. Introducing the GPS Vertical Land Motion Time Series (the $[{\mathit{R}}_{\mathit{se}}(\mathrm{P},\mathrm{t})-{\mathit{R}}_{\mathit{se}}{(\mathrm{P},\mathrm{t}}_{\mathbf{r}})]$

## 4. SSA of GSL Curves Obtained with Inclusion of Satellite Data

**SSA**to analyze a number of global sea-level curves available from the literature.

**GSL**as a function of time are provided by NASA (https://podaac-tools.jpl.nasa.gov/drive/files/allData/merged$_$alt/L2/TP$_$J1$_$OSTM/global$_$mean$_$sea$_$level/GMSL$_$TPJAOS$_$5.0$_$199209$_$202008.txt (accessed on 5 July, 2020). The SSA of the resulting curve

**GSLl**(l for long) yields a trend and components at 54.5 ± 8.7, 19.4 ± 1.7, 10.1 ± 0.6, 3.9 ± 0.1 and 31.0 ± 5.5 yr (Table 2 and Figure 9) in order of decreasing amplitude (or roughly, given the uncertainties trend, 60, 20, 11, 4 and 30 yr). These components are shown in Figure 09 (in order of decreasing period); their sum amounts to 89.4% of the series total variance (Figure 8). The 3.9 yr component could correspond to the second harmonic of the Schwabe cycle [38]. Note that the prominent 1 and 0.5 yr variations have been filtered out by [27].

**GSLl**incorporates two very different data sets (measurements from tide gauges and satellites), we have resumed the analysis for the 1993–2009

**GSLs**(s for short) based on satellite data only. For details on the structure of the data, we refer the reader to [65]. For explanations on how the data set has been created from 27 years of altimetric measurements by the successive satellites TOPEX/Poseidon (T/P), Jason-1, Jason-2 and Jason-3, we refer the reader to [66,67]. The global mean sea-level data consist in several sets of time series, some with a “Global Isostatic Adjustment applied”, and some “GIA not applied”. The latter (without GIA) is shown in Figure 10, from January 1993 to August 2020, with a sampling interval of 9.92 days.

**SSA**of the resulting curve

**GSLs**yields a trend and components at 1.00 ± 0.02, 0.49 ± 0.01, 3.06 ± 0.25, 15.4 ± 4.7, 1.50 ± 0.05 and 6.06 ± 0.73 yr in order of decreasing amplitude (or roughly, given the uncertainties trend, 15-20, 6, 3, 1.5, 1 and 0.5 yr). These components are shown in Figure 11 (in order of decreasing period); their sum amounts to 87.3% of the series total variance (Figure 10). The sum of the seven first components extracted by

**SSA**is plotted as a red curve. The 6.1, 3.1 and 1.5 yr quasi periods could correspond to the harmonics of the Schwabe cycle (cf. [38], Table 1).

## 5. Discussion

#### 5.1. Components Shared by **GSLl**, **GSLTG** and **SSN**

**GSLl**and

**GSLs**series do not share many characteristics (cf. Table 2). Their trends are similar and they both have significant 1-year and 6-month components, but the two series do not share other quasi- periodic components (unless the 15-year component of

**GSLs**can be considered to be the same as the 20 yr component of

**GSLl**, given uncertainties). Actually, the span of the

**GSLs**data is only 27 yr and should not be used to identify components with periods longer than, say, 27/2 or ∼15 yr.

**GSLl**shares seven components with

**GSLTG**: a trend of 60, 30, 20, 10, 1 and 0.5 yr components cf. Table 2).

**SSA**components of the sunspot number

**SSN**, a characteristic of solar activity. Four components of

**SSN**are found in

**GSLl**(60, 30, 20, 10 yr) and six in

**GSLTG**(90, 60, 20, 30, 10, 5 yr), taking into account the uncertainties (fi. 10.15 ± 0.58 and 10.64 ± 1.17 are both considered equivalent to the

**SSN**packet at 10.6 and 11.3 yr).

**GSLs**is only 8 mm peak to trough (Figure 11b), when tide gauges record a mean amplitude an order of magnitude larger (80 mm; Figure 5a). This could be due to the fact that tide gauges are located in shallow waters where wave amplitude is amplified; in any case, this is where the sea-level is relevant to human activities. The trend amplitude between 1860 and 2020 is 80 mm for

**GSLTG**(Figure 4b) and more than 200 mm for

**GSLl**(Figure 8). Moreover, with a

**GSLTG**curve extending over two centuries, we see that the trend of the shorter series

**GSLs**could actually be part of a longer cycle (in the same order as the ∼90 year Gleissberg cycle).

#### 5.2. Comparison with Global Pressure **GP**

**SSA**reveals that

**GSLl**and

**GSLTG**share many characteristics that could constrain the mechanisms that control both series of sea-level change. In order to strengthen this hypothesis, one can try to find whether some other geophysical phenomenon would possess similar characteristic features with the same spectral signatures. We have searched whether the Earth’s global mean pressure (

**GP**) meets these requirements. A series of monthly mean atmospheric pressure (everywhere in the world) is available was of 1846 [68]. It can be accessed through the Met Office Hadley Centre (http://www.metoffice.gov.uk/hadobs/hadslp2/data/download.html accessed on 5 July 2020) website under the name HadSPL2. Following Laplace’s work on the subject of the spatial and temporal stability of pressure ([10], book IV, chap 4, page 294), we built a series of monthly global pressure

**GP**and submitted it to

**SSA**: the first four components, i.e., the trend followed by periods of 1 yr, 6 months and ∼25 yr, account for 98% of the total variance. Thus,

**GSLTG**and

**GP**share three major components at ∼20/25 yr, 1 yr and 6 months. Comparisons between some features of

**GSLTG**and

**GP**are illustrated in Figure 12. The annual and semi-annual components match in phase and frequency and are slightly modulated with a time constant in the order of a century or more. Both series have ∼20/25 yr components that drift, one with respect to the other. Interestingly, the derivative of the trend of pressure

**GP**matches the trend of

**GSLTG**, suggesting a relation of the form

**GSLTG∼**(d/dt)

**GP**. Furthermore, the ratios of the amplitudes of the various

**SSA**components of

**GSLTG**and

**GP**are approximately constant (Table 3). Sea level and pressure respond in similar ways at all time scales.

#### 5.3. Comparison with the Mean Motion of the Rotation Pole (**RP**)

**RP**) and the mean sea-level (be it

**GSLTG**or

**GSL**) belong to the same family because of the reorganization of surface masses due to pole motion. Because the Liouville–Euler equations are a linear differential system of second order, one understands the resemblance between

**RP**and both

**GSLTG**or

**GSL**, at least during longer periods. Can the analysis of the

**RP**series bring additional light to the question of the forcing of sea level (we refer the reader to earlier work on polar motion by [31,32,51])?

**RP**) is maintained by the International Earth Rotation and Reference Systems Service (

**IERS**, https://www.iers.org/IERS/EN/DataProducts/EarthOrientationData/eop.html accessed on 5 July 2020). Two series of measurements of pole coordinates ${m}_{1}$ and ${m}_{2}$ are provided by

**IERS**under the codes EOP-C01-IAU1980 and EOP-14-C04. The first one runs from 1846 to 1 July 2020 with a sampling rate of 18.26 days, and the second runs from 1962 to 1 July 2020 with daily sampling. Figure 13 displays the trends (top) and derivatives (bottom) of the rotation pole (

**RP**) coordinates ${m}_{1}$ and ${m}_{2}$ together with those of

**GSLTG**(1807–2020). There is a suggestive anti-correlation between the trend of

**GSLTG**and the derivative of the trend of ${m}_{2}$ (

**GSLTG**∼(d/dt)

**RP**), with the former leading the latter by several decades (Figure 13, lower left). This behavior was noted for the Brest tide gauge by [32]. This is yet another line of observational evidence that the sea-level curve based on tide gauges has an underlying physical mechanism.

**RP**, i.e., the Markovitch drift, the Chandler free oscillation (that has never yet been detected in sea level) and the annual forced oscillation, carry more than 75% of the signal’s total energy (variance) [31,51,53]. Ref. [31] also showed the presence of other components at 22 yr (Hale), 11 yr (Schwabe) and a 5.5 yr harmonic. The order of magnitude of these solar components is 10${}^{-12}$ to 10${}^{-14}$ rad.sec${}^{-1}$, that is 1–4 orders of magnitude smaller than the main components (10${}^{-11}$ to 10${}^{-10}$ (rad· sec) ${}^{-1}$). In [26,39,51], it has been shown that the derivative of the Markovitch component includes the 90 yr (Gleissberg) cycle as its trend. Ref. [51] identified some other components that also appear in the

**SSN**sunspot series [39]. We limit ourselves to the shared (quasi-) periods of 90, 22, 11, 5.5, 1.4 and 1 year.

#### 5.4. The Liouville–Euler System and Solar Components in Sea Level

**RP**) and $\mathbf{f}={f}_{1}+i\ast {f}_{2}$ and ${f}_{3}$ are the excitation functions. These are explicitly written in [9], chapter 4, system 4.1.1, page 47. These functions belong to three distinct families: masses, motions (of masses), and imposed forces (torques). Parameters (${m}_{1}$,${m}_{2}$,${m}_{3}$) provide a global scalar for pole motion, and the excitation functions are also global. Because coupled system (4) is linear, any periodic component found in (${m}_{1}$,${m}_{2}$,${m}_{3}$) data/observations must also be present in (${f}_{1}$,${f}_{2}$,${f}_{3}$).

#### 5.5. Planetary Forcings

**GP**(with the sign reversed) and the trend of

**GSLTG**match quite well (Figure 12, middle left).

## 6. Summary and Concluding Remarks

**GSLTG**) and variations in the global sea level combining tide gauges and satellite data (

**GSLl**[27]); then, with much better spatial coverage but a much more restricted time span (1993-2020), satellite-only data (

**GSLs**, [65]). Our main goal has been to determine the trends and successive periodic or quasi-periodic components of these time series, using the

**SSA**method (

**SSA**) that we have used, with interesting results, in a series of previous papers [26,31,39,47,48,51].

**GSLTG**). We see all kinds of behavior, with increasing, stable or decreasing mean values (trend), giving the complete data set a funnel shape. The resulting

**GLSTG**mean oscillates around an almost constant value. From 1860 to 2020, the trend increases by 90 mm, or a contribution to the mean rise rate of 0.56 mm/yr.

**GSLTG**.

**SSA**analysis of the

**GSLTG**series identifies components with celestial periods already found when analyzing the Brest tide gauge data [26]. We have shown (Table 3) that the ratios of amplitudes of

**SSA**components (trend, 20–30 yr, 1 yr, 0.5 yr) of

**GSLTG**vs. global pressure

**GP**are almost constant (at 0.02 hPa/mm). This observation supports the idea that tide gauge data contain significant information on the physical links between mean pressure and (geoid) sea-level.

**GSLTG**and

**GSLl**sea-level curves in the present study have already been encountered in a number of geophysical and heliophysical time series. These periods (or quasi-periods) are ∼80–90, 60, 30, 20, 10–11, and 4–5 years. They can be compared to the commensurable periods of the Jovian planets acting on the Earth and Sun as proposed by [41]. The combination of the revolution periods of Neptune (165 yr), Uranus (84 yr), Saturn (29 yr) and Jupiter (12 yr) and several commensurable periods makes additional pseudo-cycles of 60 and 20 yr appear in sunspots [32,39] as well as in a number of terrestrial phenomena [31,32,41,45,46,49,51,58], particularly in sea level [55,73,74,75,76]. It is therefore not a surprise to find Jovian periods in

**GSLTG**. Even trends could be part of commensurate cycles longer than the time span over which the data are available.

**RP**and the evolution of global pressure

**GP**and the relations between some of their trends (as determined using

**SSA**) suggest that there may be physical links and causal relationships between these geophysical phenomena and the time series of observations available. The ubiquitous presence of many common components in the variations of many natural phenomena (that a priori might seem largely unrelated) has led us to return to the general forcing envisioned by [10] and to the full theory he developed. In their 1799 Treatise of Celestial Mechanics, Laplace derived the Liouville–Euler partial differential equations that describe the rotation and translation of the rotation axis of any celestial body, and showed that the only thing that influences the rotation of celestial bodies is the action of other celestial bodies. Laplace emphasized that one must consider the orbital kinetic moments of all planets in addition to gravitational attractions and concluded that the Earth’s rotation axis should undergo motions with components that carry the periods or combinations of periods of the Sun, Moon and planets (particularly Jovian planets).

**GSLTG**), and we have also shown that there were several shared periodic components with global pressure

**GP**and the Earth’s rotation axis

**RP**.

**RP**. The

**SSA**analysis of the envelopes of the derivatives of the three first polar motion components yields a number of additional periods that belong to the series of commensurable periods, among which 70 yr, 60 yr (Saturn; also found in global temperatures and oceanic oscillations), 40 yr (a commensurable revolution period of the four Jovian planets), 30 yr (Saturn) and 22 yr (Jupiter and Solar). The same is true for the first three

**SSA**components of sunspot series

**SSN**(trend or Jose 175 year cycle, linked to Neptune; 11 yr Schwabe cycle, linked to Jupiter; and 90 yr Gleissberg cycle, linked to Uranus). Almost all the (quasi-) periods found in the

**SSA**components of sea-level (

**GSLl**and

**GSLTG**), global pressure (

**GP**) and polar motion (

**RP**) of their modulations and of their derivatives can be associated with Jovian planets (Table 3). These complement the list of

**SSA**quasi-periodic and periodic components that are found in

**GSLl**,

**GSLTG**,

**GP**,

**RP**and

**SSN**(90, 60, 30, 20, 10, 5, 1 and 0.5 years) and can all be associated with planetary forcings, as envisioned by Laplace. In particular, planetary forcing factors are likely causally responsible for many of the components of sea-level variations as measured by tide gauges. It is of particular interest to search for high-quality data series on longer time intervals, that can allow one to test whether the trends themselves could be segments of components of even longer periodicities (e.g., 175 yr Jose cycle). In any case, the first

**SSA**components of the series analyzed in this paper comprise a large fraction of the signal variance: 95% for the first six components of

**GSLTG**, 89% for the first six components of

**GSLl**, 87% for the first six components of

**GSLs**, 98% for the first four components of

**GP**and 75% for the first three components of

**RP**. It is clear that one should attempt to physically model these series with this set of periods (

**SSA**components) before trying to invoke alternate sources (forcing functions).

## Author Contributions

## Funding

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

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**Figure 3.**Superposition of data series from the 31 tide gauges listed in Table 1.

**Figure 4.**Fit of the 31 tide gauges. (

**a**) Data points from the 31 tide gauges used in building

**GSLTG**and their sinusoidal fit, with 8 sine waves. (

**b**) The fit (black curve) of (

**a**) with an enlarged ordinate scale.

**Figure 5.**The first six most important components extracted from

**GSLTG**. (

**a**) First

**SSA**component (1 yr) of the

**GSLTG**data series of Figure 4b. (

**b**) Second

**SSA**component (∼90 yr) of the

**GSLTG**data series. (

**c**) Third SSA component (∼60 yr) of the

**GSLTG**data series. (

**d**) Fourth

**SSA**component (∼80 yr) of the

**GSLTG**data series. (

**e**) Fifth

**SSA**component (0.5 yr) of the

**GSLTG**data series. (

**f**) Sixth

**SSA**component (∼20 yr) of the

**GSLTG**data series.

**Figure 6.**Superposition of the histogram of recent slopes of 1548 tide gauges with that of the MIDAS (GPS) data (from Hammond et al. [8]).

**Figure 7.**Comparison of GPS and tide gauges slopes. (

**a**). The locations of tide gauges and values of the local slope of sea-level change. Color code ranges from positive (red) to negative (blue). (

**b**) The locations of GPS sites and the local changes (slopes) of vertical land movement (VLM) from the MIDAS database. Color code same as in (

**a**).

**Figure 8.**Global sea level

**GSLl**curve from [27] in blue. Sum of first 6 components extracted by

**SSA**, red curve.

**Figure 9.**First six components extracted by

**SSA**from

**GSLl**data series. (

**a**) The first

**SSA**component (trend in red) superimposed on the

**GSLl**data series. (

**b**) Second

**SSA**component (∼60 yr pseudo-period) of the

**GSLl**data series. (

**c**) Third

**SSA**component (∼30 yr pseudo-period) of the

**GSLl**data series. (

**d**) Fourth

**SSA**component (∼20 yr pseudo-period) of the

**GSLl**data series. (

**e**) Fifth

**SSA**component (∼11 yr pseudo-period) of the

**GSLl**data series. (

**f**) Sixth

**SSA**component (∼4 yr pseudo-period) of the

**GSLl**data series.

**Figure 10.**Global -sea level

**(GSLs)**(blue curve). Sum of the first seven

**SSA**components (red curve).

**Figure 11.**First seven components extracted by

**SSA**from

**GSL**data series. First

**SSA**component (trend) of the

**GSL**data series of Figure 10. Second

**SSA**component (1 yr) of the

**GSL**data series. Third

**SSA**component (0.5 yr) of the

**GSL**data series. Fourth

**SSA**component (3 yr) of the

**GSL**data series. Fifth

**SSA**component (15 yr) of the

**GSL**data series. Sixth

**SSA**component (1.5 yr) of the

**GSL**data series. Seventh

**SSA**component (6 yr) of the

**GSLs**data series.

**Figure 12.**

**Top left**, the superposition of the trends of

**GSLTG**(in black) and

**GP**(in red).

**Middle left**, the superposition of the trend of

**GSLTG**(in black) and the first derivative of the trend of

**GP**(in red).

**Bottom left**, the ∼20 yr components of GP (red) and GSLTG (black).

**Top right**and

**middle right**(a zoom), the annual oscillations of

**GSLTG**(black) and

**GP**(red).

**Bottom right**, the semi-annual cycles of

**GP**(red) and

**GSLTG**(black).

**Figure 13.**Trends (

**top**) and their derivatives (

**bottom**) of the rotation pole (

**RP**) coordinates ${m}_{1}$ (red) and ${m}_{2}$ (blue) compared with those for

**GSLTG**(

**left**; 1807–2020).

Tide Gauge Site | Lat (${}^{\circ}$) | Lon (${}^{\circ}$) |
---|---|---|

Adak Sweeper Cove | 51.863 | −176.632 |

Argentine Islands | −65.246 | −64.257 |

Auckland | −36.843 | 174.769 |

Brest | 48.382 | 4.494 |

Churchill | 58.767 | −94.183 |

Chennai | 13.100 | 80.300 |

Cochin | 9.967 | 76.267 |

East-London | −33.027 | 27.932 |

Fernandina Beach | 30.672 | −81.465 |

Honolulu | 21.307 | −157.867 |

Ketchikan | 55.332 | −131.625 |

Key West | 24.555 | −81.806 |

Knysna | −34.049 | 23.046 |

Lisbon | 38.700 | −9.133 |

Marseille | 43.279 | 5.354 |

Maasluis | 51.918 | 4.25 |

Manila, S.harbor | 14.583 | 120.967 |

Mera | 34.919 | 139.825 |

Montevideo | −34.900 | −56.250 |

Narvik | 68.428 | 17.426 |

Oslo | 59.909 | 10.735 |

Polyarny | 69.200 | 33.483 |

Port Adelaide | −34.780 | 138.481 |

Rio de Janeiro | −22.933 | −43.133 |

Swinoujscie | 53.917 | 14.233 |

Takoradi | 4.885 | −1.745 |

Tofino | 49.150 | −125.917 |

Tuapse | 44.100 | 39.067 |

Valparaiso | −33.027 | −71.626 |

Visby | 57.639 | 18.284 |

Xiamen | 24.450 | 118.067 |

Sea Level (mm) | Pressure (hPa) | Ratio (hPa/mm) | |
---|---|---|---|

Trend | 45 | 0.8 | 0.019 |

∼20–30 yr | 18 | 0.45 | 0.025 |

1 yr | 80 | 1.6 | 0.020 |

0.5 yr | 16 | 0.3 | 0.019 |

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## Share and Cite

**MDPI and ACS Style**

Courtillot, V.; Le Mouël, J.-L.; Lopes, F.; Gibert, D.
On Sea-Level Change in Coastal Areas. *J. Mar. Sci. Eng.* **2022**, *10*, 1871.
https://doi.org/10.3390/jmse10121871

**AMA Style**

Courtillot V, Le Mouël J-L, Lopes F, Gibert D.
On Sea-Level Change in Coastal Areas. *Journal of Marine Science and Engineering*. 2022; 10(12):1871.
https://doi.org/10.3390/jmse10121871

**Chicago/Turabian Style**

Courtillot, Vincent, Jean-Louis Le Mouël, Fernando Lopes, and Dominique Gibert.
2022. "On Sea-Level Change in Coastal Areas" *Journal of Marine Science and Engineering* 10, no. 12: 1871.
https://doi.org/10.3390/jmse10121871