water masses of the earth. These forces generate an oscillation which is lifting and lowering the sealevel. The third factor is the meansealevel (MSL). The MSL can be regarded as the base line of the observed sealevel, an increase of this basis would also increase the extremes. Adding up these three factors yield to the observed sealevel. Changes in extreme sea levels may result from changes in any of these factors, e.g. a positive trend in MSL leads to higher extreme sea levels. The contribution from the factors to the overall changes depends on the considered location. Changes in the atmospheric pressure and wind may lead to a different track, frequency or intensity of storms, the influ- ences to sealevel are thus regionally different. The tide is a deterministic and predictable signal, however tidal patterns around the world differ and may also change. Different effects lead to a non-uniform distribution of MSL. For ex- ample, a regionally different heating of the ocean due to global warming leads to regionally different thermal expansion (Bindoff et al., 2007). The melting of land-ice leads to a greater volume of the entire water mass, however the spatial distribution of the additional water is far from uniform. Large ice masses have a strong gravity to the surrounding water. If these ice masses melt the changes in the gravity lead to a lower attraction in its environment and therefore MSL even shrinks close to the ice sheet. On the other hand the MSL rises higher than the global mean further away. (Mitrovica et al., 2001). Changes in the circulation of the ocean or the atmospheric pressure field may influence the sea surface height regionally (G¨onnert et al., 2009). Many studies analysed the change in global meansealevel (GMSL) (e.g. Church et al., 2004; 2008; 2011; Hamlington et al., 2011; Holgate and Woodworth, 2004; Holgate, 2007; Jevrejeva et al., 2006; 2008). While such analyses are important for global climate change, they do not provide information at regional and local scales. In order to assess and to develop adequate adaptation strategies to rising sea levels, regional studies are urgently needed.
In order to demonstrate why it is important to correctly account for the (serial dependent) structure of temporal data, we document an apparently spectacular relationship between population size and lexical diversity: for five out of seven investigated languages, there is a strong relationship between population size and lexical diversity of the primary language in this country. We show that this relationship is the result of a misspecified model that does not consider the temporal aspect of the data by presenting a similar but nonsensical rela- tionship between the global annual meansealevel and lexical diversity. Given the fact that in the recent past, several studies were published that present surprising links between dif- ferent economic, cultural, political and (socio-)demographical variables on the one hand and cultural or linguistic characteristics on the other hand, but seem to suffer from exactly this problem, we explain the cause of the misspecification and show that it has profound consequences. We demonstrate how simple transformation of the time series can often solve problems of this type and argue that the evaluation of the plausibility of a relationship is important in this context. We hope that our paper will help both researchers and reviewers to understand why it is important to use special models for the analysis of data with a natural temporal ordering.
This study uses a combination of numerical and statistical methods to estimate present day return water levels at sites where only little or even no measured water level data is available. A similar method has recently been applied along different stretches of coast- lines around the globe (see e.g. H AIGH et al. 2013). This approach was adopted and mod- ified to satisfy the characteristics along the entire coastline of Schleswig-Holstein in northern Germany. It is shown that water levels derived from a hydrodynamic model can be used to calculate reliable return water levels. Regions with no or only few tide gauge stations can especially benefit from this approach. However, a precondition is to ade- quately correct the bias that is generated with the numerical simulations. The bias- correction is performed first at each individual station where water level observations exist. Then the correction is transferred to the neighbouring sites points using an Inverse
Another small low-lying island-state that is worth noting is Singapore. The rise in sealevel poses threats to Singapore as it lies only 15 meters (m) above the meansealevel, with about 30% of the island at less than 5 m above the meansealevel, according to Singapore’s National Climate Change Secretariat (NCCS). Navaratnarajah (2015) relates SLR to increases of carbon emissions and temperature and notes that warming can cause Singapore’s sealevel to increase by 9.5 m, leaving 745,000 Singaporeans’ homes submerged. Moreover, Ng and Mendelsohn (2005) examine the impact of SLR in Singapore and explore whether Singapore should defend its coast or allow it to be inundated. Based on their study, the annual cost of protecting Singapore’s coasts is estimated to rise over time as the sealevel rises and will range from $0.3 million–$5.7 million by 2050 to $0.9 million– $16.8 million by 2100. Depending on the SLR simulation, the present value of these costs ranges from $0.17 million to $3.08 million. Clearly, the regions or countries most vulnerable to SLR include atoll countries and small islands states like Kiribati and Singapore. Hence, there is a need for relevant discussions and consensus on how SLR will be dealt with through adaptation or mitigation.
ABSTRACT: As a consequence of global warming a rise of the meansealevel (MSL) is expected in the Western Baltic Sea. This fact may have practical consequences to long term planning and use of infra- structure and coastal protection measures. Especially sensitive to an MSL rise are inner coastal waters like the Schlei estuary and the Bodden coast. The intention of this study was to give a qualitative and quantitative view of the changes of water level variability due to a given MSL change for these regions. Nested model simulations with a Baltic Sea model and a high resolution estuary model were performed to estimate the effect of a given constant rise of sealevel at the Skagerak on short term water level variabil- ity. The results show significant rise of variability range in conjunction with the rising of MSL, induced by a volume change of the water body of the inner waters and its relation to the size of inflow section ar- ea. The numerical effect of too coarse grid resolution leads to an overestimation of the impact of MSL rise and approves the use of high resolution models for quantitative predictions. Nevertheless, the pre- sented model results show a significant change in water level variability of the Schlei area in addition to MSL rise. Therefor practical impacts on infrastructure management can result.
The most common proxies used to study paleo sea levels are paleo relative sea-level (RSL) indicators, i.e. fossil coastal landforms or deposits (e.g. a fossil coral reef terrace or a beach deposit) that have a quantifiable relation to a paleo sealevel (called the indicative meaning) and for which an age can be established (Van De Plassche, 1986; Shennan, 2015). The vast majority of known sea-level indicators older than Holocene dates back to the Last Interglacial (MIS 5e, ~130-116 ka). For this period, several studies attempted to collect RSL indicators in organized databases at both regional (Koike and Machida, 2001; Muhs et al., 2003; Ferranti et al., 2008; Muhs et al., 2011; O’Leary et al., 2013) and global scale (Kopp et al., 2009; Pedoja et al., 2011a; Pedoja et al., 2014; Hibbert et al., 2016). The latter are often used to either estimate global meansealevel patterns in MIS 5e (Kopp et al., 2013) or to quantify non-eustatic processes that might affect the paleo RSL elevation (Austermann et al., 2017). While Holocene sea-level studies are reaching a critical mass and a global standardized database is now under construction (Shennan, 1982; Shennan, 1989; Woodroffe and Horton, 2005; Engelhart and Horton, 2012; Khan et al., 2015; Vacchi et al., 2016), the standardization of MIS 5e sea-level data is lagging behind and lacks common approaches to standardize uncertainties (Düsterhus et al., 2016). One key point in the study of MIS 5e RSL is that the elevation and uncertainty of sea-level reconstruc- tions rely largely on the interpretation of RSL indicators. For example, different interpretations of the paleo RSL associated with a fossil coral reef can be given by either choosing to interpret a reef terrace as paleo-landform (Rovere et al., 2016a) or by assessing the modern living depths of paleo corals found on the same terrace (Hibbert et al., 2016). A second key point is to distinguish between the elevation measurement of a RSL indicator and the related paleo RSL.
The RSL height for load model NAWI-A1 (Figures 5.2 and 5.3, solid lines) is mainly reflected by the radial displacement, however, with opposite sign. The change of the global meansealevel due to the glaciation history of the northern hemisphere is smaller in magnitude. Nevertheless, this effect reduces the RSL height near Berkner Island and partially compensates the changes of the RSL height induced by the ra- dial displacement. The minimum of the RSL height is reached at 107 ka BP (SVM, −77.5 m) or 112 ka BP (LVM, −32.6 m).
ABSTRACT: The Elbe, Jade-Weser, and Ems estuaries located in the German Bight (North Sea) are not only important ecosystems, they are also used as waterways. The hydrodynamic conditions in these estu- aries are influenced by several factors. One of them is the sealevel in the North Sea. Future climate change leads to an accelerated increase of meansealevel in the North Sea. We need to know how this af- fects the hydrodynamic conditions in order to develop adaptation strategies. The objective of this work is to investigate how sealevel rise changes tidal dynamics in the interior of the estuaries. Using 3D- hydrodynamic numerical models we simulate estuarine hydrodynamic conditions. We carry out different model simulations with and without sealevel rise. The analyses show that in most parts of the estuaries high water levels rise more than low water levels. Hence tidal range is larger in the model simulations that include sealevel rise. As a result of sealevel rise the shape of the tidal curve is changed. In many parts of the estuaries flood current velocities increase more strongly than ebb current velocities. Due to the larger ratio of flood current velocity to ebb current velocity upstream sediment transport increases.
The tide-gauge time series used in this study are metric-monthly averages from the Permanent Service for MeanSeaLevel (PSMSL, Woodworth & Player, 2003). Figure 6 shows the location of the tide-gauge stations in Greenland registered with the PSMSL, with some details listed in Table 2. Only Southern Greenland is covered, with most stations providing less than 10 years of observations, the exception being Nuuk (formerly Godth˚ ab). These data are considered inadequate by many workers (e.g. Douglas, 1997), however, until longer records become available, we will consider the four longest time series to obtain estimates for present-day sea-level change rates. The corresponding stations are: Sisimiut, Nuuk, Qaqortoq and Ammassalik.
During the last decade, several studies investigated the mass loss of the Greenland and West Antarctic Ice Sheet. The melt water ﬂows into the ocean and increases the eustatic sealevel by about 0.3 mm/yr if 100 Gt/yr of mass is lost. To investigate the oceanic response to the additional melt water, diﬀerent amounts of fresh water have been added as additional volume ﬂux along the coast of Greenland. Results are compared to a reference model simulation and conﬁrm the magnitude of global meansealevel rise, estimated by other studies. The additional volume is distributed over the ocean within days, as barotropic waves are generated. In these perturbation experiments global sealevel rises due to the additional water mass, a small portion of global meansealevel change originates from varying heat exchange between ocean and atmosphere, which cannot be related to a speciﬁc region. This eﬀect is at least one order of magnitude smaller than the sealevel change caused by the mass of the melt water inﬂow. It can be attributed to the non-linear nature of oceanic processes and may be regarded as a measure of uncertainty.
The observed along-channel differences of the change in tidal asymmetry in response to sealevel rise (Fig. 5d ) could be related to the cross-section specific ratio of tidal flat width to tidal channel width which generally increases from the inlet towards the landward boundary of the tidal basins in the Wadden Sea (again representing a topographic control). Also, three-dimensional processes could be responsible for the observed along-channel differences including lateral cir- culation (Becherer et al. 2015 ; Pein et al. 2018 ) and vertical circulation (Stanev et al. 2007 ) which are both affected by the topography (geometric characteristics) of a tidal basin. Stanev et al. ( 2007 ) showed that the total transport at shallow channel sections is dominated by the surface layer transport which is controlled by a non-linear tidal response induced by the flooding and drying of tidal flats (inducing flood dominance). By contrast, the deeper channel sections (tidal inlets) are con- trolled by hypsometric properties of the tidal basin in the deeper layer (inducing ebb dominance) and by the tidally in- duced stokes drift in the upper layer (inducing flood domi- nance) compensating the seaward directed residual transport induced by the hypsometric control. Following Stanev et al. ( 2007 ), this vertical circulation provides an explanation for (vertically averaged) ebb dominance in tidal inlets and deep tidal channels and (vertically averaged) flood dominance in the shallow extensions of the channel system, which is con- firmed by our model for the reference case (Fig. 4c ). The vertical circulation is sensitive to relative changes in mean water depth of shallow tidal basins which in turn is different in along-channel direction in response to a rise in meansealevel (increasing towards the tidal flats). Hence, the predicted along-channel variation of the tidal response to sealevel rise could also be related to depth-dependent variations of vertical circulation. In particular, the significant decrease in ebb cur- rent velocity in the shallower sections of the channel systems (Fig. 5c ) could be the result of a diminishing hypsometric control formerly in part compensating the flood dominance induced by the non-linear response of tidal flats.
This is particularly relevant for regions that are more vulnerable to flooding or drowning because of very low coastlines above meansealevel (MSL) as it is in e.g. South and Southeast Asia (Cazenave and Cozannet, 2013; Nicholls et al., 1999; Nicholls and Cazenave, 2010). At the close of the 20 th century, already more than 50 % of the global population were living along low-lying coastlines, (Houghton, 1996). Now, in the 21 st century, the growth of coastal populations, expansion of mega cities (i.e. cities exceeding 8 million inhabitants), and extensive groundwater extraction have destabilized the basement geology and causing localized and regional subsidence. This accelerates local sea-level rise and increases the risk of flooding (Nicholls, 1995; Horton et al., 2005; Geyh et al., 1979). Eleven of fourteen coastal mega-cities are located in Asia (Tibbetts, 2002; Geyh et al., 1979), where the number of people at risk to flooding is the highest, as the coastlines of India, Indonesia and Vietnam belong to the most populated regions in the world (Neumann et al., 2015). For Indonesia, an increase of 0.60 m in RSL can already cause land inundation of 34.000 km² (1.9% of the entire land mass) and for Vietnam, an increase in RSL of 1 m, is supposed to cause land loss of 40.000 km² (12.1% of the entire land mass) (Warrick et al., 1996). As Indonesia is composed of many thousand low-lying islands (~17.500 Islands cover a coastline length of 88.000 km) (Marfai and King, 2007; Kench and Mann, 2017), the land loss will affect the inhabitants dramatically. Some other regions in SE Asia that are also vulnerable to sea-level rise and the consequences of climate change are Bangladesh, parts of China, the Mekong River Delta in Vietnam, or the Bangkok region of Thailand (Yusuf and Francisco, 2009; Neumann et al., 2015). However, as explained by Nicholls and Mimura (1998), predicting the effect of how future sea-level scenarios might affect the society and environment is difficult due to the incomplete knowledge of all processes affected by sea-level rise or the lack of analytical methodologies convenient for several impacts. Thus to prevent catastrophic events in regions that are at elevated risk from sea-level rise and to predict its future rates and distribution, an understanding of the driving mechanisms of sea-level variability and their interactions, is essential (Overpeck et al., 2006).
It should be mentioned that impact of 1.0 m of SLR influence is not restrained by flooding; it does even affect the beach of the Aberdyfi and other beaches around. As these beaches were submerged during the simulation with a high water depth, this may result in coastal receding and clear morphological changes. In addition, the spit in the mouth of the estuary were completely submerged over long time during the simulation. The possible changes of the beach area and shape would lead to a coastal squeeze and a limitation of future investments in this location. Fig. 5d shows flood map of 2 m SLR. The observable effects of this low probable scenario is massive flooding in the whole low land areas, and water propagated further inland to inundate Borth and south of Ynyslas villages inside land by 2 km approximately, the massive flood would submerge parts of A487, B4353 and the railway. This would make the evacuation and traveling into flood-prone very difficult task due to high water level. Adding 1 in 100-year river event to SLR scenario resulted in flooding 26.3 km² of lands, most of which with elevation below 6m above meansealevel. The major source of flooding is rivers flowing from the estuary filled with water that enters these rivers through the drainage holes and thus, flooded the surrounding lands.
Prediction of characteristics of tide in gulfs, estuaries and bays is one of the most important studies for any kind of engineering developments. The long term natural process like sealevel rise will influence the tidal characteristics and the effect will be significant in the semi-enclosed basins, like gulfs and estuaries. Global sealevel change is usually caused by melting of land-based ice and thermal expansion-as water warms. It is estimated that the sea-level for the year 1990-2100 will be rise to 280 to 340 mm (Church & White, 2006). However, as per NOAA data, the global meansealevel variation is estimated to be order of 3.16±0.4 mm/year. As the global warming based SLR is alarming in ocean waters, it is increasingly im- portant to assess the effect of the same in all the coastal processes. In this study, an attempt is made to un- derstand the effect of SLR on the tidal levels and induced currents, along the Gulf of Khambhat, India. The existing tidal hydrodynamics are also estimated to assess the percentage difference in the levels and currents due to the SLR.
Overall, the impact of the SLR is more pronounced in Pulau Duyong compared to Sandakan Town. This is probably because Sandakan Town is built up on a raised platform level that is relatively safe from the projected SLR for the year 2060. On the other hand, majority of Pulau Duyong which comprise of a low lying area and covered by mangrove forests that grow below the Mean High Water (MHW) mark. It is anticipated that there will be a reduction of about 53% of the existing 1,800 hectares of mangrove forest (about 958 hectares) due to erosion and inundation caused by the rise of 0.5 m sealevel in the year 2060. The loss is estimated to be around RM8.8 million.
Changes in tidal current velocities induced by sea-level rise are mostly compensated by the considered topographic changes of the Wadden Sea. The results demonstrate the significance of sea- level rise induced topographic changes in the Wadden Sea for estimating local effects of sea-level rise on tidal dynamics.
Effects of the considered TC on tidal currents are generally smaller (Fig. 2d,h) than effects of SLR (Fig. 2b,f), but can be in the same order of magnitude locally. Hence SLR-induced TC of the Wadden Sea should be considered for more realistic estimates of SLR effects on tidal dynamics. However, estimates of tidal flat growth and associated critical SLR rates vary largely and have been proposed only for single tidal basins so far (e.g. van Goor et al. 2003, Dissanayake et al. 2012, Becherer et al. 2015). This study investigates feedbacks of hypothetic SLR-induced morphological changes of the entire Wadden Sea on tidal dynamics and whether these changes reinforce or compensate hydrodynamic effects, which arise from SLR alone.
The basis of this translation is through an overlay process that translates the geographic information for each province into grid cells. Specifically, the provinces are allocated to grid cells by percentage of geographic area that corresponds to specific CRU grid cells. For example, Administrative Area 1 may be allocated geographically between grid cells A and B at 30 per cent and 70 per cent, respectively. In this case, the province is recorded as having proportional area allocations in each grid location. This allocation is done using the ArcGIS Intersect function to standardize the process. In a region where detailed road location information is not available, the roadstock is then uniformly distributed at the same ratio of 30 per cent and 70 per cent, respectively, as the basis for the impact analysis. The result of this allocation process is that the kilometres of road in each province are allocated proportionally at a grid cell level. This allocation can now be combined with the sealevel data to determine impacts in a specific geographic location.
In the 1980s, evidence of climate change was mounting and a number of international conferences raised worldwide concern about the issue. Governments realized how big a threat climate change was and that they had to do something about it. They also realized that they had to work together to have any chance of success. Climate change is a global issue because all countries will be affected by it and all contribute, in varying degrees. In 1988, the United Nations set up the Intergovernmental Panel on Climate Change (IPCC) which brings together thousands of scientists from around the world. Their task is to assess existing research and knowledge about climate change and its effects and to provide comprehensive reports at regular intervals. The most recent report, known as the Fourth Assessment Report (AR4), was published in 2007. It concluded beyond all reasonable doubt that greenhouse gas concentrations in the atmosphere have increased mainly as a result of human activities, and gave a grave warning of the consequences if nothing is done. In 1992, governments agreed the United Nations Framework Convention on Climate Change (UNFCCC). This international agreement has been formally accepted by 191 countries. The objective of the convention is to stabilize greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous, man‐made interference with the climate system. Under the convention, governments monitor and report the greenhouse gases they produce, develop climate change strategies, and help the poorer among them address climate change. They meet once a year to review progress and decide what to do next. The convention was designed as an umbrella under which more action would be agreed in the future. In 1997, Kyoto Protocol was agreed. This treaty commits industrialized countries to reduce or limit their greenhouse gas emissions and reach certain emission targets by 2012. Recently, the UNFCCC 15th Conference of the Parties (COP15) meeting was held in Copenhagen in December 2009. It resulted in the Copenhagen Accord under which several developing and developed countries outlined intentions and commitments on carbon emissions, pledged support for technology transfer and acknowledged the importance of forest systems in combating climate change.