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Ports are one of the structures where the effects of global warming are most severe and intense in atmospheric, oceanic, and geographical terms. According to the Intergovernmental Panel on Climate Change (IPCC)'s assessment reports, although it is possible to slow down global warming by reducing greenhouse gas (GHG) emissions, it is not foreseen to stop global warming and sea level rise (SLR) in any scenario. The rising sea level, an inevitable consequence of global warming, is a clear threat to conventional port facilities. In summary, SLR triggered by climate change, which is today's hot topic, may cause conventional port infrastructures to be flooded and lose their functionality. To cope with this threat, port facility planning, and design stages must be carried out by referring to the updated threshold values in Shared Socioeconomic Pathway (SSP) scenarios defined by the Working Groups of the IPCC. However, the uncertainty about the scale, timing, and location of SLR makes definitive solution-oriented approaches more prominent. One of these approaches is floating port structures. This study aims to reveal the role of floating port structures in the implementation of the relocation measure emphasized in the IPCC Sixth Assessment Report (AR6) for conventional ports under the threat of SLR. Initially, in this study, regions with higher SLR risk were identified by considering SSP scenarios contributed by Sixth Phase of the Coupled Model Intercomparison Project (CMIP6) data. Afterwards, the dynamic downscaling model was used to determine the regions with higher regional sea level rise (RSLR) risk and the Marine Traffic database was used to determine the ports in these regions. Thus, it is evaluated whether floating ports can be a suitable alternative in the relocation decision of ports under SLR risk. It is expected that maritime transport will be maintained at adequate security and operational levels by revealing the pros and cons of floating ports. [ABSTRACT FROM AUTHOR]

Global warming changes the Earth's climate in different ways, in particular it influences extreme weather events like storms. Strong storms cause large surges and thus have a signature in the sea level record. While previous studies focused on long‐term changes of storm surge amplitude or frequency, changes in the timing of extreme surge events have not been investigated so far. We employed the more than 150 yr long tide gauge record of Brest (France) and found a distinct shift of storm surge timing between the years 1950 and 2000. This caused extreme events to happen about three weeks earlier during the year. We developed for this study two different methods based on statistical extreme value analysis; both methods show this shift of the seasons consistently. Furthermore, by analyzing eight additional stations, we found evidence that this timing shift happened similarly over a large part of the European Atlantic coast. Therefore, we speculate that our measured shift is part of a large‐scale climate process. Plain Language Summary: Climate change leads to an increase of the sea level all over the world. This means not only that the average sea level rises, but also that extreme sea levels become higher, which presents a major threat for coastal communities. To prepare for this growing natural hazard, it is important to understand how extreme sea levels evolve in a warming climate. One of the best places to study this is the harbor of Brest, France, which has one of the longest sea level records in the world (over 150 yr). From this time series, we extracted the surge, which is the part of the sea level that is created by large‐scale atmospheric forcing, like storms. We used two statistical methods to analyze the extreme surge levels in Brest, and we found that between 1950 and 2000, the season of large surge levels shifted forward. In 2000, extreme storm surge events happened three weeks earlier than 50 yr before. We then analyzed sea level records of other stations and found the same shift over large parts of the European Atlantic coast. So we conclude that this shift of the extreme surge season might be the signature of a large‐scale climate process. Key Points: Extreme storm surge events occurred three weeks earlier in Brest in the winter 2000 than in the 1950sShift of winter storm surge timing was calculated consistently with two statistical methodsAnalysis of additional stations in Europe suggests a large‐scale process [ABSTRACT FROM AUTHOR]

Differentiating the impacts of climate change between 1.5°C and 2°C requires a regional and sector-specific perspective. Whereas for some regions and sectors the difference in climate variables might be indistinguishable from natural variability, other areas especially in the tropics and subtropics will experience significant shifts. In addition to region-specific changes in climatic conditions, vulnerability and exposure also differ substantially across the world. Even small differences in climate hazards can translate into sizeable impact differences for particularly vulnerable regions or sectors. Here, we review scientific evidence of regional differences in climate hazards at 1.5°C and 2°C and provide an assessment of selected hotspots of climate change, including small islands as well as rural, urban, and coastal areas in sub-Saharan Africa and South Asia, that are particularly affected by the additional 0.5°C global mean temperature increase. We interlink these with a review of the vulnerability and exposure literature related to these hotspots to provide an integrated perspective on the differences in climate impacts between 1.5°C and 2°C. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO 2 ) is one of the main sources of global warming, rising sea levels, and frequent outbreaks of extreme weather. China is now one of the largest energy consumer and CO 2 emitters in the world. As one of China's economic centers, Shanghai city has a perfect industrial system with large industrial scale. The industrial sector is an energy– and emission–intensive industry, which contributes the significant part of CO 2 emissions in Shanghai city. Therefore, an in–depth investigation of the main driving forces of CO 2 emissions in the industrial sector is essential to reduce CO 2 emissions in the city. This study uses Vector Autoregressive model to analyze the main factors causing the increase in CO 2 emissions in the industrial sector. The results show that economic growth leads to an increase in CO 2 emissions in the short run, but is conducive to reducing CO 2 emissions in the long run, due to the differences in fixed–asset investment and export trade. Energy consumption structure leads to a growing CO 2 emissions in the short term, and is beneficial to mitigate CO 2 emissions in the long term, owing to the gradual optimization of energy consumption structure. However, urbanization helps to reduce CO 2 emissions in the short term, but leads to an increase in CO 2 emissions in the long term, because of urban real estate and infrastructure construction investments as well as vehicle use. Energy efficiency leads to an increase in CO 2 emissions both in the short and long run since the scale effect exceeds the technical effect. Industrial structure produces a positive effect in the short run, but the impact is gradually narrowing in the long run. [ABSTRACT FROM AUTHOR]

Having great impacts on human lives, global warming and associated sea level rise are believed to be strongly linked to anthropogenic causes. Statistical approach offers a simple and yet conceptually verifiable combination of remotely connected climate variables and indices, including sea level and surface temperature. We propose an improved statistical reconstruction model based on the empirical dynamic control system by taking into account the climate variability and deriving parameters from Monte Carlo cross-validation random experiments. For the historic data from 1880 to 2001, we yielded higher correlation results compared to those from other dynamic empirical models. The averaged root mean square errors are reduced in both reconstructed fields, namely, the global mean surface temperature (by 24-37%) and the global mean sea level (by 5-25%). Our model is also more robust as it notably diminished the unstable problem associated with varying initial values. Such results suggest that the model not only enhances significantly the global mean reconstructions of temperature and sea level but also may have a potential to improve future projections. [ABSTRACT FROM AUTHOR]

Sea-level rise, as a result of global warming, may lead to more natural disasters in coastal regions where there are substantial aggregations of population and property. Thus, this paper focuses on the impact of sea-level rise on the recurrence periods of extreme water levels fitted using the Pearson type III (P-III) model. Current extreme water levels are calculated using observational data, including astronomical high tides and storm surges, while future extreme water levels are determined by superposing scenario data of sea-level rise onto current extreme water levels. On the basis of a case study using data from Shandong Province, China, results indicated that sea-level rise would significantly shorten the recurrence periods of extreme water levels, especially under higher representative concentration pathway (RCP) scenarios. Results showed that by the middle of the century, 100-year current extreme water levels for all stations would translate into once in 15-30 years under RCP 2.6, and once in ten to 25 years under RCP 8.5. Most seriously, the currently low probability event of a 1000-year recurrence would become common, occurring nearly every 10 years by 2100, based on projections under RCP 8.5. Therefore, according to this study, corresponding risk to coastlines could well be increase in future, as the recurrence periods of extreme water levels would be shortened with climate change. [ABSTRACT FROM AUTHOR]

Sea level rise associated with changing climate is expected to pose a major challenge for societies. Here, we estimate the future contribution of the Greenland ice sheet (GrIS) to sea level change in terms of different ice sheet atmospheric forcings arising from three general circulation models (GCMs), HadGEM2-ES, IPSL-CM5A-LR and MIROC5, for RCP2.6. We run the ice sheet model ISSM with higher order approximation and use a spin-up/inversion scheme to estimate the present day state. The forcing fields for surface mass balance (SMB) and ice surface temperature Ts are computed by the SEMIC model (Krapp et al., 2017) and applied as anomalies to RACMO2.3 fields. According to the three GCMs, warming of 1.5 °C has been reached at GrIS by 2005 (HadGEM2-ES, MIROC5) or as early as 1995 (IPSL-CM5A-LR). Forcing fields suffer from underestimation of polar amplification (MIROC5) and implausible distribution of changes in Ts (IPSL-CM5A-LR). HadGEM2-ES is the most plausible forcing, with globally a peak and decline behaviour leading to overshooting of 1.5 °C and over GrIS a slight recovery of SMB towards values of about half the present day SMB. We find sea level to rise for HadGEM2-ES by 71 mm by 2100 and 189 mm by 2300. Simulated an observed sea level rise 2002-2014 is of the same magnitude, but with a temporal lag to be at least five years (HadGEM2-ES). By end of 22nd century sea level contribution is still 0.46 mm/a for HadGEM2-ES. Hence, even a RCP2.6 peak and decline scenario will lead to significant changes of GrIS including elevation changes up to 100 m and loss of floating tongues. The values of this study may serve as a lower bound, as processes proven to play a major role in GrIS mass loss are not yet represented by the model, but are considerably larger than other studies. [ABSTRACT FROM AUTHOR]

Global warming induces temperature variations and sea level changes for a long period of time. Many coastal cities around the world have experienced the harmful consequences of sea level changes and temperature variations. The city of Shanghai in China also suffers from the serious consequences of these two climatic factors. The geological and climatic conditions of Shanghai make it sensitive to flooding risks during heavy rainfall events. This paper analyses the conditions of sea level changes, temperature variations, and heavy rainfall events in Shanghai. Correspondingly, eustatic sea level change, tectonic movement of the continent, and land subsidence in Shanghai have effects on sea level changes. Correlation analysis indicates extraordinary short duration rainfall events have a relationship with temperature variations due to global warming. Moreover, the number of extraordinary torrential rainfall events also has a correlation with sea level changes. Pluvial flooding and potential damage to coastal structures are more likely to have serious effects as the number of flooding hazard events due to global warming and sea level changes increases. This study also established that to efficiently protect the environment, control economic losses, and prevent potential hazards, extra countermeasures including monitoring, forecasting, and engineering technology treatment should be adopted. Monitoring measurements combined with a database system on a website was found to be useful for forecasting and simulating flooding hazards. For systematic sustainable urban water system management, appropriate treatment technologies, such as sustainable urban water system, which can control and manage water quantity and quality, namely "the Sponge City", should also be considered. [ABSTRACT FROM AUTHOR]

A coastal sensitivity index (CSI) was developed to assess the response of the Red Sea coast in Egypt to climate change in terms of sea level rise and global warming. Six different variables pertaining to the intrinsic characteristics of the coast that extends to 1200 km were utilized, notably: coastal geomorphology, coastal slope, width of the coastal plain, shoreline exposure, fauna/flora and land use. Data have been extracted, manipulated and presented using remote sensing and GIS analysis. The resulting coastal sensitivity map depicts the susceptibility levels of the Red Sea coastal plain to climate change. The most severely sensitive segments (very high CSI) account for 31 % (365 km) of the coast. They occur across unconsolidated, flat, wide, exposed, ecologically effective and/or inhabited coasts. On the other hand, the least sensitive (low CSI) coastal segments total 245 km (20 %) and are mainly rocky, steep, narrow, barren and/or inaccessible shores. Eustatic sea level rise by 1 m should inundate a coastal area of 106 km, whereas a sudden tsunami of 5 m height should overwhelm 724 km, particularly at the southern section near Shalateen. Global warming of seawater should impact the coastal zone between Hurghada and Marsa Alam (270 km long) due to the occurrence of fringing coral reef systems. The coastal sensitivity index provides a synoptic overview that could help prioritize emergency plans and protection strategies to reduce the ramifications of climate change. [ABSTRACT FROM AUTHOR]

With the warming of the global climate, the mass loss of the Greenland ice sheet is intensifying, having a profound impact on the rising of the global sea level. Here, we used Gravity Recovery and Climate Experiment (GRACE) RL06 data to retrieve the time series variations of ice sheet mass in Greenland from January 2003 to December 2015. Meanwhile, the spatial changes of ice sheet mass and its relationship with land surface temperature are studied by means of Theil–Sen median trend analysis, the Mann–Kendall (MK) test, empirical orthogonal function (EOF) analysis, and wavelet transform analysis. The results showed: (1) in terms of time, we found that the total mass of ice sheet decreases steadily at a speed of −195 ± 21 Gt/yr and an acceleration of −11 ± 2 Gt/yr2 from 2003 to 2015. This mass loss was relatively stable in the two years after 2012, and then continued a decreasing trend; (2) in terms of space, the mass loss areas of the Greenland ice sheet mainly concentrates in the southeastern, southwestern, and northwestern regions, and the southeastern region mass losses have a maximum rate of more than 27 cm/yr (equivalent water height), while the northeastern region show a minimum rate of less than 3 cm/yr, showing significant changes as a whole. In addition, using spatial distribution and the time coefficients of the first two models obtained by EOF decomposition, ice sheet quality in the southeastern and northwestern regions of Greenland show different significant changes in different periods from 2003 to 2015, while the other regions showed relatively stable changes; (3) in terms of driving factors temperature, there is an anti-phase relationship between ice sheet mass change and land surface temperature by the mean XWT-based semblance value of −0.34 in a significant oscillation period variation of 12 months. Meanwhile, XWT-based semblance values have the largest relative change in 2005 and 2012, and the smallest relative change in 2009 and 2010, indicating that the influence of land surface temperature on ice sheet mass significantly varies in different years. [ABSTRACT FROM AUTHOR]