Editing IPCC:AR6/WGI/Chapter-9 (section)

==== 9.6.4.1 Past Changes ====

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The AR5 ( [[#Church--2013b|Church et al., 2013b]] ) concluded that changes in extreme still water levels (ESWL), combining RSL, tide and surge as observed by tide gauges (Box 9.1) are ''very likely'' to be caused by observed increases in RSL, but noted ''low confidence'' in region-specific results owing to the limited number of studies considering localized contributions from storm surge, tide or wave effects. Influences from dominant modes of climate variability, particularly ENSO and NAO (Annex IV), were also noted. Climate modes affect sea level extremes in many regions, as a result of both sea level anomalies (Sections 9.2.4.2 and 9.6.1.3) and changes in storminess ( [[IPCC:Wg1:Chapter:Chapter-11#11.7|Section 11.7]] ). The SROCC ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ) concluded with ''high confidence'' that inclusion of local processes (wave effects, storm surges, tides plus other regional morphology changes due to erosion, sedimentation and compaction) is essential for estimation of changes in ESL events.

As in AR5 and SROCC, tide gauge observations show that RSL rise ( [[#9.6.1.3|Section 9.6.1.3]] ) is the primary driver of changes in ESWL at most locations and, across tide gauges, has led to a median 165% increase in high-tide flooding over 1995–2014 relative to those over 1960–1980 ( ''high confidence'' ) (Figure 9.31). Some locations exhibit substantial differences between long-term RSL trends and ESWL ( ''high confidence'' ), particularly given decadal to multi-decadal variations of other ESWL contributors ( [[#Rashid--2020|Rashid and Wahl, 2020]] ). Since SROCC, RSL rise has been shown to be the dominant contributor to ESWL rise at most gauge sites along the Chinese coast, but, at some locations, the surge contribution dominates ( [[#Feng--2019|Feng et al., 2019]] ). Trends in the difference between ESWL and mean RSL rise can result from changes (either positive or negative) in the surge or tidal components, and can include non-linear interactions between tide, surge, and RSL ( [[#Arns--2015|Arns et al., 2015]] ; [[#Schindelegger--2018|Schindelegger et al., 2018]] ). The positive phase of the 18.6-year nodal cycle of the astronomical tide is a further consideration, contributing to an increased flood hazard relative to the long-term average ( [[#Talke--2018|Talke et al., 2018]] ; [[#Peng--2019|Peng et al., 2019]] ; [[#Baranes--2020|Baranes et al., 2020]] ). Failing to consider the non-linear interactions between tide, surge and RSL may overestimate trends in ESWL ( ''low confidence'' ) ( [[#Arns--2020|Arns et al., 2020]] ). In some regions, changes in ESWL depend more on changes in surge or tide than on sea level trends.

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[[File:e84cc9a989047b79ec2dccfeaf4651e6 IPCC_AR6_WGI_Figure_9_31.png]]

'''Figure 9.31''' '''|''' '''Historical occurrences of minor extreme still water levels.''' Defined as the 99th percentile of daily observed water levels over 1995–2014. '''(a)''' Percent change in occurrences over 1995–2014 relative to those over 1960–1980. '''(b–g)''' Annual mean sea level (blue) and annual occurrences of extreme still water levels over the 1995–2014 99th percentile daily maximum (yellow) at six selected tide gauge locations. Further details on data sources and processing are available in the chapter data table (Table 9.SM.9).

Ongoing development of the Global Extreme Sea Level Analysis (GESLA) tide gauge database ( [[#Woodworth--2016|Woodworth et al., 2016]] ) along with data archaeology ( [[#Talke--2013|Talke and Jay, 2013]] ) extends availability of tide gauge records back to the mid 19th century (or earlier). Dynamical datasets used to assess trends in ESL at global or regional scales – for example, tide and surge contributions from the Global Tide and Surge Reanalysis (GTSR; [[#Muis--2016|Muis et al., 2016]] , 2020), or wave setup/swash contributions from available wave hindcasts/reanalyses ( [[#Melet--2018|Melet et al., 2018]] ) – have model biases introduced with resolution and parametrization limitations, incomplete atmospheric data, and currently span only a few decades, so they are not yet long or accurate enough to assess long-term trends in ESLs. Therefore, there is ''medium confidence'' in observed trends in ESWL, but only ''low confidence'' in modelled ESL trends.

The AR5 indicated that the amplitude and phase of major tidal constituents have exhibited long-term change, but that their effects on ESL were not well understood. The SROCC ( [[#Bindoff--2019|Bindoff et al., 2019]] ) reported changes in tides (amplification and dampening) at some locations to be of comparable importance to changes in mean sea level for explaining changes in high water levels, with the sign of change being dependent on stability of shoreline position. RSL rise causes water depth-based alterations to the resonant characteristics of the basin, changes the bottom friction and increases the wave speed ( [[#Pickering--2012|Pickering et al., 2012]] ) and remains the primary hypothesis for observed tidal changes. Other contributing processes include strong localized anthropogenic drivers (e.g., port development, dredging, flood defences, land reclamation), changes in stratification associated with ocean warming ( [[#9.2.1.3|Section 9.2.1.3]] ), and changes in seabed roughness associated with ecological change (e.g., [[#Haigh--2019|Haigh et al., 2019]] ). Tide gauge data show that, although principal tidal components have varied in amplitude on the order of 2% to 10% per century ( [[#Jay--2009|Jay, 2009]] ; [[#Ray--2009|Ray, 2009]] ), identifying direct causality remains challenging ( [[#Haigh--2019|Haigh et al., 2019]] ). Combined, observations and models indicate RSL rise and direct anthropogenic factors are the primary drivers of observed tidal changes at tide gauge stations ( ''medium confidence'' ).

The SROCC ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ) reported variations in storm surge not related to changes in RSL, and concluded with ''high confidence'' that consideration of localized storm surge processes was essential to monitor trends in ESL. SL events driven by storm surge are a response to tropical and extratropical cyclones. While historical trends in extra-tropical cyclones are less clear ( [[IPCC:Wg1:Chapter:Chapter-11#11.7.2.1|Section 11.7.2.1]] ), there is mounting evidence for an increasing proportion of stronger tropical cyclones globally, with an associated poleward migration ( [[IPCC:Wg1:Chapter:Chapter-11#11.7.1.2|Section 11.7.1.2]] ). These changes are captured in the ESL record, for example, via increasing intensity and poleward shift in the location of typhoon-driven storm surges reported across 64 years (1950–2013) in the western North Pacific ( [[#Oey--2016|Oey and Chou, 2016]] ). Along the east coast of the USA, there has been an increase in frequency of ESL events due to tropical cyclone changes since 1923 that can be statistically linked to changes in global average temperature ( [[#Grinsted--2013|Grinsted et al., 2013]] ), and the signal is projected to emerge around 2030 ( [[#Lee--2017|Lee et al., 2017]] ). At century and longer time scales, geological proxies such as overwash deposits in coastal lagoons or sinkholes can be used to reconstruct past changes in storm activity (e.g., [[#Brandon--2013|Brandon et al., 2013]] ; [[#Lin--2014|Lin et al., 2014]] ) and put recent events into historical perspective (e.g., [[#Brandon--2015|Brandon et al., 2015]] ). However, there is ''low confidence'' in the current ability to quantitatively compare geological proxies with gauge data. Historical storm surge activity is being increasingly assessed with use of hydrodynamic model simulations and data-driven global reconstructions to supplement tide gauge observations to investigate historical changes at centennial to millennial time scales (e.g., [[#Ji--2020|Ji et al., 2020]] ; [[#Muis--2020|Muis et al., 2020]] ; [[#Tadesse--2020|Tadesse et al., 2020]] ). Large regional variations and limited observational data lead to ''low confidence'' in observed trends in the surge contribution to increasing ESL.

Waves contribute to ESL via wave setup, infra-gravity waves and swash processes ( [[#Dodet--2019|Dodet et al., 2019]] ), with Extreme Total Water Level (ETWL; Box 9.1) used to represent ESWL with addition of wave setup, and Extreme Coastal Water Level (ECWL; Box 9.1) also including contributions from swash. The SROCC ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ) reported the dependency of these processes on nearshore geomorphology and deep-water wave climate, and thus sensitivity to internal climate variability and climate change. Few long-term deployments of in situ measurements in the very dynamic surf zone means that long-term records of ETWL or ECWL are limited to a few sites; tidal gauges are typically located in sheltered locations (e.g., harbours) where wave contributions are absent ( [[#Lambert--2020|Lambert et al., 2020]] ). Consequently, trends in wave contributions to ESL are typically derived from trends in wave conditions observed offshore. On the basis of satellite altimeter observations, SROCC reported increasing extreme wave heights in the Southern and North Atlantic oceans of around 1.0 and 0.8 cm yr <sup>–1</sup> , respectively, over the period 1985–2018 ( ''medium confidence'' ). The SROCC ( [[#Collins--2019|Collins et al., 2019]] ) also identified sea ice loss in the Arctic as leading to increased wave heights over the period 1992–2014 ( ''medium confidence'' ). Since SROCC, the satellite wave record has been shown to be sensitive to alternate processing techniques, leading to important differences in reported trends ( [[#Timmermans--2020|Timmermans et al., 2020]] ). The most common observation platforms for surface waves over the past 30 years are in situ buoys. However, evolving biases associated with changing instrument type, configuration and sampling methodology introduce artificial trends (e.g., [[#Gemmrich--2011|Gemmrich et al., 2011]] ; [[#Timmermans--2020|Timmermans et al., 2020]] ). Accurate metadata is required to address these issues, and, while available locally, are only beginning to be globally coordinated ( [[#Centurioni--2019|Centurioni et al., 2019]] ). Wave reanalysis and hindcast products have also been used to investigate total water level at global scale ( [[#Melet--2018|Melet et al., 2018]] ; [[#Reguero--2019|Reguero et al., 2019]] ). Their applicability for trend analysis is limited by inhomogeneous data for assimilation ( [[#Stopa--2019|Stopa et al., 2019]] ), but they inform relationships between seasonal, interannual to inter-decadal variability of climate indices and wind-wave characteristics (A.G. [[#Marshall--2015|]] [[#Marshall--2015|Marshall et al., 2015]] , 2018; [[#Kumar--2016|Kumar et al., 2016]] ; [[#Stopa--2016|Stopa et al., 2016]] ). To summarize, satellite era trends in wave heights of order 0.5 cm yr <sup>–1</sup> have been reported, most pronounced in the Southern Ocean. However, sensitivity of processing techniques, inadequate spatial distribution of observations, and homogeneity issues in available records limit confidence in reported trends ( ''medium confidence'' ).

Only a few studies have attempted to quantify the role of anthropogenic climate change in ESL events (e.g., [[#Mori--2014|Mori et al., 2014]] ; Takayabu et al., 2015; [[#Turki--2019|Turki et al., 2019]] ). Detection and attribution of the human influence on climatic changes in surges, and waves remains a challenge ( [[#Ceres--2017|Ceres et al., 2017]] ), with ''limited evidence'' to suggest in some instances – for example, poleward migration of tropical cyclones in the Western North Pacific ( [[IPCC:Wg1:Chapter:Chapter-11#11.7.1.2|Section 11.7.1.2]] ), changes in surges and waves can be attributed to anthropogenic climate change ( ''low confidence'' ). With RSL change being considered the primary driver of observed tidal changes, there is ''medium confidence'' that these changes can be attributed to human influence. The close relationship between local ESL and long-term RSL change, combined with the robust attribution of GMSL change ( [[#9.6.1.4|Section 9.6.1.4]] ), implies that observed global changes in ESL can be attributed, at least in part, to human-caused climate change ( ''medium confidence'' ), but reconciling regional variation in these changes is not yet possible ( [[#9.6.1.4|Section 9.6.1.4]] ).

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