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"SEA LEVEL"
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Sea level : a history
\"What do we mean when we talk about sea level? How and why did people begin to measure it? With Wilko Graf von Hardenberg as our guide, we follow these questions and more to the muddy littoral spaces of Venice and Amsterdam, the coasts of the Baltic Sea, the Panama and Suez canals, and through the expansion of European colonial empires and the science funding boom of the Cold War. This book is the first history of sea level as a concept and of its theoretical and practical uses. It breaks new ground by offering an innovative outlook on how human societies worldwide have revisited and reinterpreted the relationship between land and sea in modern times. What is more, as a conceptual history of one of the most widely used baselines of environmental change, Sea Level provides a much-needed historical contextualization of anthropogenic sea level rise and its impact on the global coast. By narrating how sea level has morphed from a stable geodetic baseline to a marker of anthropogenic change, von Hardenberg sheds new light on the Anthropocene itself\"-- Provided by publisher.
BOOK
Statistical Downscaling of Seasonal Forecasts of Sea Level Anomalies for U.S. Coasts
Increasing coastal inundation risk in a warming climate will require accurate and reliable seasonal forecasts of sea level anomalies at fine spatial scales. In this study, we explore statistical downscaling of monthly hindcasts from six current seasonal prediction systems to provide a high‐resolution prediction of sea level anomalies along the North American coast, including at several tide gauge stations. This involves applying a seasonally invariant downscaling operator, constructing by linearly regressing high‐resolution (1/12°) ocean reanalysis data against its coarse‐grained (1°) counterpart, to each hindcast ensemble member for the period 1982–2011. The resulting high‐resolution coastal hindcasts have significantly more deterministic skill than the original hindcasts interpolated onto the high‐resolution grid. Most of this improvement occurs during summer and fall, without impacting the seasonality of skill noted in previous studies. Analysis of the downscaling operator reveals that it boosts skill by amplifying the most predictable patterns while damping the less predictable patterns. Plain Language Summary Currently, the large computer models that form the basis of seasonal climate prediction systems produce coastal sea level forecasts spaced about 100 km apart. This is too coarse to meet the needs of U.S. coastal ocean management and services, which are becoming increasingly important as sea levels rise in a warming climate. In this study, we explored a method to provide such information on much smaller spatial scales, which better correspond to local coastal sea level measurements by tide gauges. We developed an efficient way to generate monthly sea level predictions on distances as small as 10 km apart, by applying the observed statistical relationship between sea level variations on scales of 100–1,000 km and finer‐scale coastal ocean observations to the original coarser model predictions. By testing our approach on past forecasts (“hindcasts”) from existing climate forecast systems, we found that we could improve forecasts for different local regions along both the U.S. West and East Coasts. Key Points Sea level prediction from relatively coarse operational forecasts can be enhanced to finer coastal scales using statistical downscaling Downscaling can be determined by multivariate linear regression trained from high‐resolution reanalysis and its coarse‐grained counterpart This downscaling method significantly improves skill compared to bilinearly interpolated hindcasts at several U.S. tide gauge locations
Journal Article
Global Mean Sea Level Rise Inferred From Ocean Salinity and Temperature Changes
Barystatic sea level rise (SLR) caused by the addition of freshwater to the ocean from melting ice can in principle be recorded by a reduction in seawater salinity, but detection of this signal has been hindered by sparse data coverage and the small trends compared to natural variability. Here, we develop an autoregressive machine learning method to estimate salinity changes in the global ocean from 2001 to 2019 that reduces uncertainties in ocean freshening trends by a factor of four compared to previous estimates. We find that the ocean mass rose by 13,000 ± 3,000 Gt from 2001 to 2019, implying a barystatic SLR of 2.0 ± 0.5 mm/yr. Combined with SLR of 1.3 ± 0.1 mm/yr due to ocean thermal expansion, these results suggest that global mean sea level rose by 3.4 ± 0.6 mm/yr from 2001 to 2019. These results provide an important validation of remote‐sensing measurements of ocean mass changes, global SLR, and global ice budgets. Plain Language Summary Global sea level rise (SLR) is caused by heating of the ocean, and by the input of freshwater from the melting of glaciers and ice caps. Global freshwater input to the oceans from melting ice during the 21st century has primarily been tracked by satellites that measure changes in the mass of the ocean. Here, we show that trends in global SLR can also be accurately tracked by global observations of ocean salinity changes, as freshwater runoff from melting ice enters the ocean and dilutes ocean salinity. These results show that ocean salinity measurements are critical for monitoring global sea level changes, particularly as polar warming intensifies and the melting of ice sheets accelerates. Key Points A new full‐depth ocean salinity product yields robust global freshening trend of (35 ± 10) × 10−6 yr−1 from 2001 to 2019 Combined with estimates of sea ice loss, this freshening implies that ocean mass rose by 13,000 ± 3,000 Gt from 2001 to 2019 Sea level rise derived from ocean temperature and salinity measurements is 3.4 ± 0.6 mm/yr, confirming the satellite altimetry trend
Journal Article
The causes of sea-level rise since 1900
The rate of global-mean sea-level rise since 1900 has varied over time, but the contributing factors are still poorly understood
1
. Previous assessments found that the summed contributions of ice-mass loss, terrestrial water storage and thermal expansion of the ocean could not be reconciled with observed changes in global-mean sea level, implying that changes in sea level or some contributions to those changes were poorly constrained
2
,
3
. Recent improvements to observational data, our understanding of the main contributing processes to sea-level change and methods for estimating the individual contributions, mean another attempt at reconciliation is warranted. Here we present a probabilistic framework to reconstruct sea level since 1900 using independent observations and their inherent uncertainties. The sum of the contributions to sea-level change from thermal expansion of the ocean, ice-mass loss and changes in terrestrial water storage is consistent with the trends and multidecadal variability in observed sea level on both global and basin scales, which we reconstruct from tide-gauge records. Ice-mass loss—predominantly from glaciers—has caused twice as much sea-level rise since 1900 as has thermal expansion. Mass loss from glaciers and the Greenland Ice Sheet explains the high rates of global sea-level rise during the 1940s, while a sharp increase in water impoundment by artificial reservoirs is the main cause of the lower-than-average rates during the 1970s. The acceleration in sea-level rise since the 1970s is caused by the combination of thermal expansion of the ocean and increased ice-mass loss from Greenland. Our results reconcile the magnitude of observed global-mean sea-level rise since 1900 with estimates based on the underlying processes, implying that no additional processes are required to explain the observed changes in sea level since 1900.
Observed global-mean sea-level rise since 1900 is reconciled with estimates based on the contributing processes, revealing budget closure within uncertainties and showing ice-mass loss from glaciers as a dominant contributor.
Journal Article
Forcing Factors Affecting Sea Level Changes at the Coast
We review the characteristics of sea level variability at the coast focussing on how it differs from the variability in the nearby deep ocean. Sea level variability occurs on all timescales, with processes at higher frequencies tending to have a larger magnitude at the coast due to resonance and other dynamics. In the case of some processes, such as the tides, the presence of the coast and the shallow waters of the shelves results in the processes being considerably more complex than offshore. However, ‘coastal variability’ should not always be considered as ‘short spatial scale variability’ but can be the result of signals transmitted along the coast from 1000s km away. Fortunately, thanks to tide gauges being necessarily located at the coast, many aspects of coastal sea level variability can be claimed to be better understood than those in the deep ocean. Nevertheless, certain aspects of coastal variability remain under-researched, including how changes in some processes (e.g., wave setup, river runoff) may have contributed to the historical mean sea level records obtained from tide gauges which are now used routinely in large-scale climate research.
Journal Article
A global analysis of subsidence, relative sea-level change and coastal flood exposure
Climate-induced sea-level rise and vertical land movements, including natural and human-induced subsidence in sedimentary coastal lowlands, combine to change relative sea levels around the world’s coasts. Although this affects local rates of sea-level rise, assessments of the coastal impacts of subsidence are lacking on a global scale. Here, we quantify global-mean relative sea-level rise to be 2.6 mm yr−1 over the past two decades. However, as coastal inhabitants are preferentially located in subsiding locations, they experience an average relative sea-level rise up to four times faster at 7.8 to 9.9 mm yr−1. These results indicate that the impacts and adaptation needs are much higher than reported global sea-level rise measurements suggest. In particular, human-induced subsidence in and surrounding coastal cities can be rapidly reduced with appropriate policy for groundwater utilization and drainage. Such policy would offer substantial and rapid benefits to reduce growth of coastal flood exposure due to relative sea-level rise.Land subsidence and uplift influence the rate of sea-level rise. Most coastal populations live in subsiding areas and experience average rates of relative sea-level rise three to four times faster than due to climate change alone, indicating the need for policy to address subsidence.
Journal Article