A Semi-Empirical Approach to Projecting Future Sea-Level Rise

Potsdam Institute for Climate Impact Research, 14473 Potsdam, Germany.
Science (Impact Factor: 31.48). 02/2007; 315(5810):368-70. DOI: 10.1126/science.1135456
Source: PubMed

ABSTRACT A semi-empirical relation is presented that connects global sea-level rise to global mean surface temperature. It is proposed
that, for time scales relevant to anthropogenic warming, the rate of sea-level rise is roughly proportional to the magnitude
of warming above the temperatures of the pre–Industrial Age. This holds to good approximation for temperature and sea-level
changes during the 20th century, with a proportionality constant of 3.4 millimeters/year per °C. When applied to future warming
scenarios of the Intergovernmental Panel on Climate Change, this relationship results in a projected sea-level rise in 2100
of 0.5 to 1.4 meters above the 1990 level.

    • "The age model of barrier evolution, based on previous sea-level-rise curves during the Holocene, supported by radiocarbon data, highlighted that the whole system evolved over a time period of 1 ka; while the time elapsed from this formation to the drowning of single barriers was estimated to be in the order of magnitude of centuries. Scenarios of short-term evolution of modern barrier–lagoon systems of the adjacent coastal sector, under conditions of accelerated sea-level rise, according to Church et al. (2013) (2013 IPCC report) and Rahmstorf (2007) projections, were elaborated. The study of this ancient analogue suggests that the processes of adaptation of coastal systems to the rising sea level would require times evaluable from centuries to millennia. "
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    • "SLR future projections varied depending on consideration of different factors like green house gas emission scenario lead global warming, sea water expansion, glacier and polar ice melt contribution etc. IPCC (2007) projection of 0.18 to 0.59 m SLR by the end of this century is re-projected to 0.26 to 0.98 m during 2081 -2100 as reported by Church 2013. Considering influence of melting of ice sheet towards SLR, Rahmstorf 2007; Pfeer et al. 2008; Traill et al. 2011 SLR projections was 0.5 to 2.3 m. Greenland and Antarctic ice sheets melting can even increase the SLR by 70 m as reported by Hansen et al. 2005. "
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    ABSTRACT: Remote sensing and GIS approach were utilized for inundation assessment mainly based on accurate digital elevation map (DEM) and land cover (Level II classification) prepared using high spatial resolution (2.5 m) stereo pair CARTOSAT-1 image and LISS III image of respectively. ERDAS-LPS 9.3 software along with Arc Map 10.0 was utilized for generating DEM which was overlaid on land cover for inundation assessment. In terms of area, the total forest land cover (16909.1 hectare) was classified into four major forest classes i.e. littoral mangrove forest (16234 hectare, 96%) > scrub forest (442.3 hectare, 2.6 %) > evergreen non-mangrove forest (215.6 hectare, 1.3 %) > deciduous open forest (17.2 hectare, 0.1 %). The other ecologically fragile land covers like water bodies (unlined canals/drains, perennial lakes/ponds, dry river streams, perennial river streams, wetlands (inland natural and coastal wetlands) and wastelands (open scrubland, dense scrubland and sandy coastal area) occupied 6480 hectare, 2070.1 hectare and 1118.9 hectare respectively. Based on elevation, land cover area were classified into five inundation sensitive zones viz. very high (up to 0.5 m elevation), high (0.5-1.5 m), medium (1.5-2.5 m), low (2.5 – 3.5 m) and very low (> 3.5 m) sensitive zone. For littoral mangrove forest, scrub forest and evergreen non-mangrove forest 10 % (1544.5 hectare), 7 % (36.6 hectare) and 12 % (25.1 hectare) of their total area were in very high sensitive zone. In both the inland and coastal wetland, the maximum area was under high sensitive zone (0.5-1.5 m elevation) i.e. 517.7 hectare and 489.5 hectares respectively. The present work has delineated vulnerable land cover and its findings will help in planning adaptation measures to minimize the risk due to SLR.
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    • ", 2013 ) . Other studies suggest that the AR5 may un - derestimate sea - level rise , with global mean sea level possibly rising 1 m or more above the 1990 mean by 2100 ( Rahmstorf , 2007 ; Vermeer and Rahmstorf , 2009 ) . Using statistical models , Vermeer and Rahmstorf ( 2009 ) project that global mean sea level will in - crease 1 . "
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    ABSTRACT: The response of salinity in the Delaware Estuary to climatic variations is determined using statistical models and long-term (1950-present) records of salinity from the U.S. Geological Survey and the Haskin Shellfish Research Laboratory. The statistical models include non-parametric terms and are robust against autocorrelated and heteroscedastic errors. After using the models to adjust for the influence of streamflow and seasonal effects on salinity, several locations in the estuary show significant upward trends in salinity. Insignificant trends are found at locations that are normally upstream of the salt front. The models indicate a positive correlation between rising sea levels and increasing residual salinity, with salinity rising from 2.5 to 4.4 per meter of sea-level rise. These results are consistent with results from 1D and dynamical models. Wind stress also appears to play some role in driving salinity variations, consistent with its effect on vertical mixing and Ekman transport between the estuary and the ocean. The results suggest that continued sea-level rise in the future will cause salinity to increase regardless of any change in streamflow.
    Estuarine Coastal and Shelf Science 05/2015; 157. DOI:10.1016/j.ecss.2015.01.022 · 2.25 Impact Factor
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