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"The forcing of sea level rise in the Arctic, the North Atlantic and the Mediterranean Sea"

Final Report Summary - FORSEANAM (The forcing of sea level rise in the Arctic, the North Atlantic and the Mediterranean Sea)

Project overview
Sea level (SL) rise is among the most costly and visible effects of climate change. Today 10% of the world’s population lives within 10 m of mean SL (Mcgranahan et al., 2007) and about €1 trillion worth of assets lie within 1 metre of MSL (Stern, 2007). Furthermore, with increased coastal development and as SL rises those numbers are only expected to increase. Adaptation and enhanced protection are required with a view to reducing economic losses and damage from SL change. For adaption policy to be effective, policy makers need to be provided with accurate regional SL change projections. Meeting this challenge is, however, difficult because of the numerous mechanisms exerting their effect on SL over a wide range of temporal and spatial scales. A robust understanding of the key processes controlling regional SL variability is therefore required to develop better projections and thus to contribute to more effective adaptive coastal planning.
The overall objective of this project is to better understand the mechanisms underlying the long-term SL variability in the Arctic, the North Atlantic and the Mediterranean Sea. We pay particular attention to the relationship between the Arctic and Atlantic oceans and how changes in the Atlantic affect SL in the Mediterranean. To address its objectives, the project makes use of multiple data sets, both in situ and satellite based, as well as ocean models.

Work performed and results achieved so far
FORSEANAM has produced high quality results that have significantly improved our scientific understanding of the processes driving the low-frequency SL variability.
We have found that tide gauge records along the European Atlantic coast and in the Mediterranean Sea exhibit significant decadal-scale fluctuations of up to 20 cm over the period 1870-2011. Such fluctuations are very coherent among stations and are part of a large coastal signal extending thousands of kilometers along the coast from latitudes as low as 28ºN up to the coast of Ireland. These fluctuations can be largely explained as a response of the ocean to changes in longshore wind, including the propagation of coastally trapped waves. In the Mediterranean Sea, the mass component dominates the decadal SL variability and is mainly driven by mass exchanges with the Atlantic. These water mass exchanges explain the significant correlation between Mediterranean and Atlantic tide gauge records.
The decadal variability is also considerable along the Norwegian coast and in the coastal zones of the Siberian Seas, with fluctuations of more than 20 cm. We have provided evidence that the decadal-scale fluctuations along the Norwegian coast are part of the large coherent SL signal found along the European Atlantic coast. There is a high coherency between the SL along the Norwegian coast and that in the Barents and Kara seas, suggesting that part of the Norwegian signal propagates further north into these regions of the Arctic Ocean. We have introduced an atmospheric vorticity index that explains much of the inter-annual SL variability in the Laptev, East Siberian, and Chukchi seas (correlations up to 0.81). In the East Siberian Sea, we have identified a SL decline of ~15 cm after 2003, which we relate to a strengthening of the Beaufort Gyre induced by changes in wind stress curl over the Amerasian basin.
FORSEANAM has also investigated how well methods based on empirical orthogonal functions (EOFs) can reconstruct global SL trends and variability and has produced a new global SL reconstruction for the period 1900-2011 from satellite altimetry and tide gauge data. The method without a spatially-uniform EOF (also called EOF0) uses global information, which leads to a better reconstruction of the variability, though with some underestimation. When the EOF0 is added to the basis functions the method reduces to the generalized weighted mean with regularization of altimetry records at tide-gauge locations, and thus it uses no global information. This results in a poor reconstruction of the variability. Although the trend is better captured (biases smaller than ±25%) with the EOF0, using the covariance matrix of monthly time series as the basis for determining the contribution of each tide gauge to the trend is dubious because it erroneously assumes that the interannual variability and the trend are driven by the same mechanisms. A significant fraction of the interannual to decadal variability in the new global SL reconstruction without the EOF0 is consistent with land hydrology changes associated with the El Niño-Southern Oscillation (ENSO).
The extensive knowledge acquired during the project has allowed us to estimate the contribution of internal climate variability to recent SL accelerations at 9 tide gauges from around the world. By removing this contribution we have been able to detect a statistically significant acceleration (0.022 ± 0.015 mm/yr2) in the average SL from the tide gauges between 1952 and 2011, which is due to external forcing. Furthermore, we have found that the acceleration is increasing over time. This acceleration is the result of both anthropogenic and natural external forcing.
Finally, we have investigated the ability of a barotropic model to simulate sea level extremes of meteorological origin in the Mediterranean Sea, including those caused by explosive cyclones. For this purpose, the output of the model is compared to hourly sea level observations from 6 tide gauge records (Valencia, Barcelona, Marseille, Civitavecchia, Trieste, and Antalya). We have found that the model underestimates the positive extremes significantly at all stations, in some cases by up to 65%. The differences between the model and the observations are not constant for extremes of a given height, which limits the applicability of the model for storm surge forecasting because calibration of the model is difficult. Regarding statistical properties, the 50-year return level is reasonably well captured by the model at several stations. However, the number of exceedances of the 99.9th percentile over a period of 25 years is severely underestimated by the model at all stations. We have also found that the skill of the model for predicting the timing and value of the storm surges seems to be higher for the events associated with explosive cyclones at all stations.

Potential impact and use
The scientific and socio-economic impact of the project results is expected to be significant. We have demonstrated that SL along the European coast exhibits considerable decadal-scale fluctuations. Our results clearly indicate that regional variability must be included in impact assessments so that appropriate SL rise adaptation policies and strategies can be implemented. Note that these fluctuations can be as large as 20 cm or more, which is very significant considering that global SL has increased by a similar amount since 1900. Furthermore, climate change might affect modes of natural variability causing, for instance, positive SL fluctuations to be larger and/or more frequent. We have also provided evidence of a basin-scale SL variation in the western Arctic Ocean associated with a recent spin-up of the Beaufort Gyre. Note that if the gyre started to spin down due, for instance, to a wind regime change, much of the freshwater accumulated in the centre of the Gyre might be released to the margins of the gyre and enter the North Atlantic affecting the themohaline circulation and, therefore, the climate in Europe. We have also detected a recent acceleration in SL, which is increasing over time and is largely due to anthropogenic causes. Such acceleration may continue to grow as greenhouse gas concentrations increase. Finally, we have found that the skill of barotropic models to simulate SL extremes in the Mediterranean Sea is lower than what can be inferred from previous studies. Our results provide evidence for a pressing need for further work to improve the predictive capability of the storm surge models.
References
Stern, N. (2007), The Economics of Climate Change: The Stern Review, Cambridge University Press.
Mcgranahan, G., D. Balk, B. Anderson (2007), The rising tide: assessing the risk of climate change and human settlements in low elevation coastal zones, Environment & Urbanization, 19(1), 17-37.