The scale parameter, λλ, was estimated from the GESLA (Global Ext

The scale parameter, λλ, was estimated from the GESLA (Global Extreme Sea-Level Analysis) sea-level database (see Menéndez and Woodworth, 2010) which has been collected through a collaborative activity of the Antarctic Climate & Ecosystems Cooperative Research Centre, Australia, and the National Oceanography Centre Liverpool (NOCL), UK. The data covers a large portion of the world and is sampled at least hourly Natural Product Library supplier (except where there are data gaps). The database was downloaded from NOCL on 26 October 2010 and contains 675 files. However, many of these files are near-duplicates provided by different agencies. Many are also as short as one or two years and are therefore not suitable for the analysis of extremes

(it is generally considered that ARIs of up to about four times the record length may be derived from tide-gauge records (e.g. Pugh, 1996) so that, for example, the estimation of 100-year ARIs requires records of at least 25 years duration). Hunter (2012) PTC124 ic50 performed initial data processing, resulting in 198 tidal records, each of which was at least 30 years long. However, one of these is from Trieste in the Mediterranean, which is poorly

resolved by the ocean components of the AOGCMs (the Mediterranean is omitted altogether from Meehl et al., 2007, Fig. 10.32, which shows the projected spatially varying sea-level change due to change in ocean density and dynamics). The data from Trieste was not therefore used in the present analysis, which is therefore based on 197 global sea-level records. Prior to extreme analysis, the data was ‘binned’, so as to produce files with a minimum sampling interval of one hour, and detrended. Annual maxima were estimated using a declustering algorithm such that any extreme events closer than 3 days were counted as a single event, and any gaps in time were removed from the record. These annual maxima were then Cetuximab fitted to a Gumbel distribution using the ismev   package ( Coles, 2001, p. 48) implemented in the statistical language R   ( R Development Core Team, 2008). This yielded the scale parameter, λλ,

for each of the 197 records. It is assumed that λλ does not change in time. Allowances for future sea-level rise have generally been based on global-average projections, without adjustment for regional variations (which are related to the land-ice fingerprint, GIA, and change in ocean density and dynamics). Fig. 2 shows the vertical allowance for sea-level rise from 1990 to 2100 for the A1FI emission scenario, at each of the 197 tide-gauge locations. The allowance is based on the global-average rise in mean sea level and on the statistics of storm tides observed at each location (Section 4). The uncertainty in the projections of sea-level rise was fitted to a normal distribution. The use of a raised-cosine distribution, which has thinner tails, yields a smaller allowance. Fig. 2 shows effectively the same information as Fig.

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