1 Global and Planetary Change 53 (2006) Sea-level rise at tropical Pacific and Indian Ocean islands John A. Church a,b,, Neil J. White a,b, John R. Hunter b a CSIRO Marine and Atmospheric Research, GPO Box 1538, Hobart, Tasmania, 7001, Australia b Antarctic Climate and Ecosystems Cooperative Research Centre, PB80, Hobart, Tasmania, 7001, Australia Received 20 December 2005; received in revised form 3 April 2006; accepted 11 April 2006 Available online 16 June 2006 Abstract Historical and projected sea-levels for islands in the tropical Pacific and Indian oceans are a subject of considerable interest and some controversy. The large variability (e.g. El Niño) signals and the shortness of many of the individual tide-gauge records contribute to uncertainty of historical rates of sea-level rise. Here, we determine rates of sea-level rise from tide gauges in the region. We also examine sea-level data from the TOPEX/Poseidon satellite altimeter and from a reconstruction of sea level in order to put the sparse (in space and time) tide-gauge data into context. For 1993 to 2001, all the data show large rates of sea-level rise over the western Pacific and eastern Indian Ocean (approaching 30 mm yr 1 ) and sea-level falls in the eastern Pacific and western Indian Ocean (approaching 10 mm yr 1 ). Over the region 40 S to 40 N, 30 E to 120 W, the average rise is about 4 mm yr 1. For 1950 to 2001, the average sea-level rise (relative to land) from the six longest tide-gauge records is 1.4 mm yr 1. After correcting for glacial isostatic adjustment and atmospheric pressure effects, this rate is 2.0 mm yr 1, close to estimates of the global average and regional average rate of rise. The long tide-gauge records in the equatorial Pacific indicate that the variance of monthly averaged sea-level after 1970 is about twice that before We find no evidence for the fall in sea level at the Maldives as postulated by Mörner et al. (2004). Our best estimate of relative sea-level rise at Funafuti, Tuvalu is 2±1 mm yr 1 over the period 1950 to The analysis clearly indicates that sea-level in this region is rising. We expect that the continued and increasing rate of sea-level rise and any resulting increase in the frequency or intensity of extreme sea-level events will cause serious problems for the inhabitants of some of these islands during the 21st century Elsevier B.V. All rights reserved. Keywords: sea-level changes; climate change; Indian Ocean; Pacific Ocean 1. Introduction Corresponding author. CSIRO Marine and Atmospheric Research, GPO Box 1538, Hobart, Tasmania, 7001, Australia. address: (J.A. Church). The islands in the tropical oceans are some of the regions most vulnerable to sea-level rise and the associated impacts of climate change. These impacts include changes in weather patterns (temperature, winds, precipitation etc.), sea-level rise, coastal erosion, changes in the frequency of extreme events including potential increases in the intensity of tropical cyclones/hurricanes, reduced resilience of coastal ecosystems (including bleaching and changed calcification rates of coral reefs) and saltwater intrusion into freshwater resources. Mörner et al. (2004) and Mörner (2004) recently drew attention to the potential vulnerability of the Maldives. However, Mörner et al. (2004) argued that there had been a 30 cm fall in sea-level at the Maldives over the last 50 yrs while Mörner (2004) argued that there had been no global averaged sea-level rise over the decade of the 1990s. Mörner's conclusions /$ - see front matter 2006 Elsevier B.V. All rights reserved. doi: /j.gloplacha
2 156 J.A. Church et al. / Global and Planetary Change 53 (2006) concerning a sea-level fall at the Maldives have been firmly rebutted by Woodworth (2005), Woodroffe (2005) and Kench et al. (2005). The impacts of sea-level rise on Tuvalu have also been a subject of considerable controversy (Eschenbach, 2004a,b; Hunter, 2004). The tropical Pacific and Indian Ocean regions have considerable interannual and decadal sea-level variability associated with the El Niño-Southern Oscillation (ENSO), the Asian Australian monsoon and phenomena like the North Pacific Decadal Oscillation (Trenberth and Hurrell, 1994; Chambers et al., 2002; Han and Webster, 2002; Church et al., 2004). In short tide-gauge records, this variability may obscure any longer-term sea-level change, or the variability may be misinterpreted as a regional change. For example, annual mean sealevel at some locations can change by as much as cm on interannual time scales. The availability of improved data sets over recent decades should allow more effective separation of the short-term variability from the longer-term sea-level rise. Of particular importance is the high quality data from the TOPEX/Poseidon and Jason-1 satellite altimeter missions (January 1993 to present) that allows the basin-wide scales of sea-level variability to be examined. Also important are the sea-level records from high quality tide gauges at a number of islands in the tropical Pacific Ocean. Many of these were installed in the 1970s or early 1980s to study the evolution of ENSO events and were important elements of the Tropical Ocean Global Atmosphere project (World Climate Research Program, 1985; McPhaden et al., 1998). With an increasing focus on sea-level rise in the late 1980s, the quality of individual gauges, and of the network as a whole, has been improved using modern instrumentation with rigorous datum control (most recently using continuous GPS instruments) and the extension of the network to more locations. For many of these sites, there are now more than 20 yrs of data. However, there are only a few Pacific island records extending over the full 52 yrs examined here. Modern statistical techniques have also been developed to combine the best attributes of the in situ and satellite data sets; i.e. the longer in situ records and the broad (essentially global ocean) coverage from satellites. These techniques, modeled on approaches used to estimate global surface temperatures over the last century (e.g. Kaplan et al., 1998, 2000; Rayner et al., 2003), use tidegauge data to estimate the amplitude of empirical orthogonal functions (EOFs) whose spatial structure has been estimated from the satellite altimeter data. Importantly, this technique takes account of the spatial patterns of sea-level variability, rather than regarding variations from the global mean as noise. For example, the anti-phase sea-level movements on either side of the Pacific Ocean are attributed to ENSO, rather than being regarded as unexplained random variations. The technique provides estimates of monthly averaged sea level on a near global (65 S 65 N) 1 1 ocean grid (essentially the ice free regions; Chambers et al., 2002; Church et al., 2004; Church and White, 2006). Given the potential vulnerability of the Maldives, Tuvalu and other island states in the Pacific and Indian oceans, we assemble the sea-level data sets described above to provide the best possible estimates of sea-level rise for the latter half of the 20th century for these islands. We also test the veracity of assertions (Mörner, 2004; Mörner et al., 2004) that no significant sea-level rise is occurring. The data sets and techniques used are described briefly in Section 2. The results (Section 3) indicate large interannual variability of the tropical Pacific and Indian ocean region and clear evidence that global average sea level has been rising both over the last decade and the last half of the 20th century. We find no evidence for the 30 cm fall in sea level in the 1970s to early 1980s for the Maldives as postulated by Mörner et al. (2004). 2. The data sets and methods 2.1. Preliminaries For many studies, tide-gauge and satellite altimeter data are corrected for the inverse barometer (IB) response of the ocean to variations in atmospheric pressure as this gives the most useful product for many oceanographic studies. However, most of the data presented here do not include this correction as we are interested in observed or relative sea level that is, sea level relative to the land at any given site. When we do make the IB correction (Church et al., 2004; Ponte, 2006), we use the atmospheric pressure data from the NCEP NCAR 50 year reanalysis (Kistler et al., 2001) and assume that sea level responds isostatically to local changes in atmospheric pressure relative to the global over-ocean mean. Glacial Isostatic Adjustment (GIA, also known as post-glacial rebound (PGR), Mitrovica et al., 2001) compensates tide-gauge or satellite altimeter data for the changes of ocean basin shape and gravity caused by changes in surface loading with the melting of large ice sheets from the most recent glaciations. Most of the data presented here do not include this correction as we are most interested in relative sea level. We have performed the reconstruction with the GIA included to get the best estimate of the global fields, then removed this correction to give the best data set for comparisons with tide-gauge data and to focus on relative sea-level change.
3 J.A. Church et al. / Global and Planetary Change 53 (2006) Some tide-gauges records are contaminated by vertical land movement due to processes at a range of spatial scales, from large-scale geological processes (in addition to GIA) to local harbour effects as a result of, for example, land reclamation and groundwater pumping. No correction for these effects is possible in general. All data presented here have had a seasonal (annual plus semi-annual) signal removed. Tide-gauge data have also been smoothed over ±2 months. As we are only interested in changes in sea-level at each location, we have matched the means of the data sets over their common periods for display purposes The tide-gauge data set Most of the tide-gauge data used here (apart from the data for Funafuti, Section 3.3) are monthly mean sealevels from the data archive of the Permanent Service for Mean Sea-Level (PSMSL; Woodworth and Player, 2003) for January 1950 through December 2001, a one year extension of the data set used by Church et al. (2004). We do not consider tide-gauge data after 2001 because of delays in submission of data sets to the PSMSL. We use primarily RLR (Revised Local Reference) data, but also some Metric data, downloaded from the PSMSL WWW site (http://www.pol.ac.uk/ psmsl/) in February The RLR data files are supported by documentation relating measured sea level at each site to a constant local datum over the complete record. The Metric records can have substantial and unknown datum shifts and their use in time series analysis is generally not recommended. Where such datum shifts have occurred, we have treated the sections before and after the shift separately, as in Church et al. (2004). All records are carefully screened for datum shifts (both jumps and gradual changes). Differences between reconstructed trends (on the 1 1 grid) produced with and without the Metric data are less than 0.1 mm yr 1 for both the area-weighted mean and standard deviation. Fig. 1 shows the locations referred to in this paper, but the sealevel reconstruction uses data from a global set of island and coastal tide gauges as in Church et al. (2004) The TOPEX/Poseidon satellite altimeter data set To estimate global sea-level rise from 1993 to 2001 and to estimate the global covariance structure of sealevel variability, we use the TOPEX/Poseidon alongtrack data from the Merged Geophysical Data (MGDR- B) records for January 1993 through December 2001 (cycles 11 to 342, 108 months). All standard corrections recommended by Benada (1997), except the inverse barometer correction, were applied. In addition, we applied a correction for a long-term, spatially uniform drift ( 5 mm over the first 5 yrs of the mission, then fixed at 5 mm) in the TOPEX/Poseidon TMR (radiometer)-based water vapour path delay correction (Keihm et al., 2000) and the estimated altimeter drift (by comparison of the altimeter surface heights with tide-gauge data; Mitchum, 1998, 2000). The main consequence of the latter correction is that it compensates for the 10 mm jump in measured sea-level when the TOPEX Fig. 1. Location map. A number of sites (Saipan, Kapingamarangi, Port Vila, Lautoka, Apia, Rarotonga and Penrhyn) are not mentioned in the text, but are shown here as data from their short records are shown on Fig. 2a and b. The RMS variability from smoothed, monthly TOPEX/Poseidon data from January 1993 to December 2001 is indicated by the shading.
4 158 J.A. Church et al. / Global and Planetary Change 53 (2006) side B altimeter replaced the side A altimeter because of age-related problems. The GMSL trend ( ) is 2.7 mm yr 1 (with no IB or GIA included in this figure). As we are interested in large space- and time-scale phenomena, monthly estimates of sea-level on a 1 1 grid were obtained by applying a Gaussian filter, with an e-folding scale of 300 km applied over a square with sides of 800 km, to the along-track data. Satellite altimeters measure sea-level relative to the centre of the Earth, and should also be corrected for GIA (Tamisiea et al., personal communication), but as our TOPEX/ Poseidon data set has been calibrated against tide gauges (see above), this effect has essentially been addressed to within an error of about 0.1 mm yr 1, which is negligible for our purposes The reconstructed global sea-level fields We use monthly sea-level values from a global reconstruction as described in Church et al. (2004),extended by 1 yr to December Briefly, this sea-level reconstruction (from January 1950 to December 2001 and on the same 1 1 grid as the TOPEX/Poseidon data) was generated using tide-gauge data (Woodworth and Player, 2003) to estimate the amplitudes of empirical orthogonal functions (EOFs) determined from the 9 year TOPEX/ Poseidon data set (Chambers et al., 2002; Church et al., 2004). The first 20 EOFs are used in addition to a spatially constant field (dependent on time but independent of location) which represents the global mean sea-level. This latter field (referred to as mode 0 in Church et al., 2004) is needed as the EOFs reflect the temporal/spatial variability of sea-level but cannot adequately represent significant changes in global mean sea level. Using EOFs from a restricted period to estimate sea level over a longer period assumes that the large-scale variability can be estimated adequately using these EOFs. This is discussed in Church et al. (2004), Church and White (2006) and Chambers et al. (2002). The trend in global-mean sea level estimated from this reconstruction is consistent with estimates from tidegauge data (Douglas, 1991, 1997; Holgate and Woodworth, 2004). Reconstructed sea-level time series at tidegauge sites also agree well with the original tide-gauge data, even when the tide-gauge data at a location are withheld from the reconstruction (Church et al., 2004). The main advantage of this data set is that it provides estimates of the regional and global variations of sealevel and time series of estimated sea-level at individual locations over a longer period than is often available from individual tide-gauge records alone Uncertainties The true uncertainty of sea-level trends will be underestimated if the serial correlation of the time series is ignored. In the Indo-Pacific region, the problem is often compounded by substantial interannual excursions in sea level related to ENSO events. We have derived uncertainty estimates in two ways, both techniques yielding similar results. In the first method, the trend was calculated using all the data points in a time series and the resultant uncertainty estimated assuming that the appropriate number of degrees of freedom was given by the record length divided by the integral time scale (Emery and Thompson, 1998, p. 261). The integral time scale was found to be about 3 months. In the second method, the time series was initially averaged into adjacent temporal bins that were sufficiently large for the residual (after trend removal) to be statistically uncorrelated. The uncertainty was then calculated by basing the number of degrees of freedom on the number of bins. The test for correlation was based on the Durbin Watson statistic (Von Storch and Zwiers, 1999, p. 157) or simply on an upper bound (in our case, 0.2) for the value of the lag-1 correlation (Ostrom, 1990, p. 29). Both tests yielded similar results. All uncertainty estimates are expressed as ±1 standard deviation. All area-averaged trends are either for the whole region covered by the TOPEX/Poseidon data (65 S 65 N, all longitudes) or for the region 40 S 40 N, 30 E 120 W (Fig. 1). All such averages are areaweighted means. 3. Results The root-mean-square (rms) variability in sea level for the 9 yrs of satellite data (January 2003 to December 2001, Fig. 1) reaches a maximum of around 100 mm along the equator in the eastern Pacific Ocean (the region of the equatorial cold tongue) and at low latitudes north and south of the equator in the western Pacific. In the Indian Ocean, the variability is a maximum along a band centred at about 10 S (maximum of about 80 mm) and along the eastern Indian Ocean boundary. This variability (see Church et al., 2004) reflects that the Pacific Ocean region is the centre of the strongest interannual variability of the climate system, the coupled atmosphere-ocean ENSO phenomenon, and the largest sea-level variations in the world on time scales of months to years and space scales of several hundred kilometers and longer. During El Niños, sea level is anomalously high (by tens of centimeters) in the eastern tropical Pacific and low in
5 J.A. Church et al. / Global and Planetary Change 53 (2006) the western tropical Pacific. This large interannual variability highlights the difficulty in accurately determining long-term sea-level trends and the need for long, high-quality records, a point that will be evident when we examine the individual tide-gauge records. The sea-level trends in the Pacific and Indian Ocean over the first 9 yrs of the TOPEX/Poseidon mission (Fig. 2a) demonstrate the impact of this interannual variability. The large rates of sea-level rise over the western Pacific and eastern Indian Ocean (approaching 30 mm yr 1 ) and sea-level falls in the eastern Pacific and western Indian Ocean (rates approaching 10 mm yr 1 ) reflect the (weak) El Niño like conditions in the early years of the TOPEX/Poseidon mission and the more La Nina like conditions in The trends over the same period from the reconstruction (Fig. 2b) are similar to those from TOPEX/Poseidon (correlation of 0.87), demonstrating the ability of the reconstruction technique to reproduce the large-scale interannual variability, particularly in the tropical Pacific and Indian Oceans. While there is large-scale spatial structure in the pattern of sea-level rise over the TOPEX/Poseidon period (1993 to 2001), a series of studies (see, for example, Leuliette et al., 2004; Church et al., 2004) have clearly demonstrated a global average sea-level rise over this period of about Fig. 2. Map of sea-level trends for (a) TOPEX/Poseidon data and (b) the reconstruction for 1993 to Tide-gauge trends for the same period are shown where available by the coloured dots.
6 160 J.A. Church et al. / Global and Planetary Change 53 (2006) Fig. 3. Global averaged and Pacific/Indian Ocean averaged sea levels over the period 1993 to The Pacific/Indian Ocean average is for the region shown in Figs. 1, 2 and 6. 3mmyr 1 (Fig. 3). For the region shown in Fig. 1 the trends from both the TOPEX/Poseidon data and from the reconstruction are larger (Fig. 3), about 4 mm yr 1 (4.3 mm yr 1 for TOPEX/Poseidon and 3.6 mm yr 1 for the reconstruction). Tide-gauge trends give the same overall pattern of sealevel change as the TOPEX/Poseidon and reconstructed sea-levels, but it is clear that the small number of tidegauge records alone can not give a clear impression of the overall pattern, and the mean trend over the tide gauges would not necessarily give an accurate representation of the trend over the whole region. For example, for the South Pacific Sea Level and Climate Monitoring Project, the average for the 11 longest records (averaging just under 11 yrs in 2004) is 6.0 mm yr 1 (see page 2 of Mitchell, 2004), substantially larger than the global average value of about 3 mm yr 1 and the regional average of about 4 mm yr 1 from both the satellite data and the reconstruction Pacific Ocean We now consider the tide-gauge data (for continuous, or near continuous, records longer than 24 yrs) along with the reconstructed sea levels and the corresponding TOPEX/Poseidon data (Fig. 4). For those locations located within about 15 of the equator (Guam, Chuuk, Yap, Pohnpei, Malakal, Kwajalein, Majuro, Funafuti, Honiara, Pago Pago, Kanton Island and Christmas Island), sea level has large interannual variability (peak-to-peak amplitudes as large as 45 cm) associated with ENSO events (Fig. 4, left-hand side). As a result, estimates of relative sea-level rise (Table 1, column 5)have large uncertainties. Even for the longest records considered here (52 yrs), the uncertainties are 0.3 mm yr 1 or greater. As the record length gets shorter these uncertainties increase significantly and are several mm yr 1 for a number of the shorter records (less than 24 yrs, not included in Table 1). The few tide-gauge records that commence in the 1950s or earlier (Guam, Chuuk, Kwajalein, Kanton Island and Christmas Island) indicate that interannual variability in sea level prior to 1970 is smaller (e.g. less than 50% at Guam, Kanton Island and Pago Pago) than that of the post 1970 data. This difference in variability is similar to that displayed by the SOI index (Torrence and Webster, 1999). For those locations strongly affected by ENSO events, the reconstructions reproduce much of the observed variability. The average correlation between the reconstructed and observed sea levels is 0.88 and the residual variance is 23.4% of the observed variance. For the higher latitude gauges (Wake Island, Noumea, Suva, Midway Island, Johnston Island, French Frigate Shoals, Nawiliwili Bay, Honolulu, Kahului Harbour, Papeete and Rikitea; Fig. 4, right-hand side), the variability is of reduced amplitude but higher frequency, compared with stations nearer the equator. At least part of this variability is thought to be a result of westward propagating Rossby waves (Fu and Chelton, 2001). Firing et al. (2004) have also discussed the role of largescale wind variability in forcing sea-level perturbations at Honolulu. These Rossby waves will be largely eliminated from the satellite altimeter data used here by the spatial filtering and will not be well represented in the
7 J.A. Church et al. / Global and Planetary Change 53 (2006) Fig. 4. Time series of tide-gauge (blue), TOPEX/Poseidon (green) and reconstructed sea level (red) for Pacific Ocean sites with more than 24 yrs of tide-gauge data. The light blue lines on panel (j) show the time spans of the two separate records for this site.
8 162 J.A. Church et al. / Global and Planetary Change 53 (2006) Table 1 Locations, time spans and sea-level trends for Pacific Ocean locations with more than 24 yrs of data Location Position Time span Years Tide-gauge trend Relative recons trend (tide-gauge time span) Tide-gauge trend with GIA and IB Malakal E 7 20 N 06/ / ± Yap E 9 31 N 04/ / ± Guam E N 01/ / ± Chuuk Moen Is E 7 27 N 11/ / ± Pohnpei E 6 59 N 04/ / ± Honiara E 9 26 S 12/ / ± Kwajalein E 8 44 N 01/ / ± Majuro E 7 06 N 10/ / ± Funafuti E 8 32 S 11/ / ± Kanton Is W 2 48 S 01/ / ± Kanton Is W 2 49 S 05/ / ± Pago Pago W S 01/ / ± Christmas Is W 1 59 N 02/ / ± Wake Is E N 06/ / ± Noumea E S 03/ / ± Suva E S 05/ / ± Midway Is W N 01/ / ± Johnston Is W N 06/ / ± French Frigate Shoals W N 07/ / ± Nawiliwili Bay W N 01/ / ± Honolulu W N 01/ / ± Kahului Harbor W N 01/ / ± Papeete W S 07/ / ± Rikitea W S 10/ / ± Relative recons trend (52 yrs) EOFs used in the reconstruction. As a result, the reconstructed sea-levels do not reproduce much of this high frequency variability but they do reproduce some of the major features and the long-term trends. The records for Suva and French Frigate Shoals have gaps in the sealevel data and the character of the record is somewhat different from nearby locations, calling into question the datum stability of these two gauges. The significant interannual variability indicates the need for long records to reliably estimate the rate of sealevel rise from individual sites. For example, even for the 52 year long record from Kwajalein, the uncertainty in the relative sea-level trend is as large as ±0.3 mm yr 1. The stated uncertainties (Table 1) are from the variability in the sea-level records only. For the few Pacific Island records greater than 50 years length (6 locations in Table 1), the average rate of relative sea-level rise is 1.4 mm yr 1. The corresponding average rate for relative sea-level rise from the reconstructions of 1.6 mm yr 1 is not significantly different. After GIA and inverse barometer corrections, the mean (absolute) tidegauge trend is 2.0 mm yr 1, consistent with the global average rate of sea-level rise. For the Pacific Ocean, there are 23 locations with 24 or more years of data (Table 1). Excluding the two locations with apparent problems in the record (French Frigate Shoals and Suva, both of which have jumps and trends that are anomalous compared with nearby locations, see above) and Funafuti (contaminated by vertical land movement, see Section 3.3), and using the longer Kanton Island record, the average rate of relative sea-level rise for the remaining 20 locations is 1.0 mm yr 1 for the tide-gauge data and 1.3 mm yr 1 for the reconstructions (for the same period). However, the observations contain a larger range of rates of relative sea-level change, presumably as a result of poorly quantified vertical movements (see Section 3.3 for an example), the large interannual sea-level variability and the fact that the reconstruction does not reproduce some of the smaller-scale variability. After making the GIA and inverse barometer corrections, the corresponding rates of (absolute) sea-level rise are 1.5 mm yr 1 for the observations and 1.6 mm yr 1 for the reconstructions, again consistent with global average rates of sea-level rise Indian Ocean There are far fewer island tide gauges in the Indian Ocean than the Pacific Ocean (only seven open-ocean island sites north of 40 S; Fig. 5) and the records are much shorter. There is significant interannual variability in sea-level in the southern Indian Ocean (the maximum is at about 10 to 20 S) but there is low variability near
9 J.A. Church et al. / Global and Planetary Change 53 (2006) Fig. 5. Time series of tide-gauge (blue), TOPEX/Poseidon (green) and reconstructed sea level (red) for Indian Ocean sites. The light blue lines on panel (b) show the time spans of the two separate records for this site. the Maldives. The two longest Indian Ocean records (starting in 1986) are from Port Louis (20 9 S, E; 1953 to 1964 and a separate record from 1986 to 2000) and 600 km to the east at Rodrigues Island (19 40 S, E; 1986 to 2000). The data from the two sites have similar variability (correlation 0.72, significant at the 99% level) with Rodrigues Island leading by 2 months, presumably as a result of westward propagation and/or advection of sea-level anomalies. The observed variability from TOPEX/Poseidon and tide-gauge data for both sites is similar, both having greater variance than the reconstructed sea levels. The greater variability of the tide-gauge records is likely a result of both mesoscale variability and Rossby wave influence and the fact that the reconstruction technique only captures large-scale signals. Despite these differences, the tide-gauge and reconstructed trends have some similarities over the common periods. Both these records show relative sealevel falling at rates of about 3±2 mm yr 1 from 1986 to The satellite altimeter data starting in 1993 also shows sea-level falling in this region. An earlier 12 year record for Port Louis (1953 to 1964) indicates a sea-level rise of about 2 mm yr 1, and these results together demonstrate again that short decadal changes may not be representative of long-term trends. Similarly the record from Cocos Island (1993 to 2000) is too short to give a reliable long-term trend. Here the large variability is well reproduced in the reconstruction and the estimated trend from the observations is large at 12±5 mm yr 1. Our error estimate is likely to be substantially underestimated because the record is so short that it is not possible to reliably estimate an integral time scale. The reconstructed sea levels over the longer 1950 to 2001 period give rates of relative sea-level rise of 1.5, 1.3 and 1.5 mm yr 1 (with error estimates of about 0.5 mm yr 1 )atport Louis, Rodrigues and Cocos Islands respectively. In the equatorial band, the three locations in the Maldives (Gan, 0 41 S; Male, 4 11 N; Hanimaadhoo, 6 46 N) each have short records, only starting in The variability of these three records (remembering that all records have had the seasonal signal removed and have then been smoothed) is smaller than at Port Louis and the three records are strongly correlated with each other (correlations of 0.53, 0.73 and 0.67 between the three pairs, all significant at the 99% level) and with the reconstruction (correlations of 0.85, 0.64 and 0.82). As found by Singh et al. (2001), we find that the rates of sea-level rise are large in these very short records (8.4 mm yr 1, 3.7 mm yr 1,and 4.4 mm yr 1, respectively). (Note however that this result is in contrast to Mörner et al. (2004) who state, but do not justify, that the records reveal a total absence of any secular trend.) We do not expect the rates from these short records to be representative of longer-term trends. Our error estimates of less than 2 mm yr 1 (Table 2) are likely to be substantially underestimated because the record is so short that it is not possible to reliably estimate an integral time scale. Also, these gauges may be significantly affected by vertical land motion. The rates over the