Inter-annual and decadal sea level variations in the north-western Pacific marginal seas

Progress in Oceanography 105 (2012) 4–21

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Inter-annual and decadal sea level variations in the north-western Pacific marginal seas Marta Marcos a,⇑, Michael N. Tsimplis b, Francesc M. Calafat c a

IMEDEA (UIB-CSIC), Miquel Marques, 21, 07190, Balearic Islands, Spain National Oceanography Centre Southampton, SO14 3ZH, United Kingdom c College of Marine Science, University of South Florida, St. Petersburg, United States b

a r t i c l e

i n f o

Article history: Available online 23 April 2012

a b s t r a c t Long term sea level changes in the Okhotsk, Japan/East, East China and Yellow Seas have been explored based on mean monthly values of sea level from tide gauge and altimetry measurements. The analysis of low frequency sea level variability reveals clearly differentiated areas: the Okhotsk Sea and the northern sector of the Japan/East Sea display lower sea level variances and no sea level rise. The southern Japan/ East Sea presents larger sea level variability associated with the circulation regime of the warm current entering through the Tsushima Strait and inter-annual sea level variations that are driven by steric and atmospheric changes. The largest sea level variances are found in the Yellow Sea due to the effect of atmospheric forcing over the continental shelf. Inter-annual variability is spatially varying within the Yellow Sea and the East China Sea and is mainly related to the steric sea level changes. Regional mean sea level indices have been synthesized for each area using the longest tide gauge records and have revealed correlations between the southern Japan/East and Yellow Seas with PDO and NP climatic indices. Linear trends at coastal sites in the Japan/East, East China and Yellow Seas show a rather heterogeneous pattern, with values between 1.5 and 5.5 mm/yr for the period 1960–2000. During the period 1993–2008 linear trends derived from coastal tide gauges and from altimetry observations are coherent and reveal a southwards increasing pattern with maximum averaged values reached at the Yellow Sea (4.9 ± 1.9 mm/yr) followed by the Japan/East Sea (3.8 ± 0.9 mm/yr). Decadal rates of sea level change show distinct behaviour among basins as well as with the global average. The southern Japan/East Sea, the East China Sea and the Yellow Sea display decadal variability which is out of phase with respect to the global values. Ó 2012 Elsevier Ltd. All rights reserved.

1. Introduction Global mean sea level has been accepted as increasing by 1–2 mm/yr during the 20th century (Church et al., 2004). Such estimates have been based on a relatively small subset of the globally available tide-gauges. A large part of the tide-gauge information available globally is considered as unusable in the context of global sea level rise either due to strong local land movements or due to lack of information regarding the reference stations or due to particularities in their location. However, since the launch of satellite altimetry in 1992 it has become evident that there are highly heterogeneous spatial patterns of sea level variability, with areas experiencing enhanced sea level rise and others sea level drops. Climate models also suggest spatially inhomogeneous distribution of sea level rise with respect to thermosteric changes. The increase of oceanic water mass through melting of ice sheets and glaciers is also expected to have spatially differentiated effects due to changes in land movements and the ocean dynamic response. ⇑ Corresponding author. E-mail address: [email protected] (M. Marcos). 0079-6611/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.pocean.2012.04.010

In order to assess how vulnerable is a particular region to climate change induced sea level rise it is necessary to understand how climate change will affect the processes that determine sea level at the coast in a particular location. In this respect semi-enclosed seas pose particular problems as the changes may be due to external as well as internal to the basin factors. In addition, the exchange with the open ocean can be subject to physical restrictions and possibly to hydraulic control of the exchange, which may also be a factor controlling future sea level changes. In this paper we concentrate on sea level changes in three adjacent marginal seas, namely the Okhotsk Sea, the Japan/East Sea and the area covering the Yellow Sea and the East China Sea (see Fig. 1). These marginal seas connect the Asian continent with the open ocean. Although these seas are connected to each other they display very different oceanographic features, partly due to their location and bathymetry. The Okhotsk Sea is located to the east of Russia and north of Japan, at latitude between 45° and 65°N and is connected with the open ocean by the Kuril Islands chain. It has a broad and shallow shelf (less than 200 m deep) deepening down to 3000 m at the southernmost part. During the winter season a substantial part is covered by ice. The Japan/East Sea (JES) is

M. Marcos et al. / Progress in Oceanography 105 (2012) 4–21

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Fig. 1. Map of the area and location of tide gauge stations. Stations are numbered as in Table 1. Circles are stations for which benchmark history is available (RLR) and triangles identify Metric stations, that is, stations for which benchmark history is not available.

located south of the Okhotsk Sea and connected to it through the Tartarsky and the Soya Straits. These straits are 10 km and 40 km wide respectively and less than 50 m deep, thus significantly constraining the exchange of water between the two seas. The JES is a deep basin with an average depth of 1700 m, reaching down to 4000 m and with a narrow shelf. Its circulation features includes cyclonic and anticyclonic gyres, a western boundary current, deep convection and thermohaline circulation. It is connected to the open Pacific Ocean to the east through the Tsugaru Strait and with the East China Sea (ECS) to the south through the Korea/Tsushima Strait. The Tsushima Strait is the deepest of all the straits in the JES with depths between 100 and 200 m. The flow through this strait has a major impact on the circulation and hydrographic features of the JES (Lyu et al., 2002; Lyu and Kim, 2005). The ECS is under the influence of the Kuroshio Current, entering from the eastern

coast of Taiwan and flowing along the continental shelf margin. The Yellow Sea, located to the south of the JES, is a shallow semienclosed basin with an average depth of 45 m, subjected to large tidal oscillations of up to 4 m and strong wind effects. The observational network in terms of availability of tide gauges in the area is well developed. Tide gauges register sea level changes relative to land, thus including vertical crustal motions associated with both long term processes such as Glacial Isostatic Adjustment (GIA) and rapid changes due to earthquakes. The regions under consideration are prone to tectonic activity and earthquakes inducing strong, as well as abrupt, land movements likely to affect the long term sea level measurements and contribute to the coastal vulnerability of the region to sea level rise. Many studies on sea level variability in the region have focused on high frequency sea level changes. Nam et al. (2004) explored high

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frequency sea level oscillations in the JES using an analytical model for basin resonance, demonstrating the non-isostatic response of sea level to atmospheric pressure at these frequencies. Lyu and Kim (2005) reached the same conclusion using a barotropic model to infer transport variations through the Tsushima Strait. They also pointed out that for longer periods the mean sea level in the JES responds isostatically to atmospheric pressure and it is controlled by changes in sea level outside the basin. The response of the JES to the atmospheric pressure has been addressed by Park and Watts (2005) and Inazu et al. (2006). Xu et al. (2007) investigated the basin oscillations in the JES from tide gauge and bottom pressure data, which have a fundamental mode of 6.7 h and amplitudes up to 3 cm. Mesoscale sea level signals in the JES were addressed by Hirose et al. (2005) using altimetry data assimilated in a numerical model. The response of sea level to the atmospheric pressure in a semienclosed basin may be constraint by the geostrophic control of the flow through the straits. In essence, the sea level gradient across the strait limits the difference in sea level between the two basins (Garrett, 1983). The time scales of sea level variability affected by strait restrictions have been estimated following Lascaratos and Gacˇic´ (1990):

T¼

Af gH

where A is the area of the basin, H is the depth of the strait, f is the Coriolis parameter and g is the gravity acceleration. The JES is connected with the Pacific Ocean trough various narrow and shallow straits. For the JES the area is 9.78  1011 m2 and the minimum depth of the straits connecting with the open ocean is around 100 m. Thus, geostrophic control is expected for travelling signals shorter than 28 h, much smaller than the periods considered here. Therefore at monthly and larger time scales the basin is expected to have an isostatic response to atmospheric pressure and the use of inverse barometer (IB) is justified as confirmed by the modelling work of Lyu and Kim (2005). Various studies of low frequency sea level change have been published for the area. Choi et al. (2004) find sea level rise in the JES for the period 1992–2002 at a rate of 5.8 mm/yr. They found that the first mode of oscillation of the basin explains about 38% of the variability and corresponds to volume changes. This mode is dominated by variations at monthly scales. Interannual variability dominates the second mode which explains 8% of the variance. The intraseasonal variability was also identified at seven tide gauges employed in this analysis which have highly coherent behaviour. Thus at these time scales sea level in the JES behaves coherently with no delay between the stations studied (Choi et al., 2004). The second mode of variations was found to depend on the path followed by the Tsushima Warm Current (TWC) (Choi et al., 2004). Choi et al. (2004) suggest that sea level change in the western Pacific Ocean and changes in the monsoonal wind may be the forcing parameters for sea level variability at these scales. Kim and Fukumori (2008) find sea level variability at the JES to be uniform between 20 days and 1 year. The changes based on a numerical model were found to be barotropic in nature and are stated to be the balance of near strait winds, friction and geostrophic control. The tectonically active nature of the coast creates values of land rise near Lianyungang (see Table 1 and Fig. 1 for location) of around 5.4 mm/yr. Cui and Zorita (1998) have studied sea level variability at the Chinese coasts in the Yellow Sea. They identify two weather patterns linked with sea level variability. The first is atmospheric pressure anomalies associated with the alongshore geostrophic wind. The second is a North–South pressure difference. In relation to the summer season Cui and Zorita (1998) find a pattern of pressure differences between the Yellow Sea and the JES as best correlated with the Yellow Sea sea level records.

Sea level trends from coastal tide gauges have been studied for this region by Emery and Aubrey (1986). Ren (1993) warns that at least one of the longest records, Tanggu, has been routinely corrected for land movements since 1959, thus casting significant doubts on earlier studies. Ren (1993) reports that the correction for the period 1959–1985 was 129 cm or 47.8 mm/yr. He concludes that although the record shows a trend of 1.2 mm/yr for the period 1959–1985 the actual trend is 24–48 mm/yr. Kang et al. (2005), on the basis of TOPEX/Poseidon data, identifies trends of 5.4 mm/yr from 9 years of data at the JES, 6.4 mm/yr for the southern JES. They attribute these primarily to be due to the thermosteric expansion at the top 300 m layer, which they estimate from hydrographic observations to be 5.7 ± 2.4 mm/yr. Kang et al. (2005) also compare with 13 tide gauges and they find a sea level trend of 2.9 mm/yr for 1976–2001 and a trend of 6.6 mm/yr for the 1993–2001. Remarkably the error bar from the tide gauges is 3.3 mm/yr while from the T/P is 0.4 mm/yr (Kang et al., 2005). In this paper we provide an overview of the low frequency sea level variability in three of the NW Pacific marginal seas, namely the Okhotsk Sea, the JES and the Yellow and East China Seas, using tide gauge and altimetry observations (Fig. 1). The questions we address are, first, whether on the basis of the available sea level measurements in these areas sea level rise is occurring and how fast it is in relation to the global average. Second we look at decadal accelerations and their consistency when compared with the global ocean. The open ocean in the proximity of the three marginal seas has been reported to have experienced trends of up to 20 mm/yr around the Kuroshio Current, east of Japan, for the period 1993–2003, most of which is attributed to thermal expansion (Church et al., 2008). It remains of course an open question whether for the purpose of coastal protection such trends linked with intensification of currents is at all relevant. Intuitively one would expect that such large trends should have some effect on the connected marginal seas. The paper is organized as follows: in Section 2 we describe the data sets used in this study and their inter-annual variability. In Section 3 we present sea level trends for different periods computed from tide gauge records and from altimetry. In Section 4, inter-decadal variability is explored for each marginal sea and compared with the global values. In Section 5 we develop sea level indices, as averaged regional mean sea level changes, representative of sea level oscillations in different areas and compute the associated EOFs. The causes of sea level variability are discussed in Section 6 and finally a summary and some conclusions are outlined in Section 7.

2. Data 2.1. Tide gauge data Monthly sea level records at coastal stations have been obtained from the Permanent Service for Mean Sea Level (PSMSL) (Woodworth and Player, 2003). Most of these stations (a total of 69) are accompanied with benchmark datum history (Revised Local Reference, RLR, stations). However, for the northern JES the existing information is contained in Metric data, meaning that no benchmark history is available for these stations. We utilised the available Metric time series for this area. Nine records longer than 20 years have been used. A careful intercomparison among metric records has been performed in order to detect jumps or drifts in the time series. GIA values for RLR stations are obtained for the ICE-5G(VM2) model (Peltier, 2004), delivered through the PSMSL data base and are listed in Table 1. The location of all the tide gauges is shown in Fig. 1. Stations demonstrating datum shifts have been excluded from the analysis.

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Table 1 Name and location of tide gauge stations, period of operation, number of years covered, percentage of data gaps and yearly variance. Trends for the entire period and GIA values from ICE-5G(VM2) model. Some stations are flagged with numbers: (1) record corrected according to reports in PSMSL; (2) possible outliers removed (see Figs. 4–6 for indication of the years).

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69

Station Name

Latitude

Longitude

Years

Length (years)

% Data gaps

Variance (cm2)

Trends (mm/yr)

GIA (mm/yr)

KANMEN LUSI LIANYUNGANG SHIJIUSUO YANTAI1 TANGGU1,2 QINHUANGDAO2 DALIAN1 LAOHUTAN KEELUNG II INCHON ANHUNG PORYONG (KOJONG)2 KUNSAN (OUTER PORT) WIDO MOKPO DAEHEUG SAN DO SOGWIPO JEJU WANDO KOMUNDO YOSU TONGYONG (CHUNGMU) CHUJADO CHINHAE GADEOG DO PUSAN ULSAN POHANG ULNEUNG DO MUGHO SOGCHO WONSAN2 MONBETU I MONBETU II ABASHIRI TAPPI YOSIOKA ESASHI OSHORO I OSHORO II NASE II NASE III NAKANO SIMA OKINAWA NAHA ISHIGAKI ISHIGAKI II SHIMONOSEKI III SHIMONOSEKI II HAGI TONOURA1 HAMADA II SAKAI SAIGO TAJIRI MIYAZU MAIZURU I MAIZURU II MAIZURU III MIKUNI TOYAMA WAJIMA1 KASHIWAZAKI OGI AWA SIMA NEZUGASEKI1 OGA IWASAKI

28 32 34 35 37 39 39 38 38 25 37 36 36 35 35 34 34 33 33 34 34 34 34 33 35 35 35 35 36 37 37 38 39 44 44 44 41 41 41 43 43 28 28 29 26 26 24 24 33 33 34 34 34 35 36 35 35 35 35 35 36 36 37 37 37 38 38 39 40

121 121 119 119 121 117 119 121 121 121 126 126 126 126 126 126 125 126 126 126 127 127 128 126 128 128 129 129 129 130 129 128 127 143 143 144 140 140 140 140 140 129 129 129 127 127 124 124 130 130 131 132 132 133 133 134 135 135 135 135 136 137 136 138 138 139 139 139 139

1959–2008 1961–2008 1975–1994 1975–1994 1968–1994 1975–1994 1950–1994 1980–2008 1980–1997 1956–1995 1960–2006 1989–2008 1986–2006 1981–1992 1985–1999 1960–2006 1979–2006 1985–2006 1964–2006 1983–2006 1982–2006 1970–2006 1977–2006 1984–2006 1960–1976 1977–2006 1960–2006 1962–2006 1972–2006 1979–2006 1972–2006 1974–2006 1962–1992 1955–1978 1978–2008 1965–2008 1985–2008 1984–2008 1984–1996 1930–1962 1963–2008 1962–1980 1981–2008 1984–2008 1975–2008 1966–2008 1975–1986 1986–2008 1993–2008 1955–1960 1971–1991 1894–1984 1984–2008 1957–2008 1965–2008 1966–2008 1957–1969 1951–1981 1975–2008 1981–2008 1967–2008 1975–2008 1930–2008 1955–2008 1973–1994 1965–2008 1965–2008 1970–2008 1958–1970

49 47 19 19 26 19 44 28 17 39 46 19 20 11 14 46 27 21 42 23 24 36 29 22 16 29 46 44 34 27 34 32 30 23 30 43 23 24 12 32 45 18 27 24 33 42 11 22 15 5 20 90 24 51 43 42 12 30 33 27 41 33 78 53 21 43 43 38 12

1 19 0 0 0 0 0 22 0 1 10 6 2 1 7 0 2 0 0 0 0 0 0 1 0 3 1 3 0 1 2 0 0 7 6 4 0 8 1 3 2 3 1 1 6 1 2 4 4 13 0 3 1 3 0 3 9 2 2 4 5 1 1 7 2 4 9 4 1

4.29 6.47 15.12 7.43 9.10 21.23 11.01 2.73 1.89 12.07 17.23 6.06 11.01 3.26 7.15 10.64 4.39 2.61 7.04 4.07 3.53 6.09 1.95 3.43 4.67 3.34 5.47 11.27 9.94 24.73 7.66 1.71 5.88 4.37 5.71 8.13 2.69 1.86 2.59 3.27 3.29 13.20 5.94 3.96 7.21 8.52 5.09 6.59 2.91 1.62 3.13 9.53 2.06 8.10 4.48 3.71 3.75 5.20 3.07 2.13 11.15 4.28 8.07 7.04 4.54 7.93 3.51 6.38 3.36

1.77 ± 0.33 5.40 ± 0.55 6.71 ± 2.01 2.28 ± 1.94 0.19 ± 0.75 4.17 ± 2.66 0.17 ± 0.76 2.26 ± 0.57 3.88 ± 2.50 0.60 ± 0.54 0.60 ± 0.53 1.77 ± 1.76 9.50 ± 1.66 7.80 ± 3.66 0.70 ± 2.44 3.23 ± 0.45 1.67 ± 0.87 6.46 ± 1.25 5.33 ± 0.50 1.94 ± 1.13 5.93 ± 0.97 1.91 ± 0.59 2.33 ± 0.68 1.92 ± 1.12 5.14 ± 1.58 2.12 ± 0.67 1.83 ± 0.30 1.02 ± 0.33 3.44 ± 0.48 2.65 ± 0.82 0.77 ± 0.35 2.19 ± 0.51 1.57 ± 0.76 2.09 ± 0.65 0.78 ± 0.40 1.39 ± 0.25 1.67 ± 0.73 1.46 ± 0.62 2.27 ± 1.83 0.21 ± 0.45 0.53 ± 0.28 8.11 ± 1.84 3.00 ± 0.95 5.33 ± 1.08 0.99 ± 0.66 2.11 ± 0.45 1.58 ± 3.51 4.39 ± 1.27 3.01 ± 2.42 3.95 ± 11.69 0.37 ± 1.56 0.34 ± 0.18 5.23 ± 1.17 1.64 ± 0.41 1.53 ± 0.45 2.60 ± 0.51 5.51 ± 3.52 0.11 ± 0.84 4.14 ± 0.67 4.30 ± 0.98 4.38 ± 0.51 4.13 ± 0.65 0.32 ± 0.19 0.99 ± 0.32 0.96 ± 1.17 3.84 ± 0.41 4.78 ± 0.34 1.33 ± 0.46 2.64 ± 2.54

0.69 0.78 0.73 0.71 0.66 0.70 0.69 0.69 0.69 0.54 0.81 0.81 0.81 0.81 0.79 0.76 0.71 0.65 0.67 0.74 0.74 0.80 0.81 0.70 0.80 0.80 0.80 0.77 0.74 0.49 0.65 0.67 0.74 0.75 0.75 0.73 0.67 0.66 0.65 0.69 0.69 0.45 0.45 0.46 0.46 0.46 0.36 0.37 0.78 0.79 0.78 0.74 0.74 0.69 0.62 0.72 0.76 0.77 0.77 0.77 0.77 0.79 0.72 0.81 0.77 0.76 0.76 0.68 0.66

05 N 08 N 45 N 23 N 32 N 00 N 54 N 52 N 52 N 08 N 27 N 40 N 24 N 58 N 37 N 47 N 41 N 14 N 31 N 19 N 01 N 45 N 49 N 58 N 09 N 01 N 06 N 31 N 01 N 30 N 33 N 12 N 10 N 21 N 21 N 01 N 15 N 27 N 52 N 13 N 12 N 23 N 30 N 50 N 11 N 13 N 20 N 20 N 55 N 58 N 26 N 54 N 54 N 33 N 12 N 35 N 32 N 29 N 28 N 27 N 15 N 46 N 24 N 21 N 49 N 28 N 34 N 56 N 35 N

17 E 37 E 27 E 33 E 23 E 43 E 36 E 41 E 41 E 44 E 36 E 08 E 29 E 38 E 18 E 24 E 27 E 34 E 32 E 45 E 19 E 46 E 26 E 18 E 39 E 49 E 02 E 23 E 24 E 55 E 07 E 36 E 27 E 22 E 22 E 17 E 23 E 15 E 08 E 52 E 52 E 30 E 30 E 51 E 50 E 40 E 10 E 09 E 55 E 57 E 25 E 04 E 04 E 15 E 20 E 19 E 11 E 24 E 23 E 19 E 09 E 13 E 54 E 31 E 17 E 15 E 33 E 42 E 55 E

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Fig. 2. Periods of operation of RLR (black) and non-RLR (grey) tide gauges. Stations are numbered in the same order as in Table 1 and Fig. 1.

The tide gauges used did not operate simultaneously over the whole period. The period of operation for each of them is shown schematically in Fig. 2. Only one tide-gauge goes back to 1890, two start in the 1920s while more time series become available after 1960. Gaps also exist in the time series. About 50% of the stations span periods between 20 and 40 years, two records have more than 70 years of data and seven short records are less than 15 years long. The percentage of data gaps are listed in Table 1. Data that have been reported as problematic in the PSMSL database have not been included in the analysis; these periods have been removed from the data set and the stations are flagged in Table 1. Metric stations span the period between 1920 and 1985. All the information is listed in Table 2. The spatial distribution of the tide gauge stations along the coasts of the three marginal seas of the north-western Pacific is heterogeneous, reflecting primarily national development of sea level networks. A total of 69 RLR tide gauge records have been considered, most of which are distributed along the Japanese and Korean coasts, providing a good spatial coverage in the southern JES and the northern Yellow Sea. The ECS is also monitored by eight

tide gauges. Only three stations are located in the Okhotsk Sea at the southernmost part. Mean annual sea level values have been computed by averaging the monthly time series. Only when at least 10 monthly values were available an annual mean sea level value was calculated. Mean annual sea level values from tide gauge records are plotted in Figs. 3–6, where stations have been grouped according to their location in the Yellow Sea and the ECS (Fig. 3), the southern JES and the Tsushima Strait area (Fig. 4), the northern JES (Fig. 5) and the Okhotsk Sea (Fig. 6). Sea level data are subject to quality controls by the national services which provide the data to the PSMSL and by quality controls by the PSMSL. We have further performed additional quality controls in based on the empirical knowledge that interannual variability between nearby stations in general should show some similarities, even if the trends are markedly different. For the RLR stations (1–69) the quality check consisted on computing and examining the differences among nearby detrended yearly time series for their common periods. This procedure allows, first, the visual identification of outliers and datum shifts. It also permits identifying those records whose variance is markedly different from nearby time series. For most of the stations (70%) the standard deviation of the difference between the yearly series with that of a neighbouring site is less than 2 cm. In some stations anomalous values for particular years increase the standard deviations of the differences up to 5 cm. Tanggu, Qinhuangdao and Poryong in the Yellow Sea and Wonsan in the JES are the most prominent examples (Figs. 3 and 4). We removed these years from the records to avoid possible spurious biases in the estimation of variances or trends. The stations and the values are flagged in Table 1 and the years removed from further analysis. In some stations similar outliers occur (see for example Nase II or Wajima). In the absence of nearby control stations that indicate these values as spurious the values are retained. Variances of detrended yearly series are listed in Tables 1 and 2. Higher variances around 10 cm2 are found in the western coasts of the Yellow Sea and lower in the JES with values less than 5 cm2 except for the station in Ulneung Do (number 30) located in an island in the southern JES which displays the maximum variance of 25 cm2. These results are consistent with the distribution of variances found in altimetry, as shown below (Fig. 7).

Inter-comparison of tide gauge data In the following we discuss sea level variability in terms of geographical regions. The objective is to identify consistency or inconsistencies between tide gauges. This is a prerequisite in determining which tide gauges will be used in extracting each regional sea level index in Section 5. The yearly sea level time series are shown in Figs. 3–6. In the Yellow Sea, the stations Yantai, Shijiusuo, Lianyungang and Lusi indicate similar behaviour over the period 1975–1994, mainly sea level rise. The peak in 1991–1992 is much more pronounced in the Lianyungang station and almost non-existent in

Table 2 As in Table 1 but for Metric stations.

70 71 72 73 74 75 76 77 78

Station Name

Latitude

Longitude

Years

Length (years)

% Data gaps

Variance (cm2)

Trends (mm/yr)

POSIET VLADIVOSTOK NAKHODKA VALENTIN RUDNAYA PRISTAN SOV. GAVAN UGLEGORSK KHOLMSK NEVELSK

42 43 42 43 44 48 49 47 46

130 131 132 134 135 140 142 142 141

1950–1985 1926–1985 1948–1985 1942–1963 1940–1985 1948–1979 1963–1990 1947–1990 1923–1990

35 59 37 21 45 31 27 43 68

0 2 0 0 0 0 0 0 13

5.39 5.53 2.87 2.45 6.91 3.19 11.33 3.54 2.56

0.55 ± 0.62 0.01 ± 0.27 0.04 ± 0.45 0.02 ± 0.84 0.16 ± 0.28 0.33 ± 0.37 2.20 ± 0.55 0.45 ± 0.20 0.33 ± 0.09

39 N 09 N 53 N 09 N 18 N 57 N 01 N 02 N 41 N

47 53 54 15 51 16 04 03 55

E E E E E E E E E

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Fig. 3. Yearly mean sea level values of tide gauges located in the Yellow and the East China Seas. Time series have been offset for representation purposes. Units are cm.

the Lusi station. These stations, Lianyungang (3), Shijiusuo (4) and Yantai (5) are in the areas of Jiangsu and Sandong, were reported as steady (Wang, 1998). Qinhuangdai and Tanggu, located on the northernmost part of the Yellow Sea (known as the Bohai Sea), show very small change and the major characteristic is a negative sea level value occurring in 1980 in the former station and 1984 in the latter. By contrast, Laohutan and Dalian, located in the north-eastern coast of the Yellow Sea, show similar behaviour for the common period 1980–1997, indicating sea level rise. Stations Anhung, Poryong, Kunsan and Wido appear very different and because of their short period of cover it is not possible to conclude whether any of them is good or problematic. One reviewer kindly pointed out that Kunsan reflects the local behaviour associated with dike building. Anhung appears to be consistent with Inchon although there are gaps in the latter. These two stations as well as Mokpo, Daeheung San Do, Sogwipo, Jeju and Wando, all located along the eastern coast of the Yellow Sea, show similar signals in the last 5 years of the record. However, the earlier parts of the records are very dissimilar. Whether this indicates a change in the physical forcing

or problems with the earlier parts of the records is impossible to say. Sogwipo and Jeju, both located on the same island, display the largest trends. Jeon (2008) hypothesized that the large trend in Jeju tide gauge station may have been caused by a shifting in the path of the TWC towards Jeju Island. Chujado, Tongyong and Yosu are located in the Tsushima Strait and appear similar, indicating a period of sea level rise in the period 1978–1995 but not after. Komundo, with a different location on an island, appears similar to the above up to 1998 but differs after that period. Other stations are located in the East China Sea along the Ryukyu Islands. Nase II appears to have a significant increase in sea level between 1968 and 1978, which unfortunately is not supported by the nearby Nase III because of the different periods covered. However, Naha located in a nearby island, also displays a significant sea level rise for the same period. Naha and Okinawa show similar behaviour, as expected due to their close location in the same island. Nakano Sima appears to behave similarly after 1998. For the JES very little similarity is found among stations, with some of the records (Tappi, Sogcho, Mugho, Tajiri, Saigo, Toyama, Maizuru II) essentially showing no interannual variability. Ulneung

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Fig. 3 (continued)

Do is different from others and variability is significantly larger there. This station in Ulleung Island is located in the southwestern part of the JES in a deep part of the basin and its behaviour is expected to reflect the oceanographic conditions in the area. Inter-annual sea level variability has been reported to be remarkably larger than in the relatively close Korean coast due to the North– South displacement of the polar front that divides the northern cold water region and the southern warmer region in the JES (Kim et al., 2002). Some of the stations indicate sea level rise after 1990, some sudden increase after 2002; however, there is no uniform behaviour one can deduce and the trends appear to start at different periods. Nevertheless, in most stations 1980 onwards indicates sea level rise. In the northern coasts of the JES records from Metric stations (Fig. 5) indicate coherent sea level variability. However, no sea level rise can be seen. One of the most remarkable features is a sea level minimum reached around 1980 and which is identifiable at all stations. The Sea of Okhotsk contains only three RLR records (Fig. 6), which also appear very coherent and with no sea level rise, as in the north of the JES. 2.2. Altimetric data Altimetry data were obtained from AVISO data server (http:// www.aviso.oceanobs.com/en/data/products/index.html). Gridded sea level anomalies computed with respect to a 7 year mean were selected for the area from 20 to 65 °N in latitude and from 100 to 160 °E in longitude for the period 1993 to 2008. The data set was constructed with up to four satellites: Topex/Poseidon, Envisat, GFO, Jason-1 and Jason-2 in order to improve the spatial sampling. All geophysical corrections have been applied, including a tidal correction provided by the recently released GOT4.7 model (Egbert et al., 2010). Atmospheric correction is applied using the Dynamic Atmospheric Correction currently delivered by AVISO that consists on the combination of the barotropic model MOG2D (Carrère and Lyard, 2003) for frequencies higher than 20 days and IB for lower frequencies. Nam et al. (2004) showed that the IB correction for high frequency (<20 days) sea level oscillations in the JES underestimates the effect of the atmospheric forcing by up to 10 cm. Thus this model improves the classical IB correction for the removal of aliased high frequency atmospheric signals. The spatial resolution of the gridded data set is 1/4°  1/4° and the temporal resolution

includes one measurement every 10 days approximately. Calendar monthly means were computed only when at least three measurements within a month were available. The altimetry data are routinely corrected for the atmospheric pressure effect. This produces an inconsistency with the tide gauge data which are not routinely corrected in this way. To facilitate the intercomparison the atmospheric pressure effect has been added back to the monthly time series from altimetry as IB calculated on the basis of pressure measurements from the NCEP/NCAR Reanalysis (Kalnay et al., 1996). The mean monthly sea level anomalies distribution is shown in Fig. 7a. Mesoscale patterns are evident in the JES and the ECS. The variance of sea level variability at the Okhotsk Sea is around 25 cm2 and in the JES has an average value of 55 cm2. Note though that the variance of the northern part of the JES is comparable with that of the Okhotsk Sea while its southern part is more energetic. In the Yellow Sea higher variances are found near the coasts with up to 300 cm2 over the continental shelf. The increase in variance could be due to wind effects and/or variability of coastal currents but also be caused by errors in the modelling of tides used to remove the tidal signal from the altimetry records. Variances of monthly time series at tide gauges range between 290 and 450 cm2 in the area (stations 3–7), similar to what is found in altimetry, and despite the tides in the tide gauges have been filtered. Tidal oscillations are known to be important in the Yellow Sea and in the northern coasts of the Okhotsk Sea. They are also complicated and variable with the season due to the significant contribution of baroclinic tides in some of the Straits (Kang et al., 1995, 2002). Morimoto (2009) investigated the accuracy of tidal corrections applied to altimetry data in these regions and concluded that the best available model from AVISO, the GOT4.7 model used in the current altimetry data set, reduced the tidal signal to a level comparable to that of a regional tidal model, resulting to errors of 5 cm in the open ocean. However, certain areas near the coast had errors in excess of 20 cm while areas around the straits had errors around 15 cm. These are large errors that need to be considered when the results based on altimetry are used. With this reservation we use the results from altimetry for confirmation of the coastal trends obtained from tide gauges. The spatial distribution of errors shown by Morimoto (2009) permits some confidence that basin averages are more reliable than local estimates.

M. Marcos et al. / Progress in Oceanography 105 (2012) 4–21

11

Fig. 4. As in Fig. 3, but for the southern JES and Tsushima Strait area.

2.3. Steric sea level

3. Sea level trends

Steric sea level fields were computed using the Ishii global gridded temperature (T) and salinity (S) climatology (Ishii and Kimoto, 2009). This data set has been produced by objective analysis of in situ observations from the World Ocean Database (WOD05) and World Ocean Atlas (WOA05) and consists of monthly gridded T, S fields with a spatial resolution of 1°x1°; the vertical domain extends down to 700 m, with data on 16 levels. This data base covers the whole second half of the 20th century, namely the period 1945–2006. The steric component of sea level (ZS) can be computed at each grid point as the vertical integration of the specific volume (a), which in turn depends on the temperature and salinity distributions along the water column:

Observed sea level trends for the monthly tide gauge records and for the entire period of operation are listed in Table 1 for the RLR stations and in Table 2 for the Metric stations, together with their standard errors. For the sake of comparison among stations three periods have been selected: from 1950 to 1985 when most of the metric tide gauge stations have data, from 1960 to 2008 when most RLR stations are available and from 1993 to 2008 when altimetric measurements are available. Only stations covering at least 60% of the period are considered. Sea level trends for the period 1950–1985 computed using monthly time series are plotted in Fig. 8. Tide gauges in the northern JES display coherent sea level trends, varying between 0 and 1 mm/yr with one station showing a negative value of 0.5 mm/ yr. The trends decrease northwards in this area. Although the tide gauges in the northern JES coast are not vertically referenced, they present consistent linear trends, so this justifies the use of these stations in our analysis. Inter-annual variability is also coherent among sea level records with correlations between nearby stations

ZS ¼ 

1 g

Z

Po

a  dp Pf

where Po and Pf are the pressure values at surface and 700 m depth. Since we are interested in the variability, the mean value of the time series obtained at each grid point can be subtracted.

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M. Marcos et al. / Progress in Oceanography 105 (2012) 4–21

Fig. 4 (continued)

of 0.4–0.8. The southern JES indicates mainly negative or nonincreasing sea level with the highest positive value at the northern part (station 41). Only one station is available for this period in the Okhotsk Sea, indicating sea level rise of about 2 mm/yr, thus higher than nearby tide gauges in the JES. The Yellow Sea exhibits much higher variability with trends ranging from 5 mm/yr to 3 mm/ yr attributed to the different conditions at the locations of the tide gauges. For example, station 19 is located at an island while stations 27 and 28 are at the Tsushima Strait and therefore are not expected to exhibit the same behaviour as those in the interior of the Yellow Sea (Bohai Sea). Only two stations are available for this period in the ECS (numbers 1 and 10) and display very different trends. Thus for the period 1950–1985 we conclude that there was little change in sea level in all basins. We find exceptions at stations 1, 11, 19 and 28, located in the ECS, Yellow Sea and the Tsushima Strait. These stations have trends different from zero and we consider them as indicating local factors. Sea level trends for the period 1960–2008 from monthly records are mapped in Fig. 9a. Trends and their standard errors are also plotted individually for each station (Fig. 9b). Trends vary

between 1.5 and 5.5 mm/yr. Most trends are now positive and are statistically significant at most sites where data is available for this period. Higher values are found in the Yellow Sea with up to 5.5 mm/yr and in the southern JES with values about 4 mm/yr. For this period there are no data available at the northern coast of the JES. Lower values of sea level trends are found in the northernmost stations of the southern JES and in south of the Okhotsk Sea. Sea level trends from monthly tide gauge records (corrected for GIA) and altimetry time series are mapped in Fig. 10 for the period 1993–2008. Dashed areas indicate non-significant trends (to the 95% confidence level). Significance is determined at each altimetry grid point on the basis of t-test. Tide gauge and altimetric trends are not strictly speaking comparable because they refer to different reference framework. Altimetry data show both maxima and minima trends on the east side of Japan due to the high mesoscale activity of the area and to the variability of the TWC (Kang et al., 2005). Small positive trends of about 1–2 mm/yr are found in the Okhotsk Sea from altimetric measurements with an average value of 1.27 ± 0.62 mm/yr. Sea level trends increase southwards reaching

M. Marcos et al. / Progress in Oceanography 105 (2012) 4–21

13

Fig. 5. As in Fig. 3 but for the non-RLR stations at the northern JES.

averaged values of 3.83 ± 0.94 mm/yr in the JES and 5.10 ± 1.88 mm/yr in the Yellow Sea and the ECS. For the same period most of the tide gauges do not show statistically significant trends due to the short period considered and due to data gaps. We should recall here that considered tide gauges have at least 60% of coverage during the period 1993–2008, or, in other words with up to 40% missing data. Thus the coastal records do not always have the same time span as the altimetric time series. The altimetric sea level trends are statistically significant in the JES, ECS and Yellow Sea and in the central part of the Okhotsk Sea. Most tide gauges with significant trends display values consistent with altimetric trends, within the uncertainty range, which is between 1 and 2 mm/yr. Four of the tide gauges with data during the period 1993–2008 present trends much higher than the nearby altimetric measurements. These stations are Poryong (13), Mokpo (16), Pohang (29) and Mikuni (61). Mokpo is located downstream along a river where three dikes were built, which may explain such disagreement. It is unclear whether land movements are the cause of these discrepancies for the other three stations since no GPS data analysis is still available at these locations. Seasonal sea level trends are computed for winter (December– March) and summer (June–September) seasons. For the period 1960–2008 the Yellow Sea winter and summer trends are, within the associated error bars the same except for Qinhuangdao (number 7), where summer trends (0.4 ± 0.1 mm/yr) are significantly smaller than winter trends (0.9 ± 0.2 mm/yr). In the JES summer trends are smaller than winter trends by up to 1 mm/yr in the central area of Japan. In the Okhotsk Sea the only station with data during 1960–2008 presents summer trend (1.5 ± 0.1 mm/yr) slightly larger than winter trend (0.9 ± 0.2 mm/yr). 4. Decadal rates of sea level change Decadal rates of sea level change have been computed as the linear trends of 10-year periods of tide gauge records overlapped year to year. Tide gauge sites have been separated by areas. Results are plotted in Fig. 11 for the Okhotsk Sea, northern and southern JES, the ECS and Yellow Sea separately. The average decadal rates for each area are compared with the global rate from Holgate (2007). Decadal variability is evident at the four sub-regions. The largest decadal rates of sea level change are found in the ECS with

values between 5 mm/yr and more than 20 mm/yr for individual stations reached in early 1970s and up to 11 mm/yr for the average, followed by the Yellow Sea. In the southern JES the decadal sea level trends vary between 10 mm/yr and more than 15 mm/yr for individual stations, while the average values range between 1 mm/yr and 10 mm/yr. A gradual decrease in the decadal rates of change is observed in this area from the beginning of the record up to 1960 followed by an increase. Decadal oscillations of similar amplitude about 10 m/yr are superimposed. In the northern JES the situation is very different. Decadal rates of sea level change range between 6 mm/yr and 14 mm/yr for individual stations and 4 mm/yr and 8 mm/yr for the averaged values. No trend is detected. In the Okhotsk Sea the three tide gauges display coherent decadal ser level rates between 4 mm/yr and 8 mm/yr from 1960 onwards. Regional decadal trends of sea level have been compared with the global values derived by Holgate (2007) (red1 lines in Fig. 11). The tide gauges in the Okhotsk Sea and in the northern JES show very similar behaviour as the global rates although the signals appear enhanced when compared with the global ones. This is despite the fact that both areas do not show sea level rise overall by contrast with the estimates of Holgate (2007). The southern JES, the ECS and Yellow Sea show different variation than the global values. However, within the spread of the estimates from the various tide gauges one cannot confirm whether the region as a whole behaves differently or that local factors obscure the global signal. 5. Regional mean sea level indices The inconsistencies between nearby tide gauges and the gaps in their records can, to an extent, be overcome by synthesizing sea level indices for each of the five areas, namely the northern and southern JES, the ECS, the Yellow Sea and the Okhotsk Sea. These indices have been developed using the longest sea level records. As observed trends at tide gauge locations are partly due to land movement which is local and not necessarily uniform in the various regions, trends had to be removed from each record before 1 For interpretation of colour in Figs. 7–11, the reader is referred to the web version of this article.

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M. Marcos et al. / Progress in Oceanography 105 (2012) 4–21

Fig. 6. As in Fig. 3 but for the Okhotsk Sea.

proceeding. The development of regional mean sea level indices can only be performed for periods where several tide gauges have data. Of course the bias in the spatial distribution cannot be remedied by this methodology. Thus the index for the Okhotsk Sea where only three tide gauges records exist in the southern part may not be considered as representative of the whole basin. Detrended annual sea level records covering the periods 1960–2008 for the southern JES, 1964–2006 for the Yellow Sea, 1956–1995 for the ECS, 1950–1985 for the northern JES and 1965–2008 for the Okhotsk Sea with at least 80% of data have been considered for each area. The selection results in nine stations in the southern JES, six stations in the northern JES, three stations

(a)

in the Yellow Sea, three stations in the ECS and three in the Okhotsk Sea. Despite the larger number of stations available in the ECS and in the Yellow Sea, only three were selected in each case in order to cover a period of time as long as possible with overlapping data. The stations used and their correlation with the corresponding index are listed in Table 3. All correlations are significant to the 90% confidence level. Large values of correlation (0.8–0.9) are found in the Okhotsk Sea and the northern JES. The detrended yearly time series were averaged area to obtain the regional mean sea level indices. Results are presented in Fig. 12. The main feature of the sea level changes in the southern JES is a relative drop in mean sea level over the period 1975–1995. Sea level after 1995 stands higher than the previous period in the southern JES. Similar decadal behaviour is found between regional mean sea level indices at the southern JES and the Yellow Sea, suggesting a common origin. In both of them a relative sea level rise of about 4–5 cm is observed from 1995 onwards, which is not reproduced in the Okhotsk Sea where, during this period, mean sea level remains unchanged. Nothing can be concluded for the ECS since the index stops in 1995. However, note that trends were removed and therefore the comments made are in relation to any basin wide trend. An Empirical Orthogonal Function (EOF) analysis has been applied to the five indices with the aim of extracting coherent sea level oscillation patterns. The period for which the EOF analysis can be performed is the common period for the indices 1965–1985. The main advantage of applying EOFs to the indices instead of to the individual tide gauge records is that the problem with data gaps is avoided. Results for the spatial patterns of the first two EOFs are shown in Fig. 13. The corresponding explained variances are 48% and 24% respectively, while the remaining three are 17%, 7% and 4%. The significance of the EOFs has been checked following Overland and Preisendorfer (1982). The rule applied consists on generating five random independent series with normally distributed variables of the same length as the data, with zero mean and unit variance, which are used to compute eigenvalues. This process has been repeated 1000 times and the 5th and 95th percentiles have been obtained for each eigenvalue. The distribution of the eigenvalues has then been compared with the normalized eigenvalues computed with data. The first two EOFs of the regional mean sea level indices lie within the pair of values given by the lower and higher percentiles. According to the rule suggested by Preisendorfer and Barnett (1977) only the first EOF is above the level of noise, while the second is below but close to it. As pointed out by Overland and

(b)

Fig. 7. Mean sea level (a) and variances (b) from monthly gridded altimetry for the period 1993–2008. Units are cm and cm2 respectively.

M. Marcos et al. / Progress in Oceanography 105 (2012) 4–21

15

Fig. 8. Trends and uncertainties for the period 1950–1985. Stations are labelled according to Fig. 1 and areas are separated by dashed lines: Yellow Sea and Tsushima Strait, Northern coast of the JES and southern coast of the JES.

(a)

(b)

Fig. 9. Sea level trends at tide gauge stations for the period 1960–2008. (a) In the map white squares indicate that trends are not statistically significant and black dots indicate tide gauge stations without data for this period. (b) Trends and uncertainties for each tide gauge station. Numbers follow those in Fig. 1 and Table 1.

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Sea level trends 1993−2008 mm/yr 20

63 oN

15

54 oN

10

5

o 45 N

0 o

36 N

−5 o

27 N

o

104 E

o

112 E

o

120 E

o

128 E

o

136 E

o

144 E

o

152 E

o

160 E

o

−10

168 E

Fig. 10. Sea level trends for the period 1993–2008 for tide gauges (corrected for GIA) and altimetric measurements. White squares at tide gauges indicate non-significant trends and black dots indicate tide gauge stations without data for this period. Dashed areas indicate altimetric non-significant trends.

Preisendorfer (1982) it does not discard that other principal components may have a geophysical relevance. In fact, the spatial distribution of the second mode is physically consistent with the observed similar behaviour between the Okhotsk Sea and the northern JES. In this section we will therefore discuss the first two EOFs, although only the first one will be used to search for the origin of sea level variability within the next section. The first EOF has the same sign and similar amplitudes for all areas, indicating that they oscillate in phase and reflecting the large scale sea level variability. Its amplitude decreases southward, being minimum at the Yellow Sea and the ECS. The correlation of the temporal amplitude of the first EOF with the regional mean sea level indices is 0.8 in the Okhotsk Sea and in the northern and southern JES, while it is only 0.4 in the Yellow Sea and the ECS (all values are significant at the 90% confidence level). Thus the first EOF is a good approach of the regional sea level variability, except for the Yellow Sea and the ECS. The second EOF shows a dipole structure with the Okhotsk Sea and the northern JES oscillating in opposite phase with respect to the rest of the areas. This second EOF evidences the similarities between the Okhotsk Sea and the northern JES, which oscillate in phase and with similar amplitudes.

6. Causes of sea level variability The sources of sea level variability of the computed indices and their first EOF have been explored by comparing the time series with atmospheric pressure and steric sea level changes in the area and with the main climatic indices driving the variability in the north western Pacific. Monthly atmospheric pressure at sea level has been obtained from the NCEP/NCAR Reanalysis (Kalnay et al., 1996). Yearly regional averages are computed the region 26– 50°N and 112–152°E. Yearly steric sea level has been averaged over five different areas: the northern and southern JES, the Yellow Sea,

the ECS and the Okhotsk Sea. Steric changes in all areas were found to be dominated by temperature variations, rather than by salinity. Correlations of yearly detrended sea level indices with yearly atmospheric pressure, seasonal (winter and summer) atmospheric pressure and yearly steric sea level computed with different integration depths are listed in Table 4. Correlations significant at the 99% confidence level are highlighted in bold. Fig. 14 displays the correlated time series appropriately scaled. Linear regressions between sea level and atmospheric pressure are used to estimate the scale coefficients. Significant correlations with atmospheric pressure are found in three areas: in southern JES regional mean sea level is correlated with yearly atmospheric pressure (0.48); the Okhotsk mean sea level displays correlations with yearly (0.57) and winter (0.56) atmospheric pressure. In this area inter-annual changes in atmospheric pressure are controlled by winter variations. Because the sea level index we use only represents the southernmost part of the Okhotsk Sea it should not be understood that the whole of the Okhostk Sea is well correlated with atmospheric pressure. The Yellow Sea shows correlations with steric sea level (0.50) and with summer atmospheric pressure (0.53). Likewise, the ECS is correlated with steric sea level (0.60). Yeh and Kim (2010) found a warming trend in sea surface temperature (SST), closely related to steric sea level, in these two regions. They associated this increase with large scale winter atmospheric pressure variability, in particular to the anomalous anticyclonic circulation over the central North Pacific. However, we do not find such trend in steric sea level. In the Yellow Sea and in the ECS steric sea level changes are smaller than regional mean sea level variations (see Fig. 14), suggesting that other mechanisms, such as wind variability and/ or baroclinic circulation changes may also be significantly contributors. Sea level in the Southern JES is also highly correlated with averaged steric sea level in the area (0.74). Steric sea level appears to be the major cause of both the variability and the amplitude of inter-annual changes in averaged sea level (Fig. 14). Choi et al.

M. Marcos et al. / Progress in Oceanography 105 (2012) 4–21

17

Fig. 11. Decadal rates of sea level change for the five seas. Shadowed area represents individual tide gauges, black thick lines are the average rate for each area and red lines are the global average by Holgate (2007).

(2004) show that the TWC is the major physical feature determining the heat content of this area. Thus it can be conjectured that it is the variability in TWC heat content that determines the sea level variability in this area. An increase in sea level driven by the steric contribution is observed in southern JES from 1980 onwards, in agreement with an SST trend found by Yeh et al. (2010) for the same period. The first EOF of the regional sea level indices is not correlated with atmospheric pressure. Given the differences found in the steric signal of the five areas we consider the calculation of an average steric effect as meaningless. Thus the first EOF has not been correlated with any averaged steric sea level. The climatic indices considered are the Pacific Decadal Oscillation index (PDO; Mantua et al., 1997), the North Pacific Oscillation

(NP; Trenberth and Hurrell, 1994), the West Pacific Oscillation index (WPO; Barnston and Livezey, 1987) and the Kuroshio Position Index (KPI; Kawabe, 1995). Correlations between sea level and climatic indices are presented in Table 5. A 5-year running average has been applied to correlate all time series, except to when KPI and PDO are used, in order to filter out inter-annual changes and focus on decadal climate variability. The PDO index represents the main climatic pattern in the North Pacific Ocean and its variability is reflected in the heat content of the upper ocean. Thus, we expect good correlations with the PDO where correlation between sea level and the steric signal have been found, namely the southern JES, the Yellow Sea and the ECS. We find significant correlation of sea level with the PDO in the former two regions but not in the ECS.

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Table 3 Correlations of tide gauges records with the sea level indices time series at the corresponding area. Southern JES Pusan Mugho Oshoro II Sakai Saigo Wajima Kashiwazaki Awa Sima Nezugaseki

Northern JES 0.53 0.52 0.68 0.87 0.90 0.94 0.92 0.88 0.71

Posiet Vladivostok Nakhodka Rudnaya Pristan Kholmsk Nevelsk

Okhotsk Sea 0.75 0.88 0.79 0.85 0.84 0.73

Monbetu I Monbetu II Abashiri

Yellow Sea 0.88 0.95 0.95

Lusi Inchon Jeju

East China Sea 0.39 0.75 0.68

Kanmen Keelung II Naha

0.69 0.72 0.68

Fig. 12. Regional mean sea level indices for five areas computed through averaging with detrended yearly time series with at least 80% of data. Standard deviations are also shown. Note the different vertical and time scales.

The NP index is correlated with the Yellow Sea and the southern JES regional mean sea level indices, although correlations are smaller than those obtained for the PDO. NP index is a measure of the atmospheric circulation in the north Pacific and is coherent with ocean temperature anomalies (Trenberth and Hurrell, 1994). Thus, as it is expected it correlates with steric sea level variability at decadal scales (0.3 at the Yellow Sea and the southern JES). Yeh

and Kim (2010) found that a NP-like pattern is also correlated with SST in the Yellow Sea and in the ECS. The fact that we do not find significant correlation in ECS is not necessarily in contradiction with Yeh and Kim (2010) results, since steric sea level does not seem to be the dominant mechanism on sea level variability in this region, as suggested above. The WPO index, built using 700 mbar heights, represents a climatic pattern consisting on a dipole

M. Marcos et al. / Progress in Oceanography 105 (2012) 4–21

Fig. 13. Spatial patterns of the first three EOFs computed for the regional mean sea level indices.

Table 4 Correlations between yearly sea level indices and first EOF with atmospheric pressure and steric sea level variations. Correlations significant to the 99% level are highlighted in bold.

N. Japan S. Japan Yellow Sea ECS Okhotsk Sea EOF 1

Pressure

Winter p.

Summer p.

Ste 700

Ste 500

Ste 300

Ste 100

0.23 0.48 0.19

0.08 0.26 0.04

0.10 0.32 0.53

0.07 0.74 0.50

0.72 0.50

0.72 0.50

0.74 0.50

0.01 0.57

0.30 0.56

0.23 0.15

0.60 0.30

0.60

0.60

0.60

0.11

0.22

0.34

–

–

–

–

structure with one of its centres over the Kamchatka Peninsula (Barnston and Livezey, 1987). The positive/negative phase of such oscillations is associated with below/above-average air temperatures over the eastern north Asia. The two areas correlated with WPO are thus the closest to the centre of action, the Okhotsk Sea and the northern JES. The first EOF also shows a high correlation, which is consistent with the larger amplitudes of the first principal component in the two areas referred. Finally, the KPI, which is a measure of the North–South displacement of the Kuroshio Current, is correlated with the ECS and southern JES regional mean sea level indices at inter-annual scales. Non-filtered series have been used in this case since the interest is focused on the inter-annual changes rather than on decadal variability. The sensitivity of the ECS averaged sea level to KPI is not surprising, since the index is built with stations located within the path of the current. On the other hand, the southern JES regional mean sea level is under the direct influence of the TWC. Therefore, the correlation with KPI suggests that the interannual variations of the TWC are statistically correlated with those of the Kuroshio Current. This may be taken to support the suggestion by some authors (Lie and Cho, 1994; Isobe, 1999; Guo et al., 2006) that they are linked. Other climatic indices, such as the Arctic Oscillation Index (AO), the Polar–Eurasian Index (POL) and the Western North Pacific Monsoon Index (WNPMI; Wang et al., 2001) were also tested but no significant correlations were found.

7. Summary and conclusions Sea level variability at inter-annual and decadal scales in the Okhotsk, Japan and Yellow Seas has been analysed based on tide

19

gauge measurements and altimetry observations. A total of 69 RLR tide gauge stations together with nine non-RLR stations have been used in this study, most of which are located in the JES. The southern JES and the Korean Peninsula are monitored by a dense network of tide gauge stations. About 30 RLR stations are longer than 20 years, including two very long records with more than 70 years of data. Conversely, in the Okhotsk Sea only three RLR stations are available. Additionally, there are about 30 tide gauge records available at PSMSL database not vertically referenced and distributed along the Yellow and JESs. Due to the lack of RLR data in the northern coast of the JES, those non-RLR tide gauges longer than 20 years and located in this area have also been considered. As part of the quality control procedure all tide gauge records have been compared with nearby series in order to detect reference jumps or outliers not reported in the PSMSL data base. Some suspicious measurements have been removed from RLR records in the Yellow and JESs, but no reference jumps could be detected. However, probably due to vertical land movements linear trends are not homogeneous, especially in the southern JES. The nonRLR tide gauge records display a coherent and homogeneous behaviour in terms of inter-annual variations (with correlations between nearby stations of up to 0.8) and linear trends, which suggests that they can be used for long term sea level analysis. Unfortunately these time series are only available up to the 1980s, either because they are not operated since then or because these stations have not yet been updated in the PSMSL data base. Given the good quality of these historical tide gauge records it would be desirable to extent the sea level measurements at these sites and reference the new data with the historical series. Sea level variance at monthly scales presents a clear increasing pattern southwards. Minimum values are found at the Okhotsk Sea with an average value of 25 cm2, while larger values are found in the Yellow Sea. Maximum values of sea level variances of up to 300 cm2 are observed at the continental shelf of the Yellow Sea. When the variance is computed using IB-corrected altimetric sea level observations, the variances in the Yellow Sea are smaller by more than 100 cm2, indicating thus that this large variability is attributed to the meteorological forcing. Sea level variability at inter-annual scales reveals clearly differentiated areas. Within the JES the northern and southern coasts are subjected to the influence of different circulation regimes originated at the current entering through the Tsushima Strait and behave independently in terms of sea level. The warmer southern area presents much higher variability according to the larger changes and meanders observed in the TWC. In this area inter-annual sea level changes are mainly of steric origin, as evidenced from the high correlations found between the corresponding regional mean sea level index and the yearly steric sea level and the similarity in their amplitudes (Fig. 14). This finding is in agreement with Kang et al. (2005) who investigated the origin of the observed sea level rise from altimetric measurements using in situ hydrographic stations and concluded that it was mainly thermosteric. Sea level in the southern JES is also driven by the direct atmospheric forcing, provided the high correlations found between the sea level pressure and the regional mean sea level index. This is in agreement with Yeh et al. (2010), who considered that the primary cause of SST low frequency variability, closely related to steric and in this case to total sea level variability, is the changes in the mean sea level pressure gradient and wind speed over JES. However, our finding creates a different question. Minobe et al. (2004) found significant correlations between sea level pressure over the north Pacific and upper water temperatures in the JES indicating that both effects are interrelated. If indeed our interpretation is correct and steric sea level in itself is responsible for recent sea level changes in this area why mass addition from melting ice sheets is not a contributing factor? Surely an assumption of

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Fig. 14. Regional mean sea level indices and yearly time series of atmospheric pressure and/or steric sea level which show correlations according to Table 4.

Table 5 Correlations (significant to the 99%) between sea level indices and the first EOF with climatic indices. All time series have been smoothed using a 5-year running average for computing correlations, except the KPI.

N. Japan S. Japan Yellow Sea ECS Okhotsk Sea EOF 1

PDO

NP

WPO

KPI

0.09 0.34 0.35 0.13 0.12 0.03

0.24 0.48 0.39 0.25 0.16 0.11

0.60 0.09 0.37 0.14 0.38 0.80

– 0.50 0.28 0.52 0.12 –

uniform distribution of mass from melting ice sheets should produce some effect in this region too. Conversely, the northern coast displays less variability not related neither to steric sea level changes nor to direct atmospheric pressure, although the coverage of hydrographic observations is much poorer here and could be less significant (Minobe et al., 2004). Minobe et al. (2004) pointed out the similarities between this area and the Okhotsk Sea in terms of steric changes during the summer season (ice covers a significant part of the area during winter), which was suggested to be related to the transport changes of the Soya Warm Current (Minobe and Nakamura, 2004). As with the northern coast of the JES, no significant correlation was found between steric sea level and sea level in the Okhotsk Sea, although we are referring here to a limited domain. The regional mean sea level index at the Yellow Sea is correlated with summer atmospheric pressure changes at inter-annual scales, while the mean sea level at the ECS does not display any correlation

with direct atmospheric forcing. Cui and Zorita (1998) established that the atmospheric forcing is a main factor influencing sea level along the Chinese coast. They identified two different winter atmospheric patterns strongly correlated with sea level changes between latitudes 20°N and 40°N. Such patterns, defined as the North–South and East–West pressure gradients, represent the effects of wind stress over the ocean. We have found significant correlations (0.4) between the Yellow Sea mean sea level index and these patterns, in agreement with Cui and Zorita (1998). In the ECS, however, no relationship was found, although in this case only one station is located along the Chinese coast and two are in the Ryukyu Islands. Both in the Yellow Sea and the ECS high correlations are found with steric sea level, although the amplitudes of steric sea level changes are smaller than variations in observed averaged sea level. Therefore, major forcing mechanisms of sea level variations in the Yellow Sea and in the ECS are attributed to the combined effect of steric changes and wind forcing. Yeh and Kim (2010) found correlations between the atmospheric pressure patterns over the North Pacific and the SST in the Yellow Sea and ECS, which would in turn influence sea level through the steric changes. Linear trends of quality checked monthly tide gauge time series are heterogeneous in areas where relevant land movements have been reported such as the southern JES (Senjyu, 2006). Trends vary between 1.5 and 5.5 mm/yr for the period 1960–2000 in the Japan and Yellow Seas and the southern Okhotsk Sea. Conversely, linear trends in the northern JES present a coherent behaviour ranging between 0.5 and 1 mm/yr for the period 1950–1985 and decreasing northwards. Altimetric trends are coherent with coastal trends derived from tide gauge records for the common period 1993–2008. In the Okhotsk Sea, where there is a lack of

M. Marcos et al. / Progress in Oceanography 105 (2012) 4–21

coastal sea level observations, altimetry measurements reveal a homogeneous and small trend over the basin for the period 1993–2008. Sea level trends increase southwards for the two other basins reaching the average value of 4.9 ± 1.9 mm/yr in the Yellow Sea. Mesoscale activity is present in the southern JES and reflected in higher than average sea level trends for the observation period. The different behaviour of the basins is also evident at interdecadal variability. Rates of sea level change in the northern JES are small, with values between 0.5 and 0.5 mm/yr, in comparison with the global values which reach up to 5 mm/yr for the same period. Variability is larger in the southern coasts of the JES with values of about 5 mm/yr similar to those of the global average. However, the rates of change in the JES are out of phase with respect to the global average. The same applies to the Yellow Sea, where mean rates of change reach up to 8 mm/yr in opposite phase than the global mean. Therefore decadal rates of sea level change in marginal seas are not expected to follow the global behaviour and as a consequence mean sea level changes should be carefully considered on the basis of regional observations. Acknowledgments M. Marcos acknowledges a ‘‘Juan de la Cierva’’ and a ‘‘Ramon y Cajal’’ contracts and F.M. Calafat acknowledges an FPI grant all funded by the Spanish Ministry of Science and Innovation. M.N. Tsimplis is grateful to the organization of the Pacific-Asian Marginal Seas 15th meeting for their invitation to participate. Altimetry data have been provided by AVISO (http://www.aviso.oceanobs.com/). The work has been partly supported by Lloyd’s Register Trust Fund and by the VANIMEDAT2 project (CTM2009-10163-C02-01). References Barnston, A.G., Livezey, R.E., 1987. Classification, seasonality and persistence of lowfrequency atmospheric circulation patterns. Monthly Weather Review 115 (6), 1083–1126. Carrère, L., Lyard, F., 2003. Modeling the barotropic response of the global ocean to atmospheric wind and pressure forcing – comparisons with observations. Geophysical Research Letters 30 (6), 1275. http://dx.doi.org/10.1029/ 2002GL016473. Choi, B.-J., Haidvogel, D.B., Cho, Y.-K., 2004. Nonseasonal sea level variations in the Japan/East sea from satellite altimeter data. Journal of Geophysical Research 109, C12028. http://dx.doi.org/10.1029/2004JC002387. Church, J.A., White, N.J., Coleman, R., Lambeck, K., Mitrovica, J.X., 2004. Estimates of the regional distribution of sea-level rise over the 1950 to 2000 period. Journal of Climate 17, 2609–2625. Church, J., White, N.J., Aarup, T., Wilson, W.S., Woodworth, P.L., Domingues, C.M., Hunter, J.R., Lambeck, K., 2008. Understanding global sea levels: past, present and future. Sustainability Science. http://dx.doi.org/10.1007/s11625-008-0042-4. Cui, M., Zorita, E., 1998. Analysis of the sea-level variability along the Chinese coast and estimation of the impact of a CO2-perturbed atmospheric circulation. Tellus 50A, 333–347. Egbert, G.D., Erofeeva, S.Y., Ray, R.D., 2010. Assimilation of altimetry data for nonlinear shallow-water tides: quarter-diurnal tides of the northwest European shelf. Continental Shelf Research 30, 668–679. http://dx.doi.org/10.1016/ j.csr.2009.10.011. Emery, K.O., Aubrey, D.G., 1986. Relative sea-level changes from tide-gauge records of eastern Asia mainland. Marine Geology 72, 33–45. Garrett, C., 1983. Variable sea level and strait flow in the Mediterranean: a theoretical study of the response to meteorological forcing. Oceanologica Acta 6, 79–87. Guo, X., Miyazawa, Y., Yamagata, T., 2006. The Kuroshio onshore intrusion along the shelf break of the east China sea: the origin of the Tsushima warm current. Journal of Physical Oceanography 36, 2205–2231. Hirose, N., Fukumori, I., Kim, C.-H., Yoon, J.-H., 2005. Numerical simulation and satellite altimeter data assimilation of the Japan sea circulation. Deep-Sea Research II 52, 1443–1463. http://dx.doi.org/10.1016/j.dsr2.2004.09.034. Holgate, S.J., 2007. On the decadal rates of sea level change during the twentieth century. Geophysical Research Letters 34, L01602. http://dx.doi.org/10.1029/ 2006GL028492. Inazu, D., Hirose, N., Kizu, S., Hanawa, K., 2006. Zonally asymmetric response of the japan sea to synoptic pressure forcing. Journal of Oceanography 62, 909–916. Ishii, M., Kimoto, M., 2009. Reevaluation of historical ocean heat content variations with time-varying XBT and MBT depth bias corrections. Journal of Oceanography 65, 287–299.

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