Latest Observational Results from the Superconducting Gravimeter at Station Wuhan and Investigation of Ocean Tide Models

Solid Earth is affected by tidal cycles triggered by the gravity attraction of the celestial bodies. However, about 70% the Earth is covered with seawater which is also affected by the tidal forces. In the coastal areas, the ocean tide loading (OTL) can reach up to 10% of the earth tide, 90% for tilt, and 25% for strain (Farrell, 1972). Since 2007, a high-precision continuous gravity observation network in China has been established with 78 stations. The long-term high-precision tidal data of the network can be used to validate, verifying and even improve the ocean tide model (OTM).In this paper, tidal parameters of each station were extracted using the harmonic analysis method after a careful editing of the data. 8 OTMs were used for calculating the OTL. The results show that the Root-Mean-Square of the tidal residuals (M0) vary between 0.078-1.77 &#956;gal, and the average errors as function of the distance from the sea for near(0-60km), middle(60-1000km) and far(>1000km) stations are 0.76, 0.30 and 0.21 &#956;gal. The total final gravity residuals (Tx) of the 8 major constituents (M2, S2, N2, K2, K1, O1, P1, Q1) for the best OTM has amplitude ranging from 0.14 to 3.45 &#956;gal. The average efficiency for O1 is 77.0%, while 73.1%, 59.6% and 62.6% for K1, M2 and Tx. FES2014b provides the best corrections for O1 at 12 stations, while SCHW provides the best for K1 ,M2and Tx at 12,8and 9 stations. For the 11 costal stations, there is not an obvious best OTM. The models of DTU10, EOT11a and TPXO8 look a litter better than FES2014b, HAMTIDE and SCHW. For the 17 middle distance stations, SCHW is the best OTM obviously. For the 7 far distance stations, FES2014b and SCHW model are the best models. But the correction efficiency is worse than the near and middle stations&#8217;.The outcome is mixed: none of the recent OTMs performs the best for all tidal waves at all stations. Surprisingly, the Schwiderski&#8217;s model although is 40 years old with a coarse resolution of 1&#176; x 1&#176; is performing relative well with respect to the more recent OTM. Similar results are obtained in Southeast Asia (Francis and van Dam, 2014). It could be due to systematic errors in the surroundings seas affecting all the ocean tides models. It's difficult to detect, but invert the gravity attraction and loading effect to map the ocean tides in the vicinity of China would be one way.

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Errors in recent ocean tide models: possible origin and cause

Progress In Oceanography ◽

10.1016/s0079-6611(98)00007-x ◽

1997 ◽

Vol 40 (1-4) ◽

pp. 325-336 ◽

Cited By ~ 8

Author(s):

A.J.E. Smith ◽

O.B. Andersen

Keyword(s):

Ocean Tide ◽

Ocean Tide Models

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An Assessment of Global Ocean Barotropic Tide Models Using Geodetic Mission Altimetry and Surface Drifters

Journal of Physical Oceanography ◽

10.1175/jpo-d-20-0089.1 ◽

2021 ◽

Vol 51 (1) ◽

pp. 63-82

Author(s):

Edward D. Zaron ◽

Shane Elipot

Keyword(s):

Shallow Water ◽

Deep Water ◽

Variance Reduction ◽

Model Performance ◽

Data Sources ◽

Global Ocean ◽

Ocean Tide ◽

Analysis Model ◽

Surface Drifters ◽

Ocean Tide Models

AbstractThe accuracy of three data-constrained barotropic ocean tide models is assessed by comparison with data from geodetic mission altimetry and ocean surface drifters, data sources chosen for their independence from the observational data used to develop the tide models. Because these data sources do not provide conventional time series at single locations suitable for harmonic analysis, model performance is evaluated using variance reduction statistics. The results distinguish between shallow and deep-water evaluations of the GOT410, TPXO9A, and FES2014 models; however, a hallmark of the comparisons is strong geographic variability that is not well summarized by global performance statistics. The models exhibit significant regionally coherent differences in performance that should be considered when choosing a model for a particular application. Quantitatively, the differences in explained SSH variance between the models in shallow water are only 1%–2% of the root-mean-square (RMS) tidal signal of about 50 cm, but the differences are larger at high latitudes, more than 10% of 30-cm RMS. Differences with respect to tidal currents variance are strongly influenced by small scales in shallow water and are not well represented by global averages; therefore, maps of model differences are provided. In deep water, the performance of the models is practically indistinguishable from one another using the present data. The foregoing statements apply to the eight dominant astronomical tides M2, S2, N2, K2, K1, O1, P1, and Q1. Variance reduction statistics for smaller tides are generally not accurate enough to differentiate the models’ performance.

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