The coastal mean dynamic topography in Norway observed by CryoSat‐2 and GOCE

Abstract

New‐generation synthetic aperture radar altimetry, as implemented on CryoSat‐2, observes sea surface heights in coastal areas that were previously not monitored by conventional altimetry. Therefore, CryoSat‐2 is expected to improve the coastal mean dynamic topography (MDT). However, the MDT remains highly reliant on the geoid. Using new regional geoid models as well as CryoSat‐2 data, we determine three geodetic coastal MDT models in Norway and validate them against independent tide‐gauge observations and the operational coastal ocean model NorKyst800. The CryoSat‐2 MDTs agree on the ∼3–5 cm level with both tide‐gauge geodetic and ocean MDTs along the Norwegian coast. In addition, we compute geostrophic surface currents to help identifying errors in the geoid models. We find that even though the regional geoid models are all based on the latest satellite gravity data as provided by GOCE, the resulting circulation patterns differ. We demonstrate that some of these differences are due to erroneous or lack of marine gravity data. This suggests that there is significant MDT signal at spatial scales beyond GOCE, and that the geodetic approach to MDT determination benefits from the additional terrestrial gravity information provided by a regional geoid model. We also find that the border of the geographical mode mask of CryoSat‐2 coincides with the Norwegian Coastal Current, making it challenging to distinguish between artifacts in the CryoSat‐2 observations during mode switch and ocean signal.

Comparison between geodetic and oceanographic approaches to estimate mean dynamic topography for vertical datum unification: evaluation at Australian tide gauges

“…Finally, our values are comparable to estimates from, e.g., Ophaug et al (2015) and Idžanović et al (2017) along the Norwegian coast and Lin et al (2015) along the Pacific coasts of Japan and North America. Although there may be correlation among some of the ocean models, they generally appear to provide errors of a similar magnitude, or less, than those from the geoid models at the tide gauge locations (Fig.…”

“…However, the comparisons conducted in Section 3 do go some way to providing upper and lower bounds. Previous studies around Australia (Featherstone and Filmer 2012;Filmer 2014) and in other regions (Woodworth et al 2012;Hughes et al 2015;Lin et al 2015;Ophaug et al 2015;Higginson et al 2015;Mazloff et al 2014;Idžanović et al 2017) found standard deviation (SD) of differences among MDT models ranging from ~±30 mm to ~±80 mm. The resolution-induced (omission) errors discussed above are subsumed within these SDs, but will vary depending on the spatial resolution of the different models (Table 1).…”

Improving the Coastal Mean Dynamic Topography by Geodetic Combination of Tide Gauge and Satellite Altimetry

“…This can be done through the integration with very highresolution ocean model. Local analysis into the Norwegian MDT demonstrated the value of SAR altimetry in mapping local coastal topographies from CryoSat-2 (Idžanović et al, 2017). Along the Norwegian coast strong levelling ties between tide gauges permit a comparison, which is not dependent on direct GPS measurements at each gauge.…”

Determining Coastal Mean Dynamic Topography by Geodetic Methods

“…Frequently, regional geoid models are extended over oceans as a by-product. When the marine gravity data come from terrestrial gravity measurements (as opposed to altimetry), the resulting geoid models are suitable for determining the coastal MDT (Higginson et al, 2015;Hipkin, 2000;Idžanović et al, 2017;Lin et al, 2015;Ophaug et al, 2015). Otherwise, caution must be taken in the interpretation of the resulting MDT.…”