This report is a quantitative study of gravity field and geoid, mean sea surface, mean ocean dynamic topography and tides for the Arctic Ocean, for a large range of existing and new models. The report gives quantitative assessments of errors and error covariances of the different fields, mainly for use of understanding total errors in the mean sea surface (MSS). The error studies are especially directed towards the CryoSat sea-ice freeboard processor, where the MSS is the basic reference surface, especially in order to quantify if this processor will benefit from adaptive “smart” interpolation, where the varying error covariances of the MSS are taken into account. As part of the studies a new Arctic gravity field model and geoid has been derived, based on all available terrestrial and airborne gravity data and GRACE satellite data, augmented with gravity field information from ICESat. Rigorous error and covariance of studies of the computed geoid model have been done, showing that the new Arctic geoid is accurate to better than 10 cm over most of the region. Mean dynamic ocean topography is estimated from remote sensing by combining ERS and ICESat altimetry with the geoid, and compared to four different oceanographic models. The comparison shows large differences between the different oceanographic models, and a reasonable agreement to the results from remote sensing. This part of the study illustrates the potential of future radar altimetry missions such as Cryosat for determining ocean dynamic topography and its temporal changes, in addition to the sea ice freeboard heights. A number of tidal models are intercompared, and compared to tide gauge data in the Canadian Arctic. The presence of sea-ice is found to damp the tidal amplitudes and it appears that tidal errors will be a major regionally-dependent error source in sea surface determination for CryoSat. The error covariances and model comparisons are used in a “smart” adaptive estimator scheme, where a linear interpolator operator, similar to the future CryoSat freeboard estimator, is used to quantify errors of the interpolator. Some suggestions for utilization of GOCE data are included in the report, as well as recommendations and a future outlook. The work described in this report was done under ESA Contract. Responsibility for the contents resides in the author or organisation that prepared it. Authors: R. Forsberg, H. Skourup, O. B. Andersen, P. Knudsen, S. W. Laxon, A. Ridout, J. Johannesen, F. Siegismund, H. Drange, C. C. Tscherning, D. Arabelos, A. Braun, and V. Renganathan NAME OF ESA STUDY MANAGER Mark Drinkwater Division: Mission Science Division Directorate: Earth Observations Programmes ESA BUDGET HEADING

Simulated CryoSat ice thickness measurements have been assimilated into a coupled ice‐ocean model to examine the impact in Arctic ocean prediction systems. The model system is based on the HYbrid Coordinate Ocean Model (HYCOM) and the EVP ice rheology, and the data assimilation method is the Ensemble Kalman Filter (EnKF). It is shown how ocean salinity, surface temperature, and ice concentration fields are affected by the ice thickness assimilation, and how these fields are improved relative to a free‐run experiment of the model. The ice thickness assimilation primarily affects the surface properties of the ocean. By running two different assimilation experiments, it is shown how the choice of stochastic forcing is crucial to the performance of the assimilation. Specifically, it is shown how stochastic wind forcing is important to correctly describe model prediction errors, which are important for the data assimilation step. The assimilation experiments illustrate how the ice thickness observations can have a strong impact on the ice thickness estimates of the model system. The manner in which the EnKF forcing is set up is crucial, but with the correct setup, the assimilation of ice thickness measurements could have a beneficial effect on the modeled ice thickness and ocean fields.

The RA-2 altimeter is intended to continue an uninterrupted series of measurements of sea-level and ice-sheet elevation start- ed by ERS-1 in 1991. To fully exploit these measurements, an absolute reference in the time series, and a distinction between instrumental artifacts and significant geophysical signals, is necessary. Therefore, the range bias and instrument drift shall be determined with a accuracy of 1 cm and 1 mm/year respectively. Such accuracies can only be achieved by using: • a large number of measurements to reduce random errors; • a diversity of measurement techniques and independent data analysis to reduce susceptibility to systematic errors. Due to the limited temporal sampling of the 35-day repeat orbit of EnviSat, the resulting overall concept is a regional cali- bration which makes use of the north-western Mediterranean basin as a reference surface, with a number of particular of high-confidence "super-sites". Measurement of the vertical-incidence backscatter coefficient, sigma-0, by radar altimeters has been used for the determina- tion of wind-speed over the ocean. The models used are empirical and so it has been sufficient to perform relative calibration between missions. These are traced back to GEOS-3 resulting in a minimum uncertainty in the absolute sigma-0, for all al- timeters, of 1 dB. Recent applications of the altimeter sigma-0, such as physically based models of sea-state bias and wave period, require an absolute sigma-0 measurement. The measurement technique makes use of a newly-developed transponder, using a delay-line for clutter suppression. The al- timeter will operate in a preset mode, and will acquire individual echoes over the transponder. Special data-processing tech- niques are also being developed. During the six month of commissioning an in-flight instrument verification activity will also be performed, with the following main objectives: • Instrument verification of main capabilities and operations in all its modes. • Instrument parameter tuning and optimisation: verification of optimum setting of the instrument parameter per- formed in the lab on-ground, can only be done in-flight, once the instrument is acquiring scientifically meaningful data. • Algorithm parameter optimisation, and verification of the auxiliary data retrieval and use in these algorithms. This verification is crucial for any calibration to be accurate. Therefore, despite the 6 months saturation of the overall veri - fication activity, sometime after the RA-2 switch-on, the data shall be such that is accurate enough for calibration purposes.

Various recent marine altimetric gravity fields based on geodetic mission altimetry are compared with ship borne gravity in four regions around Greenland. This is done over different states of the ocean surface ranging from ice free open ocean to permanently ice covered ocean. Distinguishing between results obtained over these different states is important because, usually, the accuracy of the altimetric products decreases with increasing coverage of ice and proximity to coast.

It is important for global climate research to understand the Arctic Ocean and, in particular, the variations - with time and place - in its sea ice thickness. A new effort is now underway to redress the gap in our scientific knowledge of the Arctic. This article focuses on two relatively new methods for observing and mapping gravity that are major contributors to these new studies in Arctic science. These techniques are: retracked Earth Remote Sensing (ERS) satellite altimetry and Naval Research Laboratory (NRL) airborne gravimetry. Other contributors to this endeavor include the ongoing Scientific Ice Experiment (SCICEX) program to collect unclassified marine geophysical data from U.S. Navy nuclear powered submarines as well release of previously classified U.S. Navy bathymetric data.

The L1b processor is designed to process raw, level0, data from the RA-2 instrument to apply engineering and other corrections. From the Level 0 data (which are basically telemetry data) the Level 1b processor is applied and output the Level 1b product. In doing this auxiliary data is used. These algorithms and the parameters used in this process shall be verified and possibly tuned. Later the output of the Level 1b will be used to produce the Level 2, which is the product commonly used by the scientific community. The investigations, modifications applied to the algorithms as results of the investigations and the final results are described in this paper.

The derivation of a marine gravity field from satellite altimetry over permanently ice-covered regions of the Arctic Ocean provides much new geophysical information about the structure and development of the Arctic sea floor. The Arctic Ocean, because of its remote location and perpetual ice cover, remains from a tectonic point of view the most poorly understood ocean basin on Earth. A gravity field has been derived with data from the ERS-1 radar altimeter, including permanently ice-covered regions. The gravity field described here clearly delineates sections of the Arctic Basin margin along with the tips of the Lomonosov and Arctic mid-ocean ridges. Several important tectonic features of the Amerasia Basin are clearly expressed in this gravity field. These include the Mendeleev Ridge; the Northwind Ridge; details of the Chukchi Borderland; and a north-south trending, linear feature in the middle of the Canada Basin that apparently represents an extinct spreading center that ''died'' in the Mesozoic. Some tectonic models of the Canada Basin have proposed such a failed spreading center, but its actual existence and location were heretofore unknown.

Sea ice presents a serious impediment to both shipping and off-shore operations in the polar regions. Since sea ice conditions can change within a matter of hours, near real time monitoring is required. Airborne data are available in some areas, but collection is expensive and coverage limited. Satellite images can provide wider coverage, but cloud cover, darkness and the need for rapid processing and dissemination can limit their use. Information on sea ice cover over longer periods is needed for global climate monitoring. Microwave sensors provide the most practical means of monitoring global sea ice cover since they can operate both at night and day and observe through clouds. Previous studies have concentrated on the use of passive microwave data.Here we discuss the routine monitoring of sea ice using the ERS-1 radar altimeter. The low data rate and somewhat simple nature of the data, lend themselves to the mapping of global sea ice cover and to operational applications.We review the processing adopted at the U.K. EODC.

Over land ice and land, satellite altimeters provide valuable topographic information, in spite of having been designed primarily to operate over the ocean. There is a need, however, for careful data quality assessment and screening as erroneous elevation measurements can be included within the telemetered data, especially when the range tracker encounters complex echoes, or rapidly varying topography. The ERS‐1 Fast Delivery (FD) data product provides an excellent source of near real‐time data, which has already been used for ice sheet mapping. This is a reduced data set consisting of on‐board parameters generated once per second. In this paper we show that by applying thresholds to two parameters, significant amounts of poorly tracked data can be eliminated. The effectiveness of this filtering technique is demonstrated by a comparison of filtered and unfiltered altimeter data with a digital elevation model. This filtering technique is applied to the first 35 day repeat cycle of FD data obtained over land to produce the first map of global topography from ERS‐1.

Sea ice maps are required by a diverse range of users for scientific research and operational activities. Satellite remote sensing provides opportunities for monitoring and producing sea ice maps at a range of scales, in near real time. During March 1994 ESYS Limited and the University College London Mullard Space Science Laboratory (MSSL) operated a sea ice demonstration project to supply near real time sea ice maps in the southern ocean. The sea ice information was derived from a number of data sources: DMSP SSM/I data; ERS-1 SAR and Radar Altimeter fast delivery data; NOAA AVHRR data; and PoSAT-1 imagery. The maps were supplied to three users, two involved in yacht races in the southern ocean and a ship on an oceanographic research cruise in the waters of the Princess Elizabeth Trough region of Antarctica. The demonstration was successful, supplying the users with sea ice information which they had previously not received and combining data from various sources to produce sea ice maps. The demonstration also developed operational skills within ESYS and enabled the transfer of knowledge from MSSL to ESYS.

(1993). Antarctic ice sheet topography mapped with the ERS-1 radar altimeter. International Journal of Remote Sensing: Vol. 14, No. 9, pp. 1649-1650.

This chapter contains sections titled: Introduction Instrument Description Sea Ice Scattering Models at Normal Incidence Theory Versus Measurement Summary

Previous work has shown that interannual variations in total sea ice extent may provide a sensitive indicator of global climate change. Data from passive microwave instruments have allowed mapping of global sea ice extents from 1973–76 and from 1978 up to September 1987, [Gloerson and Campbell, 1988]. In this paper data from another microwave instrument, the Geosat radar altimeter, have been used to map the Antarctic sea ice extent for the period November 1986 to January 1989. Comparison with total Antarctic sea ice extents derived from the Scanning Multichannel Microwave Radiometer (SMMR) show excellent agreement during the freeze up period but show significant differences during the late part of the melt period.

RESUME As part of the winter Marginal Ice Zone Experiment (MIZEX-87) an aircraft with Synthetic Aperature Radar (SAR) flew under a concurrent GEOSAT track across the pack ice east of Greenland in ApriLl987. Results from a comparison of cluster analysis of the SAR image with altimeter echo components are presented and interpreted. Both the SAR and altimeter are shown to discriminate distinct zones of ice characteristics within the pack ice. This study represents a collaborative effort between ERS-1 and GEOSAT principal investigators and is expected to lead to improved ice monitoring algorithms for both satellites.