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In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings mentioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology. The paper starts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the “Green” Ocean, extending the frontier from biogeochemistry to marine ecology. Applications are described in a subsequent section, which covers Operational Oceanography, Weather, Hurricane Wave and Wind Forecasting, Climate projection. Instruments’ development and satellite missions’ evolutions are described in a fourth section. A fifth section covers the key observations that altimeters provide and their potential complements, from other Earth observation measurements to in situ data. Section 6 identifies the data and methods and provides some accuracy and resolution requirements for the wet tropospheric correction, the orbit and other geodetic requirements, the Mean Sea Surface, Geoid and Mean Dynamic Topography, Calibration and Validation, data accuracy, data access and handling (including the DUACS system). Section 7 brings a transversal view on scales, integration, artificial intelligence, and capacity building (education and training). Section 8 reviews the programmatic issues followed by a conclusion.

Since the beginning of the 1990s, sea level is routinely measured using high-precision satellite altimetry. Over the past ~25 years, several groups worldwide involved in processing the satellite altimetry data regularly provide updates of sea level time series at global and regional scales. Here we present an ongoing effort supported by the European Space Agency (ESA) Climate Change Initiative Programme for improving the altimetry-based sea level products. Two main objectives characterize this enterprise: (1) to make use of ESA missions (ERS-1 and 2 and Envisat) in addition to the so-called 'reference' missions like TOPEX/Poseidon and the Jason series in the computation of the sea level time series, and (2) to improve all processing steps in order to meet the Global Climate Observing System (GCOS) accuracy requirements defined for a set of 50 Essential Climate Variables, sea level being one of them. We show that improved geophysical corrections, dedicated processing algorithms, reduction of instrumental bias and drifts, and careful linkage between missions led to improved sea level products. Regarding the long-term trend, the new global mean sea level record accuracy now approaches the GCOS requirements (of ~0.3 mm/year). Regional trend uncertainty has been reduced by a factor of ~2, but orbital and wet tropospheric corrections errors still prevent fully reaching the GCOS accuracy requirement. Similarly at the interannual time scale, the global mean sea level still displays 2-4 mm errors that are not yet fully understood. The recent launch of new altimetry missions (Sentinel-3, Jason-3) and the inclusion of data from currently flying missions (e.g., CryoSat, SARAL/AltiKa) may provide further improvements to this important climate record. [ABSTRACT FROM AUTHOR]

The current mean sea level (MSL) continuous record, essential for the understanding of climate evolution, is computed with the altimetric measurements of the TOPEX/Poseidon mission, succeeded by Jason-1 and later Jason-2. The accurate continuity of the record is ensured by the conservation of the "historical" TOPEX orbit, but also by calibration phases between the successive missions which enable a rigorous computation of their relative biases. In order to extend the current MSL record, Jason-3 will be the natural successor of Jason-2: on the same orbit with a calibration phase. Shortly after Jason-3, another altimetric climate-oriented mission, Sentinel-3a, will be launched on a different orbit. In this paper, simulated altimetric sea level data is used to study the sensitivity of the MSL continuous record to the change of the "historical" orbit for the new Sentinel-3a orbit. By estimating the impact of the absence of calibration phase on the MSL continuous record trend accuracy at global and regional scale and the impact of the orbit change on the long-term continuity of this MSL record, this study shows that linking Sentinel-3a data instead of Jason-3 to the MSL continuous record would prevent from meeting climate users requirements regarding the MSL trend accuracy. [ABSTRACT FROM AUTHOR]

We investigate sea level variability in the Arctic Ocean from observations. Variability estimates are derived both at the basin scale and on smaller local spatial scales. The periods of the signals studied vary from high frequency (intra-annual) to long term trends. We also investigate the mechanisms responsible for the observed variability. Different data types are used, the main one being a recent reprocessing of satellite altimetry data in the Arctic Ocean. Satellite altimetry data is compared to tide gauges measurements, steric sea level derived from temperature and salinity fields and GRACE ocean mass estimates. We establish a consistent regional sea level budget over the GRACE availability era (2003- 2009) showing that the sea level drop observed by altimetry over this period is driven by ocean mass loss rather than steric effects. The comparison of altimetry and tide gauges time series show that the two techniques are in good agreement regarding sea level trends. Coastal areas of high variability in the altimetry record are also consistent with tide gauges records. An EOF analysis of September mean altimetry fields allows identifying two regions of wind driven variability in the Arctic Ocean: the Beaufort Gyre region and the coastal European and Russian Arctic. Such patterns are related to atmospheric regimes through the Arctic Oscillation and Dipole Anomaly. [ABSTRACT FROM AUTHOR]

This paper gives an overview of an empirical cross-calibration technique developed for the Surface Water Ocean Topography mission (SWOT). The method is here used to detect and to mitigate two spatially coherent errors in SWOT topography data: the baseline roll error whose signature is linear across track, and the baseline length error whose signature is quadratic across track. Assuming that topography data are corrupted by coherent error signatures that we can model, we extract the signatures, and we empirically use the error estimates to correct SWOT data. The cross-calibration is tackled with a two-step scheme. The first step is to get local estimates over cross-calibration zones, and the second step is to perform a global interpolation of local error estimates and to mitigate the error everywhere. Three methods are used to get local error estimates: 1) we remove a static first guess reference such as a digital elevation model, 2) we exploit overlapping diamonds between SWOT swaths, and 3) we exploit overlapping segments with traditional pulse-limited altimetry sensors. Then, the along-track propagation is performed taking the local estimates as an input, and an optimal interpolator (1-D objective analysis) constrained with a priori statistical knowledge of the problem. The rationale of this paper is to assume that SWOT's scientific requirements are met on all errors but the ones being cross-calibrated. In other words, the algorithms presented in this paper are not needed at this stage of the mission definition, and they are able to deal with higher error levels (e.g., if hardware constraints are relaxed and replaced by additional ground processing). Even in our most pessimistic theoretical scenarios of baseline roll and baseline length errors (up to 70 cm RMS of uncorrected topography error), the cross-calibration algorithm reduces coherent errors to less than 2 cm (outer edges of the swath). Residual errors are subcentimetric for very low-frequency errors (e.g., orbital revolution). Sensitivity tests highlight the benefits of using additional pulse-limited altimeters and optimal inversion schemes when the problem is more difficult to solve (e.g., wavelengths of less than 1000 km), but also to provide a geographically homogeneous correction that cannot be obtained with SWOT's sampling alone. [ABSTRACT FROM AUTHOR]