Collecte Localisation Satellites (France)

Objective analysis of altimetric data (sea level anomaly) usually assumes that measurement errors are well represented by a white noise, though there are long-wavelength errors that are correlated over thousands of kilometers along the satellite tracks. These errors are typically 3 cm rms for TOPEX/Poseidon (T/P), which is not negligible in low-energy regions. Analyzing maps produced by conventional objective analysis thus reveals residual long-wavelength errors in the form of tracks on the maps. These errors induce sea level gradients perpendicular to the track and, therefore, high geostrophic velocities that can obscure ocean features. To overcome this problem, an improved objective analysis method that takes into account along-track correlated errors is developed. A specific data selection is used to allow an efficient correction of long-wavelength errors while estimating the oceanic signal. The influence of data selection is analyzed, and the method is first tested with simulated data. The method is then applied to real T/P and ERS-1 data in the Canary Basin (a region typical of low eddy energy regions), and the results are compared to those of a conventional objective analysis method. The correction for the along-track long-wavelength error has a very significant effect. For T/P and ERS-1 separately, the mapping difference between the two methods is about 2 cm rms (20% of the signal variance). The variance of the difference in zonal and meridional velocities is roughly 30% and 60%, respectively, of the velocity signal variance. The effect is larger when T/P and ERS-1 are combined. Correcting the long-wavelength error also considerably improves the consistency between the T/P and ERS-1 datasets. The variance of the difference (T/P–ERS-1) is reduced by a factor of 1.7 for the sea level, 1.6 for zonal velocities, and 2.3 for meridional velocities. The method is finally applied globally to T/P data. It is shown that it is tractable at the global scale and that it provides an improved mapping.

Abstract. The new DUACS DT2014 reprocessed products have been available since April 2014. Numerous innovative changes have been introduced at each step of an extensively revised data processing protocol. The use of a new 20-year altimeter reference period in place of the previous 7-year reference significantly changes the sea level anomaly (SLA) patterns and thus has a strong user impact. The use of up-to-date altimeter standards and geophysical corrections, reduced smoothing of the along-track data, and refined mapping parameters, including spatial and temporal correlation-scale refinement and measurement errors, all contribute to an improved high-quality DT2014 SLA data set. Although all of the DUACS products have been upgraded, this paper focuses on the enhancements to the gridded SLA products over the global ocean. As part of this exercise, 21 years of data have been homogenized, allowing us to retrieve accurate large-scale climate signals such as global and regional MSL trends, interannual signals, and better refined mesoscale features.An extensive assessment exercise has been carried out on this data set, which allows us to establish a consolidated error budget. The errors at mesoscale are about 1.4 cm2 in low-variability areas, increase to an average of 8.9 cm2 in coastal regions, and reach nearly 32.5 cm2 in high mesoscale activity areas. The DT2014 products, compared to the previous DT2010 version, retain signals for wavelengths lower than ∼ 250 km, inducing SLA variance and mean EKE increases of, respectively, +5.1 and +15 %. Comparisons with independent measurements highlight the improved mesoscale representation within this new data set. The error reduction at the mesoscale reaches nearly 10 % of the error observed with DT2010. DT2014 also presents an improved coastal signal with a nearly 2 to 4 % mean error reduction. High-latitude areas are also more accurately represented in DT2014, with an improved consistency between spatial coverage and sea ice edge position. An error budget is used to highlight the limitations of the new gridded products, with notable errors in areas with strong internal tides.

The future international Surface Water and Ocean Topography (SWOT) Mission, planned for launch in 2021, will make high-resolution 2D observations of sea-surface height using SAR radar interferometric techniques. SWOT will map the global and coastal oceans up to 77.6° latitude every 21 days over a swath of 120 km (20 km nadir gap). Today’s 2D mapped altimeter data can resolve ocean scales of 150 km wavelength whereas the SWOT measurement will extend our 2D observations down to 15-30 km, depending on sea state. SWOT will offer new opportunities to observe the oceanic dynamic processes at these scales, that are important in the generation and dissipation of kinetic energy in the ocean, and act as one of the main gateways connecting the interior of the ocean to the upper layer. The active vertical exchanges linked to these scales have impacts on the local and global budgets of heat and carbon, and on nutrients for biogeochemical cycles. This review paper highlights the issues being addressed by the SWOT science community to understand SWOT’s very precise SSH / surface pressure observations, and it explores how SWOT data will be combined with other satellite and in-situ data and models to better understand the upper ocean 4D circulation (x,y,z,t) over the next decade. SWOT’s new SAR-interferometry technology aims to observe ocean SSH scales down to 15-30 km in wavelength. At these scales, SSH includes “balanced” geostrophic eddy motions and high-frequency internal tides and internal waves. This presents both a challenge in reconstructing the 4D upper ocean circulation, or in the assimilation of SSH in models, but also an opportunity to have global observations of the 2D structure of these phenomena, and to learn more about their interactions. At these small scales, the ocean dynamics evolve rapidly, and combining SWOT 2D SSH data with other satellite or in-situ data with different space-time coverage is also a challenge. SWOT’s new technology will be a forerunner for the future altimetric observing system, and so advancing on these issues today will pave the way for our future.

Abstract. Since the mid-1990s, a series of FES (finite element solution) global ocean tidal atlases has been produced and released with the primary objective to provide altimetry missions with tidal de-aliasing correction at the best possible accuracy. We describe the underlying hydrodynamic and data assimilation design and accuracy assessments for the latest FES2014 release (finalized in early 2016), especially for the altimetry de-aliasing purposes. The FES2014 atlas shows extremely significant improvements compared to the standard FES2004 and (intermediary) FES2012 atlases, in all ocean compartments, especially in shelf and coastal seas, thanks to the unstructured grid flexible resolution, recent progress in the (prior to assimilation) hydrodynamic tidal solutions, and use of ensemble data assimilation technique. Compared to earlier releases, the available tidal constituent's spectrum has been significantly extended, the overall resolution has been augmented, and additional scientific byproducts such as loading and self-attraction, energy diagnostics, or lowest astronomical tides have been derived from the atlas and are available. Compared to the other available global ocean tidal atlases, FES2014 clearly shows improved de-aliasing performance in most of the global ocean areas and has consequently been integrated in satellite altimetry geophysical data records (GDRs) and gravimetric data processing and adopted in recently renewed ITRF standards (International Terrestrial Reference System, 2020). It also provides very accurate open-boundary tidal conditions for regional and coastal modelling.

GLORYS12 is a global eddy-resolving physical ocean and sea ice reanalysis at 1/12° horizontal resolution covering the 1993-present altimetry period, designed and implemented in the framework of the Copernicus Marine Environment Monitoring Service (CMEMS). The model component is the NEMO platform driven at the surface by atmospheric conditions from the ECMWF ERA-Interim reanalysis. Ocean observations are assimilated by means of a reduced-order Kalman filter. Along track altimeter sea level anomaly, satellite sea surface temperature and sea ice concentration, as well as in situ temperature and salinity vertical profiles are jointly assimilated. A 3D-VAR scheme provides an additional correction for the slowly-evolving large-scale biases in temperature and salinity. The performance of the reanalysis shows a clear dependency on the time-dependent in situ observation system. The general assessment of GLORYS12 highlights a level of performance at the state-of-the-art and the capacity of the system to capture the main expected climatic interannual variability signals for ocean and sea ice, the general circulation and the inter-basins exchanges. In terms of trends, GLORYS12 shows a higher than observed warming trend together with a slightly lower than observed global mean sea level rise. Comparisons made with an experiment carried out on the same platform without assimilation show the benefit of data assimilation in controlling water mass properties and sea ice cover and their low frequency variability. Moreover, GLORYS12 represents particularly well the small-scale variability of surface dynamics and compares well with independent (non-assimilated) data. Comparisons made with a twin experiment carried out at 1/4° resolution allows characterizing and quantifying the strengthened contribution of the 1/12° resolution onto the downscaled dynamics. GLORYS12 provides a reliable physical ocean state for climate variability and supports applications such as seasonal forecasts. In addition, this reanalysis has strong assets to serve regional applications and provide relevant physical conditions for applications such as marine biogeochemistry. In the near future, GLORYS12 will be maintained to be as close as possible to real time and could therefore provide relevant and continuous reference past ocean states for many operational applications.

Abstract. Since 19 October 2016, and in the framework of Copernicus Marine Environment Monitoring Service (CMEMS), Mercator Ocean has delivered real-time daily services (weekly analyses and daily 10-day forecasts) with a new global 1∕12∘ high-resolution (eddy-resolving) monitoring and forecasting system. The model component is the NEMO platform driven at the surface by the IFS ECMWF atmospheric analyses and forecasts. Observations are assimilated by means of a reduced-order Kalman filter with a three-dimensional multivariate modal decomposition of the background error. Along-track altimeter data, satellite sea surface temperature, sea ice concentration, and in situ temperature and salinity vertical profiles are jointly assimilated to estimate the initial conditions for numerical ocean forecasting. A 3D-VAR scheme provides a correction for the slowly evolving large-scale biases in temperature and salinity. This paper describes the recent updates applied to the system and discusses the importance of fine tuning an ocean monitoring and forecasting system. It details more particularly the impact of the initialization, the correction of precipitation, the assimilation of climatological temperature and salinity in the deep ocean, the construction of the background error covariance and the adaptive tuning of observation error on increasing the realism of the analysis and forecasts. The scientific assessment of the ocean estimations are illustrated with diagnostics over some particular years, assorted with time series over the time period 2007–2016. The overall impact of the integration of all updates on the product quality is also discussed, highlighting a gain in performance and reliability of the current global monitoring and forecasting system compared to its previous version.

The lack of an accurate geoid still prevents precise computation of the ocean absolute dynamic topography from satellite altimetry and only sea level anomalies (SLA) can be accurately deduced. In the new context of Global Ocean Data Assimilation Experiment (GODAE) where models are assimilating satellite altimetry, the estimation of a realistic mean dynamic topography (MDT) consistent with SLA is a crucial issue. In a first “direct” approach, a MDT is computed by subtracting the geoid model EIGEN‐2 from the Mean Sea Surface Height CLS01, determined from 7 years of altimetric data (TOPEX and ERS1,2) at spherical harmonic degree 30. To provide the scales shorter than 660 km, the Levitus climatology is merged with the resulting MDT, both weighted by their respective errors. This solution provides a “first guess” for the computation of a global and higher resolution MDT. Then, a “synthetic” technique is used to combine in situ measurements and altimetric data: TOPEX and ERS1,2 altimetric anomalies are subtracted from in situ measurements of the full dynamical signal (based on buoy velocities from the WOCE‐TOGA program and XBT, CTD casts). The resulting values provide local estimates of the mean field, in terms of currents or dynamic topography, which are used to improve the first guess using an inverse technique. The MDT obtained is compared to other mean dynamic fields, and a verification using independent in situ data shows improvements in most areas. It exhibits a more energetic representation of the subtropical and subpolar gyres; sea level gradients associated with the main currents are strongly enhanced. Differences with independent velocity observations are globally lower than 13 cm/s rms.

Abstract Fish population variability and fisheries activities are closely linked to weather and climate dynamics. While weather at sea directly affects fishing, environmental variability determines the distribution, migration, and abundance of fish. Fishery science grew up during the last century by integrating knowledge from oceanography, fish biology, marine ecology, and fish population dynamics, largely focused on the great Northern Hemisphere fisheries. During this period, understanding and explaining interannual fish recruitment variability became a major focus for fisheries oceanographers. Yet, the close link between climate and fisheries is best illustrated by the effect of “unexpected” events—that is, nonseasonal, and sometimes catastrophic—on fish exploitation, such as those associated with the El Niño–Southern Oscillation (ENSO). The observation that fish populations fluctuate at decadal time scales and show patterns of synchrony while being geographically separated drew attention to oceanographic processes driven by low-frequency signals, as reflected by indices tracking large-scale climate patterns such as the Pacific decadal oscillation (PDO) and the North Atlantic Oscillation (NAO). This low-frequency variability was first observed in catch fluctuations of small pelagic fish (anchovies and sardines), but similar effects soon emerged for larger fish such as salmon, various groundfish species, and some tuna species. Today, the availability of long time series of observations combined with major scientific advances in sampling and modeling the oceans’ ecosystems allows fisheries science to investigate processes generating variability in abundance, distribution, and dynamics of fish species at daily, decadal, and even centennial scales. These studies are central to the research program of Global Ocean Ecosystems Dynamics (GLOBEC). This review presents examples of relationships between climate variability and fisheries at these different time scales for species covering various marine ecosystems ranging from equatorial to subarctic regions. Some of the known mechanisms linking climate variability and exploited fish populations are described, as well as some leading hypotheses, and their implications for their management and for the modeling of their dynamics. It is concluded with recommendations for collaborative work between climatologists, oceanographers, and fisheries scientists to resolve some of the outstanding problems in the development of sustainable fisheries.

An accurate knowledge of the ocean mean dynamic topography (MDT) is mandatory for the optimal use of altimetric data, including their assimilation into operational ocean forecasting systems. A new global 1/4° resolution MDT was computed for the 1993–1999 time period with improved data and methodology compared to the previous RIO05 MDT field. First, a large‐scale MDT is obtained from the CLS01 altimetric Mean Sea Surface and a recent geoid model computed from 4.5 years of GRACE (Gravity Recovery and Climate Experiment) data. Altimetric sea level anomalies and in situ measurements are then combined to compute synthetic estimates of the MDT and the corresponding mean currents. While the RIO05 MDT was based on 10 years of in situ dynamic heights and drifting buoy velocities, the new field benefits from an enlarged data set of in situ measurements ranging from 1993 to 2008 and includes all hydrological profiles from the Argo array. Moreover, the processing of the in situ data has been updated. A new Ekman model was developed to extract the geostrophic velocity component from the drifting buoy measurements. The handling of hydrologic measurements has also been revisited. Compared to the previous RIO05 solution, the new global MDT resolves much stronger gradients in western boundary currents, with mean velocities being doubled in some places. Moreover, in comparison to several other recent MDT estimates, we find that the new CNES‐CLS09 MDT is in better agreement with independent in situ observations.

In the past two decades, the Argo Program has collected, processed and distributed over two million vertical profiles of temperature and salinity from the upper two kilometers of the global ocean. A similar number of subsurface velocity observations near 1000 dbar have also been collected. This paper recounts the history of the global Argo Program, from its aspiration arising out of the World Ocean Circulation Experiment, to the development and implementation of its instrumentation and telecommunication systems, and the various technical problems encountered. We describe the Argo data system and its quality control procedures, and the gradual changes in the vertical resolution and spatial coverage of Argo data from 1999 to 2019. The accuracies of the float data have been assessed by comparison with high-quality shipboard measurements, and are concluded to be 0.002°C for temperature, 2.4 dbar for pressure, and 0.01 PSS-78 for salinity, after delayed-mode adjustments. Finally, the challenges faced by the vision of an expanding Argo Program beyond 2020 are discussed.

Abstract Accurate estimate of ocean surface currents is both a challenging issue and a growing end‐users requirement. In this paper ocean currents are calculated at two levels (surface and 15 m depth) as the sum of the geostrophic and Ekman components. First, a new, global, ° Mean Dynamic Topography, called the CNES‐CLS13 MDT, has been calculated and is now available for use by the oceanographic community. By exploiting information from surface drifters and Argo floats, the new MDT resolves spatial scales beyond the resolution permitted by the recent Gravity and Ocean Circulation Experiment (GOCE) geoid models (125 km). Associated mean geostrophic speeds in strong currents are increased by 200% on average compared to GOCE‐based mean currents. In addition, for the first time, a two‐level, monthly, empirical Ekman model that samples a spiral‐like behavior is estimated. We show that combining both pieces of information leads to improved ocean currents compared to other existing observed products.

Abstract. For more than 20 years, the multi-satellite Data Unification and Altimeter Combination System (DUACS) has been providing near-real-time (NRT) and delayed-time (DT) altimetry products. DUACS datasets range from along-track measurements to multi-mission sea level anomaly (SLA) and absolute dynamic topography (ADT) maps. The DUACS DT2018 ensemble of products is the most recent and major release. For this, 25 years of altimeter data have been reprocessed and are available through the Copernicus Marine Environment Monitoring Service (CMEMS) and the Copernicus Climate Change Service (C3S). Several changes were implemented in DT2018 processing in order to improve the product quality. New altimetry standards and geophysical corrections were used, data selection was refined and optimal interpolation (OI) parameters were reviewed for global and regional map generation. This paper describes the extensive assessment of DT2018 reprocessing. The error budget associated with DT2018 products at global and regional scales was defined and improvements on the previous version were quantified (DT2014; Pujol et al., 2016). DT2018 mesoscale errors were estimated using independent and in situ measurements. They have been reduced by nearly 3 % to 4 % for global and regional products compared to DT2014. This reduction is even greater in coastal areas (up to 10 %) where it is directly linked to the geophysical corrections applied to DT2018 processing. The conclusions are very similar concerning geostrophic currents, for which error was globally reduced by around 5 % and as much as 10 % in coastal areas.

Abstract. This paper describes an observation-based approach that efficiently combines the main components of the global ocean observing system using statistical methods. Accurate but sparse in situ temperature and salinity profiles (mainly from Argo for the last 10 yr) are merged with the lower accuracy but high-resolution synthetic data derived from satellite altimeter and sea surface temperature observations to provide global 3-D temperature and salinity fields at high temporal and spatial resolution. The first step of the method consists in deriving synthetic temperature fields from altimeter and sea surface temperature observations, and salinity fields from altimeter observations, through multiple/simple linear regression methods. The second step of the method consists in combining the synthetic fields with in situ temperature and salinity profiles using an optimal interpolation method. Results show the revolutionary nature of the Argo observing system. Argo observations now allow a global description of the statistical relationships that exist between surface and subsurface fields needed for step 1 of the method, and can constrain the large-scale temperature and mainly salinity fields during step 2 of the method. Compared to the use of climatological estimates, results indicate that up to 50% of the variance of the temperature fields can be reconstructed from altimeter and sea surface temperature observations and a statistical method. For salinity, only about 20 to 30% of the signal can be reconstructed from altimeter observations, making the in situ observing system essential for salinity estimates. The in situ observations (step 2 of the method) further reduce the differences between the gridded products and the observations by up to 20% for the temperature field in the mixed layer, and the main contribution is for salinity and the near surface layer with an improvement up to 30%. Compared to estimates derived using in situ observations only, the merged fields provide a better reconstruction of the high resolution temperature and salinity fields. This also holds for the large-scale and low-frequency fields thanks to a better reduction of the aliasing due to the mesoscale variability. Contribution of the merged fields is then illustrated to describe qualitatively the temperature variability patterns for the period from 1993 to 2009.

Data from four satellite altimeters are combined with the aim of improving the representation of the mesoscale variability in the Global Ocean. All missions [Jason‐1, ERS‐2/ENVISAT, Topex/Poseidon interleaved with Jason‐1 and Geosat Follow‐On] are cross‐calibrated previously to produce weekly gridded maps. In areas of intense variability, the rms differences between a classical configuration of two altimeters and the scenario merging four missions can reach 10 cm and 400 cm 2 /s 2 in SLA and EKE, respectively, which represents an important percentage of the signal variance. A comparison with surface drifters shows that the four altimeter scenario improves the recovery of mesoscale structures that were not properly sampled with Jason‐1 + ERS‐2/ENVISAT. Finally, the consistency between altimetric and tide gauge data is improved by about 25% when coastal sea level is estimated with 4 satellites compared to the results obtained with 2 altimeters.

Global observations of ocean swell, from satellite Synthetic Aperture Radar data, are used to estimate the dissipation of swell energy for a number of storms. Swells can be very persistent with energy e‐folding scales exceeding 20,000 km. For increasing swell steepness this scale shrinks systematically, down to 2800 km for the steepest observed swells, revealing a significant loss of swell energy. This value corresponds to a normalized energy decay in time β = 4.2 × 10 −6 s −1 . Many processes may be responsible for this dissipation. The increase of dissipation rate in dissipation with swell steepness is interpreted as a laminar to turbulent transition of the boundary layer, with a threshold Reynolds number of the order of 100,000. These observations of swell evolution open the way for more accurate wave forecasting models, and provide a constraint on swell‐induced air‐sea fluxes of momentum and energy.

Abstract. The Mediterranean Forecasting system Pilot Project has concluded its activities in 2001, achieving the following goals: 1. Realization of the first high-frequency (twice a month) Voluntary Observing Ship (VOS) system for the Mediterranean Sea with XBT profiles for the upper thermocline (0–700 m) and 12 n.m. along track nominal resolution; 2. Realization of the first Mediterranean Multidisciplinary Moored Array (M3A) system for the Near-Real-Time (NRT) acquisition of physical and biochemical observations. The actual observations consists of: air-sea interaction parameters, upper thermocline (0–500 m) temperature, salinity, oxygen and currents, euphotic zone (0–100 m) chlorophyll, nutrients, Photosinthetically Available Radiation (PAR) and turbidity; 3. Analysis and NRT dissemination of high quality along track Sea Level Anomaly (SLA), Sea Surface Temperature (SST) data from satellite sensors to be assimilated into the forecasting model; 4. Assembly and implementation of a multivariate Reduced Order Optimal Interpolation scheme (ROOI) for assimilation in NRT of all available data, in particular, SLA and VOS-XBT profiles; 5. Demonstration of the practical feasibility of NRT ten day forecasts at the Mediterranean basin scale with resolution of 0.125° in latitude and longitude. The analysis or nowcast is done once a week; 6. Development and implementation of nested regional (5 km) and shelf (2–3 km) models to simulate the seasonal variability. Four regional and nine shelf models were implemented successfully, nested within the forecasting model. The implementation exercise was carried out in different region/shelf dynamical regimes and it was demonstrated that one-way nesting is practical and accurate; 7. Validation and calibration of a complex ecosystem model in data reach shelf areas, to prepare for forecasting in a future phase. The same ecosystem model is capable of reproducing the major features of the primary producers’ carbon cycle in different regions and shelf areas. The model simulations were compared with the multidisciplinary M3A buoy observations and assimilation techniques were developed for the biochemical data. This paper overviews the methodological aspects of the research done, from the NRT observing system to the forecasting/modelling components and to the extensive validation/calibration experiments carried out with regional/shelf and ecosystem models. Key words. Oceanography: general (ocean prediction; instruments and techniques) Oceanography: physical (currents)

The Atlantic Ocean overturning circulation is important to the climate system because it carries heat and carbon northward, and from the surface to the deep ocean. The high salinity of the subpolar North Atlantic is a prerequisite for overturning circulation, and strong freshening could herald a slowdown. We show that the eastern subpolar North Atlantic underwent extreme freshening during 2012 to 2016, with a magnitude never seen before in 120 years of measurements. The cause was unusual winter wind patterns driving major changes in ocean circulation, including slowing of the North Atlantic Current and diversion of Arctic freshwater from the western boundary into the eastern basins. We find that wind-driven routing of Arctic-origin freshwater intimately links conditions on the North West Atlantic shelf and slope region with the eastern subpolar basins. This reveals the importance of atmospheric forcing of intra-basin circulation in determining the salinity of the subpolar North Atlantic.

Uncertainty in ocean analysis methods and deficiencies in the observing system are major obstacles for the reliable reconstruction of the past ocean climate. The variety of existing ocean reanalyses is exploited in a multi-reanalysis ensemble to improve the ocean state estimation and to gauge uncertainty levels. The ensemble-based analysis of signal-to-noise ratio allows the identification of ocean characteristics for which the estimation is robust (such as tropical mixed-layer-depth, upper ocean heat content), and where large uncertainty exists (deep ocean, Southern Ocean, sea ice thickness, salinity), providing guidance for future enhancement of the observing and data assimilation systems.

Abstract. Since December 2010, the MyOcean global analysis and forecasting system has consisted of the Mercator Océan NEMO global 1/4° configuration with a 1/12° nested model over the Atlantic and the Mediterranean. The open boundary data for the nested configuration come from the global 1/4° configuration at 20° S and 80° N. The data are assimilated by means of a reduced-order Kalman filter with a 3-D multivariate modal decomposition of the forecast error. It includes an adaptive-error estimate and a localization algorithm. A 3-D-Var scheme provides a correction for the slowly evolving large-scale biases in temperature and salinity. Altimeter data, satellite sea surface temperature and in situ temperature and salinity vertical profiles are jointly assimilated to estimate the initial conditions for numerical ocean forecasting. In addition to the quality control performed by data producers, the system carries out a proper quality control on temperature and salinity vertical profiles in order to minimise the risk of erroneous observed profiles being assimilated in the model. This paper describes the recent systems used by Mercator Océan and the validation procedure applied to current MyOcean systems as well as systems under development. The paper shows how refinements or adjustments to the system during the validation procedure affect its quality. Additionally, we show that quality checks (in situ, drifters) and data sources (satellite sea surface temperature) have as great an impact as the system design (model physics and assimilation parameters). The results of the scientific assessment are illustrated with diagnostics over the year 2010 mainly, assorted with time series over the 2007–2011 period. The validation procedure demonstrates the accuracy of MyOcean global products, whose quality is stable over time. All monitoring systems are close to altimetric observations with a forecast RMS difference of 7 cm. The update of the mean dynamic topography corrects local biases in the Indonesian Throughflow and in the western tropical Pacific. This improves also the subsurface currents at the Equator. The global systems give an accurate description of water masses almost everywhere. Between 0 and 500 m, departures from in situ observations rarely exceed 1 °C and 0.2 psu. The assimilation of an improved sea surface temperature product aims to better represent the sea ice concentration and the sea ice edge. The systems under development are still suffering from a drift which can only be detected by means of a 5-yr hindcast, preventing us from upgrading them in real time. This emphasizes the need to pursue research while building future systems for MyOcean2 forecasting.

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.