Alice Carret

Since more than 10 years, CryoSat-2 (CS2) has observed and monitored the Arctic Ocean, providing unprecedented spatial and temporal coverage. Satellite altimetry enables to measure sea ice thickness, one essential variable to understand the sea ice dynamics. Numerous sea-ice products developed by the community showed the skills of CS2 to retrieve sea-ice thickness. Nevertheless, several questions remain to better quantify the quality of the measurements. One of them is to better assess the snow depth, a key parameter to obtain the sea ice thickness. In 2018, ICESat-2 mission was launched carrying a LIDAR altimeter. We took advantage of the difference of penetration in the snow layer of laser and Ku-Band altimetry to compute a snow depth product covering the ICESat-2 period. This product is then validated and compared to in situ datasets, reanalysis, models and other snow depth products from satellite missions such as SARAL. Results are quite good concerning the comparison to in situ datasets giving us confidence in the product reliability. In July 2020, the orbit of CryoSat-2 was raised, as part of the CRYO2ICE project, to coincide in space and time to tracks from NASA high resolution altimeter ICESat-2 over the Arctic ocean. This is a unique opportunity to benefit from along-track colocalised data. We present here a methodology to compare ICESat-2 and CryoSat-2 along coincident tracks and compare the resulting snow depth product to gridded products. The lack of in situ measurements is one of the main limitations to analyze the along-track product contribution. Finally we focus on the advantages of combining laser and Ku-band altimetry to lower the uncertainties. The snow depth uncertainties of our product are about 6 cm on average. This ESA-supported study should help prepare the Copernicus CRISTAL mission, which will include a Ka/Ku dual-frequency altimeter for the first time.

Over the last 3 decades, satellite altimetry has observed sea surface height variations, providing a regular monitoring of the surface ocean circulation. Altimetry measurements have an intrinsic signal-to-noise ratio that limits the spatial scales of the currents that can be captured. However, the recent progress made on both altimetry sensors and data processing allows us to observe smaller geophysical signals, offering new perspectives in coastal areas where these structures are important. In this methodological study, we assess the ability of three altimeter missions with three different technologies to capture the Northern Current (northwestern Mediterranean Sea) and its variability, namely Jason-2 (Ku-band low-resolution-mode altimeter, launched in 2008), SARAL/AltiKa (Ka-band low-resolution-mode altimeter, launched in 2013) and Sentinel-3A (synthetic aperture radar altimeter, launched in 2016). Therefore, we use a high-resolution regional model as a reference. We focus along the French coast of Provence, where we first show that the model is very close to the observations of high-frequency radars and gliders in terms of surface current estimates. In the model, the Northern Current is observed 15–20 km from the coast on average, with a mean core velocity of 0.39 m s⁻¹. Its signature in terms of sea level consists of a drop whose mean value at 6.14^∘ E is 6.9 cm, extending over 20 km. These variations show a clear seasonal pattern, but high-frequency signals are also present most of the time. In comparison, in 1 Hz altimetry data, the mean sea level drop associated with the Northern Current is overestimated by 3.0 cm for Jason-2, but this overestimation is significantly less with SARAL/AltiKa and Sentinel-3A (0.3 and 1.4 cm respectively). In terms of corresponding sea level variability, Jason-2 and SARAL altimetry estimates are larger than the model reference (+1.3 and +1 cm respectively), whereas Sentinel-3A shows closer values (−0.4 cm). When we derive geostrophic surface currents from the satellite sea level variations without any data filtering, in comparison to the model, the standard deviations of the velocity values are also very different from one mission to the other (3.7 times too large for Jason-2 but 2.4 and 2.9 times too large for SARAL and Sentinel-3A respectively). When low-pass filtering altimetry sea level data with different cutoff wavelengths, the best agreement between the model and the altimetry distributions of velocity values are obtained with a 60, 30 and 40–50 km cutoff wavelength for Jason-2, SARAL and Sentinel-3A data respectively. This study shows that using a high-resolution model as a reference for altimetry data allows us not only to illustrate how the advances in the performances of altimeters and in the data processing improve the observation of coastal currents but also to quantify the corresponding gain.

Over the last three decades, satellite altimetry has observed Sea Surface Height variations, providing a regular monitoring of the ocean circulation. Altimetry measurements have an intrinsic signal-to-noise ratio that strongly limits the space scales, and then the geophysical information that can be captured with this instrument. However, the recent progress made on both altimetry sensors and data processing, offers new perspectives in terms of research-oriented and operational applications. In this paper we present a methodological study that helps to better quantify the impact of this progress in terms of coastal circulation. We focus on a case study: the Northern Current, a narrow slope current (less than 60 km wide) located in the North Western Mediterranean Sea. We first use a high resolution numerical model validated with HF radars and underwater glider data to define the general characteristics of the Northern Current in terms of surface velocity and sea surface height signature. These characteristics are then compared with corresponding estimates of sea surface height velocity derived from 1-Hz altimetry data sets from three missions: Jason 2 (Ku-band LRM), SARAL (Ka-band LRM) and Sentinel-3A (SAR). The data from all missions were processed with the coastal-specific X-TRACK strategy. We show that near Toulon, the model is very close to the observations in terms of current estimates, providing a very good reference for altimetry data located in this area. The Northern Current is observed 15 km to the coast on average, with a mean core velocity of 0.44 m s⁻¹. Its signature in sea level consists of a drop whose mean value at 6.14° E is 6.9 +/− 2.2 cm extending over 18 +/− 4 km. These variations show a clear seasonal pattern, but high frequency signals are also present most of the time. In 1-Hz altimetry data, the mean sea level drop associated with the Northern Current is overestimated by 3.6 cm for Jason 2, 0.3 cm for SARAL and 1.4 cm for Sentinel-3A. In terms of corresponding sea level variability, Jason 2 and SARAL altimetry estimates are larger than the model reference (+1.3 cm and +1 cm, respectively) whereas Sentinel-3A shows closer values (−0.4 cm). Without any sea level data filtering, the standard deviation of altimetry-derived velocity values is 3.7, 2.4 and 2.9 times too large for Jason-2, SARAL and Sentinel-3A, respectively. When filtering sea level data, the distribution of altimetry velocities tends to converge towards the model reference with a 50-km, 30-km and 40-km cutoff wavelength for Jason-2, SARAL and Sentinel-3A data, respectively.

Satellite altimetry data have revealed a global mean sea level rise of 3.1 mm/yr since 1993 with large regional sea level variability. These remote data highlight complex structures especially in strongly eddying regions. A recent study showed that over 38% of the global ocean area, the chaotic variability may hinder the attribution to the atmospheric forcing of regional sea level trends from 1993 to 2015. This study aims to complement this work by focusing on the atmospherically forced and chaotic interannual variability of regional sea level and its components. At interannual time scales, variability can hamper the detection of regional sea level trends. A global 1/4° ocean/sea‐ice 50‐member ensemble simulation is analyzed to disentangle the imprints of the atmospheric forcing and of the chaotic ocean variability on the interannual variability of regional sea level and of its steric and manometric components over 1993–2015. The atmospherically forced and chaotic interannual variabilities of sea level mainly have a steric origin, except in coastal areas. The chaotic part of the interannual variability of sea level and its components is stronger in the Pacific and Atlantic Oceans than in the Indian Ocean. The chaotic part of the interannual variance of sea level and of its steric component exceeds 20% over 48% of the global ocean area; this fractional area reduces to 26% for the manometric component. These results confirm the substantial imprint of the chaotic interannual variability on sea level components, questioning in several regions the attribution of their observed evolution to atmospheric causes.

Satellite altimetry data have revealed a global mean sea level rise of 3.1 mm/yr since 1993 with large regional sea level trend variability. These remote data highlight complex structures especially in strongly eddying regions. A recent study showed that over 38% of the global ocean area, the chaotic variability that spontaneously emerges from the ocean may hinder the attribution to the atmospheric forcing of regional sea level trends from 1993 to 2015. This study aims at complementing this work by first focusing on the atmospherically-forced and chaotic contributions of regional sea level interannual variability and its components (steric and manometric sea level interannual variability). A global ¼° ocean/sea-ice 50-member ensemble simulation is considered to disentangle the imprints of the atmospheric forcing and of the chaotic ocean variability over 1993-2015. The atmospherically-forced and chaotic interannual variabilities of sea level mainly have a steric origin , except in coastal areas. The chaotic part of the interannual variability of sea level and its components is stronger in the Pacific and Atlantic oceans than in the Indian ocean. The chaotic part of the interannual variability of sea level and of its steric component exceeds 20% over 48% of the global ocean area; this fractional area reduces to 26% for the manometric component. As the chaotic part of the regional sea level interannual variability has a substantial imprint, this study then interested in quantifying the periods when it becomes dominant over the atmospherically-forced contribution. This is assessed using spectral analysis on the ensemble simulation in the frequency domain for the sea level and its steric and manometric components over the global ocean as well as in some basins of interest. This enables us to better characterise and quantify the chaotic ocean variability contribution to regional sea level changes and its components.

During the last 15 years, substantial progress has been achieved in altimetry data processing, now providing data with enough accuracy to illustrate the potential of these observations for coastal applications. In parallel, new altimetry techniques improve data quality by reducing land contamination and enhancing the signal-to-noise ratio. Satellite altimetry provides more robust and accurate measurements ever closer to the coast and resolve shorter ocean signals. An important issue is now to learn how to use altimetry data in conjunction with other coastal observing techniques. Here, we cross-compare and combine the coastal currents provided by large datasets of ship-mounted acoustic Doppler current profilers (ADCPs), gliders, high-frequency (HF) radars and altimetry. We analyze how the different available observing techniques, with a particular focus on altimetry, capture the Northern Current variability at different timescales. We also study the coherence, divergence and complementarity of the information derived from the different instruments considered. Two generations of altimetry missions and both 1 Hz and high-rate measurements are used: Jason-2 (nadir Ku-band radar) and SARAL/AltiKa (nadir Ka-band altimetry); their performances are compared. In terms of mean speed of the Northern Current, a very good spatial continuity and coherence is observed at regional scale, showing the complementarity among the types of current measurements. In terms of current variability, there is still a good spatial coherence but the Northern Current amplitudes derived from altimetry, glider, ADCP and HF radar data differ, mainly because of differences in their respective spatial and temporal resolutions. If we consider seasonal variations, 1 Hz altimetry captures ∼60 % and ∼55 % of the continental slope current amplitude observed by the gliders and by the ADCPs, respectively. For individual dates this number varies a lot as a function of the characteristics of the Northern Current on the corresponding date, with no clear seasonal tendency observed. Compared to Jason-2, the SARAL altimeter data tend to give estimations of the NC characteristics that are closer to in situ data in a number of cases. The much noisier high-rate altimetry data appear to be more difficult to analyze but they provide current estimates that are generally closer to the other types of current measurements. Thus, satellite altimetry provides a synoptic view of the Northern Current circulation system and variability, which helps to interpret the other observations. Its regular sampling allows for the observation of many features that may be missed by irregular in situ data.

During the last 15 years, substantial progress has been achieved in altimetry data processing, providing now data with enough accuracy to illustrate the potential of these observations for coastal applications. In parallel, new altimetry techniques improve the data quality by reducing the land contamination and by enhancing the signal-to-noise ratio. Satellite altimetry provides ever more robust and accurate measurements ever closer to the coast and resolve ever shorter ocean signals. An important issue is now to learn how to use altimetry data in conjunction with the other coastal observing techniques. Here, we demonstrate the ability of satellite altimetry to observe part of the Northern Current variability. We cross-compare and combine the currents provided by large data sets of ship-mounted ADCPs, gliders, HF radars and altimetry. We analyze how the different available observing techniques capture the current variability at different time-scales. We also study the coherence/divergence/complementarity of the informations derived from the different instruments considered. Two generation of altimetry missions are used: Jason 2 (nadir Ku-band radar) and SARAL/AltiKa (nadir Ka-band altimetry); their performances are compared. In terms of mean speed of the Northern Current, a very good spatial continuity and coherence is observed at regional scale, showing the complementarity between all the types of current measurements. In terms of current variability, there is still a good spatial coherence but the amplitude of the seasonal variations is underestimated by ~ 50 % in altimetry, compared to both gliders and ADCPs, because of a too low spatial resolution. For individual dates this number varies a lot as a function of the distance to the coast and width of the Northern Current. Compared to Jason 2, the SARAL/AltiKa data tend to give estimations of the NC characteristics that are closer to in situ data in a number of cases. Satellite altimetry obviously provides a synoptic view of the Northern Current circulation system and variability which helps to interpret the other current observations. Its regular sampling allows the observation of many features that may be missed by in situ measurements.

Technological advances in the recent satellite altimeter missions of Jason-2, SARAL/AltiKa and CryoSat-2 have improved their signal-to-noise ratio, allowing us to observe finer-scale ocean processes with along-track data. Here, we analyse the noise levels and observable ocean scales in the northwestern Mediterranean Sea, using spectral analyses of along-track sea surface height from the three missions. Jason-2 has a higher mean noise level with strong seasonal variations, with higher noise in winter due to the rougher sea state. SARAL/AltiKa has the lowest noise, again with strong seasonal variations. CryoSat-2 is in synthetic aperture radar (SAR) mode in the Mediterranean Sea but with lower-resolution ocean corrections; its statistical noise level is moderate with little seasonal variation. These noise levels impact on the ocean scales we can observe. In winter, when the mixed layers are deepest and the submesoscale is energetic, all of the altimeter missions can observe wavelengths down to 40–50 km (individual feature diameters of 20–25 km). In summer when the submesoscales are weaker, SARAL can detect ocean scales down to 35 km wavelength, whereas the higher noise from Jason-2 and CryoSat-2 blocks the observation of scales less than 50–55 km wavelength. This statistical analysis is completed by individual case studies, where filtered along-track altimeter data are compared with co-located glider and high-frequency (HF) radar data. The glider comparisons work well for larger ocean structures, but observations of the smaller, rapidly moving dynamics are difficult to co-locate in space and time (gliders cover 200 km in a few days, altimetry in 30 s). HF radar surface currents at Toulon measure the meandering Northern Current, and their good temporal sampling shows promising results in comparison to co-located SARAL altimetric currents. Techniques to separate the geostrophic component from the wind-driven ageostrophic flow need further development in this coastal band.