Jason-1 Missions Research Articles

Comparison of different methods to account for the plasmaspheric electron content in GNSS-derived ionospheric altimeter corrections and their impact on sea level trend estimation

Global ionospheric maps based on GNSS measurements are nowadays often used to correct satellite altimeter measurements when the instruments have only one frequency or measure over coasts and inland waters. If these corrections do not account for the free electron fraction over the altimeter satellites, this leads to systematic deviations in the range measurements and thus in the estimated sea level. This study compares and assesses different approaches to reduce GNSS-based corrections for the plasmaspheric electron content. It is shown that using a simple scaling with a constant factor of 0.881 gives the best results for the Jason-1 mission, while correcting with the commonly used model ratios leads to higher sea level trend artefacts and larger noise levels, especially for periods of lower solar activity. Using this approach, the sea level trend error for both Jason-1 and Sentinel-6A can be reduced to below 0.1 mm/year, with standard deviations of the differences from the dual-frequency altimeter corrections of 6.74 mm. A simple machine learning approach (boosted regression tree) is also investigated and shows promising results. However, due to the higher processing capacity requirements and the larger deviations from long-term trend, further improvements are recommended before such an approach can be used in routine processing of altimeter corrections.Graphical

Validating Sea-Level Altimetry Data against Tide Gauge for Coastal Risk Analysis in Mozambique

Satellite altimetry data provide a solution to the lack of in situ tide gauge data, which are essential for comprehending various marine processes worldwide. In the present study, we seek to validate ALES-retrieved sea-level data against tide gauge observations from four ground stations on the coast of Mozambique. The approach consisted of extracting data from selected tracks of the Jason-1, Jason-2 and Jason-3 missions, and processing it to (i) remove outliers, (ii) collocate alongside tide gauge data, (iii) remove the tidal component and detrend, and (iv) perform a set of statistical analyses. Good agreement was found between the altimetry and tide gauge data in three of the four stations (Maputo, r = 0.59; Inhambane, r = 0.87; and Pemba, r = 0.75), with the exception of Beira. The annual and semi-annual cycles in the two datasets revealed that the altimetry signal is smaller in amplitude and ahead (with a few exceptions) of tide gauge by a varying number of days in each location. Both the annual and semi-annual cycles are far more comparable in Pemba, where the amplitude in particular has the same order of magnitude, followed by the Maputo station. The study concluded that the selected altimetry data for Pemba and Maputo stations are valid and can be used for coastal risk analysis and other applications. No altimetry data could be validated for Inhambane and Beira stations due to lack of consistent and sufficiently long tide gauge records. This difficulty urges the need for improved maintenance practices of ground stations located near human settlements that rely on sound information of the sea level and its variability to protect lives, infrastructure and livelihoods.

River ice phenology and thickness from satellite altimetry: potential for ice bridge road operation and climate studies

Abstract. River ice is a key component of the cryosphere. Satellite monitoring of river ice is a rapidly developing area of scientific enquiry, which has wide-ranging implications for climate, environmental and socioeconomic applications. Spaceborne radar altimetry is widely used for monitoring river water regimes; however, its potential for the observation of river ice processes and properties has not been demonstrated yet. Using Ku-band backscatter measurements from the Jason-2 and Jason-3 satellite missions (2008–2019), we demonstrate the potential of radar altimetry for the retrieval of river ice phenology dates and ice thickness for the first time. The altimetric measurements were determined to be sensitive enough to detect the first appearance of ice and the beginning of thermal breakup on the lower Ob River (Western Siberia). The uncertainties in the retrieval of ice event timing were within the 10 d repeat cycle of Jason-2 and Jason-3 in 88 %–90 % of the cases analysed. The uncertainties in the river ice thickness retrievals made via empirical relations between the satellite backscatter measurements and in situ observations, expressed as the root mean square error (RMSE), were of 0.07–0.18 m. A novel application of radar altimetry is the prediction of ice bridge road operations, which is demonstrated herein. We established that the dates of ferry closing and ice road opening and closing in the city of Salekhard can be predicted with an accuracy (expressed as RMSE) of 3–5 d.

The Copernicus Sentinel-6 mission: Enhanced continuity of satellite sea level measurements from space

Given the considerable range of applications within the European Union Copernicus system, sustained satellite altimetry missions are required to address operational, science and societal needs. This article describes the Copernicus Sentinel-6 mission that is designed to provide precision sea level, sea surface height, significant wave height, inland water heights and other products tailored to operational services in the ocean, climate, atmospheric and land Copernicus Services. Sentinel-6 provides enhanced continuity to the very stable time series of mean sea level measurements and ocean sea state started in 1992 by the TOPEX/Poseidon mission and follow-on Jason-1, Jason-2 and Jason-3 satellite missions. The mission is implemented through a unique international partnership with contributions from NASA, NOAA, ESA, EUMETSAT, and the European Union (EU). It includes two satellites that will fly sequentially (separated in time by 5 years). The first satellite, named Sentinel-6 Michael Freilich, launched from Vandenburg Air Force Base, USA on 21st November 2020. The satellite and payload elements are explained including required performance and their operation. The main payload is the Poseidon-4 dual frequency (C/Ku-band) nadir-pointing radar altimeter that uses an innovative interleaved mode. This enables radar data processing on two parallel chains the first provides synthetic aperture radar (SAR) processing in Ku-band to improve the received altimeter echoes through better along-track sampling and reduced measurement noise; the second provides a Low Resolution Mode that is fully backward-compatible with the historical reference altimetry measurements, allowing a complete inter-calibration between the state-of-the-art data and the historical record. A three-channel Advanced Microwave Radiometer for Climate (AMRC) provides measurements of atmospheric water vapour to mitigate degradation of the radar altimeter measurements. The main data products are explained and preliminary in-orbit Poseidon-4 altimeter data performance data are presented that demonstrate the altimeter to be performing within expectations.

Coastal sea level anomalies and associated trends from Jason satellite altimetry over 2002\u20132018

Climate-related sea level changes in the world coastal zones result from the superposition of the global mean rise due to ocean warming and land ice melt, regional changes caused by non-uniform ocean thermal expansion and salinity changes, and by the solid Earth response to current water mass redistribution and associated gravity change, plus small-scale coastal processes (e.g., shelf currents, wind & waves changes, fresh water input from rivers, etc.). So far, satellite altimetry has provided global gridded sea level time series up to 10–15 km to the coast only, preventing estimation of sea level changes very close to the coast. Here we present a 16-year-long (June 2002 to May 2018), high-resolution (20-Hz), along-track sea level dataset at monthly interval, together with associated sea level trends, at 429 coastal sites in six regions (Northeast Atlantic, Mediterranean Sea, Western Africa, North Indian Ocean, Southeast Asia and Australia). This new coastal sea level product is based on complete reprocessing of raw radar altimetry waveforms from the Jason-1, Jason-2 and Jason-3 missions.

Backscattering signatures at Ka, Ku, C and S bands from low resolution radar altimetry over land

Radar backscattering coefficients from synthetic aperture radars and scatterometers are commonly used to characterize the land surface properties and monitor their temporal evolution. Radar altimetry is mostly used, over land, to provide time series of water stage of lakes, rivers and wetlands and the topography of the ice sheets. Very few studies used the radar altimetry backscattering coefficients for geophysical applications except to determine changes in Arctic lakes state surface, surface soil moisture in semi-arid environments or flood extent at high latitude. As radar altimetry missions acquired data in four frequency bands (mostly C and Ku but also S and Ka), this study proposes the first thorough analysis of the backscattering signatures of land surfaces using observations from ERS-2, Jason-1, ENVISAT, Jason-2 and SARAL radar altimetry missions The spatial and temporal variations of several altimetric information (backscattering coefficient, waveform peakiness, leading edge width and trailing edge slope) are examined at global scale, for each frequency band separately, as well as for their differences. Their relationship with related variations in the surface characteristics (i.e., soil type, soil moisture, presence of water and snow) are evidenced. Finally, spatial patterns and temporal variations computed over selected regions, representative of the major bioclimatic areas, are related to their surface properties and changes.

Altimetry-based sea level trends along the coasts of Western Africa

We present results of contemporary coastal sea level changes along the coasts of Western Africa, obtained from a dedicated reprocessing of satellite altimetry data done in the context of the ESA ‘Climate Change Initiative’ sea level project. High sampling rate (20 Hz) sea level data from the Jason-1 and Jason-2 missions over a 14-year-long time span (July 2002 to June 2016) are considered. The data were first retracked using the ALES adaptative leading edge subwaveform retracker. The X-TRACK processing system developed to optimize the completeness and accuracy of the corrected sea level time series in coastal ocean areas was then applied. From the 14-year long sea level time series finally obtained, we estimate sea level trends along the Jason-1 & 2 tracks covering the study region. We analyze regional variations in sea level trends, with a focus on the changes observed between the open ocean to the coastal zone. Compared to the conventional 1 Hz sea level products dedicated to open ocean applications, the retracked 20 Hz measurements used in this study allow us to retrieve valid sea level information much closer to the coast (less than 3–4 km to the coast, depending on the satellite track location). The main objective of this study is twofold: (1) provide sea level products in the coastal areas from reprocessed altimetry data and (2) check whether sea level changes at the coast differ from that reported in the open ocean with conventional altimetry products. In the selected region, results show that over the study period, sea level trends observed near the coast of Western Africa are significantly different than offshore trends. In order to assess the robustness of the results, detailed analyses are performed at several locations to discriminate between possible drifts in the geophysical corrections and physical processes potentially able to explain the sea level changes observed close to the coast.

Sea State Bias Variability in Satellite Altimetry Data

Sea State Bias (SSB) contributes to global mean sea level variability and it needs cm-level range adjustment due to the instrumental drift over time. To investigate its variations and correct the global and regional sea level trend precisely, we calculate the temporal and spatial variability of the SSB correction in TOPEX, Jason-1, Jason-2 and Jason-3 missions, separately, as well as in the combined missions over the period 1993–2017. The long-term trend in global mean operational 2D non-parametric SSB correction is about −0.03 ± 0.03 mm/yr, which accounts for 1% of current global mean sea level change rate during 1993–2016. This correction contributes to sea level change rates of −1.27 ± 0.21 mm/yr and −0.26 ± 0.13 mm/yr in TOPEX-A and Jason-2 missions, respectively. The global mean SSB varies up to 7–10 mm during the very strong ENSO events in 1997–1998 and 2015–2016. Furthermore, the TOPEX SSB trend, which is consistent with recently reported sea level trend drift during 1993–1998, may leak into the determined global sea level trend in the period. Moreover, the Jason-1/2 zonal SSB variability is highly correlated with the significant wave height (SWH). On zonal average, SSB correction causes about 1% uncertainty in mean sea level trend. At high SWH regions, the uncertainties grow to 2–4% near the 50°N and 60°S bands. This should be considered in the study of regional sea level variability.

Improved Sea State Bias Estimation for Altimeter Reference Missions With Altimeter-Only Three-Parameter Models

This paper presents an in-depth study concerning the development of a sea state bias (SSB) model designed with three parameters exclusively derived from altimeter data and globally applied to all reference altimeter missions. The proposed technique, first tested for the Jason-1 mission, proves to have a good performance for a wide range of ocean conditions when compared with the state-of-the-art SSB corrections currently in use. In addition to the significant wave height ( $H_{s}$ ) and wind speed ( $U~_{{10}}$ ), a third predictor acting as a mediator parameter gathered by the mean wave period ( $T_{z}$ ) has been used. Two different empirical algorithms for altimeter ocean wave period have been tested and implemented, improving the SSB model performance in some ocean regions. The methodology relies on nonparametric modulation and statistical techniques based on smoothing splines embedded in a generalized additive model. This SSB modeling approach shows good performance when applied to all reference missions, in particular to TOPEX and Jason-2 missions, slightly reducing the explained variance of sea-level anomaly (SLA) when compared with the established SSB models. The approach is computationally efficient, capable of generating a stable SSB model using a small training data set when little information is available, as is the case with the recent Jason-3 mission. Model performance is assessed by comparison with existing SSB corrections for each reference mission, intercomparisons during the period of the tandem phases, and by SLA variance analysis, providing a consistent set of SSB corrections for the four reference missions.

Relationships between pacific and atlantic ocean sea surface temperatures and water levels from satellite altimetry data in the Amazon rivers

ABSTRACT The influence of SST (Sea Surface Temperature) of adjacent oceans on the variability of water levels in the Amazon basin was investigated by using radar altimetry from the ENVISAT and Jason-2 missions. Data from the in situ network was used to compare the correlations of water level and SST anomalies in the sub-basins of the Amazonas-Peru, Solimões, Negro and Madeira Rivers. The analysis was made on the monthly and annual scales between 2003 and 2015. The correlations with anomalies of levels from altimetry presented higher accuracy indices than those from the conventional network. In general, ATN and PAC are better correlated with the entire basin. During the flood months, most of the sub-basins presented negative associations with ATN. In the months of ebb, the response to the indexes varies according to the region. The satellite altimetry data permitted to reach regions non-monitored by the conventional network. We also analyzed the impacts of hydrological extremes in all these sub-regions in the last 13 years. In Western Amazon, the drought of 2010 stands out, associated with the warming of the Tropical Atlantic and the El Niño. In the Negro River, the water level anomalies were the lowest in the basin during the 2005 drought. In the Purus River, the effects of the 2010 drought that affected the entire Amazon, were higher in 2011 due to its strong relationship with the Atlântic and Pacific oceans. In general, hydrological extremes are stronger or highlighted when SST increases simultaneously in both oceans.

Climatic variability of water circulation in the Caspian Sea based on satellite altimetry data

ABSTRACTOscillations of the Caspian Sea level is the result of interrelated hydrometeorological processes and climate change not only in the catchment area of the sea but also far beyond it. The change in the tendency of the mean sea level variations in the middle 1970s, when the long-term sea level fall was replaced by its rapid and significant rise, is an important indicator of the changes in the natural regime of the Caspian Sea. Now, monitoring of the Caspian Sea level is based on tide gauge and satellite altimetry data. However, climatic variability of water circulation in the Caspian Sea remains unclear. Traditionally, currents in the Caspian Sea have been investigated by numerical methods. Instrumental observations of the currents in the Caspian Sea are mostly carried out in the shelf zone. Available data cover very short periods and reflect variability only in synoptic and higher frequency of the sea dynamics. This paper presents the results of the application of satellite altimetry methods for investigation of interannual variability of sea water circulation in different parts of the Caspian Sea and in the sea as a whole using the data of TOPEX/Poseidon, Jason-1and Jason-2 missions from 1993 to 2012. Satellite altimetry data provide a unique possibility to analyze climatic variability of water circulation in the Caspian Sea. The author discusses the technique of calculating synoptic dynamic topography as a superposition of the annual average climatic dynamic topography calculated by the thermohydrodynamic model for the time period of 1948‒2004 and sea level anomalies calculated by satellite altimetry data. The analysis of vorticity of geostrophic currents confirms predominance of cyclonic circulation in the Northern and Middle Caspian Sea and anticyclonic circulation in the Southern Caspian Sea. The analysis shows that interannual variability in average current velocity and vorticity are opposite to each other. From 1993 to 2007, vorticity was decreasing at the rate of −0.17 ± 0.02 10–7 per year, and average current velocity was increasing at the rate of +0.11 ± 0.06 cm s−1 per year. After 2008, the tendency of variability has changed to the opposite. Vorticity was increasing at the rate of +0.75 ± 0.12 10–7 per year, but velocity of currents was decreasing at the rate of −0.47 ± 0.19 cm s−1 per year.

An estimation of tropospheric corrections using GPS and synoptic data: Improving Urmia Lake water level time series from Jason-2 and SARAL/AltiKa satellite altimetry

Tropospheric correction is one of the most important corrections in satellite altimetry measurements. Tropospheric wet and dry path delays have strong dependence on temperature, pressure and humidity. Tropospheric layer has particularly high variability over coastal regions due to humidity, wind and temperature gradients. Depending on the extent of water body and wind conditions over an inland water, Wet Tropospheric Correction (WTC) is within the ranges from a few centimeters to tens of centimeters. Therefore, an extra care is needed to estimate tropospheric corrections on the altimetric measurements over inland waters. This study assesses the role of tropospheric correction on the altimetric measurements over the Urmia Lake in Iran. For this purpose, four types of tropospheric corrections have been used: (i) microwave radiometer (MWR) observations, (ii) tropospheric corrections computed from meteorological models, (iii) GPS observations and (iv) synoptic station data. They have been applied to Jason-2 track no. 133 and SARAL/AltiKa track no. 741 and 356 corresponding to 117–153 and the 23–34 cycles, respectively. In addition, the corresponding measurements of PISTACH and PEACHI, include new retracking method and an innovative wet tropospheric correction, have also been used. Our results show that GPS observation leads to the most accurate tropospheric correction. The results obtained from the PISTACH and PEACHI projects confirm those obtained with the standard SGDR, i.e., the role of GPS in improving the tropospheric corrections. It is inferred that the MWR data from Jason-2 mission is appropriate for the tropospheric corrections, however the SARAL/AltiKa one is not proper because Jason-2 possesses an enhanced WTC near the coast. Furthermore, virtual stations are defined for assessment of the results in terms of time series of Water Level Height (WLH). The results show that GPS tropospheric corrections lead to the most accurate WLH estimation for the selected virtual stations, which improves the accuracy of the obtained WLH time series by about 5%.

STAR: Spatio-temporal altimeter waveform retracking using sparse representation and conditional random fields

Satellite radar altimetry is one of the most powerful techniques for measuring sea surface height variations, with applications ranging from operational oceanography to climate research. Over open oceans, altimeter return waveforms generally correspond to the Brown model, and by inversion, estimated shape parameters provide mean surface height and wind speed. However, in coastal areas or over inland waters, the waveform shape is often distorted by land influence, resulting in peaks or fast decaying trailing edges. As a result, derived sea surface heights are then less accurate and waveforms need to be reprocessed by sophisticated algorithms. To this end, this work suggests a novel Spatio-Temporal Altimetry Retracking (STAR) technique. We show that STAR enables the derivation of sea surface heights over the open ocean as well as over coastal regions of at least the same quality as compared to existing retracking methods, but for a larger number of cycles and thus retaining more useful data. Novel elements of our method are (a) integrating information from spatially and temporally neighboring waveforms through a conditional random field approach, (b) sub-waveform detection, where relevant sub-waveforms are separated from corrupted or non-relevant parts through a sparse representation approach, and (c) identifying the final best set of sea surfaces heights from multiple likely heights using Dijkstra's algorithm. We apply STAR to data from the Jason-1, Jason-2 and Envisat missions for study sites in the Gulf of Trieste, Italy and in the coastal region of the Ganges–Brahmaputra–Meghna estuary, Bangladesh. We compare to several established and recent retracking methods, as well as to tide gauge data. Our experiments suggest that the obtained sea surface heights are significantly less affected by outliers when compared to results obtained by other approaches.

CAWRES: A Waveform Retracking Fuzzy Expert System for Optimizing Coastal Sea Levels from Jason-1 and Jason-2 Satellite Altimetry Data

This paper presents the Coastal Altimetry Waveform Retracking Expert System (CAWRES), a novel method to optimise the Jason satellite altimetric sea levels from multiple retracking solutions. CAWRES’ aim is to achieve the highest possible accuracy of coastal sea levels, thus bringing measurement of radar altimetry data closer to the coast. The principles of CAWRES are twofold. The first is to reprocess altimeter waveforms using the optimal retracker, which is sought based on the analysis from a fuzzy expert system. The second is to minimise the relative offset in the retrieved sea levels caused by switching from one retracker to another using a neural network. The innovative system is validated against geoid height and tide gauges in the Great Barrier Reef, Australia for Jason-1 and Jason-2 satellite missions. The regional investigations have demonstrated that the CAWRES can effectively enhance the quality of 20 Hz sea level data and recover up to 16% more data than the standard MLE4 retracker over the tested region. Comparison against tide gauge indicates that the CAWRES sea levels are more reliable than those of Sensor Geophysical Data Records (SGDR) products, because the former has a higher (≥0.77) temporal correlation and smaller (≤19 cm) root mean square errors. The results demonstrate that the CAWRES can be applied to coastal regions elsewhere as well as other satellite altimeter missions.

Jason continuity of services: continuing the Jason altimeter data records as Copernicus Sentinel-6

Abstract. The Sentinel-6 mission is proposed as a multi-partner programme to continue the Jason satellite altimeter data services beyond the Jason-2 and Jason-3 missions. The Sentinel-6 mission programme consists of two identical satellites flying in sequence to prolong the climate data record of sea level accumulated by the TOPEX/Poseidon, Jason-1, Jason-2, and Jason-3 missions from 2020 to beyond 2030. The Sentinel-6 mission intends to maintain these services in a fully operational manner. A key feature is the simultaneous pulse-limited and synthetic aperture radar processing allowing direct and continuous comparisons of the sea surface height measurements based on these processing methods and providing backward compatibility. The Sentinel-6 mission will also include radio occultation user services.

Impact of Atmospheric and Oceanic De-aliasing Level-1B (AOD1B) products on precise orbits of altimetry satellites and altimetry results

We have extended backwards from 2001 to 1979 the current release 05 (RL05) of the Gravity Recovery and Climate Experiment (GRACE) Atmospheric and Oceanic De-aliasing Level-1B (AOD1B) product and studied the impact of this and a previous release 04 (RL04) of the AOD1B product on precise orbits of five altimetry satellites (ERS-1, ERS-2, TOPEX/Poseidon, Envisat and Jason-1) for the time span 1991–2012, as compared to the case when no AOD1B product is used. We have found that using AOD1B RL05 product reduces root mean square (RMS) fits of satellite laser ranging (SLR) observations by about 1.0–6.4 per cent, 2-d arc overlaps in radial, cross-track and along-track directions by about 1.3–12.0, 0.3–10.0 and 2.0–10.0 per cent, respectively, for various satellites tested, as compared to the case without AOD1B product. Using AOD1B RL05 product instead of RL04 one reduces SLR RMS fits by 0.1–0.7 per cent, 2-d arc overlaps in radial, cross-track and along-track directions by 0.1–0.6, 0.1–1.3 and 0.2–1.2 per cent, respectively, for the satellite orbits tested. The multi-mission crossover analysis shows that the application of an AOD1B product reduces the scatter of radial errors by 0.4–2.8 per cent for the satellite missions studied. At the regions with the most pronounced changes the use of the AOD1B products improves the consistency between the sea level as measured by the TOPEX and ERS-2 missions and by the Jason-1 and Envisat missions by 5 to 10 per cent (globally by about 2 per cent). The results of our study show that extended AOD1B RL05 product performs better than the AOD1B RL04 and improves orbits of altimetry satellites and consistency of sea level products.

Identification and Reduction of Retracker-Related Noise in Altimeter-Derived Sea Surface Height Measurements

AbstractData from the Jason-2 calibration/validation mission phase have been analyzed to identify the correlation between sea surface height (SSH) and significant wave height (SWH) errors. A cross-spectral analysis indicates that the SSH and SWH errors are nearly white and significantly correlated at scales from 12 to 100 km, consistent with the hypothesized error source, the waveform retracker. Because of the scale separation between the SWH signal and noise, it is possible to correct the SSH data by removing the SSH noise correlated with the SWH noise. Such a correction has been implemented using the empirical correlation found during the Jason-2 calibration orbit phase and applied to independent data from other phases of the Jason-1 mission. The efficacy of the correction varies geographically, but variance reductions between 1.6 and 2.2 cm2 have been obtained, corresponding to reductions of 20%–27% in the noise floor of along-track spectra. The corrections are obtained from and applied to conventional, 1 Hz, altimetry data and lead to improvements in the signal-to-noise ratio for identification of high-frequency narrowband processes—for example, internal tides—from these data.

Temperature, radiation and aging analysis of the DORIS Ultra Stable Oscillator by means of the Time Transfer by Laser Link experiment on Jason-2

The Time Transfer by Laser Link (T2L2) experiment on-board the Jason-2 satellite was launched in June 2008 at 1335km altitude. It has been designed to use the Satellite Laser Ranging (SLR) space technique as an optical link between ground and space clocks. T2L2, as all the instruments aboard Jason-2, is referenced to the Ultra Stable Oscillator (USO) provided by the Doppler Orbitography and Radio-positioning Integrated by Satellite (DORIS) system. A complex data processing has been developed in order to extract time & frequency products as the relative frequency bias of the USO from ground-to-space time transfer passages. The precision of these products was estimated of a few parts in 10−13 given the very good in-flight performance of T2L2 with a ground-to-space time stability of a few picoseconds (ps) over 100s. Frequency bias from T2L2 were compared with results from operational orbit computation, notably with the DIODE (Détermination Immédiate d’Orbite par Doris Embarqué) outputs (see Jayles et al. (2016) same issue) at the level of 1·10−12.The present paper is focusing on the main physical effects which drive the frequency variations of the Jason-2 USO during its flight, notably over the South Atlantic Anomaly (SAA) area. In addition to the effects of radiation we studied the effect of the residual temperature variations, in the range 8–11°C (measured on-board). A model was established to represent these effects on the short term with empirical coefficients (sensitivities of the USO) to be adjusted. The results of fitting the model over ∼200 10-day periods, from 2008 to 2014, show the sensitivities of the Jason-2 USO to temperature and radiation. The analysis of the 6-year output series of empirical coefficients allows us to conclude that: (i) the temperature to frequency dependence is very stable along time at the level of around −1.2·10−12per°C, (ii) the radiation effects are much lower than those previously detected on the Jason-1 USO with a factor>10. The swept material used by manufacturers for the Jason-2 quartz oscillator has such properties to avoid non-linear effects >1–2·10−12, (iii) the model is available at 1min or less over the Jason-2 mission, with a level of consistency of 5·10−13, which is the average RMS of the post-fit residuals.

Assessing SARAL/AltiKa Data in the Coastal Zone: Comparisons with HF Radar Observations

We present an initial assessment of SARAL/AltiKa data in the coastal band. The study focuses on the Ibiza Channel where the north-south water exchanges play a key role in controlling the circulation variability in the western Mediterranean. In this area, the track 16 of SARAL/AltiKa intercepts the domain covered by a coastal high-frequency (HF) radar system, which provides surface currents with a range up to 60 km. We evaluate the performance of the SARAL/AltiKa Ssalto/Duacs delayed-time along-track products compared to the HF radar surface velocity fields. SARAL/AltiKa data are retrieved at a distance of only 7 km from the coast, putting in evidence the emerging capabilities of the new altimeter. The derived velocities resolved the general features of the seasonal mesoscale variability with reasonable agreement with HF radar fields (significant correlations of 0.54). However, some discrepancies appear, which might be caused by instrumental hardware radar errors, ageostrophic velocities as well as inaccurate corrections and editing in the altimeter data. Root mean square (rms) differences between the estimated SARAL/AltiKa and the HF radar velocities are about 13 cm/s. These results are consistent with recent studies in other parts of the ocean applying similar approaches to Topex/Poseidon and Jason-1 missions and using coastal altimeter corrections.

Nonstationary Internal Tides Observed Using Dual-Satellite Altimetry

AbstractDual-satellite crossover data from the Jason-2 and Cryosat-2 altimeter missions are used in a novel approach to quantify stationary and nonstationary tides from time-lagged mean square sea surface height (SSH) differences, computed for lags from 1 to 1440 h (60 days). The approach is made feasible by removing independent estimates of the stationary tide and mesoscale SSH variance, which greatly reduces the sampling error of the SSH statistics. For the semidiurnal tidal band, the stationary tidal variance is approximately 0.73 cm2, and the nonstationary variance is about 0.33 cm2, or 30% of the total. The temporal correlation of the nonstationary tide is examined by complex demodulation and found to be oscillatory with first 0 crossing at 400 h (17 days). Because a significant fraction of the time-variable mesoscale signal is resolved at time scales of roughly 150 h by the present constellation of satellite altimeters, the results suggest that it may be feasible to predict the nonstationary tide from modulations of the resolved mesoscale, thus enhancing the efficacy of tidal corrections for planned wide-swath altimeters such as the Surface Water and Ocean Topography (SWOT) mission.