Altimetry for the future: Building on 25 years of progress

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

Altimetry for the future: building on 25 years of progress

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

Comparison of Retrieval Algorithms for the Wet Tropospheric Path Delay

WOS:000345894600024International audienceThis paper provides a comparative analysis of statistical algorithms for the retrieval of the wet tropospheric correction from microwave radiometers in the context of altimetry missions. The algorithms are based on the algorithms used in Envisat and Jason-1 missions. The objective of this comparison is two-folds:1) To find which regression method is better suited for the retrieval between the neural network algorithm and the log linear regression.2) To tackle the problem of variable selection, i.e. to find the best set of variables to include as inputs in order to reduce the retrieval error. In particular, we want to determine whether the lack of a radiometer third channel at 18GHz can be compensated by the altimeter backscattering coefficient.Several configurations of algorithms, including those used in the operational processing of altimetry missions such as JASON-1 or ENVISAT, are built and compared on the same learning and test databases to determine which retrieval strategy is more appropriate. The database is composed of atmospheric and oceanographic conditions taken from the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses and the brightness temperatures are simulated using a radiative transfer model. The importance of each input for the different algorithms is analyzed and the performances of the different algorithms are assessed in terms of error (bias and standard deviation) but also in terms of geographical distribution of the errors and correlation with other environmental variables. The results are then validated on Jason-2 radiometer measurements.Our results show that, in terms of variable selection, better results were obtained when the brightness temperature at 18 GHz was used instead of the backscattering coefficient. Moreover, better estimations of the wet tropospheric path delay were obtained with neural networks

SARAL/AltiKa Wet Tropospheric Correction: In-Flight Calibration, Retrieval Strategies and Performances

International audienceThe SARAL/AltiKa mission is a complement of the Jason altimeter series. A two-channels (23.8 GHz and 37 GHz) microwave radiometer (MWR) is combined to the altimeter in order to correct the altimeter range for the excess path delay (referred as WTC for wet tropospheric correction. First, the in-flight calibration of AltiKa MWR is assessed from a systematic comparison to other radiometers using a complete set of metrics (comparison to simulations and over geophysical targets). Then the “mixed” empirical approach successfully used for Envisat shows nonoptimal performances for the WTC retrieval. In order to find the potential sources of issues, this method is compared to a purely empirical relationship established between measured brightness temperatures (TB) and altimeter backscattering coefficient ($\sigma_{0}$) on one hand and modeled WTC on the other hand. Various retrieval configurations for both AltiKa MWR and advanced microwave radiometer (AMR) on Jason-2, are for the first time systematically compared with respect to their performances against the variance of sea surface height differences at crossovers. Finally, the issues on the “mixed” approach are attributed to the differences between simulated and measured at Ka-band. Now, a configuration of the empirical approach proved to have performances closed to what is initially expected with the “mixed” approach

Assessment of the “Zero-Bias Line” Homogenization Method for Microwave Radiometers Using Sentinel-3A and Sentinel-3B Tandem Phase

The long-term stability of microwave radiometers (MWR) on-board altimetry missions is critical to reduce the uncertainty on the global mean sea level estimate. Harmonization and homogenization steps are applied to MWR observations in that perspective. The Sentinel-3 tandem phase provides a unique opportunity to quantify the uncertainties on the “zero-bias line” homogenization approach defined by Bennartz et al. (2020). Initially developed to improve the performance of the wet tropospheric correction retrieval, it is used here to provide a common reference for the inter-calibration between Sentinel-3A and Sentinel-3B MWR. A simplified version of the “zero-bias line” approach, a linear correction depending on brightness temperatures, allows to strongly reduce the bias between the two radiometers for both channels (about 0.5 K) and the standard deviation of the difference (0.3 K). The full version of the approach adding a dependency on wind speed has improved the quality of the WTC retrieval (Bennartz et al. 2020) but degrades the performance of the homogenization. It is thus recommended to apply the simplified version of this approach in the processing of fundamental data record. The quantification of the uncertainties on the homogenization approach is only possible due to the ideal configuration of the Sentinel-3 tandem phase. The same dataset and the same metrics could be used to assess other approaches

Contributions of altimetry and Argo to non‐closure of the global mean sea level budget since 2016

Over 1993-2016, studies have shown that the observed global mean sea level (GMSL) budget is closed within the current data uncertainties. However, non-closure of the budget was recently reported when using Jason-3, Argo and GRACE/GRACE Follow-On data after 2016. This non-closure may result from errors in the datasets used to estimate the GMSL and its components. Here, we investigate possible sources of errors affecting Jason-3 and Argo data. Comparisons of Jason-3 GMSL trends with other altimetry missions show good agreement within 0.4 mm/yr over 2016-present. Besides, the wet tropospheric correction uncertainty from the Jason-3 radiometer contributes to up to 0.2 mm/yr. Therefore, altimetry alone cannot explain the misfit in the GMSL budget observed after 2016. Argo-based salinity products display strong discrepancies since 2016, attributed to instrumental problems and data editing issues. Re-assessment of the sea level budget with the thermosteric component provides about 40 % improvement in the budget closure. Plain Language Summary Sea level rise, due to the addition of meltwater from glaciers and ice-sheets in the oceans and to the thermal expansion of seawater, is commonly used as an indicator for climate change. The sea level budget provides information on temporal changes in one or more components of the budget, on process understanding, on missing contributions and allows cross validation of the observing systems involved in the sea level budget (satellite altimetry, Argo oceanic float and GRACE/GRACE Follow-On satellite gravimetry). The sea level budget was closed until 2015-2016, i.e. the observed global mean sea level agrees well with the sum of components. However, since 2016, the budget is not closed anymore. In this study, we show that errors in Argo salinity measurements are responsible for about 40 % of the budget error while the altimetry data cannot explain the remaining error. Other sources of errors should be further investigated to fully understand the error in the budget after 2016, in particular satellite GRACE/GRACE Follow-On gravity measurements or missing physical contributions