Wet Tropospheric Correction Research Articles

Contrasting Discrepancy in the Sea Level Budget Between the North and South Atlantic Ocean Since 2016

AbstractThe discrepancy in the observed global mean sea level budget increased significantly since 2016, but the budget discrepancy over basin‐scales is unclear. In this contribution, we investigate the sea level budget discrepancies in major basins with observations from satellite altimetry, satellite gravimetry, and Argo floats. During 2016–2020, we find substantial discrepancy of 5.72 ± 0.98 mm/yr over the North Atlantic Ocean, and the basin scale discrepancies are smaller elsewhere. Our analysis suggests that three factors, including the wet tropospheric correction (WTC) effect, deep ocean warming signal, and the contemporary ocean bottom deformation (OBD), together reduce the discrepancy by only 1 mm/yr for the North Atlantic Ocean. We decompose sea level observations into the spherical harmonic domain and observe increased discrepancy in low‐degree variations of C10 and C21 since 2016. These two coefficients result in a contrasting signal between the North and South Atlantic Ocean and contribute to the large discrepancy over the North Atlantic Ocean. We further demonstrate that the C10 and C21 discrepancies are independent of the three factors. However, we find regional salinity biases in the Argo data that reduce the discrepancy for the North Atlantic Ocean. Our findings add to the debate about recent sea level budget and imply that further analysis of the Argo North Atlantic data set may be useful.

Global and regional ocean mass budget closure since 2003

In recent sea level studies, discrepancies have arisen in ocean mass observations obtained from the Gravity Recovery and Climate Experiment and its successor, GRACE Follow-On, with GRACE estimates consistently appearing lower than density-corrected ocean volume observations since 2015. These disparities have raised concerns about potential systematic biases in sea-level observations, with significant implications for our understanding of this essential climate variable. Here, we reconstruct the global and regional ocean mass change through models of ice and water mass changes on land and find that it closely aligns with both GRACE and density-corrected ocean volume observations after implementing recent adjustments to the wet troposphere correction and halosteric sea level. While natural variability in terrestrial water storage is important on interannual timescales, we find that the net increase in ocean mass over 20 years can be almost entirely attributed to ice wastage and human management of water resources.

Wet Tropospheric Correction for the HY-2C Altimeter over the Coastal Ocean Based on GNSS and ERA5 Data

For the impact of land, sea ice, rainfall and strong wind, the wet tropospheric correction (WTC) of HY-2C (the third marine dynamic environmental monitoring satellite of China) altimeter cannot be obtained accurately by the calibration microwave radiometer (CMR) over the coastal ocean. The conducted evaluation of the HY-2C CMR WTC over the coastal ocean by the Global Navigation Satellite System (GNSS) and ECMWF Reanalysis v5 (ERA5) data showed that the CMR WTC is abnormal or invalid. To solve this issue, a new method to determine the WTC of the HY-2C altimeter based on objective analysis (OA) by combining the GNSS WTC, ERA5 WTC and valid CMR WTC is developed. The OA WTC and HY-2C CMR WTC are compared to the Integrated Global Radiosonde Archive (IGRA) WTC to validate the OA method. The results show that the RMSE of the WTC differences significantly decreases and the correlation coefficient increases. The number of available WTC data increases over the open ocean. The variances of sea level anomaly corresponding to the OA WTC in most areas are significantly smaller than those of the HY-2C CMR WTC. In general, the availability and accuracy of HY-2C altimeter data are largely enhanced with the OA WTC.

On-Orbit Calibration and Wet Tropospheric Correction of HY-2C Correction Microwave Radiometer

HY-2C is the third satellite in China’s ocean dynamic environment satellite series, and carries a correction microwave radiometer (CMR) to correct the wet tropospheric path delay for the aligned radar altimeter. To effectively use the brightness temperatures (TB) of CMR to retrieve path delay, an on-orbit calibration effort is required. In this study, an antenna pattern correction (APC) method and a neural network method are used to perform an on-orbit calibration for CMR’s antenna temperatures and a model based on the Whale Optimization Algorithm (WOA), Levenberg–Marquardt (LM) algorithm, and Back-Propagation neural network (WOA–LM–BP) has been proposed to retrieve the wet tropospheric correction (WTC) of CMR. The on-orbit calibration results, compared with the simulated brightness temperatures calculated by the radiative transfer model (RTM), have shown that compared with the APC method, the neural network method can almost eliminate the latitude variation, and the total bias and standard deviation of the on-orbit calibrated TB at all channels have obviously decreased. The retrieved WTC results also have shown that the retrieved WTC of CMR has a good agreement with the corresponding ones from the model-derived WTC and Jason-3.

Estimation of the sea state bias error budget for pulse-limited satellite altimetry

Using an empirical, non-parametric sea state bias (SSB) modeling method, which was developed as a tool for SSB error analysis (Putnam, Alexa Forthcoming), we provide an error budget for overall SSB error, as well as the contributing sources of this error budget. The error analysis compares methods used to derive SSB models from observed altimeter measurements, collinear differences of measurements from adjacent repeat cycles, and methods using both collinear and crossover differences of measurements. Our error analysis reveals systematic error caused by ionosphere correction uncertainty in SSB models obtained from direct measurements, and wet troposphere correction uncertainty in SSB models generated using difference measurements. Results also expose a correlation to altimeter measurement error, with the backscatter coefficient accounting for over 20% of the SSB evaluation error and SWH accounting for approximately 50-60%. The error analysis presented here suggests SSB errors are lower than the often-used approximation of SSB error as 1% of SWH, except at SWH values less than 2 m where errors are likely larger. We find that increasing the pulse repetition frequency of the altimeter reduces SSB errors. The future for improving empirical, nonparametric SSB estimation primarily depends on improving measured SWH.

Current observed global mean sea level rise and acceleration estimated from satellite altimetry and the associated measurement uncertainty

Abstract. We present the latest release of the global mean sea level (GMSL) record produced by the French space agency Centre National d’Etudes Spatiales (CNES) and distributed on the AVISO+ website. This dataset is based on reprocessed along-track data, so-called L2P 21, of the reference missions TOPEX/Poseidon (TP) and Jason-1, Jason-2 and Jason-3. The L2P 21 CNES/AVISO+ GMSL record covers the period January 1993 to December 2021 and is now delivered with an estimate of its measurement uncertainties following the method presented in Ablain et al. (2019). Based on the latest calibration (Cal) and validation (Val) knowledge, we updated the uncertainty budget of the reference altimetry mission measurements and demonstrate that the CNES/AVISO+ GMSL record now achieves stability of performances of ± 0.3 mm yr−1 at the 90 % confidence level (C.L.) for its trend and ±0.05 mm yr−2 (90 % C.L.) for its acceleration over the 29 years of the altimetry record. Thanks to an analysis of the relative contribution of each measurement uncertainty budget contributor, i.e. the altimeter, the radiometer, the orbit determination and the geophysical corrections, we identified the current limiting factors to the GMSL monitoring stability and accuracy. We find that the radiometer wet troposphere correction (WTC) and the high-frequency errors with timescales shorter than 1 year are the major contributors to the GMSL measurement uncertainty over periods of 10 years (30 %–70 %), for both the trend and acceleration estimations. For longer periods of 20 years, the TP data quality is still a limitation, but more interestingly, the International Terrestrial Reference Frame (ITRF) realization uncertainties becomes dominant over all the other sources of uncertainty. Such a finding challenges the altimetry observing system as it is designed today and highlights clear topics of research to be explored in the future to help the altimetry community to improve the GMSL measurement accuracy and stability.

Reducing the Uncertainty in the Satellite Altimetry Estimates of Global Mean Sea Level Trends Using Highly Stable Water Vapor Climate Data Records

AbstractThe global mean sea level (GMSL) has risen by 3.3 ± 0.2 mm.yr−1 (68% confidence level) over 1993–2021. The wet troposphere correction (WTC) used to compute the altimetry‐based mean sea level data is known to be a large source of error in the GMSL long‐term stability. The WTC is derived from the microwave radiometers (MWR) on board the altimetry missions. In order to improve the long‐term estimates of the GMSL, we propose an alternative WTC computation based on highly stable climate data records (CDRs) of water vapor derived from independent MWR measurements on board meteorological satellites. A polynomial model is applied to convert water vapor to WTC. The CDR‐derived WTC enables reducing the low frequency uncertainty of the WTC applied to the altimetry data, hence reducing the uncertainty of the GMSL trend estimate. Furthermore, over 2016–2021, the comparison of MWR‐based with CDR‐based WTC shows a likely drift of the Jason‐3 MWR WTC on the order of −0.5 mm.yr−1 that would lead to an overestimation of the GMSL trend from 2016.

Brightness Temperature and Wet Tropospheric Correction of HY-2C Calibration Microwave Radiometer Using Model-Derived Wet Troposphere Path Delay from ECMWF

The Calibration Microwave Radiometer (CMR) is a three-band radiometer deployed on the HY-2C satellite in a near-Earth orbit, and since it launched, there are few studies presented on the performance of CMR to date. Therefore, this paper focuses on providing an assessment of HY-2C CMR brightness temperature and wet troposphere correction (WTC). CMR works at 18.7 GHz, 23.8 GHz and 37 GHz in a nadir-viewing direction, aligned with the HY-2C radar altimeter. The wet troposphere path delay of the radar altimeter signal caused by water vapour and cloud liquid water content can be monitored and corrected by CMR. In this paper, guided by the concept of antenna pattern correction algorithm and a purely statistical method, we directly establish the function between the CMR antenna temperature and the model-derived WTC calculated by the European Centre from Medium-Range Weather Forecasting (ECMWF) Reanalysis data, which can obtain the brightness temperature and the WTC of CMR simultaneously. Firstly, the algorithm principle of CMR to establish the function between the antenna temperature and the model-derived WTC is introduced, and then the brightness temperature of CMR is evaluated using reference brightness temperatures of the Advanced Microwave Radiometer 2 (AMR-2) on Jason-3 satellite at crossover points. Furthermore, the performance of the CMR WTC is validated in three ways: (1) directly comparing with the colocated WTC measured by Jason-3 AMR-2, (2) directly comparing with model-derived WTC from ECMWF, which allows a rapid check at a global scale, (3) comparing the standard deviation of the Sea Surface Height (SSH) difference at crossover points using different WTC retrieval methods. The linear fit with Jason-3 brightness temperature and WTC in all non-precipitation conditions demonstrated a good agreement with Jason-3. In addition, the WTC of CMR has an obvious decrease in the standard deviation of the SSH difference compared with model-derived WTC, indicating the CMR can significantly improve the accuracy of the HY-2C SSH measurements. All the assessments indicate that the CMR performances are satisfying the expectations and fulfilling the mission requirements.

The Impact of Altimetry Corrections of Sentinel-3A Sea Surface Height in the Coastal Zone of the Northwest Atlantic

Corrections to altimeter-measured sea surface height anomalies (SSHA) have a larger proportional effect for synthetic aperture radar (SAR) altimetry than conventional, pulse-limited altimetry because of lower range noise. Here, we quantified the impact of the current generation of altimeter corrections in the coastal zone of the Northwest Atlantic, a region with significant dynamic activity. In this study, we used the sea level variance analysis to determine the change in variance for the altimeter corrections—range, geophysical, and mean surface—compared to the baseline. We also evaluated the performance of two coastal retrackers, ALES (empirical) and SAMOSA++ (fully analytical), against the SSHA from the Radar Altimeter Database System (RADS), which uses the standard SAR retracker. Tide corrections caused the largest change in sea level variance, followed by wet tropospheric corrections and sea state bias. Most non-standard altimeter corrections failed to reduce the sea level variance and performed markedly worse closer to the coast. Coastal retrackers showed a higher deviation from the standard SSHA closer to the coast, especially when the backscatter coefficient was high and the significant wave height was low. We conclude that further development of coastal corrections is needed. Contrary to our prior expectation, we found that standard altimetry corrections appear to perform as well as alternative more advanced/tailored corrections.

An Improved Altimetry Wet Tropospheric Correction Retrieval Over Coastal Regions for the Sentinel-3 Mission

An Improved Altimetry Wet Tropospheric Correction Retrieval Over Coastal Regions for the Sentinel-3 Mission

Wet tropospheric correction for satellite altimetry using SIRGAS-CON products

Abstract The wet tropospheric correction (WTC) is a required correction to satellite altimetry measurements, mainly due to the atmospheric water vapor delay. On-board microwave radiometers (MWR) provide information for WTC estimation but fail in coastal zones and inland waters. In view to recover the WTC in these areas, the Global Navigation Satellite System (GNSS)-derived Path Delay Plus (GPD+) method, developed by the University of Porto, uses Zenith Tropospheric Delays from GNSS global and regional networks’ stations combined with other sources of information, providing a WTC solution for all along-track altimeter points. To densify the existing dataset used by GPD+, it is necessary to add new GNSS stations, mainly in the southern hemisphere, in regions such as South America, Africa and Oceania. This work aims to exploit the SIRGAS-CON data and its potential for densification of the GPD+ input dataset in Latin America and to improve GPD+ performance. The results for the three analyzed satellites (Sentinel-3A, Sentinel-3B and CryoSat-2) show that, when compared with the WTC from GNSS and radiosondes, the densified GPD+ WTC leads to a reduction in the RMS of the WTC differences with respect to the non-densified GPD+ solution, up to 2 mm for the whole region and up to 5 mm in some locations.

Feasibility of maintaining satellite altimetry calibration site based on qianliyan islet at the Yellow Sea

The calibration of the sea surface height (SSH) measured by satellite altimeters is essential to understand altimeter biases. Many factors affects the construction and maintenance of a permanent calibration site. In order to calibrate Chinese satellite altimetry missions, the feasibility of maintaining a calibration site based on the Qianliyan islet in Yellow Sea of China is taken into account. The related calibration facilities, such as the permanent tide gauge, GNSS reference station and meteorological station, were already operated by the Ministry of Natural Resources of China. The data could be fully used for satellite altimeter calibration with small fiscal expenditure. In addition, the location and marine environments of Qianliyan were discussed. Finally, we used the Jason-3 mission to check the possibility of calibration works. The result indicates that the brightness temperatures of three channels measured by microwave radiometer (MWR) and the derived wet tropospheric correction varies smoothly, which means the land contamination to MWR could be ignored. The high frequency waveforms at the Qianliyan site present no obvious difference from the normal waveforms received by satellite radar altimeter over the open ocean. In conclusion, the Qianliyan islet will not influence satellite altimetry observation. Following these analyses, a possible layout and mechanism of the Qianliyan calibration site are proposed.

Synergistic Use of the SRAL/MWR and SLSTR Sensors on Board Sentinel-3 for the Wet Tropospheric Correction Retrieval

The Sentinel-3 satellites are equipped with dual-band Microwave Radiometers (MWR) to derive the wet tropospheric correction (WTC) for satellite altimetry. The deployed MWR lack the 18 GHz channel, which mainly provides information on the surface emissivity. Currently, this information is considered using additional parameters, one of which is the sea surface temperature (SST) extracted from static seasonal tables. Recent studies show that the use of a dynamic SST extracted from Numerical Weather Models (ERA5) improves the WTC retrieval. Given that Sentinel-3 carries on board the Sea and Land Surface Temperature Radiometer (SLSTR), from which SST observations are derived simultaneously with those of the Synthetic Aperture Radar Altimeter and MWR sensors, this study aims to develop a synergistic approach between these sensors for the WTC retrieval over open ocean. Firstly, the SLSTR-derived SSTs are evaluated against the ERA5 model; secondly, their impact on the WTC retrieval is assessed. The results show that using the SST input from SLSTR, instead of ERA5, has no impact on the WTC retrieval, both globally and regionally. Thus, for the WTC retrieval, there seems to be no advantage in having collocated SST and radiometer observations. Additionally, this study reinforces the fact that the use of dynamic SST leads to a significant improvement over the current Sentinel-3 WTC operational algorithms.

Wet Tropospheric Correction Methods for Wide-Swath Altimeters

Wet troposphere path delay (WPD) is a crucial error source for wide-swath altimeters with high-resolution observations. This study generated a simulated wide-swath through the nadir microwave radiometer (MWR) track and evaluated four wide-swath wet tropospheric correction (WTC) methods based on multisource data from 2017 with strict spacetime windows. The Numerical Weather Model (NWM) method can provide a basic correction for the wide-swath altimeter. The MWR method, based on the extension of nadir 1-beam MWR, could not provide a reliable correction. The residual error increased rapidly after deviating from the nadir profile. The overall root-mean-square error (RMSE) of the combination method was approximately 0.58 cm and had high uniformity within the swath. Even at the far end of the swath, the correction was better than that on the NWM and MWR methods. The objective analysis (OA) method using linear spatiotemporal objective analysis had the best result among the four correction methods. The overall RMSE was only 0.49 cm, which was 34% lower than the NWM method. High consistency was maintained at each cross-track position of the swath. The last two wide-swath WTC methods provided in this study had high performance. For the wide-swath altimeter, the combination method is a scheme worthy of consideration, as it can provide WTC results conveniently, quickly, and accurately. Although the operation of the OA method is complex and depends on multisource observation data, it promises to be a high-quality scheme for the wide-swath altimeter WTC when a more accurate WTC value is required.

Wet tropospheric delay estimation of satellite altimeters based on machine learning

Wet path delay (WPD) is an important source of satellite altimeters’ transmission error, which must be fully corrected to ensure data quality. After decades of study, WPD can now be accurately negated by measuring the brightness temperature with a microwave radiometer (MWR). However, due to hardware and financial limitations, many satellites are not equipped with MWRs, and WPD can only be corrected by mathematical models. Currently available empirical models, which are mostly established by traditional fitting methods, are unable to reach the accuracy required by altimeters, so it is necessary to further improve the correction accuracy of the models. Based on three machine learning algorithms, we established three high-precision wet tropospheric correction (WTC) models suitable for satellite altimeters. We analyzed the global navigation satellite system dataset and three MWR datasets, i.e., Jason-3, Sentinel-3A, and Sentinel-3B, for data quality and consistency and combined these datasets for modeling. In addition, several input features were extracted from existing knowledge on tropospheric delay. Through a comparative analysis of different feature combinations, temperature (T), water vapor pressure (e), and total content of water vapor were selected as the input features. Then we established three WTC models based on multilayer perceptron, random forest, and the adaptive network-based fuzzy inference system (ANFIS), respectively. With a dataset from Jason-2 that was not used during modeling as the verification set, we verified the generalizability of these WTC models from the global, latitudinal, and seasonal perspectives. Moreover, three traditional WTC models were compared with the ones developed here. The results show that the WTC models established based on machine learning algorithms outperform traditional WTC models. The WTC model based on ANFIS boasts the best calculation accuracy in all aspects, over 50% higher than that of traditional WTC models.

Contributions of Altimetry and Argo to Non‐Closure of the Global Mean Sea Level Budget Since 2016

AbstractOver 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 data sets 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. Reassessment of the sea level budget with the thermosteric component provides about 40% improvement in the budget closure.

Calibrating the Haiyang-2A Calibration Microwave Radiometer When the 18.7-GHz Band Fails

The wet tropospheric correction (WTC) retrieved from the onboard calibration microwave radiometer (CMR) of Haiyang-2A (HY-2A) is critical in monitoring the global sea level. However, the CMR WTC became significantly biased from June 2017 due to the failure of the 18.7-GHz band, which caused massive errors in the sea surface height (SSH) measurements. We investigate the accuracy of the CMR WTC derived from the two remaining bands to address this problem. A comprehensive evaluation using multisource data demonstrates that the dual-band + backscattering coefficient (BC) algorithm achieves comparable accuracy to the three-band algorithm, and it does not suffer from any large errors when the equipment works well. Hence, we calibrated the HY-2A CMR data with the dual-band + BC algorithm when the 18.7-GHz band failed, and the accuracy of the CMR WTC is improved from 2.34 to 1.39 cm compared with European Center for Medium-Range Weather Forecasts (ECMWF) ERA5 data. In addition, the SSH measurements are improved significantly by a maximum of 2 cm in mean value using the dual-band + BC WTC during the failure period of HY-2A CMR. Compared with Jason-3 SSH measurements, the HY-2A with dual-band + BC shows a slightly larger difference than HY-2A with three-band by 0.1 cm in rms. This method prolongs the operational lifetime of the HY-2A CMR and could be used in the reprocessing of HY-2A observations.

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.

A coastally improved global dataset of wet tropospheric corrections for satellite altimetry

Abstract. The accuracy of satellite radar altimetry (RA) is known to deteriorate towards the coastal regions due to several reasons, amongst which the improper account for the wet path delay (WPD) can be pointed out. The most accurate WPDs for RA are derived from the on-board microwave radiometer (MWR) radiance measurements, acquired simultaneously as the altimeter ranges. In the coastal zone, however, the signal coming from the surrounding land contaminates these measurements and the water vapour retrieval from the MWR fails. As meteorological models do not handle coastal atmospheric variability correctly yet, the altimeter measurements are rejected whenever MWR observations are absent or invalid. The need to solve this RA issue in the coastal zone, simultaneously responding to the growing demand for data in these regions, motivated the development of the GNSS (Global Navigation Satellite System) derived Path Delay (GPD) algorithm. GPD combines WPD from several sources through objective analysis (OA) to estimate the WPD or the corresponding RA correction accounting for this effect, the wet tropospheric correction (WTC), for all along-track altimeter points for which this correction has been set as invalid or is not defined. The current GPD version (GPD Plus, GPD+) uses as data sources WPD from coastal and island GNSS stations, from satellites carrying microwave radiometers, and from valid on-board MWR measurements. GPD+ has been tuned to be applied to all, past and operational, RA missions, with or without an on-board MWR. The long-term stability of the WTC dataset is ensured by its inter-calibration with respect to the Special Sensor Microwave Imager (SSM/I) and SSM/I Sounder (SSMIS). The dataset is available for the TOPEX/Poseidon (T/P); Jason-1 and Jason-2 (NASA and CNES); Jason-3 (NASA and EUMETSAT); ERS-1, ERS-2, Envisat and CryoSat-2 (ESA); SARAL/AltiKa (ISRO and CNES); and GFO (US Navy) RA missions. The GPD+ WTC for Sentinel-3 (ESA and EUMETSAT) shall be released soon. The present paper describes the GPD+ database and its assessment through statistical analyses of sea level anomaly (SLA) datasets, calculated with GPD+, the ECMWF Reanalysis Interim (ERA-Interim) model or MWR-derived WTCs. Global results, as well as results for three regions (the North American and European coasts and the Indonesia region), are presented for ESA's recent Envisat Full Mission Reprocessing (FMR) V3.0. Global results show that the GPD+ WTC leads to a reduction in the SLA variance of 1–2 cm2 in the coastal zones, when used instead of the ERA WTC, which is one of the WTCs available in these products and can be adopted when the MWR-derived WTC is absent or invalid. The improvement of the GPD+ WTC over the ERA WTC is maximal over the tropical oceans, particularly in the Pacific Ocean, showing that the model-derived WTC is not able to capture the full variability in the WPD field yet. The statistical assessment of GPD+ for the North American coast shows a reduction in SLA variance, when compared to the use of the ERA-derived WTC, of 1.2 cm2, on average, for the whole range of distances from the coast considered (0–200 km). Similar results are obtained for the European coasts. For the Indonesia region, the use of the GPD+ WTC instead of that from ERA leads to an improvement, on average, on the order of 2.2 cm2 for distances from the coast of up to 100 km. Similar results have been obtained for the remaining missions, particularly for those from ESA. Additionally, GPD+ recovers the WTC for a significant number of along-track altimeter points with missing or invalid MWR-derived WTCs, due to land, rain and ice contamination and instrument malfunctioning, which otherwise would be rejected. Consequently, the GPD+ database has been chosen as the reference WTC in the Sea Level Climate Change Initiative (CCI) products; GPD+ has also been adopted as the reference in CryoSat-2 Level-2 Geophysical Ocean Products (GOP). Strategies to further improve the methodology, therefore enhancing the quality of the database, are also discussed. The GPD+ dataset is archived on the home page of the Satellite Altimetry Group, University of Porto, publicly available at the repository https://doi.org/10.23831/FCUP_UPORTO_GPDPlus_v1.0 (Fernandes et al., 2019).

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.