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Satellite Altimetry is one of the main techniques for observing the oceans on a global scale and has contributed to the knowledge of the Mean Sea Level (MSL) and its variations. The main measurement of altimetric satellites is the distance between the satellite and the ocean surface (Range), which is incorrect owing to errors caused by the interaction of the signal with the atmosphere and the sea surface, requiring corrections to account for these effects. The troposphere is responsible for most of these errors, caused by its dry and wet components. The Dry Tropospheric Correction (DTC) is mainly due to atmospheric gases and pressure, being already well established and modeled with high accuracy. Oppositely, the Wet Tropospheric Correction (WTC), caused mainly due to the water vapor present in the troposphere, is much more variable in space and time than the DTC, therefore, more difficult to model. The altimetric satellites are equipped with instruments called Microwave Radiometers (MWR), which measure the amount of water vapour under the satellite path, providing information for the estimation of the WTC. The MWR works well in the open ocean, the surface for which the instrument has been designed, and for which the retrieval algorithms are often tuned, but it fails in coastal zones and inland waters, due to the presence of land in the MWR footprint, and also in areas where ocean ice and heavy rain occur. In view to recover the WTC in these regions, the GNSS (Global Navigation Satellite System) derived Path Delay Plus (GPD+) method, developed by the University of Porto, uses Zenith Tropospheric Delays (ZTD) from GNSS global and regional networks’ stations combined with other sources of information, such as valid on-board MWR measurements, Scanning Image Microwave Radiometers (SI-MWR) and Numeric Weather Models (NWM) from the European Center for Medium-Range Weather Forecasts (ECMWF), to estimate this correction with high accuracy all over the planet. The International GNSS Service (IGS) network, used by GPD+, has GNSS stations spread across the globe, but the coverage is not dense enough, with regions where there are few or no stations. Regional networks are used in order to increase the number of stations and the amount of information. GPD+ currently uses the regional networks EUREF Permanent Network (EPN) and SuomiNet, both located in the northern hemisphere. In order to densify the existing GNSS dataset used in GPD+, it is necessary to add new stations, mainly in the southern hemisphere, in regions such as South America, Africa and Oceania. This work aims to exploit the Latin America and Caribbean SIRGAS-CON network and its potential for densification of the GPD+ input dataset in this region. The accuracy and stability of the WTC derived from SIRGAS-CON ZTD were analyzed, by comparison with WTC from IGS ZTD and ERA5 NWM, and the stations that meet GPD+ requirements were selected for the WTC computation by the algorithm. The WTC computed by GPD+ with and without data from SIRGAS-CON stations were compared with the GNSS-derived WTC, by means of a non-independent and non-collocated comparison at altimetry points from CryoSat-2, Sentinel-3A and Sentinel-3B, in the Latin America and Caribbean regions. The results show that the RMS of the WTC differences for the solution with SIRGAS-CON stations is lower than the solution without SIRGAS-CON stations, for the three satellites, mainly in coastal zones, reaching up 2 mm, which indicates an improvement in the algorithm performance after the addition of the new network. An independent evaluation with data from radiosondes is currently in progress. It is expected that the results of this second evaluation are in line with the results obtained so far, confirming the positive impact of the SIRGAS-CON ZTD in the estimations of the GPD+ WTC in the densified regions.

The computation of sea surface height measurements from satellite altimetry is nowadays a straightforward procedure, enabling sea level variation studies globally. Amongst the various range corrections that need to be applied to the range measured by the altimeter, the wet tropospheric path delay is still one of the most significant error sources. The most accurate way to retrieve the corresponding wet tropospheric correction (WTC) is through the measurements of microwave radiometers (MWR) on board altimetry missions, collocated with those from the altimeter. For the altimeter reference missions, three-band MWR have been used, with frequency bands around 18 GHz, 23 GHz and 36 GHz. In the case of the dual-band MWR on board European Space Agency’s (ESA) missions, the lack of the lowest frequency channel, which provides mainly information on the surface emissivity and its contribution in the measured MWR brightness temperatures (TB), is currently taken into account by considering additional parameters, namely the altimeter backscatter coefficient, σ0, the sea surface temperature (SST), and the atmospheric temperature vertical decrease rate (γ800). Although the altimeter σ0 parameter is collocated with the MWR measurements, the SST is currently extracted from external static seasonal tables. Recent studies show that the use of a dynamic SST extracted from Numerical Weather Models (ERA5) improves the WTC retrieval, whereas the γ800 parameter provides redundant information. The Copernicus Sentinel-3 mission payload, besides the Synthetic Aperture Radar Altimeter (SRAL) and MWR sensors, includes the Sea and Land Surface Temperature Radiometer (SLSTR), among other collocated sensors, from which gridded SST observations are derived over ocean, simultaneously with observations from the SRAL and MWR sensors. In this context, the objective of the present work is the development of a synergistic approach for the ESA Sentinel-3 mission between the SRAL and MWR sensors with the SLSTR instrument. The aim is to derive the SST measurement from the SLSTR sensor for each SRAL observation and assess its impact in the WTC retrieval over open ocean, thus removing the need for the extraction of the SST parameter from external sources. In a first stage, the SLSTR-derived SST are evaluated against the ERA5 model; their impact in the WTC retrieval is assessed in a second stage. The results show that the use of the SLSTR-derived SST, compared to those from ERA5, has no significant impact on the WTC retrieval over open ocean, both globally and regionally. Thus, for the WTC retrieval, there seems to be no advantage in having collocated SST and altimeter and radiometer observations. Additionally, this study reinforces that the use of dynamic SST leads to a significant improvement over the current Sentinel-3 WTC operational algorithms.

Amongst its instruments, the Copernicus Sentinel-3 (S3) missions carry the Synthetic Aperture Radar Altimeter (SRAL) for precise sea surface height (SSH) observations and its companion Microwave Radiometer (MWR) for the retrieval of the path delay in the altimeter range caused by the presence of water vapour and cloud liquid water in the atmosphere. In the scope of an activity sponsored by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), the University of Porto (UPorto) has been developing an improved WTC for the S3 missions. This improvement is accomplished by means of GPD+, Global Navigation Satellite Systems (GNSS)-derived Path Delay Plus, an algorithm developed at UPorto to retrieve enhanced WTC for radar altimeter missions. The requested improvement is particularly relevant over surfaces where the WTC from the on-board MWR is not available or is invalid due to e.g. the presence of land or ice in the large MWR footprint, such as coastal zones, inland waters and high latitudes. GPD+ is a data combination procedure (Objective Analysis), where valid observations from the on-board radiometer are combined with external measurements from GNSS and imaging radiometers (SI-MWR), to obtain new WTC estimates for all altimeter points for which the Baseline MWR WTC is invalid. In this way, GPD+ preserves the properties of the best available WTC, from the on-board MWR, and further extends this correction to regions and epochs where and when the former is not valid. To ensure the continuity and consistency of the corrections, all input data used in GPD+ undergo various quality checks and calibration procedures. The various MWR (both the on-board and external SI-MWR) are calibrated against the Special Sensor Microwave Imager/Sounder(SSMI/S), considered a stable radiometric reference. The corrections have been assessed by comparisons with other WTC sources: radiometers, GNSS and atmospheric models from the European Centre for Medium range Weather Forecasts (ECMWF). The GPD+ WTC validation includes analysis of sea level anomaly (SLA) along-track variance differences and SLA Root Mean Square (RMS) differences at crossovers (mean cycle values, function of latitude and function of distance from coast). This paper presents the most recent results of the GPD+ WTC for Sentinel-3A and Sentinel-3B, since the start of each mission until April 2021. The main features of the S3 GPD+ WTC include: are continuous and consistent corrections, valid over all surface types; are calibrated against the SSMI/S dataset, taken as reference; improve data coverage, mostly in coastal and polar regions, and fill existing gaps in the valid MWR observations; are improved WTC both with respect to the Baseline MWR WTC for each satellite and to the ECMWF model-derived WTC. The operational provision of the corrections is being implemented, with predicted inclusion in the S3 SRAL/MWR Level 2 products starting in mid-2022.

Satellite altimetry has become a standard tool for many Earth Observation studies applied to sea, glaciers, rivers, inland waters and lakes, in order to measure the height of a water body above a reference ellipsoid. The signal emitted by the altimeter sensor is highly dependent on the wet tropospheric correction (WTC), due to its interaction with water vapour suspended in this atmospheric layer. Since water vapour does not behave as a well-mixed gas, its prediction becomes a delicate task. Therefore, microwave radiometers are on board the altimeter satellites in order to determine the WTC very accurately over open-ocean. Despite the ability of this passive sensor to produce collocated measurements with the altimeter, other sources of WTC are needed in locations where observations are invalidated due to the presence of non-ocean surfaces in its footprint, such as in coastal areas and high latitudes. This study aims to investigate ground-based radiometers (MWRGB) as a reliable source of water vapour measurements for deducing the WTC of altimetric observations. For this purpose, the WTC from the MWRGB is assessed by comparison with other four external WTC sources: (1) microwave radiometers on board (MWROB) altimetry missions such as Sentinel-3 A and B, SARAL/AltiKa, and Jason-3; (2) Global Navigation Satellite Systems (GNSS); (3) radiosonde (RS); and (4) ECMWF (European Centre for Medium-Range Weather Forecasts) - ERA5 atmospheric model. The first three comparisons can be collocated or not while the latter is collocated through spatial and temporal interpolation. Among all the comparisons, the only one that is not independent is the comparison with radiosonde, since the information provided by this source is also introduced in the MWRGB retrieval algorithms. MWRGB from one observatory of the Atmospheric Radiation Measurements (ARM) user facility have been used in this study, which is the ENA (Eastern North Atlantic). In addition, retrievals from two ARM algorithms were used in order to evaluate which one best suits the needs of Satellite Altimetry – NN or MWRRETV2. For the ENA observatory, collocated comparisons, or up to 40 km, show RMS of WTC differences in the range 1.02 cm - 1.41 cm. The collocated comparison with ERA5 show RMS of 1.09 cm - 1.19 while the comparison with GNSS, which is non-collocated at only 51 m, shows a higher value of 1.41 cm. Furthermore, the comparisons with MWROB up to 40 km present an RMS in the range of 1.02 cm - 1.30 cm. For the comparison with RS, which is non-collocated at 89 km, an RMS of nearly 2.37 cm is found, which may be explained by the large distance between the two datasets, close to the limit of the WTC spatial correlation scale. The intra-algorithm assessment showed that in general the NN and MWRRETV2 algorithms have great similarity in their results, with a variation of RMS of WTC differences in the range of 0 – 2.8 mm. Therefore, for the needs of Satellite Altimetry up to 40 km, the NN algorithm proves to be a reliable source for deducing WTC, due to the near real-time latency of its retrieved data. At last, two neural network algorithms were tuned to estimate the WTC directly from MWRGB brightness temperatures (TB) observations, which are: (WTCGB_2TB) using 2 inputs - TB from both the 23.8 and 30 GHz bands; and (WTCGB_3TB), using 3 inputs – the former two TB with further inclusion of the TB from the 90 GHz band. Thus, the training dataset consisted of 100,000 samples which refer to 1 year of observations, 3 or 2 TB as inputs, and model-interpolated WTC for the same instants as output. An independent assessment for the WTC values retrieved from both algorithms was carried out against GNSS data. WTCGB_2TB presented an RMS of 1.42 cm while the WTCGB_3TB obtained a better performance of 1.34 cm. Furthermore, the comparison with the NN algorithm, for the same period, showed an RMS of 1.41 cm, which was higher than the result found for the WTCGB_3TB.

The concept of a small radar altimeter constellation has already been proposed but not yet implemented due to technological limitations or high costs associated with the operation of such a constellation. Yet, some oceanic processes are still poorly studied and understood due to the lack of adequate sampling of the ocean by past and current satellite altimetry missions. With the increase in popularity of the CubeSat concept and the current availability of low-cost and high-performance components, improving the space-time resolution of satellite altimetry with a constellation of small satellites becomes a possible scenario. The MAGAL Constellation is a future constellation of small satellites carrying radar altimeters that aims to improve the understanding of ocean circulation variability in local, regional, and global scales through improving the spatiotemporal resolution of sea surface topography measurements. By operating as a collective unit, the measurements provided by MAGAL are expected to augment those from the current large satellite radar altimeters. Hence, the framework should be collaborative, to better tackle the gaps of the reference programs, improving the collective data products with an enhanced data set over the open ocean, while also targeting the coastal processes. Four main use cases have been selected, for which the sampling of the ocean with higher spatial and temporal resolutions is required: better characterization of the mesoscale variability at local and regional scales to support operational oceanography; eddy detection and tracking; monitoring of marine debris pathways, and the monitoring of the water level of inland water bodies. To achieve these goals, six CubeSat, no larger than 24U, are being considered which, to reduce the launch cost, are all launched simultaneously into the same orbital plane. The orbital characteristics of the constellation have been selected to provide full coverage of the Earth’s surface with a 5-day repetition cycle and distance between adjacent tracks of ~88 km at the Equator. The altitude must be higher than 500 km, to reduce the effect of atmospheric drag, and less than 600 km, due to the restrictions imposed by altimeter and power budget. A sun-synchronous orbit with 97.4° inclination has been selected for repeatability. The separation of the satellites in the orbital plane, as well as orbit corrections, are to be provided by the thruster system. The MAGAL platform will be miniaturized and manufactured in series, minimizing production, operational and launching costs. The design process will take advantage of the new Space 4.0 industry to integrate readily COTS subsystems (navigation, tracking, cooling and propulsion). Profiting from its low cost, replacement of end-of-life satellites (~3 years) can be accommodated in the same or complementary orbital planes. However, the altimeter payload state-of-the-art demands the development of a new era of small, lower power consuming altimeters. The radar altimeter will operate at a frequency of 13 GHz, with a Frequency Modulated Continuous Wave (FMCW) architecture. The FMCW architecture was selected as it has a lower power consumption (20 W consumption for 1 W transmission RF power) than traditional pulsed radar altimeters. For this radar altimeter to work correctly, with an adequate observation footprint, the antenna must be at least 1.5 m diameter deployable dish antenna. The signal will then be received and treated using digital signal processing using a FPGA approach. A Data Analysis Center (DAC) will also be developed based on cloud-based services, surpassing security issues. The DAC will be responsible for storage of acquired data, and processing of those data, including overlay of different layers from multiple sources (e.g. meteorology), in the back-end side, producing scientific and commercial information. A front-end layer will be responsible for displaying processed data in various graphical interfaces, allowing overlaid correlations between data and layers. The project MAGAL Constellation (Nr. 033688) is co-financed by the European Regional Development Fund through COMPETE 2020, LISBOA 2020 and by FCT under the UT Austin-Portugal interface program, and will consider the insights from the European Union agenda for sustainable development, addressing as many fields of action as possible, and adding value alongside the underlying technology development. Besides providing an integrated approach, bringing together the sea’s economy and its sustainable growth into the future, the MAGAL project will contribute to the knowledge advancement in these fields.