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Sea level rise is one of the greatest socio-economic impacts of climate change in the 21st Century. Whilst global mean sea level is an essential climate variable (ECV) for assessing the integrated response of the Earth system to climate change, regional sea level variability is of primary concern for policy-making decisions and the development of adaptation strategies in coastal localities. Redistribution of terrestrial mass, in the form of hydrological and land ice mass fluxes, partly drives this regional sea level variability due to its impact on the Earth’s gravity, rotation and deformation (GRD), termed ‘Sea Level Fingerprints’ or Barystatic-GRD fingerprints. With increasing mass losses projected from ice sheets and glaciers over the coming centuries, the magnitude and relative contribution of these Barystatic-GRD fingerprints to regional sea level change are expected to increase. As a result, accurately quantifying this phenomenon and its uncertainty is critical when assessing contemporary and future regional sea level variability.Current contemporary Barystatic-GRD fingerprints are typically either calculated using a single mass loading observation source or provide discontinuous coverage since 1992 (the satellite altimetry era). Here, we present a continuous monthly Barystatic-GRD fingerprint product from 1992-2017, computed from an ensemble of mass loadings derived from differing observation techniques. To achieve this, we use the Ice Sheet and Sea Level Model (ISSM) sea level equation solver, which uses a finite element approach to solving the sea level equation at high spatial-temporal resolution, whilst maintaining computational efficiency. This enables us to use an ensemble modelling framework, ensuring the computed Barystatic-GRD fingerprint encompasses the variability between differing observation techniques. Additionally, it allows us to propagate the observation uncertainties into the fingerprint uncertainty in a robust manner. As well as the total Barystatic-GRD fingerprint, we assess the contribution of individual terrestrial components (Antarctica, Greenland, Glaciers, and hydrological mass change). This work is part of the Fingerprinting Approach to Close Regional Sea Level Budgets using ESA-CCI (FACTORS), a European Space Agency Climate Change Initiative Research Fellowship.

The Earth energy imbalance (EEI) at the top of the atmosphere is responsible for the accumulation of energy in the climate system. While necessary to better understand the Earth’s warming climate, measuring the EEI is challenging as it is a globally integrated variable whose variations are small (0.5-1 W.m−2) compared to the amount of energy entering and leaving the climate system (~ 340 W.m-2). Accuracies better than 0.1 W.m−2 are needed to evaluate the temporal variations of the EEI at decadal and longer time-scales. The CERES experiment provides EEI time variations with a typical uncertainty of ± 0.1 W.m−2 and shows a trend in EEI of 0.50 +/- 0.47 W.m−2 per decade over the period 2005-2019. The combination of space altimetry and space gravimetry measurements provides an estimate of the ocean heat content (OHC) change which is an accurate proxy of EEI (because >90% of the excess of energy stored by the planet in response to the EEI is accumulated in the ocean in the form of heat). In Marti et al. (2021), the global OHC was estimated at global scales based on the combination of space altimetry and space gravimetry measurements over 2002-2016. Changes in the EEI were then derived with realistic estimates of its uncertainty. Here we present the improvements brought to the global OGC and EEI over an extended period (2002-2021), such as the calculation of the expansion efficiency of heat over the total water column, the improvement of ocean mass solution, the empirical correction of the wet tropospheric correction of Jason-3 altimeter measurements (Barnoud et al., 2022). The space geodetic GOHC-EEI product based on space altimetry and space gravimetry is available on the AVSIO website at https://doi.org/10.24400/527896/a01-2020.003. References: Barnoud A., Picard B., Meyssignac B., Marti F., Ablain M., Roca R. Reducing the uncertainty in the satellite altimetry estimates of global mean sea level trends using highly stable water vapour climate data records. Submitted to JGR: Oceans. Marti, F., Blazquez, A., Meyssignac, B., Ablain, M., Barnoud, A., Fraudeau, R., Jugier, R., Chenal, J., Larnicol, G., Pfeffer, J., Restano, M., and Benveniste, J.: Monitoring the ocean heat content change and the Earth energy imbalance from space altimetry and space gravimetry, Earth Syst. Sci. Data, 14, 229–249, https://doi.org/10.5194/essd-14-229-2022, 2022.

This presentation provides an update on the ESA radar altimetry processing services portfolio, known as SARvatore, for the exploitation of CryoSat-2 (CS-2) and Sentinel-3 (S-3) data from L1A (FBR) data products up to SAR/SARin L2 geophysical data products. The following on-line & on-demand services compose the portfolio, now hosted in the ESA Altimetry Virtual Lab at the EarthConsole® (https://earthconsole.eu): The ESA-ESRIN SARvatore (SAR Versatile Altimetric Toolkit for Research & Exploitation) for CS-2 and S-3 services. These processor prototypes allow the users to customize the processing at L1b & L2 by setting a list of configurable options, including those not available in the operational processing chains (e.g., SAMOSA+ and ALES+ SAR retrackers). The TUDaBo SAR-RDSAR (TU Darmstadt – U Bonn SAR-Reduced SAR) for CS-2 and S-3 service. It allows users to generate reduced SAR, unfocused SAR & LRMC data. Several configurable L1b & L2 processing options and retrackers (BMLE3, SINC2, TALES, SINCS, SINCS OV) are available. The TU München ALES+ SAR for CS-2 and S-3 service. It allows users to process L1b data applying the empirical ALES+ SAR subwaveform retracker, including a dedicated SSB solution. The Aresys FF-SAR (Fully-Focused SAR) for CS-2 & S-3 service. It provides the capability to produce L1b products with several configurable options and with the possibility of appending the ALES+ FFSAR output to the L1b products. In the future, the service will be extended to process Sentinel-6 data. The following new services will be made available: the CLS SMAP S-3 FF-SAR processor (s-3-smap, http://doi.org/10.5270/esa-cnes.sentinel-3.smap) and the ESA-ESTEC/isardSAT L1 Sentinel-6 Ground Prototype Processor. All output data products are generated in standard netCDF format and are therefore also compatible with the multi-mission “Broadview Radar Altimetry Toolbox” (BRAT, http://www.altimetry.info). The Altimetry Virtual Lab is a community space for simplified processing services and knowledge-sharing, hosted on the EarthConsole®, a powerful EO data processing platform now on the ESA Network of Resources. This enables SARvatore Services to remain open for worldwide scientific applications, including for R&D studies on the retrieval of radar altimetry measured variables contributing to Inland Water monitoring (write to altimetry.info@esa.int for further information).

Radar altimeters have so far had limited use in the coastal zone, the area with most societal impact. This is due to both lack of, or insufficient accuracy in the necessary corrections, and more complicated altimeter signals. This letter examines waveform data from the Envisat RA-2 as it passes regularly over Pianosa (a 10-km2 island in the northwestern Mediterranean). Forty-six repeat passes were analyzed, with most showing a reduction in signal upon passing over the island, with weak early returns corresponding to the reflections from land. Intriguingly, one third of cases showed an anomalously bright hyperbolic feature. This feature may be due to extremely calm waters in the Golfo della Botte (northern side of the island), but the cause of its intermittency is not clear. The modeling of waveforms in such a complex land/sea environment demonstrates the potential for sea surface height retrievals much closer to the coast than is achieved by routine processing. The long-term development of altimetric records in the coastal zone will not only improve the calibration of altimetric data with coastal tide gauges but also greatly enhance the study of storm surges and other coastal phenomena.

The scope of this presentation is to provide an update on the ESA radar altimetry services portfolio for the exploitation of CryoSat-2 (CS-2) and Sentinel-3 (S-3) data from L1A (FBR) data products up to SAR/SARin L2 geophysical data products. At present, the following on-line & on-demand services compose the portfolio:The ESA-ESRIN SARvatore (SAR Versatile Altimetric TOolkit for Research & Exploitation) for CS-2 and S-3 services. These processor prototypes allow the users to customize the processing at L1b & L2 by setting a list of configurable options, including those not available in the operational processing chains (e.g. SAMOSA+ and ALES+ SAR retrackers). The TUDaBo SAR-RDSAR (TU Darmstadt – U Bonn SAR-Reduced SAR) for CS-2 and S-3 service. It allows users to generate reduced SAR, unfocused SAR & LRMC data. Several configurable L1b & L2 processing options and retrackers (BMLE3, SINC2, TALES, SINCS, SINCS OV) are available. The TU München ALES+ SAR for CS-2 and S-3 service. It allows users to process official L1b data and produces L2 products by applying the empirical ALES+ SAR subwaveform retracker, including a dedicated SSB solution. The Aresys FF-SAR (Fully-Focused SAR) for CS-2 service. Currently under development, it will provide the capability to produce L1b products with several configurable options and with the possibility of appending the ALES+ FFSAR output to the L1b products. In the future, these services will be extended and the following new services will be made available: the Aresys FF-SAR services for S-3 & Sentinel-6, the CLS SMAP S-3 FF-SAR processor (s-3--smap) and the ESA-ESTEC/isardSAT L1 Sentinel-6 Ground Prototype Processor. All output data products are generated in standard netCDF format, and are therefore also compatible with the multi-mission “Broadview Radar Altimetry Toolbox” (BRAT, http://www.altimetry.info).The SARvatore Services are being migrated from the ESA G-POD (https://gpod.eo.esa.int/) to the Altimetry Virtual Lab, a community space for simplified services access and knowledge-sharing. It will be hosted on EarthConsole (https://earthconsole.eu), a powerful EO data processing platform now also on the ESA Network of Resources. This enables SARvatore Services to remain open for worldwide scientific applications (info at altimetry.info@esa.int).

HYDROCOASTAL is a two-year project funded by ESA, with the objective to maximise exploitation of SAR and SARin altimeter measurements in the coastal zone and inland water, by evaluating and implementing new approaches to process SAR and SARin data from CryoSat-2, and SAR altimeter data from Sentinel-3A and Sentinel-3B. Optical data from Sentinel-2 MSI and Sentinel-3 OLCI instruments will also be used in generating River Discharge products. New SAR and SARin processing algorithms for the coastal zone and inland waters will be developed and implemented and evaluated through an initial Test Data Set for selected regions. From the results of this evaluation a processing scheme will be implemented to generate global coastal zone and river discharge data sets. A series of case studies will assess these products in terms of their scientific impacts. All the produced data sets will be available on request to external researchers, and full descriptions of the processing algorithms will be provided.The scientific objectives of HYDROCOASTAL are to enhance our understanding of interactions between the inland water and coastal zone, between the coastal zone and the open ocean, and the small-scale processes that govern these interactions. Also, the project aims to improve our capability to characterize the variation at different time scales of inland water storage, exchanges with the ocean and the impact on regional sea-level changes.The technical objectives are to develop and evaluate new SAR and SARin altimetry processing techniques in support of the scientific objectives, including stack processing, and filtering, and retracking. Also, an improved Wet Troposphere Correction will be developed and evaluated.The presentation will describe the different SAR altimeter processing algorithms that are being evaluated in the first phase of the project, and present results from the evaluation of the initial test data set. It will focus particularly on the performance of the new algorithms over inland water.

Given the major role of the Atlantic Ocean in the climate system, it is essential to characterize the temporal and spatial variations of its heat content. The 4DATLANTIC-OHC Project (https://eo4society.esa.int/projects/4datlantic-ohc/) aims at developing and testing space geodetic methods to estimate the local ocean heat content (OHC) changes over the Atlantic Ocean from satellite altimetry and gravimetry. The strategy developed in the frame of the ESA MOHeaCAN Project (https://eo4society.esa.int/projects/moheacan/) is pursued and refined at local scales both for the data generation and the uncertainty estimate. At two test sites, OHC derived from in situ data (RAPID and OVIDE-AR7W) are used to evaluate the accuracy and reliability of the new space geodetic based OHC change. The Atlantic OHC product will be used to better understand the complexity of the Earth’s climate system. In particular, the project aims at better understanding the role played by the Atlantic Meridional Overturning Circulation (AMOC) in regional and global climate change, and the variability of the Meridional Heat transport in the North Atlantic. In addition, improving our knowledge on the Atlantic OHC change will help to better assess the global ocean heat uptake and thus estimate the Earth’s energy imbalance more accurately as the oceans absorb about 90% of the excess energy stored by the Earth system.The objectives of the 4DATLANTIC-OHC Project will be presented. The scientific requirements and data used to generate the OHC change products over the Atlantic Ocean and the first results in terms of development will be detailed. At a later stage, early adopters are expected to assess the OHC products strengths and limitations for the implementation of new solutions for Society. The project started in June 2021 for a 2-year duration.Visit https://www.4datlantic-ohc.org to follow the main steps of the project.

River discharge monitoring is crucial for many activities ranging from the management of water resources to flood risk mitigation. Due to the limitations of the in situ stations (e.g., low station density, incomplete temporal coverage as well as delays in data access), the river discharge is not always continuously monitored in time and in space. This prompted researchers and space agencies, among others, in developing new methods based on satellite observations for the river discharge estimation.In the last decade, ESA has funded the SaTellite based Runoff Evaluation And Mapping and River Discharge Estimation (STREAMRIDE) project, which proposes the combination of two innovative and complementary approaches, STREAM and RIDESAT, for estimating river discharge. The innovative aspect of the two approaches is an almost exclusive use of satellite data. In particular, precipitation, soil moisture and terrestrial water storage observations are used within a simple and conceptual parsimonious approach (STREAM) to estimate runoff, whereas altimeter and Near InfraRed (NIR) sensors are jointly exploited to derive river discharge within RIDESAT. By modelling different processes that act at the basin or at local scale, the combination of STREAM and RIDESAT is able to provide less than 3-day temporal resolution river discharge estimates in many large rivers of the world (e.g., Mississippi, Amazon, Danube, Po), where the single approaches fail. Indeed, even if both the approaches demonstrated high capability to estimate accurate river discharge at multiple cross sections, they are not optimal under certain conditions such as in presence of densely vegetated and mountainous areas or in non-natural basins with high anthropogenic impact (i.e., in basin where the flow is regulated by the presence of dams, reservoirs or floodplains along the river; or in highly irrigated areas).Here, we present some new advancements of both STREAM and RIDESAT approaches which help to overcome the limitations encountered. In particular, specific modules (e.g., reservoir or irrigation modules for STREAM approach) as well as algorithm retrieval improvements (e.g., to take into account the sediment and the vegetation for RIDESAT algorithm) were implemented. Furthermore, in order to exploit the complementarity of the two approaches, the two river discharge estimates were also integrated within a simple data integration framework and evaluated over sites located on the Amazon and Mississippi river basins. Results demonstrated the added-value of a complementary river discharge estimate with respect to a stand-alone estimate.

The Earth energy imbalance (EEI) at the top of the atmosphere is responsible for the accumulation of energy in the climate system. While necessary to better understand the Earth’s warming climate, measuring the EEI is challenging as it is a globally integrated variable whose variations are small (0.5-1 W.m−2) compared to the amount of energy entering and leaving the climate system (~ 340 W.m-2). Accuracies better than 0.1 W.m−2 are needed to evaluate the temporal variations of the EEI at decadal and longer time-scales, characteristic of the response to anthropogenic and natural forcing. Since the ocean absorbs about 90% of the excess energy stored by the Earth system, estimating the ocean heat content (OHC) provides an accurate proxy of the EEI. Here, the OHC is estimated at global scale based on the combination of space altimetry and space gravimetry measurements. Changes in the EEI are derived with realistic estimates of its uncertainty. The mean EEI value is estimated at +0.74±0.22 W m-2 (90% confidence level) between August 2002 and August 2016 and this value is increasing at a rate of 0.02 ± 0.05 W.m-2 (90% confidence level). Comparisons against independent estimates based on Argo data and on CERES measurements show good agreement within the error bars of the global mean and the time variations in EEI. On the other hand, discrepancies are also detected at inter-annual scales indicating that the current accuracy of EEI needs further improvement at these time scales. Estimates of the regional OHC change are also provided preliminarily and will be improved in the following months with a focus on the Atlantic Ocean. In particular, the role of the halosteric effects will be further investigated and the resulting product will be assessed against hydrographic data. The space geodetic OHC-EEI product is freely available at https://doi.org/10.24400/527896/a01-2020.003.

Africa stands to gain from Earth Observation (EO) science, products and applications. However, its use and application remain below potential on the continent. This article examines how EO can better serve the needs of African users. First, we argue that a successful uptake of EO services is conditional on understanding the African context and matching EO development and deployment to it. Using reference cases, we find that actors outside Africa drive most EO initiatives, whereas country-level expenditures on EO remain low. Recent developments, such as the African space policy and strategy, and initiatives in partnerships with Africa-based organisations to develop a community of practice on EO hold the potential to fill the identified gaps. The analysis indicates that most EO users are either government organisations or researchers, with very few cases involving other types of users. It is generally assumed that users at the local levels are educated and digitally literate, or that the transmission of EO-based knowledge is achieved by government officers and researchers. Although still very few, potentials are emerging for the private sector to deploy EO products and services such as crop or index-based insurance directly to farmers. These private initiatives have prospects for further developing indigenous EO capacity as envisioned in the African space policy and strategy. We then formulate recommendations for a transdisciplinary approach that integrates user contexts, attributes and needs to enhance the uptake of EO products and services in Africa. We conclude by proposing actions to close some of the identified gaps and seize emerging opportunities. Supplementary Information The online version contains supplementary material available at 10.1007/s10712-022-09724-1.

Satellite altimetry is a key technique to measure water level change in continental water bodies. Altimetry-based water level time series of rivers are typically constructed at locations where the satellite ground tracks intersect the rivers, the so-called virtual stations. The relatively low sampling frequency (10–27 days) of the repeat missions may result in an under-sampling of the hydrological regime in rivers with sub-monthly to weekly events. We are currently in a unique position with more than a handful satellite altimetry missions simultaneously mapping the surface elevation of the Earth. In combination, these missions contain an unexploited potential to obtain a more detailed picture of the hydrological regime of many of the Earth's rivers. The task of combining water levels measured at different locations and/or by satellites with different orbits is however, challenging due to e.g. topography, intermission biases, variation in river morphology, and other unidentified causes.In this work, we present a new method to combine multi-mission altimetry-based water levels from a river reach. This will also enable the use of geodetic missions like CryoSat-2 and SARAL/AltiKa (after June 2016) in water level time series. To combine the data we set up a state-space model where the process part is a first-order autoregressive process. The observations as a function of time and distance along the reach are described as a sum of the water level at a given time scaled by a distance-dependent factor, the mean water level at the given distance, and an error term. The scale factor and the mean water level are modeled with spline functions. We employ the model for the six rivers Lena, Solimões, Mississippi, Danube, Po, and Red, which range in width from 3 km to a few hundred meters. For each river, we consider a reach of 200–300 km and apply water levels from the satellite altimetry missions CryoSat-2, Sentinel-3A/3B, and SARAL/AltiKa. The selected reach must have a continuous elevation profile and preferable no major tributaries, which might alter the hydrological regime considerably. The length of the reach is a compromise of ensuring enough data but not violating the aforementioned criteria.When validated against in situ data we find a root mean square error ranging from 0.34 m (Solimões River) to 2.53 m (Lena River) and a correlation ranging from 0.83 (Danube River) to 0.99 (Solimões River). These summary statistics are based on approximately 2000–3000 pairs of in situ and modeled water levels. We find the largest increase in detail for the reconstructed water levels for the Danube, Po, and Red Rivers, where the water level variations are under-sampled at the virtual stations. For the Po River, we can detect sub-weekly events with the model and for the Lena River, the spring flood related to ice and snowmelt is better captured when combining the data. An additional advantage of the approach is that the water level time series can be reconstructed at all locations along the considered reach.