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This presentation describes the Copernicus Imaging Microwave Radiometer (CIMR) Sentinel expansion mission. The mission is designed to provide measurement evidence in support of developing, implementing, and monitoring the impact of the European Integrated Policy for the Arctic. Since changes in the Polar regions have profound impacts globally, CIMR will provide a new view of the cryosphere using a suite of unique low-frequency, yet high spatial resolution, microwave radiometer measurements over the high latitudes and the entire global domain. Products will be provided within 3 hours of sensing and for specific operational activities, within 1 hour over specific regions. CIMR will serve users in the Copernicus Ocean, Land and Climate Services fueling down-stream cryosphere applications. The primary instrument is a conically scanning low-frequency, high spatial resolution multi-channel microwave radiometer. A dawn-dusk orbit and large swath width of ~2000 km ensures 95% global coverage each day with a single satellite. Channels centred at L-, C-, X-, Ku- and Ka-band are fully polarised with effective spatial resolution of ≤60 km, ≤15km, ≤5 km and

The flow (flux) of climate-critical gases, such as carbon dioxide (CO2), between the ocean and the atmosphere is a fundamental component of our climate and an important driver of the biogeochemical systems within the oceans. Therefore, the accurate calculation of these air–sea gas fluxes is critical if we are to monitor the oceans and assess the impact that these gases are having on Earth's climate and ecosystems. FluxEngine is an open-source software toolbox that allows users to easily perform calculations of air–sea gas fluxes from model, in situ, and Earth observation data. The original development and verification of the toolbox was described in a previous publication. The toolbox has now been considerably updated to allow for its use as a Python library, to enable simplified installation, to ensure verification of its installation, to enable the handling of multiple sparingly soluble gases, and to enable the greatly expanded functionality for supporting in situ dataset analyses. This new functionality for supporting in situ analyses includes user-defined grids, time periods and projections, the ability to reanalyse in situ CO2 data to a common temperature dataset, and the ability to easily calculate gas fluxes using in situ data from drifting buoys, fixed moorings, and research cruises. Here we describe these new capabilities and demonstrate their application through illustrative case studies. The first case study demonstrates the workflow for accurately calculating CO2 fluxes using in situ data from four research cruises from the Surface Ocean CO2 ATlas (SOCAT) database. The second case study calculates air–sea CO2 fluxes using in situ data from a fixed monitoring station in the Baltic Sea. The third case study focuses on nitrous oxide (N2O) and, through a user-defined gas transfer parameterisation, identifies that biological surfactants in the North Atlantic could suppress individual N2O sea–air gas fluxes by up to 13 %. The fourth and final case study illustrates how a dissipation-based gas transfer parameterisation can be implemented and used. The updated version of the toolbox (version 3) and all documentation is now freely available.

Snow lying on top of sea ice plays an important role in the radiation budget because of its high albedo and the Arctic freshwater budget, and it influences the Arctic climate: it is a fundamental climate variable. Importantly, accurate snow depth products are required to convert satellite altimeter measurements of ice freeboard to sea ice thickness (SIT). Due to the harsh environment and challenging accessibility, in situ measurements of snow depth are sparse. The quasi-synoptic frequent repeat coverage provided by satellite measurements offers the best approach to regularly monitor snow depth on sea ice. A number of algorithms are based on satellite microwave radiometry measurements and simple empirical relationships. Reducing their uncertainty remains a major challenge. A High Priority Candidate Mission called the Copernicus Imaging Microwave Radiometer (CIMR) is now being studied at the European Space Agency. CIMR proposes a conically scanning radiometer having a swath >1900 km and including channels at 1.4, 6.9, 10.65, 18.7 and 36.5 GHz on the same platform. It will fly in a high-inclination dawn–dusk orbit coordinated with the MetOp-SG(B). As part of the preparation for the CIMR mission, we explore a new approach to retrieve snow depth on sea ice from multi-frequency satellite microwave radiometer measurements using a neural network approach. Neural networks have proven to reach high accuracies in other domains and excel in handling complex, non-linear relationships. We propose one neural network that only relies on AMSR2 channel brightness temperature data input and another one using both AMSR2 and SMOS data as input. We evaluate our results from the neural network approach using airborne snow depth measurements from Operation IceBridge (OIB) campaigns and compare them to products from three other established snow depth algorithms. We show that both our neural networks outperform the other algorithms in terms of accuracy, when compared to the OIB data and we demonstrate that plausible results are obtained even outside the algorithm training period and area. We then convert CryoSat freeboard measurements to SIT using different snow products including the snow depth from our networks. We confirm that a more accurate snow depth product derived using our neural networks leads to more accurate estimates of SIT, when compared to the SIT measured by a laser altimeter at the OIB campaign. Our network with additional SMOS input yields even higher accuracies, but has the disadvantage of a larger “hole at the pole”. Our neural network approaches are applicable over the whole Arctic, capturing first-year ice and multi-year ice conditions throughout winter. Once the networks are designed and trained, they are fast and easy to use. The combined AMSR2 + SMOS neural network is particularly important as a precursor demonstration for the Copernicus CIMR candidate mission highlighting the benefit of CIMR.

Microseisms in the dominant double-frequency band, around 5 s period and their ubiquitous presence makes them an interesting signal for exploring the solid Earth and associated natural hazards (e.g. Olivier et al. 2019). These microseisms are generated by opposing ocean waves of equal frequencies (Hasselmann 1963) that generally arise within the locally generated sea state at high frequencies (class I, Ardhuin et al. 2011), due to coastal reflection (class II) or when swell from a distant storm collides with another wave system, which generally corresponds to the strongest microseism sources (class III). Improving on solid Earth knowledge and natural hazard monitoring can benefit from a better quantitative knowledge of these sources. Similar applications to the study of the stratosphere can use atmospheric infrasound that are generated by the same opposing ocean waves, the microbaroms (Brekhovskikh et al. 1973, De Carlo et al. 2020). So far, very few direct measurements of wave properties have been able to quantify the presence of waves in opposite directions, and the magnitude of microseism sources has relied on numerical simulations. Here we use sun glitter measurements from the Copernicus-Sentinel 2 satellites, as processed in the SARONG project (http://www.sarong.global/). We show that the presence of opposing waves gives a strong anomaly in the phase of co-spectra of optical images from Sentinel 2 (S2). When using only 2 time-lagged images this feature generally limits the possibility to measure surface currents from waves shorter than about 25 m, that always have a significant energy in opposing directions (class I microseism sources).Caption: Processing from Sentinel 2 Level-1c images to phase speeds. Top: data from Copernicus Sentinel 2 on 29 April 2016 off California (See Figs. 3-9 in Kudryavtsev et al. 2017). Bottom: simulated S2 data based on in situ wave spectrum determined from directional moments using the Maximum Entropy Method. The phase speed anomalies, highlighted with the dashed magenta circle near the Nyquist wavelength L = 20 m, disappear when no energy propagates in opposing directions.The same also happens for longer components when strong (class III) microseism sources are present. However this signature is also an opportunity to directly measure the sources of microseisms and quantify the energy in opposing directions using 2 or more different time lags (Ardhuin et al., in 2021). Given its coastal coverage, we find that S2 is particularly well suited for estimating reflection coefficients of waves off the coast, which is a major source of uncertainty for microseism and microbarom source modelling. Ardhuin, F., Stutzmann, E., Schimmel, M., & Mangeney, A. (2011). Ocean wave sources of seismic noise. Journal of Geophysical Research, 116(C9). doi:10.1029/2011jc006952Kudryavtsev, V., Yurovskaya, M., Chapron, B., Collard, F., & Donlon, C. (2017). Sun glitter imagery of ocean surface waves. Part 1: Directional spectrum retrieval and validation. Journal of Geophysical Research: Oceans, 122(2), 1369–1383. doi:10.1002/2016jc012425 Olivier, G., Brenguier, F., Carey, R., Okubo, P., & Donaldson, C. (2019). Decrease in seismic velocity observed prior to the 2018 eruption of Kīlauea volcano with ambient seismic noise interferometry. Geophysical Research Letters. doi:10.1029/2018gl081609

Across spatial and temporal scales, sea-ice motion has implications on ship navigation, the sea-ice thickness distribution, sea ice export to lower latitudes and re-circulation in the polar seas, among others. Satellite remote sensing is an effective way to monitor sea-ice drift globally and daily, especially using the wide swaths of passive microwave missions. Since the late 1990s, many algorithms and products have been developed for this task. Here, we investigate how processing sea-ice drift vectors from the intersection of individual swaths of the Advanced Microwave Scanning Radiometer 2 (AMSR2) mission compares to today’s status-quo (processing from daily averaged maps of brightness temperature).We document that the “swath-to-swath” (S2S) approach results in many more (two orders of magnitude) sea-ice drift vectors than the “daily-maps” (DM) approach. These S2S vectors also validate better when compared to trajectories of on-ice drifters. For example, the RMSE of the 24 hour Arctic sea-ice drift is 0.9 km for S2S vectors, and 1.3 km for DM vectors from the 36.5 GHz imagery of AMSR2.Through a series of experiments with actual AMSR2 data and simulated Copernicus Imaging Microwave Radiometer (CIMR) data, we study the impact that geo-location uncertainty and imaging resolution have on the accuracy of the sea-ice drift vectors. We conclude by recommending that a “swath-to-swath” approach is adopted for the future operational Level-2 sea-ice drift product of the CIMR mission. We outline some potential next steps towards further improving the algorithms, and making the user community ready to fully take advantage of such a product.This work is currently under revision at EGU The Cryosphere as https://tc.copernicus.org/preprints/tc-2020-332/

The threat of sea level rise to coastal communities is an area of significant concern to the well-being and security of future generations. Environmental policy actions and decisions affecting coastal states are being made now. Given the considerable range of applications, sustained altimetry satellite missions are required to address operational, science and societal needs. This article describes the Copernicus Sentinel-6 mission that is designed to address the needs of the European Copernicus programme for precision sea level, near-real-time measurements of sea surface height, significant wave height, and other products tailored to operational services in the climate, ocean, meteorology and hydrology domains. It is designed to provide enhanced continuity to the very stable time series of mean sea level measurements and ocean sea state started in 1992 by the TOPEX/Poseidon (T/P) 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 main payload is the Poseidon-4 dual frequency (C/Ku-band) nadir-pointing radar altimeter providing synthetic aperture radar (SAR) processing in Ku-band to improve the signal through better along-track sampling and reduced measurement noise. The altimeter has an innovative interleaved mode enabling radar data processing on two parallel chains, one with the SAR enhancements and the other furnishing a "Low Resolution Mode" that is fully backward-compatible with the historical T/P and Jason measurements, so that complete inter-calibration between the state-of-the-art data and the historical record can be assured. A three-channel Advanced Microwave Radiometer for Climate (AMR-C) developed by NASA JPL provides measurements of atmospheric water vapour that would otherwise degrade the radar altimeter measurements. An experimental High Resolution Microwave Radiometer (HRMR) is also included in the AMR-C design to support improved performance in coastal areas. Additional sensors are included in the payload to provide Precise Orbit Determination, atmospheric sounding via GNSS-Radio Occultation and radiation monitoring around the spacecraft.Early in-orbit performance data are presented.

Over the coming decade, the quartet of Sentinel-3 satellite altimeters will provide a continuous record of ice sheet elevation change. To ensure consistency of measurement between each of the four satellites, requires rigorous in-flight inter-comparison. To facilitate this, Sentinel-3B was initially flown in a unique tandem formation with Sentinel-3A, enabling near-instantaneous, co-located measurements to be acquired. Here, we analyse tandem measurements of ice sheet elevation, to show that both instruments operate with statistically equivalent accuracy and precision, even over complex ice margin terrain. This analysis demonstrates that both satellites can be used interchangeably to study ice sheet evolution.

ESA initiated in 2018 an architectural design study to prepare the development of the next generation of the optical component of Sentinel 2 and Sentinel 3. This encompasses the next generation of the Multi Spectral Imager (MSI), Ocean and Land Color Imager (OLCI) and Sea and Land Surface Temperature Radiometer (SLSTR) observations. The aim of this activity was to analyse and trade-off different architectural options for the Next-Generation of the Copernicus Space Component optical imaging missions in the 2032 time horizon, considering user needs, addressing mainly the Copernicus Marine and Land services, starting from user requirements for Copernicus Next Generation derived from EC studies and related workshops. It also did draw from the experience and lessons learned regarding the current generation of Sentinel 2 and Sentinel 3, to ensure continuity of services and further enhancement as identified, necessary to meet new and emerging user needs. The study investigated also trends both in terms of other spaceborne optical missions by national agencies in Europe and worldwide, as well as commercial missions e.g. with the advent of “New Space” constellations of small satellites. Observation gaps and potential synergies were identified to avoid duplication when establishing the architecture of the next generation of the Copernicus Space Component optical imaging family for land and ocean applications. A wide range of scenarios have been analysed for possible combination of several observation capabilities within the same instrument, on the same platform or on satellites flying in formation, assessing pros and cons with respect to scenarios with free-flyer satellites for each observation capability. Based on the above analysis of user needs, gap/synergy analysis and architectural concept trade-offs, high level mission assumptions and technical requirements are being established for the continuity of the MSI, OLCI and SLSTR observations, including any additional elements, as identified, to meet user requirements in the respective Copernicus services and application areas.

Sea state data are of major importance for climate studies, marine engineering, safety at sea and coastal management. However, long-term sea state datasets are sparse and not always consistent, and sea state data users still mostly rely on numerical wave models for research and engineering applications. Facing the urgent need for a sea state climate data record, the Global Climate Observing System has listed “Sea State” as an Essential Climate Variable (ECV), fostering the launch in 2018 of the Sea State Climate Change Initiative (CCI). The CCI is a programme of the European Space Agency, whose objective is to realise the full potential of global Earth observation archives established by ESA and its member states in order to contribute to the ECV database. This paper presents the implementation of the first release of the Sea State CCI dataset, the implementation and benefits of a high-level denoising method, its validation against in situ measurements and numerical model outputs, and the future developments considered within the Sea State CCI project. The Sea State CCI dataset v1 is freely available on the ESA CCI website (http://cci.esa.int/data, last access: 25 August 2020) at ftp://anon-ftp.ceda.ac.uk/neodc/esacci/sea_state/data/v1.1_release/ (last access: 25 August 2020). Three products are available: a multi-mission along-track L2P product (http://dx.doi.org/10.5285/f91cd3ee7b6243d5b7d41b9beaf397e1, Piollé et al., 2020a), a daily merged multi mission along-track L3 product (http://dx.doi.org/10.5285/3ef6a5a66e9947d39b356251909dc12b, Piollé et al., 2020b) and a multi-mission monthly gridded L4 product (http://dx.doi.org/10.5285/47140d618dcc40309e1edbca7e773478, Piollé et al., 2020c).

Surface currents are poorly known over most of the oceans. Satellite-borne Doppler Waves and Current Scatterometers (DWCS) can be used to fill this observation gap. The Sea surface KInematics Multiscale (SKIM) proposal, is the first satellite concept built on a DWCS design at near-nadir angles, and now one of the two candidates to become the 9th mission of the European Space Agency Earth Explorer program. As part of the detailed design and feasibility studies (phase A) funded by ESA, airborne measurements were carried out with both a Ku-Band and a Ka-Band Doppler radars looking at the sea surface at near nadir-incidence in a real-aperture mode, i.e. in a geometry and mode similar to that of SKIM. The airborne radar KuROS was deployed to provide simultaneous measurements of the radar backscatter and Doppler velocity, in a side-looking configuration, with an horizontal resolution of about 5 to 10m along the line of sight and integrated in the perpendicular direction over the real-aperture 1-way 3-dB footprint diameter (about 580m). The KaRADOC system has a much narrower beam and footprint that only about 45m in diameter. The experiment took place in November 2018 off the French Atlantic coast, with sea states representative of the open ocean and a well known tide-dominated current regime. The data set is analyzed to explore the contribution of non-geophysical velocities to the measurement and how the geophysical part of the measured velocity combines wave-resolved and wave-averaged scales. We find that the measured Doppler velocity contains a characteristic wave phase speed, called here C0 that is analogous to the Bragg phase speed of coastal High Frequency radars that use a grazing measurement geometry, with little variations ΔC associated to changes in sea state. The Ka-band measurements at an incidence of 12° are 10% lower than the theoretical estimate C0~2.4m/s for typical oceanic conditions defined by a wind speed of 7m/s and a significant wave height of 2m. For Ku-band the measured data is 30% lower than the theoretical estimate 2.8m/s. ΔC is of the order of 0.2m/s for a 1m change in wave height, and cannot be confused with a 1m/s change in tidal current. The actual measurement of the current velocity from an aircraft at 4 to 18° incidence angle is, however, made difficult by uncertainties on the measurement geometry, which are much reduced in satellite measurements.

Climatologies, or long-term averages, of essential climate variables are useful for evaluating models and providing a baseline for studying anomalies. The Surface Ocean CO2 Atlas (SOCAT) has made millions of global underway sea surface measurements of CO2 publicly available, all in a uniform format and presented as fugacity, fCO2. As fCO2 is highly sensitive to temperature, the measurements are only valid for the instantaneous sea surface temperature (SST) that is measured concurrently with the in-water CO2 measurement. To create a climatology of fCO2 data suitable for calculating air–sea CO2 fluxes, it is therefore desirable to calculate fCO2 valid for a more consistent and averaged SST. This paper presents the OceanFlux Greenhouse Gases methodology for creating such a climatology. We recomputed SOCAT's fCO2 values for their respective measurement month and year using monthly composite SST data on a 1° × 1° grid from satellite Earth observation and then extrapolated the resulting fCO2 values to reference year 2010. The data were then spatially interpolated onto a 1° × 1° grid of the global oceans to produce 12 monthly fCO2 distributions for 2010, including the prediction errors of fCO2 produced by the spatial interpolation technique. The partial pressure of CO2 (pCO2) is also provided for those who prefer to use pCO2. The CO2 concentration difference between ocean and atmosphere is the thermodynamic driving force of the air–sea CO2 flux, and hence the presented fCO2 distributions can be used in air–sea gas flux calculations together with climatologies of other climate variables.

We present a Multisensor Matchup System (MMS) that allows systematic detection of satellite based sensor-to-sensor matchups and the extraction of local subsets of satellite data around matchup locations. The software system implements a generic matchup-detection approach and is currently being used for validation and sensor harmonisation purposes. An overview of the flexible and highly configurable software architecture and the target processing environments is given. We discuss improvements implemented with respect to heritage systems, and present some performance comparisons. A detailed description of the intersection algorithm is given which allows a fast matchup detection in geometry and time.

We applied coincident Earth observation data collected during 2008 and 2009 from multiple sensors (RA2, AATSR and MERIS, mounted on the European Space Agency satellite Envisat) to characterise environmental conditions and integrated sea–air fluxes of CO2 in three Arctic seas (Greenland, Barents, Kara). We assessed net CO2 sink sensitivity due to changes in temperature, salinity and sea ice duration arising from future climate scenarios. During the study period the Greenland and Barents seas were net sinks for atmospheric CO2, with integrated sea–air fluxes of −36 ± 14 and −11 ± 5 Tg C yr−1, respectively, and the Kara Sea was a weak net CO2 source with an integrated sea–air flux of +2.2 ± 1.4 Tg C yr−1. The combined integrated CO2 sea–air flux from all three was −45 ± 18 Tg C yr−1. In a sensitivity analysis we varied temperature, salinity and sea ice duration. Variations in temperature and salinity led to modification of the transfer velocity, solubility and partial pressure of CO2 taking into account the resultant variations in alkalinity and dissolved organic carbon (DOC). Our results showed that warming had a strong positive effect on the annual integrated sea–air flux of CO2 (i.e. reducing the sink), freshening had a strong negative effect and reduced sea ice duration had a small but measurable positive effect. In the climate change scenario examined, the effects of warming in just over a decade of climate change up to 2020 outweighed the combined effects of freshening and reduced sea ice duration. Collectively these effects gave an integrated sea–air flux change of +4.0 Tg C in the Greenland Sea, +6.0 Tg C in the Barents Sea and +1.7 Tg C in the Kara Sea, reducing the Greenland and Barents sinks by 11% and 53%, respectively, and increasing the weak Kara Sea source by 81%. Overall, the regional integrated flux changed by +11.7 Tg C, which is a 26% reduction in the regional sink. In terms of CO2 sink strength, we conclude that the Barents Sea is the most susceptible of the three regions to the climate changes examined. Our results imply that the region will cease to be a net CO2 sink in the 2050s.

Coccolithophores are the primary oceanic phytoplankton responsible for the production of calcium carbonate (CaCO3). These climatically important plankton play a key role in the oceanic carbon cycle as a major contributor of carbon to the open ocean carbonate pump (~50%) and their calcification can affect the atmosphere-to-ocean (air-sea) uptake of carbon dioxide (CO2) through increasing the seawater partial pressure of CO2 (pCO2). Here we document variations in the areal extent of surface blooms of the globally important coccolithophore, Emiliania huxleyi, in the North Atlantic over a 10-year period (1998–2007), using Earth observation data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). We calculate the annual mean sea surface areal coverage of E. huxleyi in the North Atlantic to be 474 000 ± 104 000 km2, which results in a net CaCO3 carbon (CaCO3-C) production of 0.14–1.71 Tg CaCO3-C per year. However, this surface coverage (and, thus, net production) can fluctuate inter-annually by −54/+8% about the mean value and is strongly correlated with the El Niño/Southern Oscillation (ENSO) climate oscillation index (r=0.75, p

Climatologies, or long-term averages, of essential climate variables are useful for evaluating models and providing a baseline for studying anomalies. The Surface Ocean Carbon Dioxide (CO2) Atlas (SOCAT) has made millions of global underway sea surface measurements of CO2 publicly available, all in a uniform format and presented as fugacity, fCO2. fCO2 is highly sensitive to temperature and the measurements are only valid for the instantaneous sea surface temperature (SST) that is measured concurrent with the in-water CO2 measurement. To create a climatology of fCO2 data suitable for calculating air–sea CO2 fluxes it is therefore desirable to calculate fCO2 valid for climate quality SST. This paper presents a method for creating such a climatology. We recomputed SOCAT's fCO2 values for their respective measurement month and year using climate quality SST data from satellite Earth observation and then extrapolated the resulting fCO2 values to reference year 2010. The data were then spatially interpolated onto a 1° × 1° grid of the global oceans to produce 12 monthly fCO2 distributions for 2010. The partial pressure of CO2 (pCO2) is also provided for those who prefer to use pCO2. The CO2 concentration difference between ocean and atmosphere is the thermodynamic driving force of the air–sea CO2 flux, and hence the presented fCO2 distributions can be used in air–sea gas flux calculations together with climatologies of other climate variables.