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Regional horizontal and vertical patterns of ocean kinetic energy (KE) during 1983–2018 are studied using a numerical simulation. The analysis is focused on time‐mean and transient components of KE. For understanding its contribution to the total as function of timescale, the transient part is further sub‐divided into six frequency bands, with periods >16 months, 16–8 months, 8–4 months, 4–1 months, 1 month–5 days and <5 days. Near the surface, besides intensification due to wind‐forced generation, transient KE is enhanced in boundary currents, in equatorial wave guides and in the Southern Ocean. In the deep, KE is enhanced in re‐circulation regions under boundary currents and at eastern sides of topographic ridges. On scales <5 days it is enhanced over shelf and in quiet ocean interior areas. The largest fraction of transient energy resides in the eddy‐populated band 1 week–4 months. Decadal changes of KE are associated with mean flow variations and changes on inter‐ and intra‐annual periods, especially in the Atlantic and Southern Oceans. Changes in the subpolar Atlantic are correlated with the North Atlantic Oscillation and in the Southern Ocean with the Southern Annular Mode. A decrease/increase in Atlantic/Pacific KE is noticed over the investigated period. Trends are found in the Gulf Stream, Kuroshio Current and along the Antarctic Circumpolar Current, which shows an increase in mean and transient energy in the Indian/west Pacific sectors and a decrease in the Atlantic sector. The strong variations between decades suggest that trends are part of multi‐decadal variability. Plain Language Summary: Horizontal, vertical and temporal distributions of ocean kinetic energy (KE) during 1983–2018 are studied with a numerical simulation. We focus the time‐averaged and time‐varying KE, the latter sub‐divided into periods: >16 months, 16–8 months, 8–4 months, 4–1 months, 1 month–5 days and <5 days. KE is large in the upper ocean due to wind forcing and decreases with depth. It is large in currents along ocean western boundaries, in equatorial regions and along the Southern Ocean circumpolar current. In the deep, KE is large in re‐circulation regions under strong currents and at eastern sides of bottom topography. Variations <5 days are large over shelves and in the ocean interior away from boundary currents. The largest fraction of energy resides between 1 week and 4 months, where rotating water bodies are dominant. A decrease in Atlantic and increase in Pacific KE were noticed. Changes in subpolar Atlantic and in Southern Ocean are related to climate modes, namely the North Atlantic Oscillation and the Southern Annular Mode. The Southern Ocean shows an energy increase in the Indian/west‐Pacific sectors and a decrease in the Atlantic sector. Strong variations between decades suggest changes are part of longer timescale variations. Key Points: Ocean kinetic energy (KE) is surface intensified. In the deep, it is enhanced primarily in the vicinity of topographic structuresThe largest fraction of transient KE is found at eddy‐rich periods (1 week–3 months), showing a sustained decrease globallySubpolar Atlantic KE changes are linked to the North Atlantic Oscillation and Southern Ocean changes to the Southern Annular Mode [ABSTRACT FROM AUTHOR]

Sea level rise (SLR) is a long‐lasting consequence of climate change because global anthropogenic warming takes centuries to millennia to equilibrate for the deep ocean and ice sheets. SLR projections based on climate models support policy analysis, risk assessment and adaptation planning today, despite their large uncertainties. The central range of the SLR distribution is estimated by process‐based models. However, risk‐averse practitioners often require information about plausible future conditions that lie in the tails of the SLR distribution, which are poorly defined by existing models. Here, a community effort combining scientists and practitioners builds on a framework of discussing physical evidence to quantify high‐end global SLR for practitioners. The approach is complementary to the IPCC AR6 report and provides further physically plausible high‐end scenarios. High‐end estimates for the different SLR components are developed for two climate scenarios at two timescales. For global warming of +2°C in 2100 (RCP2.6/SSP1‐2.6) relative to pre‐industrial values our high‐end global SLR estimates are up to 0.9 m in 2100 and 2.5 m in 2300. Similarly, for a (RCP8.5/SSP5‐8.5), we estimate up to 1.6 m in 2100 and up to 10.4 m in 2300. The large and growing differences between the scenarios beyond 2100 emphasize the long‐term benefits of mitigation. However, even a modest 2°C warming may cause multi‐meter SLR on centennial time scales with profound consequences for coastal areas. Earlier high‐end assessments focused on instability mechanisms in Antarctica, while here we emphasize the importance of the timing of ice shelf collapse around Antarctica. This is highly uncertain due to low understanding of the driving processes. Hence both process understanding and emission scenario control high‐end SLR. Plain Language Summary: Taking a co‐production approach between scientists and practioners, we provide high‐end sea level rise (SLR) estimates for practitioner application based on an expert evaluation of physical evidence and approaches currently used in policy environments to understand high end risk. We do this for two global warming scenarios, a modest and a strong one, for two time slices 2100 and 2300. The large and growing differences between the scenarios beyond 2100 emphasize the long‐term benefits of mitigation. However, even a modest warming may cause multi‐meter SLR on centennial time scales with profound consequences for coastal areas. Earlier high‐end assessments focused on instability mechanisms in Antarctica, while here we emphasize the importance of the timing of ice shelf collapse around Antarctica as well as how practitioners use high end projections to frame risk. We stress that both emission scenario and limited physical understanding control the outcome. Key Points: A high‐end estimate of sea level rise in 2100 and 2300Decisionmaker/practitioner perspective on high‐endTiming of collapse of ice shelves critical [ABSTRACT FROM AUTHOR]

Sea Surface Salinity (SSS) is an increasingly used Essential Ocean and Climate Variable. The Soil Moisture and Ocean Salinity (SMOS), Aquarius, and Soil Moisture Active Passive (SMAP) satellite missions all provide SSS measurements, with very different instrumental features leading to specific measurement characteristics. The Climate Change Initiative Salinity project (CCI + SSS) aims to produce a SSS Climate Data Record (CDR) that addresses well‐established user needs based on those satellite measurements. To generate a homogeneous CDR, instrumental differences are carefully adjusted based on in‐depth analysis of the measurements themselves, together with some limited use of independent reference data. An optimal interpolation in the time domain without temporal relaxation to reference data or spatial smoothing is applied. This allows preserving the original datasets variability. SSS CCI fields are well suited for monitoring weekly to interannual signals, at spatial scales ranging from 50 km to the basin scale. They display large year‐to‐year seasonal variations over the 2010–2019 decade, sometimes by more than ±0.4 over large regions. The robust standard deviation of the monthly CCI SSS minus in situ Argo salinities is 0.15 globally, while it is at least 0.20 with individual satellite SSS fields. r2 is 0.97, similar or better than with original datasets. The correlation with independent ship thermosalinographs SSS further highlights the CCI data set excellent performance, especially near land areas. During the SMOS‐Aquarius period, when the representativity uncertainties are the largest, r2 is 0.84 with CCI while it is 0.48 with the Aquarius original data set. SSS CCI data are freely available and will be updated and extended as more satellite data become available. Plain Language Summary: Salinity measures the mass of dissolved salts in seawater. Together with temperature and pressure, it determines the seawater density, which is crucial in driving oceanic motions. Low sea surface salinity (SSS) can be the result of freshwater inputs such as rain, river runoffs, and ice melt. In contrast, high SSS often characterize regions of strong evaporation. The salinity imprint of these processes is then carried by ocean currents over long distances and long periods of time. SSS also impacts ocean circulation through its effect on density, and modulates ocean‐atmosphere exchanges of heat and gases. SSS is a hence key variable for ocean and climate studies, both as a passive tracer and as an important actor of oceanic processes. Since 2010, three satellite missions have monitored SSS with an unprecedented spatial and temporal resolution. For the first time, data from these satellites are combined, taking each instrument specific features into account. The resulting data set enables global SSS to be monitored and studied with unprecedented accuracy over the 2010–2019 period, at a 50 km, weekly or monthly resolution. It reveals large SSS signals related to phenomena affecting climate in various parts of the world ocean. Key Points: 2010–2019 Sea Surface Salinity fields built from three satellite missions data setsMonitors sea surface salinity variability at large meso‐ to basin scale with unprecedented accuracy and spatio‐temporal coverageAnswers the need for Sea Surface Salinity global fields at higher resolution than 1 month, 1° [ABSTRACT FROM AUTHOR]

The effects of temporal changes in the marine geoid on estimates of the ocean dynamic topography are being investigated. Influences from mass redistribution due to changes of land hydrology, ice sheets, glacial isostatic adjustment (GIA), and ocean and atmospheric dynamics are considered, and the associated crustal deformation is included. The strongest signals are associated with the seasonal cycle caused by changes in terrestrial water storage and ice sheets as well as the redistribution of atmospheric mass. Second to this is the importance of an overall trend caused by GIA and decreasing ice sheets over Greenland and Antarctica. On long spatial scales, the amplitude of regional trends estimated for the geoid height has a sizable fraction of those from sea level anomaly (SLA) for the period 1993–2016, also after subtraction of steric height of the upper 1,000 m to analyze trends in deep ocean geostrophic currents. The estimated strong negative geoid height trend south of Greenland for the period 1993–2016 opposes changes in dynamic sea level for the same period thereby affecting past studies on changes of both the strength of the subpolar gyre based on SLA and the meridional overturning circulation on a section between Cape Farewell and Portugal applying ocean dynamic topography and hydrography. We conclude that temporal geoid height trends should be considered in studies of (multi)decadal trends in sea level and circulation on large spatial scales based on altimetry data referenced to a geoid field. Plain Language Summary: Changes in ocean surface currents are routinely obtained from satellite altimetry data. A correction for changes in the geoid, the equipotential surface of gravity closest to sea level, is considered small and thus usually neglected. We investigate temporal geoid height changes and potential implications on ocean circulation studies using space‐borne gravity data and results from ocean and atmosphere models to discover the individual processes of mass redistribution in the climate system causing thereby changes in the geoid height. We found the largest signals in the seasonal cycle for terrestrial hydrology in the Amazone basin and in negative trends for the Greenland and West Antarctic Ice sheets. For the period 1993–2016 and on spatial scale larger than 1,000 km or so the magnitude of the negative marine geoid height trend south of Greenland is similar to the strength of the negative trend in geocentric sea level from altimetry. This outcome affects past studies on changes in the strength of the subpolar gyre and the Atlantic meridional overturning circulation that neglect geoid height variations. We conclude that temporal geoid height trends should be considered in studies of (multi)decadal trends in sea level and circulation on large spatial scales based on altimetry data. Key Points: The strongest geoid height changes are associated with regionally pronounced seasonal signals and secular trendsIn the Subpolar North Atlantic the geoid height trend biases circulation trend estimates based on altimetryAltimetry data need correction for geoid height change when long‐term variations in ocean dynamics are studied [ABSTRACT FROM AUTHOR]

C‐band microwave sea surface radar backscatter observations from the FINO‐2 tower in the western Baltic are analyzed with respect to their relevance for air‐sea CO2 transfer velocity parameterizations. The scatterometer measurements observed from a height of 25 m above the sea surface using a multifrequency scatterometer instrument of the University of Hamburg were obtained quasi‐simultaneously with eddy covariance CO2 flux measurements. Both data sets are merged here to derive a gas transfer velocity parameterization based on radar backscatter measurements. At the location of the FINO‐2 tower, the resulting time‐averaged gas transfer velocity amounts to 26.95 cm/hr. In combination with ΔPCO2 measurements available from the vicinity of the FINO‐2 platform, a time‐mean CO2 flux of 0.23 μmol·m−2·s−1 into the Baltic was estimated. Applied to monthly mean satellite‐based C‐band ASCAT scatterometer data, the newly derived gas transfer velocity parameterization provides estimates of seasonal and annual mean global maps of air‐sea transfer velocities. The new results agree in their general pattern with previous estimates using wind speed parameterization. However, the backscatter‐based transfer velocities appear smaller at higher latitudes. Globally averaged air‐sea CO2 fluxes would thereby be reduced by 20%. To what extent this is a robust result, or if it depends on the fact that the training data set did not represent conditions, has to be investigated in the future. Key Points: Derivation of new air‐sea flux parameterization for CO2 fluxesApplication of new parameterization to satellite scatterometer dataProvision of seasonal and annual mean CO2 estimates [ABSTRACT FROM AUTHOR]

An approach to analyze high‐end sea level rise is presented to provide a conceptual framework for high‐end estimates as a function of time scale, thereby linking robust sea level science with stakeholder needs. Instead of developing and agreeing on a set of high‐end sea level rise numbers or using an expert consultation, our effort is focused on the essential task of providing a generic conceptual framework for such discussions and demonstrating its feasibility to address this problem. In contrast, information about high‐end sea level rise projections was derived previously either from a likely range emerging from the highest view of emissions in the Intergovernmental Panel on Climate Change assessment (currently the Representative Concentration Pathway 8.5 scenario) or from independent ad hoc studies and expert solicitations. Ideally, users need high‐end sea level information representing the upper tail of a single joint sea level frequency distribution, which considers all plausible yet unknown emission scenarios as well as involved physical mechanisms and natural variability of sea level, but this is not possible. In the absence of such information we propose a framework that would infer the required information from explicit conditional statements (lines of evidence) in combination with upper (plausible) physical bounds. This approach acknowledges the growing uncertainty in respective estimates with increasing time scale. It also allows consideration of the various levels of risk aversion of the diverse stakeholders who make coastal policy and adaptation decisions, while maintaining scientific rigor. Key Points: Previous publication of high end sea level differs in their meaningDevelopment of new concept for high‐end sea level estimatesHigh‐end estimates have to be a function of scenario and time frame considered [ABSTRACT FROM AUTHOR]

During recent decades, through theoretical considerations and analyses of observations and model simulations, the scientific community has fundamentally advanced our understanding of the coupled climate system, thereby establishing that humans affect the Earth's climate. Resulting from this remarkable accomplishment, the COP21 agreement marks a historic turning point for climate research by calling for actionable regional climate change information on time scales from seasonal to centuries for the benefit of humanity, as well as living and nonliving elements of the Earth environment. Out of the underlying United National Framework Convention on climate Change process, improving seamless regional climate forecast capabilities emerges as a key challenge for the international research community. Addressing it requires a multiscale approach to climate predictions. Here we offer a vision that emphasizes enhanced scientific understanding of regional to local climate processes as the foundation for progress. The scientific challenge is extreme due to the rich complexity of interactions and feedbacks between regional and global processes, each of which affects the global climate trajectory. To gain the necessary scientific insight and to turn it into actionable climate information require technical development, international coordination, and a close interaction between the science and stakeholder communities. Plain Language Summary: During recent decades, through theoretical considerations and analyses of observations and model simulations, the scientific community has fundamentally advanced our understanding of the coupled climate system, thereby establishing that humans affect the Earth's climate. Building on this remarkable accomplishment, the COP21 agreement marks a historic turning point for climate research by calling for actionable regional climate change information on time scales from seasonal to centuries for the benefit of humanity and the full biosphere. Out of the underlying United National Framework Convention on climate Change process, improving seamless regional climate forecast capabilities emerges as a closely linked challenge for the international research community. Addressing this challenge requires a multiscale approach to climate predictions. Here we offer a vision for realizing an approach that emphasizes enhanced scientific understanding of regional to local climate processes as the foundation for progress. The scientific challenge is extreme due to the rich complexity of interactions and feedbacks between regional and global processes, each of which affects the global climate trajectory. Technical development, international coordination, and a close interaction between the science and stakeholder communities are also required. In their absence scientific insight cannot be gained or turned into actionable climate information. Key Points: The challenge of improving seamless regional climate forecast requires enhanced scientific understanding of regional to local climate processesEstablishing actionable climate information calls for the technical development of multiscale approaches to climate predictionsReaching these goals relies on international coordination and on a close interaction between the science and stakeholder communities [ABSTRACT FROM AUTHOR]

Several existing statistical and dynamical reconstructions of past regional sea level variability and trends are compared with each other and with tide gauges over the 48 year period 1960-2007, partially predating the satellite altimetry era. Evaluated statistical reconstructions were built from tide-gauge data (TGR), and dynamical reconstructions from ocean data assimilation (ODA) approaches. Although most of the TGRs yield global-mean time series of sea level with trends deviating within only ±0.1 mm yr−1, the spatial anomalies of the trends deviate substantially between the reconstructions over the period predating altimetry. In contrast, TGRs match observed regional trend patterns fairly well during the satellite altimetry era. TGRs match tide-gauge data better than ODA results; however, they exhibit less variability in the open ocean compared to altimetric data. Over the prealtimetry period, all reconstructed regional sea level trend patterns deviate substantially from each other. In terms of detrended correlations in this earlier period, the reconstructions match tide gauges, and each other, much better in the Pacific than in the Atlantic. An ensemble of all TGR and ODA estimates provides some improvements in correlations and trends to both tide gauges and altimetry. Nevertheless, a lack of independent open ocean sea surface height data predating altimetry makes impossible the validation of the ensemble for prealtimetry open ocean sea level trends and variability. Estimating regional sea level changes prior to altimetry therefore remains an unsolved challenge. [ABSTRACT FROM AUTHOR]