Recent trends in the wind-driven California current upwelling system

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordLong-term changes in the marine ecosystems of the Eastern Boundary Upwelling Systems (EBUS) are predicted due to anthropogenic climate change. In particular, global ocean acidification is having a profound effect on the coastal waters of the EBUS, affecting the entire trophic chain, net primary production (NPP) and related economic activities such as fisheries. Another predicted change related to human activity is that of upwelling dynamics with expected long-term changes in upwelling winds as proposed by Bakun (1990), Bakun et al. (2015) and Rykaczewski et al. (2015). Although these predicted long-term changes may emerge only later in the 21st century, this has fueled many studies using historical data. Long-term increase in upwelling winds has thus been a much debated topic, showing that there is considerable uncertainty depending on the EBUS considered, the effect of natural climate fluctuations, the choice of wind dataset, the time period considered, and the methodologies and significance tests applied. Therefore, there is an immediate interest in being able to monitor upwelling using verified and self-consistent wind data sets. This work focused on a sensitivity study of the estimated trends in upwelling winds in the California Current Upwelling System (CCUS), for the most recent period 1996–2018, using the two state-of-the-art satellite wind analyses and two atmospheric model re-analyses. Embedded into the strong modulation by natural climate fluctuations on interannual and decadal time scales, we do see an increase in upwelling-favorable winds in the core of the CCUS, with a local increase of more than 25% in seasonal upwelling transport for the period considered. In this central upwelling zone, a good agreement on stronger equatorward winds for the winter and spring seasons is found between the different datasets, although with different significance levels. Conversely, conflicting results are found in the southernmost part of the CCUS between the satellite analyses and the model reanalyses. Systematic, time-dependent differences are found between the wind products, highlighting the need to further investigate the poorly documented temporal stability of these widely used wind long-term climatology products. The observed spatial structuring of the estimated wind trends is consistent with the trend analysis of water chlorophyll-a, partial pressure of CO2, and basity (pH) analysis products. This result is consistent with changes being important for modulating the carbonate system within the CCUS.European Space Agenc

Salinity from Space Unlocks Satellite-Based Assessment of Ocean Acidification

Approximately a quarter of the carbon dioxide (CO2) that we emit into the atmosphere is absorbed by the ocean. This oceanic uptake of CO2 leads to a change in marine carbonate chemistry resulting in a decrease of seawater pH and carbonate ion concentration, a process commonly called “Ocean Acidification”. Salinity data are key for assessing the marine carbonate system, and new space-based salinity measurements will enable the development of novel space-based ocean acidification assess- ment. Recent studies have highlighted the need to develop new in situ technology for monitoring ocean acidification, but the potential capabilities of space-based measurements remain largely untapped. Routine measurements from space can provide quasi-synoptic, reproducible data for investigating processes on global scales; they may also be the most efficient way to monitor the ocean surface. As the carbon cycle is dominantly controlled by the balance between the biological and solubility carbon pumps, innovative methods to exploit existing satellite sea surface temperature and ocean color, and new satellite sea surface salinity measurements, are needed and will enable frequent assessment of ocean acidification parameters over large spatial scales

The Sea State CCI dataset v1: towards a sea state climate data record based on satellite observations

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 multimission monthly gridded L4 product (http://dx.doi.org/10.5285/47140d618dcc40309e1edbca7e773478, Piollé et al., 2020c)

Optimum satellite remote sensing of the marine carbonate system using empirical algorithms in the global ocean, the Greater Caribbean, the Amazon Plume and the Bay of Bengal

Improving our ability to monitor ocean carbonate chemistry has become a priority as the ocean continues to absorb carbon dioxide from the atmosphere. This long-term uptake is reducing the ocean pH; a process commonly known as ocean acidification. The use of satellite Earth Observation has not yet been thoroughly explored as an option for routinely observing surface ocean carbonate chemistry, although its potential has been highlighted. We demonstrate the suitability of using empirical algorithms to calculate total alkalinity (AT) and total dissolved inorganic carbon (CT), assessing the relative performance of satellite, interpolated in situ, and climatology datasets in reproducing the wider spatial patterns of these two variables. Both AT and CT in situ data are reproducible, both regionally and globally, using salinity and temperature datasets, with satellite observed salinity from Aquarius and SMOS providing performance comparable to other datasets for the majority of case studies. Global root mean squared difference (RMSD) between in situ validation data and satellite estimates is 17 μmol kg−1 with bias  < 5 μmol kg−1 for AT and 30 μmol kg−1 with bias  < 10 μmol kg−1 for CT. This analysis demonstrates that satellite sensors provide a credible solution for monitoring surface synoptic scale AT and CT. It also enables the first demonstration of observation-based synoptic scale AT and CT temporal mixing in the Amazon plume for 2010–2016, complete with a robust estimation of their uncertainty

Copernicus Marine Service ocean state report, issue 4

This is the final version. Available from Taylor & Francis via the DOI in this record. FCT/MCTE

Importance of the sea surface curvature to interpret the normalized radar cross-section

International audienceAsymptotic models (small perturbation and small slope approximation at first‐order, Kirchhoff approximation or two‐scale model) used to predict the normalized radar cross section of the sea surface generally fail to reproduce in detail backscatter radar measurements. In particular, the predicted polarization ratio versus incidence and azimuth angles is not in agreement with experimental data. This denotes the inability of these standard models to fully take into account the roughness properties with respect to the sensor's configuration of measurement (frequency, incidence, and polarization). On the basis of particular assumptions, to decompose the scattered electromagnetic field between zones covered with freely propagating waves and others where roughness and slopes are enhanced, recent works were able to match observations. In this paper, we do not assume such a decomposition but study the latest improvements obtained in the field of approximate scattering theories of random rough surfaces using the local and resonant curvature approximations. These models are based on an extension of the Kirchhoff Approximation up to first order to relate explicitly the curvature properties of the sea surface to the polarization strength of the scattered electromagnetic field. Consistency with previous approaches is discussed. As shown, dynamically taking into account the sea surface curvature properties of the surface is crucial to better interpret normalized radar cross‐section and polarization ratio sensitivities to both sensor characteristics and geophysical environment conditions. The proposed developments, termed the Resonant Curvature Approximation (RCA), are found to reproduce experimental data versus incidence angle and azimuth direction. The polarization sensitivity to the wind direction and incidence angle is largely improved. Finally, Gaussian statistical assumption adopted to derive the analytical expression of the normalized radar cross section is also discussed. In particular, the third‐order cumulant function is shown to better reproduce the second‐order up‐/down‐wind azimuth modulation. The proposed developments appear very promising for improvement of our understanding and analysis of both sea surface radar backscatter and Doppler signals