Otras

Recent developments on the wind geophysical model function (GMF) of Ku-band scatterometers include a sea surface temperature (SST) dependent term. It has been found that the SST effects on the radar backscatter are wind speed dependent and more pronounced in vertical polarization (VV) than in horizontal polarisation (HH) at higher incidence angles, and are mainly relevant at Ku radar wavelengths rather than at C-band. The new Ku-band GMF, NSCAT-5, was initially based on a physical model and RapidScat radar backscatter measurements, which are only available at two incidence angles, i.e., 48.8⁰ and 55.2⁰, for HH and VV beams, respectively. A more recent CDOP-2 AS study (OSI_AVS_17_01) confirms only small differences when verifying the NSCAT-5 GMF at similar incidence angles, using data from the recently-launched Indian SCATSat-1, which operates at 49.1⁰ (HH) and 57.9⁰ (VV) incidence angle. In order to further consolidate the NSCAT-5 GMF, the current study looks for quality control (QC) dependencies. It is found that indeed, the developed GMF is not particularly sensitive to different QC thresholds. Finally, an improved QC method, based on the successful experience with previous Ku-band rotating pencil-beam scatterometers, is developed for SCATSat-1 data.

In this study, the azimuth cut-off approach, which is typically adopted to estimate wind speed from Synthetic Aperture Radar (SAR) imagery collected under nominal wind conditions, is discussed with respect to high wind regime cases. First, the key roles played by the pixel spacing, the size of the boxes used to partition the SAR imagery and the image texture (homogeneity) are discussed in terms of their effects on the azimuth cut-off (λc) estimation. Then, the reliability of the λc estimation is analyzed by measuring the distance between the measured and fitted autocorrelation functions (ACFs). This analysis shows that it is of paramount importance to filter unfeasible/unreliable λc values. To identify those values in an objective way a criterion is proposed that is based on the χ2 test performed over a large dataset of Sentinel-1 SAR imagery. The effectiveness of the χ2 test is verified by correlating the accepted estimates against auxiliary significant wave height data.

The impact of specular point location estimate inaccuracies on satellite delay-Doppler map (DDM) observed distortions is assessed in this paper. A set of raw reflected Global Navigation Satellite System (GNSS-R) echoes acquired by the satellite constellation Cyclone GNSS (CYGNSS) during hurricanes Irma and Harvey has been recompressed by progressively reducing the Doppler frequency inaccuracy at the specular point. The results show that recompressing raw echoes with highly accurate specular point location estimates strongly reduces the DDM distortions.

The monitoring of the global distribution of sea surface salinity (SSS) is vital to understand the ocean’s role in the Earth’s climate. Until the advent of the spaceborne L-band radiometers, SSS observations were mainly acquired by in-situ sensors (moored buoys, drifters, and thermosalinographs). As a result, knowledge of the spatial and temporal variability of salinity has been scarce due to the lack of a comprehensive set of salinity observations. While in-situ data (e.g., Argo floats) were being used in a growing number of studies, numerical models were also widely used as a complementary source of such information. The spatiotemporal resolution achieved by satellite salinity measurements has no equivalent among the other existing salinity observations systems. Since the launch of the Soil Moisture and Ocean Salinity (SMOS) mission (2009) and then the Aquarius mission (2001), more than seven years of satellite-derived SSS data, with a spatial and temporal resolution adequate for climate and ocean general circulation studies, have become available. The L-band radiometers onboard SMOS and Aquarius have proven to be challenging and various spatial and temporal averaging and data fusion techniques have been implemented to better recover structured and meaningful geophysical information from remote sensing SSS retrievals. A comprehensive validation is therefore essential to characterize the information provided by the different salinity products.

Work Package (WP) 5000 uses the knowledge acquired in previous TGSCATT WPs to consolidate, validate and document the Level-1 to Level-2 inversion algorithms for TDS-1. Validation entails the development of extended TDS-1 matchup datasets with new independent measurements to validate the performance of the inversion algorithms over a wide range of conditions. The task should result in documentation of the TDS-1 Level 2 inversion algorithms in the form of Algorithm Theoretical Basis Documents (ATBD). Over the course of the TGSCATT project, a new Level 2 SGR-ReSI wind dataset, using the so-called Calibrated Bistatic Radar Equation (CBRE) approach [1], has been made available to the team. Such wind dataset addresses several systematic and random errors present in earlier SGR-ReSI data versions and is therefore of high interest to the project. As such, WP5000 has been somewhat redefined and is now focused on the objective validation of the new wind dataset.

Recent developments on the wind geophysical model function (GMF) of Ku-band scatterometers include a sea surface temperature (SST) dependent term. It has been found that the SST effects on the radar backscatter are wind speed dependent and more pronounced in vertical polarization (VV) than in horizontal polarisation (HH) at higher incidence angles, and are mainly relevant at radar wavelengths smaller than C-band. The new Ku-band GMF, NSCAT-5, is developed based on a physical model and RapidScat radar backscatter measurements, which are only available at two incidence angles, i.e., 48.8⁰ and 55.2⁰, for HH and VV beams, respectively. The objective of this paper is to verify the NSCAT-5 GMF at similar incidence angles, using data from the scatterometer onboard Indian SCATSat-1 satellite, which operates at 49.1⁰ (HH) and 57.9⁰ (VV) incidence angles. First, the SCATSat-1 backscatter sensitivity to sea surface wind and SST is assessed using the C-band Advance Scatterometer (ASCAT) winds as reference. Second, the approach used to derive the NSCAT-5 GMF for RapidScat is adapted to derive a SST-dependent GMF for SCATSat-1. The new GMF will be used to consolidate the current NSCAT-5 model, and then evaluated for SCATSat-1 wind retrieval.

The functionality available on modern ‘smartphone’ mobile devices, along with mobile application software and access to the mobile web, have opened up a wide range of ways for volunteers to participate in environmental and biodiversity research by contributing wildlife and environmental observations, geospatial information, and other context-specific and time-bound data. This has brought about an increasing number of mobile phone based citizen science projects that are designed to access these device features (such as the camera, the microphone, and GPS location data), as well as to reach different user groups, over different project durations, and with different aims and goals. In this chapter we outline a number of key considerations when designing and developing mobile applications for citizen science, with regard to (1) interoperability and data standards, (2) participant centred design and agile development, (3) user interface & user experience design, and (4) motivational factors for participation.

After more than eight years of Soil Moisture and Ocean Salinity (SMOS) aquisitions, an empirical characterization of the biases and the computation of an effective brightness temperature uncertainty is possible. In this work we show that both parameters strongly depend on the geographical location of the acquisition. Metrics based on the differences between expected and theoretical values of the bias and uncertainty are developed and used for a quantitative assessment of the locations where SMOS errors are currently being worse characterized. This characterization can be used for the definition of an empirical bias correction and a more accurate cost function which are expected to provide a better SMOS SSS product.

Desde el invierno de 2013, no se han observado episodios relevantes de formación de aguas profundas en el Mediterráneo Occidental. Ello podría estar relacionado con la suavidad de estos últimos inviernos. No obstante, en 2018 sí ha habido episodios fríos importantes para producir aguas densas, pero no suficientes como para lograr cantidades significativas de nueva agua profunda. En la presente comunicación se plantea la posibilidad de que desde el agotamiento del agua profunda anterior al 2005 en toda la cuenca, en 2015 como más tarde, la formación de nueva agua profunda requiera unas pérdidas de calor latente superiores a las necesarias anteriormente. Este requerimiento, junto a la tendencia global al calentamiento podría causar un debilitamiento de la circulación termohalina mediterránea, con diversas consecuencias a escala regional y global. Entre ellas, una disminución de los intercambios de agua con el Océano y de los niveles de oxígeno en aguas profundas.

Typhoon is one of the most powerful and destructive natural disasters. Accurate forecasting of Typhoon track and intensity is very important to disaster prevention and reduction. Satellite observations can effectively compensate for the shortcomings of traditional methods of sea surface measurement and provide all-weather observation over the sea surface, which is of great significance to improve the numerical prediction of strong convective weather over ocean. The spaceborne radar observes the backscattering caused by the sea surface roughness, and then, the sea surface wind can be retrieved. The Synthetic Aperture Radar (SAR) is an important data source for sea surface monitoring. A variety of meteorological hydrological elements can be retrieved by SAR observation, and it has been used in data assimilation in recent years [1]. SAR imagery is also used to monitor strength and structure of typhoons [2]. The accuracy of sea surface winds retrieved from SAR has been found to be comparable to that of scatterometer data [3], and these wind fields can be used with a data assimilation system to provide the initial conditions for the numerical weather prediction (NWP) model [4]. In this study, a data assimilation scheme is proposed to assimilate the Sentinel-1 SAR retrieved winds in the Weather Research and Forecasting (WRF) model. Numerical simulation experiments of the typhoon Lionrock (2016) and hurricane Hermine (2016) are conducted to test and compare different data assimilation methods.

User friendly tools strongly influence the use of scientific measurements from marine observatory platforms. Nowadays, because of the huge amount of marine data, available in many different formats, automate methodologies are required to effectively reduce the human effort. This work presents oceanobs, an open-source Python package that provides a wide range of tools to analyze data from marine observatories, including procedures for feature extraction, quality control generation, filtering methods and content visualization. Here we present the philosophy of implementation of the package and we focus on the data Quality Control production.

It has recently been found that the visibility denormalization process introduces a spatial error distribution due to small sporadic offset jumps in the PMS detectors. The radiometric impact of this error at system level is very low. However, due to the good performance of the SMOS instrument, a study has recently been conducted to evaluate the amplitude of such visibility errors and develop a mitigation technique. The main results of this study are summarized in this presentation.

The main circulation patterns in the western Mediterranean are revisited and updated. The schemes are based on the previous literature, adapted and reviewed. The update concerns in particular the circulation at intermediate depths, exemplified by the Levantine Intermediate Water circulation, and includes deep water cascading and recent observations from drifting floats and mooring recordings.

The viability of any Citizen Science (CS) research program is absolutely conditioned to the engagement of the citizen. In a CS framework in which participants are expected to perform actions that can be later on validated, the incorporation of a reputation system can be a successful strategy to increase the overall data quality and the likelihood of engagement, and also to evaluate how close citizens fulfill the goals of the CS research program. Under the assumption that participant actions are validated using a simple discrete rating system, current reputation models, thoroughly applied in e-platform services, can be easily adapted to be used in CS frameworks. However, current reputation models implicitly assume that rated items and scored agents are the same entity, and this does not necessarily hold in a CS framework, where one may want to rate actions but score the participants generating it. We present a simple approach based on a Bayesian network representing the flow described above (user, action, validation), where participants are aggregated in a discrete set of user classes and we use the global evidence in the data base to estimate both the prior and the posterior distribution of the user classes. Afterwards, we evaluate the expertise of each participant by computing the user-class likelihood of the sequence of actions/validations observed for that user. As a proof of concept we implement our model in a real CS case, namely the Mosquito Alert project.

Air-sea fluxes are greatly enhanced by the winds and wind structures generated by Mesoscale Convective Systems (MCSs). In contrast to global numerical weather prediction models, space-borne scatterometers are able to resolve the small-scale wind variability in and near MCSs. Heavy rain events (rain bursts) occurring in MCSs produce strong gusts and large divergence and curl in surface winds. In this report wind fields from the ASCAT-A and ASCAT-B tandem mission, collocated with Meteosat Second Generation rain fields, were used to develop a methodology capable of identifying and quantifying correlations between wind and rain. Categories of wind divergence, wind stress divergence, and rainfall intensity were defined and a spatial neighbourhood spanning a 25km-by-25km block of WVCs was searched to identify coincidences of extreme rain and extreme convergence/divergence. This showed that when there is extreme rain, there is extreme convergence/ divergence in the vicinity. The coincidences were tabulated in 3-by-3 and 2-by-2 contingency tables from which cross-correlations were calculated for each time step in the collocation. The resulting response curves for extreme convergence and extreme divergence each had a well-defined peak. The time lag for the convergence peak was 30 minutes, implying that extreme rain generally appears after (lags) extreme convergence. The overall conclusion then is that the temporal scale of moist convection is determined by the slower updraft process. Results for wind divergence and wind stress were qualitatively similar, wind stress divergence showing the stronger response. This is probably due to its focus on high winds. The report also notes that extreme convergence/divergence are concentrated in spatial patches and recommends for further study to relate the spatial features with the statistics, and as a focus for studying the changes in the divergence fields between the ASCAT-A and ASCAT-B passes.

Recent developments on the wind geophysical model function (GMF) of Ku-band scatterometers include a sea surface temperature (SST) dependent term. It has been found that the SST effects on the radar backscatter are wind speed dependent and more pronounced in vertical polarization (VV) than in horizontal polarisation (HH) at higher incidence angles, and are mainly relevant at radar wavelengths smaller than C-band. The new Ku-band GMF, NSCAT-5, is based on a physical model and RapidScat radar backscatter measurements, which are only available at two incidence angles, i.e., 48.8⁰ and 55.2⁰, for HH and VV beams, respectively. The aim of this study is to perform a preliminary verification of the NSCAT-5 GMF at similar incidence angles, using data from the recently-launched Indian SCATSat-1, which operates at 49.1⁰ (HH) and 57.9⁰ (VV) incidence angle. A more comprehensive validation will be carried out later in 2017, as part of a follow-on CDOP-3 VSA activity, including a more recent calibration version (1.2.3) and so-called stressequivalent winds.

The assimilation of Advanced Scatterometer (ASCAT) winds has proven to be beneficial for the European Center for Medium Range Weather Forecasting (ECMWF) system, particularly over the Tropics. In this study, several important aspects of the ASCAT data are addressed in order to further test and improve the impat of scatterometer wind data assimilation into ECMWF Integrated Forecasting System (IFS). First, and improved wind quality control (QC) is proposed and used to remove unrepresentative ASCAT winds. Second, a new ASCAT wind product, more representative of the ECMWF model resolved scales, is produced by averaging the relatively-high resolution ASCAT wind vector cells to lowe resolution in an aggregation process. Two months of ASCAT low resolution data are then used to evaluate the impact of the refined QC and the aggregation technique on the IFS data assimilation.

A new debiased non-Bayesian methodology has demonstrated to be very effective for the retrieval of Sea Surface Salinity (SSS) from brightness temperature (TB) measured by Soil Moisture and Ocean Salinity (SMOS) interferometric radiometer. Applying this methodology it is possible to retrieve SSS values in marginal seas or cold waters where the operational retrieval does not. Another important improvement is the possibility of defining a SMOS-based climatology to characterize spatial biases. Recently, using data from the Soil Moisture Active Passive (SMAP) mission, JPL has started to produce a new 9-km resolution TB product. The existence of such product offers the possibility of increasing the spatial resolution and quality of the mentioned SMOS SSS product using fusion techniques. The aim of this work is to produce high resolution SSS maps in marginal seas derived from the fusion of SMAP 9- km TB and SMOS non-Bayesian debiased SSS products.

ESA’s Soil Moisture and Ocean Salinity (SMOS) mission has been in orbit for over 7 years, with its Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) functioning well. This 7 year period has provided a wealth of information which has enabled us to understand and consolidate the performance of the payload in great detail. More importantly, we know now the things that work well, those that need improvement, and how the instrument could be enhanced if we were to build it again. This paper presents the lessons learnt from SMOS after 7 years in orbit.

The impact of Radio Frequency Interference (RFI) is a very serious problem for spaceborne microwave radiometry. Many Soil Moisture Ocean Salinity (SMOS) images show serious contamination by the RFI. SMOS is even more impacted by the RFI than real aperture case because the grating lobes are usually higher in Synthetic Aperture Interferometric Radiometer (SAIR) compared to real aperture one. RFI effects should properly be mitigated or filtered out to retrieve the geophysical parameters from SMOS measurements. This work presents a feasibility study of RFI mitigation/filtering for SAIRs. Instead of dealing with brightness temperature image directly, RFI filtering of the subspace of covariance matrix is introduced.

TheCapeVerde(CV)Basinisthesiteoffrontsandcurrentsthatfunction as both barriers and connectors between the tropical and subtropical oceans. Here we review former studies and analyze historical, satellite and numerical data in order to portray the oceanography of the CV Basin, with emphasis on its eastern boundary— the Mauritania Slope (MS) Ocean. This is complemented with the analysis of novel hydrographic data from the continental slope. The CV Basin is a dynamic region, forced by seasonally varying winds that drive both coastal and offshore upwelling, the latter linked to the Guinea Dome. Its circulation is controlled by the seasonally changing Dome to the south and southwest, with associated cyclonic currents, and by the CV frontal system to the north, with along-slope flow convergence and offshore export. The MS Ocean is the site of the Poleward Undercurrent, undistin- guishable from the offshore Mauritania Current during winter–spring. The pre- dominant thermocline water–mass is the nutrient-rich South Atlantic Central Water, almost pure in upper layers (100–300 m)—providing for the high primary produc- tion in the entire region—and with substantial North–Atlantic contribution in its lower part (300–550 m)—in what constitutes the poorly–ventilated low oxygen minimum zone; nutrient concentrations keep increasing with depth until the core of the Antarctic Intermediate Waters (700–800 m). The CV Basin holds both the highest primary production and lowest oxygen concentrations for the entire tropical

Human activities in continental margins have progressively increased during the last decades, threatening vulnerable marine ecosystems in many conti- nental slopes, such as cold-water coral reefs, seamounts and canyons. In order to protect these ecosystems and ensure the sustainable management of resources, countries and organizations should endorse effective policy actions. However, nowadays about only 0.8% of the oceans and 6% of the territorial seas belong to conservation area systems, a lack of protection that is particularly acute in deep-sea waters. The Mauritanian continental margin is the outcome of exceptional marine features, with abrupt canyon systems, sediment slides and a giant carbonate-mounds barrier occurring together. Mauritanian waters have both tropical and subtropical origins, being affected by coastal and offshore upwelling that leads to elevated productivity and abundant fishery resources. Soft-bottom habitats hold high diversity of species, and hard-bottoms sustain assemblages of suspension- feeders and vulnerable species. Nevertheless, despite the recent increase of ex- tractive activities, the location and characterization of those Mauritanian deep-water areas of biological or ecological interest that require protection remain poorly known. The Maurit surveys have offered the opportunity to perform a first approach to the biodiversity and ecosystems in soft and hard bottoms of the Mauritanian outer shelf and slope. This last chapter provides an integrated overview of the demersal and benthic communities inhabiting Mauritanian deep waters and describes areas of particular ecological and/or biological interest that are vulnerable habitats and should be preserved according to international conventions.

It has recently been demonstrated that boresight averaged Faraday rotation angle (FRA) can be retrieved directly from SMOS full-pol radiometric data. However, in order to extend FRA retrievals to the full Alias-Free Field of View (AF-FoV), SMOS relatively poor pixel radiometric sensitivity and accuracy must be compensated by spatial and temporal averaging. This requires some kind of tradeoff to constrain systematic FRA estimation bias both within SMOS AF-FoV and along the orbit. This work presents the first results given by a SMOS end-to-end FRA simulator, currently under development, that is used to trim and assess the performance of several FRA retrieval approaches.

Local systematic differences between scatterometer and global numerical weather prediction (NWP) model stress equivalent winds (SEW) are due to unresolved geophysical processes by the model, e.g., ocean currents and moist convection. A scatterometer-based correction,which contains the mesoscale information present in the Advanced Scatterometer (ASCAT) observations, sets the grounds for a high-resolution ocean forcing product. To assess the effectiveness of such correction, a Monte Carlo simulation procedure is applied to NWP SEW. It allows for a thorough evaluation of the NWP error reduction, which depends on the scatterometer sampling. The local NWP biases are reduced at the cost of a somewhat increased variance, and the total error mitigation is constrained to regions covered by the scatterometer at least 3 times over 5 days. Despite the limited sampling in the tropics, the real NWP corrected SEW over the West African coast show areas of increased wind variability associated to moist convection.

The dependency of the azimuth wavelength cut-off on the wind speed has been studied through a dataset of Sentinel-1 multi look SAR images co-located with wind speed measurements, significant wave height and mean wave direction from ECMWF operational output. A Geophysical Model Function (GMF) has been fitted and a retrieval exercise has been done comparing the results to a set of independent wind speed scatterometer measurements of the Chinese mission HY-2A. The preliminary results show that the dependency of the azimuth cut-off on the wind speed is linear only for fully developed sea states and that the agreement between the retrieved values and the measurements is good especially for high wind speed. A similar approach has been used to assess the dependency of the azimuth cut-off also for X-band COSMO-SkyMed data. The dataset is still incomplete but the preliminary results show a similar trend.

The empirical dependence of the azimuth wavelength cut-off on the significant wave height and on the wind speed have been studied. The azimuth cut-off is estimated on the fitting of a Gaussian function to the azimuth autocorrelation function of the radar cross section. The feasibility of estimating the significant wave height and/or the wind speed has been investigated as well. We use SAR images acquired by the European Sentinel 1 from the beginning of November 2014 to the end of April 2015 co-located with the scatterometer winds acquired by the Chinese sensor HSCAT and the significant wave height from ECMWF forecasts. The correlation between the azimuth cut-off and the significant wave height is rather strong. A linear geophysical model function is fitted in order to estimate it. The dependence on the wind speed is secondary and becomes remarkable only when the sea state is fully developed. A significant wave height retrieval exercise is proposed and the results are compared with the buoy measurements of the National Data Buoy Center (NDBC) network

In this chapter, different kinds of oil spill beaching maps are proposed for the Mediterranean. These beaching maps can be useful as a complementary tool to vulnerability analysis and risk assessment in the Mediterranean. Firstly, it is defined an oil beaching map for a single point, which is the situation, for example, in the analysis of an oil platform. Next, the oil beaching map is defined for a line, analysing the main route of oil tankers in the Mediterranean. The final oil beaching maps defined show the percentage of particles which reach the coast in an interval of time: one week, two weeks, one month and two months. The information depicted in the maps is based on Lagrangian simulations using particles as a proxy of oil spills evolving according the environmental conditions provided by a hindcast model of the Mediterranean circulation.

In contrast with scatterometer wind data, Numerical Weather Prediction (NWP) models do not well resolve the mesoscale sea surface wind flow under increased wind variability conditions, such as in the vicinity of low-pressure centers, frontal lines, and moist convection. In this paper, several important issues are addressed in order to improve the impact of scatterometer data assimilation into global and regional NWP models, including model error structure functions, situation-dependent Observation/ Background error estimation, and improved scatterometer wind quality control.

This paper reviews several wind quality-sensitive parameters derived from HY-2A scatterometer data, such as the windinversion residual (or Maximum Likelihood Estimator, MLE) and its spatially averaged value, and the singularity exponent (SE) derived from an image processing technique, called singularity analysis. Their sensitivity to data quality is evaluated using the collocated European Centre for Medium-range Weather Forecasting (ECMWF) model output and satellite radiometer rain data. It shows that SE is the best quality indicator, followed by the spatially averaged MLE and the conventional MLE. A set of MLE and SE thresholds are derived from the sensitivity analysis in order to optimize the quality control (QC) for the HY-2A scatterometer.

New ocean products from the Soil Moisture and Ocean Salinity (SMOS) mission are being developed at the Barcelona Expert Centre. Besides the already operational 9- day and monthly sea surface salinity (SSS) products, two additional daily SSS products have been recently become operational: a simple user-friendly product containing all swath-based Level 2 data for each day, and a more elaborated product that uses multifractal fusion techniques to increase the spatial and temporal resolution. Finally, experimental BEC products are also presented which provide SSS values in regions strongly affected by radiofrequency interference (RFI). Recent progress on Land-Sea contamination mitigation has been applied to the BEC products.

El projecte LIFE MEDACC (\"Mediterranean Adaptation to Climate Change\") ha estudiat l’evolució recent dels cabals en capçalera del Segre, el Ter i la Muga, amb l’objectiu d’avaluar l’impacte dels forçaments climàtics i els canvis d’usos del sòl. En aquesta comunicació ens centrarem en la Muga, on els cabals s’han reduït a la capçalera i han augmentat a la plana litoral. Mentre a la capçalera hi ha hagut disminució de la precipitació i un procés d\'aforestació per abandonament de conreus, a la part baixa s’hauria incrementat la precipitació. Això planteja una possible influència de l’evaporació marina i vents litorals en la precipitació. Aquests dos factors ‐relacionats amb intercanvis aire‐mar‐ s’han obtingut a l’estació de l’Estartit (Empordà), prop de la conca del riu. Llur evolució podria explicar la reducció de precipitacions primaverals i estivals, i alhora un reforçament durant la tardor, prop de la costa.

This work is devoted to describe the new processing techniques that are being conceived, developed and implemented at the Barcelona Expert Centre (BEC) for the generation of sea surface salinity (SSS) maps from the Soil Mooisture and Ocean Salinity (SMOS) mission. Several algorithms to mitigate the ripples and sidelobes present in the SMOS brightness temperature (TB) images, to characterize the spatial correlations in the SMOS antennas, to correct for the systematic SSS-derived biases, and to improve the spatial and temporal resolution of the SSS products, have been recently developed and are presented in this paper.

The global water balance and the relative magnitudes of its global and regional components are of fundamental importance to society and are largely unmeasured over the ocean. The advent of satellite sea surface salinity (SSS) measurements by the Soil Moisture and Ocean Salinity (SMOS) mission launched in November 2009 and the Aquarius on the fourth Argentine Satélite de Aplicaciones Cientificas (SAC-D) satellite mission launched in June 2011, respectively, opened a new era in ocean sciences. This paper outlines the new measurement systems, including a preliminary assessment on the technological challenges, and provides an overview of results, including the salt budget in the North Atlantic, tropical instability waves, Rossby waves, mesoscale motions, freshening of surface coastal waters from riverine outflow and impact on hurricane forecasting in northwest Atlantic, and SSS response to La Niña. As the SSS time series lengthen with continued mission operations, SSS data will receive additional attention in numerous studies, including the El Niño/La Niña phenomenon, Gulf Stream meanders, and global salt budget of the water balance.

Subcell wind variability can be directly characterized using several ASCAT-derived parameters. Triple collocation analysis is useful in the subcell variability study. At 25 km resolution, ASCAT provides the best quality winds in general. The assessment and validation of the quality of satellite scatterometer vector winds is challenging under increased subcell wind variability conditions, since reference wind sources such as buoy winds or model output represent very different spatial scales from those resolved by scatterometers (i.e., increased representativeness error). In this paper, moored buoy wind time series are used to assess the correlation between subcell wind variability and several Advanced Scatterometer (ASCAT)-derived parameters, such as the wind-inversion residual, the backscatter measurement variability factor, and the singularity exponents derived from an image processing technique, called singularity analysis. It is proven that all three ASCAT parameters are sensitive to the subcell wind variability and complementary in flagging the most variable winds, which is useful for further application. A triple collocation (TC) analysis of ASCAT, buoy, and the European Centre for Medium-range Weather Forecasting (ECMWF) model output is then performed to assess the quality of each wind data source under different variability conditions. A novel approach is used to compute the representativeness errors, a key ingredient for the TC analysis. The experimental results show that the estimated errors of each wind source increase as the subcell wind variability increases. When temporally averaged buoy winds are used instead of 10 min buoy winds, the TC analysis results in smaller buoy wind errors (notably at increased wind variability conditions) while ASCAT and ECMWF errors do not significantly change, further validating the proposed TC approach. It is concluded that at 25 km resolution,ASCAT provides the best quality winds in general.

In this tecnical note we analyze two different approaches for salinity retrieval in SMOS: the standard Bayesian approach and a new not-Bayesian approach. In both cases systematic, a bias correction based on SMOS-based climatologies is applied. The performance of both approaches are analysed and discussed.

The Cape Verde Front (CVF) separates the North Atlantic subtropical gyre (NASG) from the north‐eastern North Atlantic tropical gyre (NATG). Within the NASG, the Canary Current (CC) and the Canary Upwelling Current (CUC) comprise a relatively shallow (down to about 200‐300 m) flow of North Atlantic Central Waters (NACW): the CC is found far offshore as a wide and poorly defined current while the CUC is a near‐slope intense baroclinic jet linked to the coastal upwelling front. Within the top 300 m of the NATG, the along‐slope Mauritania Current and the Cape Verde Current (CVC, a north‐eastern extension of the North Equatorial Counter Current that broadly rotates around the Guinea Dome) carry South Atlantic Central Waters northwards. As a result, the frontal system is the site of intense along‐slope flow convergence and offshore transport in the top 300 m of the water column. Further deep, down to some 500 m, the interior flow is very weak in both gyres, likely dominated by mesoscale features, except along the continental slope, where the northward Poleward Undercurrent (PUC) feeds through localized inputs from the interior ocean; in particular, within the NATG the CVC appears as responsible for southward transfer of NACW, across the CVF, which eventually reaches the PUC.

North of Cape Blanc, the north‐easterly winds cause offshore flow of surface waters that are replaced by subsurface inflow of relatively cold and nutrient‐rich waters, driving the vertical cell of coastal upwelling. This vertical circulation, together with surface heating and horizontal mixing, causes the coastal upwelling front (typically about 200 m deep) that separates cold onshore from warm offshore waters. A southward baroclinic coastal jet is associated to this front, which causes vertical shear and mixing that contribute to the intensity of the vertical cell. Very importantly, this jet feeds from upstream waters, resulting in an along‐slope coherent flow, or the horizontal cell of coastal upwelling - this is the Canary Upwelling Current (CUC) that connects all surface coastal African waters north of Cape Blanc. Further south, because of the northward offshore flow and the seasonality of the winds, the connection remains only during winter and spring, very close to shelf break and in the top 100 m. North of Cape Blanc, a Poleward Undercurrent (PUC) flows in the relatively homogenous upwelled waters that found over the continental slope. South of Cape Blanc the PUC appears as a nearshore expression of the Mauritania Current. Both the southward CUC and the northward PUC constitute the true skeleton of the Canary Current Large Marine Ecosystem.

Inorganic nutrients increase with depth as a result of the enhanced remineralization of organic matter with aging waters (the time since they were last near the sea surface), and the opposite happens with dissolved oxygen (except within the saturated surface mixed layer). In the Canary Current Large Marine Ecosystem there is also a marked latitudinal gradient, with the Cape Verde Front separating relatively nutrient‐poor and oxygen‐rich subtropical waters from the nutrient‐rich and oxygen‐poor tropical waters. Along a latitudinal band off North‐West Africa, coastal upwelling brings the subsurface waters towards the sea surface, locally raising the inorganic nutrient levels. This becomes an important lateral source to both gyre especially to the nutrient‐poor subtropical one, taking place through lateral mixing (mainly as a result of the instability of the coastal‐upwelling baroclinic jet) and localized coastal filaments (in those regions, typically capes, where the coastal flow converges and offshore advection takes place). In the southernmost portion of our domain, within tropical waters, there is also high (wind‐induced) offshore primary production. This, together with the slow ventilation of the subsurface waters, leads to much enhanced remineralization, producing a region with very low oxygen and high inorganic nutrient levels, the oxygen minimum zone of the North Atlantic Ocean.

In the last 10 years the number of jellyfish shoals that reach the swimming area of the Mediterranean Sea are increasing constantly. The term \"Jellyfish\" refers to animals from different taxonomic groups but the Scyphomedusae are within the most significant one. Four species of Scyphomedusae are the most conspicuous ones inhabiting the studied area, the Barcelona metropolitan area. Jellyfish are usually found at the surface waters, forming big swarms. This feature makes possible to detect them remotely, using a visual camera and image processing algorithms. In this paper we present the characteristics of a remote piloted aircraft capable to perform monitoring flights during the whole summer season. The requirements of the aircraft are to be easy to operate, to be able to flight at low altitude (100 m) following the buoy line (200 m from the beach line) and to be save for other users of the seaside. The remote piloted aircraft will carry a vision system and a processing board able to obtain useful information on real-time.

Understanding the spatio-temporal variability of phytoplankton in aquaculture areas is necessary for the appropriate management of natural resources and the prevention of toxic outbreaks. With this objective, we combined synoptic cruises, time series of physical parameters, and modeling, to study the ecosystem of Alfacs Bay, an important shellfish and fish production area commonly affected by toxic outbreaks.Synoptic cruises performed during relevant harmful species proliferations, such as a Karlodinium spp. outbreak in 2007, showed the existence of a preferential phytoplankton accumulation area in the inner NE side of the Bay. We explored the role of nutrient supply (which takes place mainly through the irrigation channels discharging into the northern coast) and the hydrodynamic regime in explaining the observed phytoplankton distribution patterns. Based on a 3D hydrodynamic model combined with a particle-tracking module, we suggest that the phytoplankton confinement in that area could be fostered by the estuarine circulation dynamics taking place in the bay.

Despite the fact that water covers two-thirds of the Earth’s surface, it is surprisingly vulnerable to human influence and activity. Marine ecosystems receive large amounts of a variety of pollutants from either treated or untreated wastewater. The extensive use of chemicals and their introduction into the environment has resulted in increased public concern for the potential threats to ecosystems, human health and safety. Persistent organic pollutants such as polychlorinated biphenyls, polycyclic aromatic hydrocarbons, polybrominated diphenyl ethers and pesticides, as well as heavy metals, surfactants; endocrine disrupting chemicals or personal care products and pharmaceuticals are pollutants usually present in marine environments. This book focuses on discussing the types of marine pollutants. It provides topics on the environmental significance and management strategies available. (Imprint: Nova)

Why a chapter on Perspectives and Integration in SOLAS Science in this book? SOLAS science by its nature deals with interactions that occur: across a wide spectrum of time and space scales, involve gases and particles, between the ocean and the atmosphere, across many disciplines including chemistry, biology, optics, physics, mathematics, computing, socio-economics and consequently interactions between many different scientists and across scientific generations. This chapter provides a guide through the remarkable diversity of cross-cutting approaches and tools in the gigantic puzzle of the SOLAS realm. Here we overview the existing prime components of atmospheric and oceanic observing systems, with the acquisition of ocean–atmosphere observables either from in situ or from satellites, the rich hierarchy of models to test our knowledge of Earth System functioning, and the tremendous efforts accomplished over the last decade within the COST Action 735 and SOLAS Integration project frameworks to understand, as best we can, the current physical and biogeochemical state of the atmosphere and ocean commons. A few SOLAS integrative studie illustrate the full meaning of interactions, paving the way for even tighter connections between thematic fields. Ultimately, SOLAS research will also develop with an enhanced consideration of societal demand while preserving fundamental research coherency. The exchange of energy, gases and particles across the air-sea interface is controlled by a variety of biological, chemical and physical processes that operate across broad spatial and temporal scales. These processes influence the composition, biogeochemical and chemical properties of both the oceanic and atmospheric boundary layers and ultimately shape the Earth system response to climate and environmental change, as detailed in the previous four chapters. In this crosscutting chapter we present some of the SOLAS achievements over the last decade in terms of integration, upscaling observational information from processoriented studies and expeditionary research with key tools such as remote sensing and modelling. Here we do not pretend to encompass the entire legacy of SOLAS efforts but rather offer a selective view of some of the major integrative SOLAS studies that combined available pieces of the immense jigsaw puzzle. These include, for instance, COST efforts to build up global climatologies of SOLAS relevant parameters such as dimethyl sulphide, interconnection between volcanic ash and ecosystem response in the eastern subarctic North Pacific, optimal strategy to derive basin-scale CO2 uptake with good precision, or significant reduction of the uncertainties in sea-salt aerosol source functions. Predicting the future trajectory of Earth’s climate and habitability is the main task ahead. Some possible routes for the SOLAS scientific community to reach this overarching goal conclude the chapter

The consistency of MIRAS amplitude calibration along the mission is a key issue to ensure a stable and accurate longterm dataset of ESA’s SMOS soil moisture and ocean salinity data. Recent studies have revealed latitudinal and seasonal drifts in some receivers of the instrument. This paper focuses on the assessment of MIRAS amplitude calibration consistency using the available long-term dataset. A methodology is presented to evaluate residual amplitude calibration errors and to investigate the origin of these deviations.

The results of a simulated CO2 (C) and a global ice volume (V ) time series, derived from a simple relaxation model of the glacialinterglacial cycles[1], have been analyzed using non-linear techniques. On a first approximation, we have compared simulated time series with the corresponding observational time series, obtaining correlations of 0.88 between the proxy-record !18O([2]) and simulated V , and 0.79 between the reconstructed atmospheric CO2 concentration([2–7]) and simulated C, used to quantify the maximum observational variance that this simple model is able to explain. Fourier transform, wavelet transform, cross-wavelet transform, wavelet coherence and cross-recurrence analysis are useful tools to quantify the performance of a model at reproducing the dynamics embedded in observational time series. The analysis shows that the model reproduces closely the dynamics embedded in the ice volume time series, but for the CO2 case the coherence between simulated and observational CO2 is only sporadic, indicating that both time series do not follow the same dynamical behavior, although, in the deglacial periods the two carbon series become dynamically close. The analysis reinforces the hypothesis that some specific mechanisms included in the model are able to closely reproduce the glacial-interglacial oscillations and thus suggests which specific mechanisms should be more seriously investigated in the climate system. These techniques may be applied to other climatic time series to quantify the performance of a model simulating the dynamics of the climate system

The current ASCAT Wind Data Processor (AWDP) uses the 2D variational ambiguity removal (2DVAR) scheme to select a unique wind field from a set of retrieved ambiguities. This has led to spatially consistent and accurate ASCAT Level 2 wind products. Nevertheless, recent research shows that 2DVAR picks up the wrong wind direction ambiguities in regions where the background field shows mislocation of fronts (convergence) or misses convective systems. In this paper, the exploitation of complementary information derived from the inversion and from an image processing technique is proposed to improve the current 2DVAR for ASCAT in mesoscale conditions.

Surface Soil Moisture (SSM) affects the soil surface energy balance and thus affects the Land Surface Temperature (LST), and viceversa. Currently, LST and SSMare remotely sensed using TIR sensors and L-band radiometers, respectively. The NASA’s Terra/Aqua missions provide full coverage of LST measurements under clear sky conditions using MODIS. The ESA’s SMOS mission is the first satellite providing frequent SSM and ocean salinity observations at global scale. In this paper, a sensitivity study about the relationship of the LST and SSM is performed using in-situ measurements from the REMEDHUS network and spaceborne observations from MODIS and SMOS. Results show that the correlation between SSM and LST (both in-situ and remotely sensed) is highest using the daily maximum LST. This could help improving SSM algorithms and deriving new SSM products at higher resolution from the synergy of microwave and TIR observations.

The Advanced Scatterometer (ASCAT) onboard the Me top satellite series is designed to measure the ocean surface wind vectors globally. Generally, ASCAT provides wind products at excellent quality. The quality of the Advanced Scatterometer (ASCAT) derived winds is known to be generally degraded with increasing values of the inversion residual or maximum likelihood estimator (MLE). In the current ASCAT Wind Data Processor (AWDP), an MLE-based Quality control (QC) is adopted to filter poor-quality winds, which has proven to be effective in screening artifacts in the ASCAT winds, associated with increased sub-cell wind variability, notably under rain conditions. However, some poorly verifying winds, which appear in areas with convection, are not screened by the operational QC.

Particle modeling is usually exploited, along with measured data, to infer the water content. However, the particle properties must be accurately known. In this paper, a methodology to estimate the hyperspectral complex-refractive-index signatures of marine particles is presented. It is is based on the Mie-Lorentz and T-matrix characterizations to obtain the particle inherent optical properties and uses a genetic algorithm for search optimization. This methodology is tested by accurately estimating the hyperspectral complex refractive indexes on two different examples, including monodisperse and polydisperse particle size distributions of spherical and nonspherical particles.

An ocean calibration method for scatterometer wind data is developed at KNMI. The method is based on a direct comparison of measured backscatter data with simulated backscatter data from Numerical Weather Prediction (NWP) winds. This NWP Ocean Calibration tool (NOC) is used to improve the scatterometer wind products and can be used to eliminate systematic interbeam biases and across-swath dependencies (when present) in the wind product. Monte Carlo simulations are useful to assess the accuracy of the NOC method and to determine the sensitivity with respect to binning and sampling errors. As such, simulation runs with realistic “true” wind distribution and realistic measurement and NWP wind-component error values are performed. A reprocessing of QuikSCAT data over its whole lifespan (1999-2009) is being performed by KNMI. The averaged NOC residuals over a longer period are used to calculate correction factors and used to improve the wind retrieval.

Hyperspectral optical observations and the development of new processing strategies are key for a better understanding of complex marine ecosystems and space-time distribution of ecological parameters. In this paper, the methodologies to implement a simulator of hyperspectral-resolved optical data corresponding to highly dynamic marine environments are presented. The simulator is based on a coupled radiative transfer and Lagrangian hydrodynamic model, which is organized in four basic blocks: a hydrodynamic model, a particle tracking model, a transformation function and a radiative transfer model. The transformation function is needed to adapt the output of the tracking model (given in number of particles per unit volume) to mass concentration, suitable for the radiative transfer model. The transformation function has been derived considering an allometric relationship between both magnitudes, since it is found in nature. The simulator is finally tested by considering the Alfacs Bay (NW Mediterranean Sea), as a case study site.