The Station for Climate Observations on the island of Lampedusa (http://www.lampedusa.enea.it), in the central Mediterranean sea, is composed of an Atmospheric Observatory and a recently developed Oceanographic observatory. The Atmospheric Observatory, AO, was set up in 1997 at Capo Grecale, the North-Eastern promontory of Lampedusa (35.52°N, 12.63°E), while the Oceanographic Observatory, OO, has been installed on a buoy deployed in August 2015 at about 15 km South-West of AO (35.49°N, 12.47°E), where the seabed is of 74 m.
In the framework of the activities to strengthen the Oceanic Observatory a program aiming at the continuous measurements of the sea surface skin temperature (SST) has been recently started. The program takes advantage of the location of the Atmospheric Observatory, that is placed in proximity of a 50 m cliff over the sea; from this position radiometers may be pointed towards the sea and may be dedicated to the observation of ocean optical properties. The geographical characteristics of Lampedusa (an open sea small island located more than 100 km from the nearest Tunisian coast) and of the Atmospheric Observatory make it possible to carry out continuous and accurate measurements of the open sea SST.
Preliminary measurements are carried out with a model KT 19.85 Heitronics Infrared Radiation Pyrometer, IRP, measuring the integrated radiance in the 9.6 – 11.5 μm spectral range. The IRP is hosted in a ventilated box installed on the roof of the observatory. Regular cleaning of the entrance window and checks on the instrument operation are carried out to avoid possible biases. In this preliminary configuration the IRP observation angle is 74°. At this stage, the correction for the sea surface reflection is made using concurrent measurements of downwelling longwave irradiance in different bands, routinely made at AO.
The IRP observations complement additional SST measurements made at different depths (1, 2, 18 m) at the Oceanographic Observatory using SeBird SBE39 and SBE37 sensors. The SST derivation and the first set of observations are presented, also in relation to the measurements at OO and the large set of atmospheric parameters collected at AO. A first comparison with SST derived from MODIS is also discussed.
The present measurements of SST at Lampedusa will be used for validation of satellite observations, for the investigation of the relationship among SST, atmospheric structure and composition (i.e., aerosol, clouds, water vapour and atmospheric thermal structure) and the surface heat budget, and to study the sea temperature profile diurnal behaviour.

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Sea surface temperature (SST) is an essential climate variable that is extensively used for numerical weather prediction (NWP), monitoring the climate system and its changes and understanding of air-sea interactions. It has been retrieved from thermal infrared (IR) satellite instruments for over 30 years. IR retrievals are, however, affected by clouds and aerosols and this makes it difficult to perform retrievals in area with persistent cloud cover. The advantage of passive microwave (PMW) retrievals is that the effects of clouds and aerosols are negligible.

A global SST climate data record (CDR) for the period 2002-2016 has been generated within the SST project of the European Space Agency Climate Change Initiative (ESA-CCI) using passive microwave data from AQUA’s Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) and GCOM-W1’s Advanced Microwave Scanning Radiometer - 2 (AMSR2). Two retrieval algorithms have been developed; one for wind speed (WS) and one for SST. A two-step multi-regression model is used to retrieve WS from satellite brightness temperatures and NWP fields. The SST retrieval algorithm is a two-step multi-linear regression model, which uses localized algorithms to retrieve SST from brightness temperatures, retrieved wind speed and NWP fields.

The PMW SSTs have been validated against drifting buoy measurements. The best-quality AMSR-E PMW retrievals give SSTs with a bias of -0.02 K with a standard deviation of 0.46 K. The AMSR2 results show an average difference of 0.002 with a standard deviation of 0.45 K for the best-quality retrievals. The SST uncertainty has been estimated using a global regression model and shows good agreement with observed uncertainties. The temporal stability of the climate data record has been assessed and shows that the performance of the AMSR-E and AMSR2 datasets is similar and that there are no large inconsistencies. Furthermore, the advantages of a PMW climate data record over an IR climate data record have been investigated. The results are promising and show that passive microwave observations provide a viable alternative to infrared satellite observations for retrieving SST.

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Sea Surface Temperature (SST) is an identified essential variable by the Global Climate Observing system (GCOS). Satellite observations have promoted the important role of SST in climate related studies, atmospheric and oceanic modelling, bio-chemical processes and oceanic CO2 studies. The diurnal variability of SST, driven by the coincident occurrence of moderately low winds and solar heating, is currently not properly understood and resolved in models and products from the Copernicus Marine Environment Monitoring Service (CMEMS) of high spatial resolution. This results in erroneous estimation of air-sea interactions and heat budget, which causes demised model accuracy. In addition, diurnal SST variability complicates merging of SST from different satellite sensors thus having a direct impact on efforts to create climate records. Finally, a misrepresentation of the diurnal variability of the upper ocean temperature may result in large errors when modelling harmful algal blooms.

The “Improved Diurnal Variability Forecast Of Ocean Surface Temperature through Community Model development (DIVOST-COM)” project aims at developing and integrating a diurnal variability model with the Baltic Modelling & Forecasting Centre (MFC) 3D physical-biological model and the SST Technical Advisory Council (TAC) Level 4 analysis to improve existing products and services for the Baltic Sea. To achieve this, the existing 1-dimensional General Ocean Turbulence Model (GOTM) will be developed to a common modelling tool, which uses the MFC PHY-BIO forecast and SST Thematic Assembly Centre (TAC) products as input to resolve and forecast the vertical temperature structure of the upper ocean with very high resolution. The optimal way of using CMEMS forecasts as boundary conditions and the impact of interactive physical-bio-optical interaction on the ocean surface temperature will be evaluated.

The project focuses on the Baltic Sea as a test area but the recommendations provided will be applicable for all Modelling and Forecasting Centres (MFCs) and Thematic Assembly Centres (TACs). Modelled temperatures are to be compared to the existing CMEMS HIROMB-BOOS Model (HBM) Baltic (BAL) Monitoring & Forecasting Centre (MFC) outputs. Furthermore, SEVIRI, Sentinel-3 and Baltic L4 SST products will be used to evaluate the ability of the ocean model to reproduce the fine resolution upper ocean thermal structure and its diurnal variability, when identifiable. A better upper ocean thermal structure will impact coupling activities with atmospheric models, improve the CMEMS L4 SST products, aid interpretation of SST trends and offer improvements in biological and CO2 modelling activities. This study presents preliminary results from the DIVOST-COM project related to the first activities, including the initial impact assessment of the 1D GOTM model to the HBM model and comparisons with Copernicus observed SST fields.

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The interactions between atmosphere and ocean largely affect regional and global climate, as well as weather evolution at both local and global scales. These interaction processes are essentially governed by heat, momentum, freshwater and gasses exchange at the air-sea interface. Heat fluxes include the radiative components. The radiation budget is the sum of downward shortwave and longwave radiation, minus shortwave and longwave radiation emitted by the ocean. The main goal of this research is to assess satellite estimates of the ocean surface radiation budget and evaluate the contribution of atmospheric aerosols in radiation modulation. Atmospheric aerosols modulate downward infrared and shortwave radiation and affect satellite estimates. In addition, they influence Sea Surface Temperature (SST) estimates and, consequently, determine longwave radiation emitted by the sea surface.
Estimates of air-sea radiative fluxes either derived from satellites or applying bulk formulae to meteorological parameters have been compared with direct measurements made at the ENEA Station for Climate Observations on the island of Lampedusa, in the central Mediterranean Sea. Lampedusa is an integrated atmospheric/oceanic observatory composed by two sections: a ground-based laboratory operating since 1997, dedicated to the investigation of changes in atmospheric composition and structure and their effects on the surface radiation, and an oceanic buoy operating since 2015, dedicated to the investigation of air-sea interactions and to ground-truth of satellite observations. The instruments installed on the buoy also include a Vaisala MAWS401 meteorological station, Kipp and Zonen CMP21 and CGR4 radiometers for shortwave and longwave irradiances. Among other measurements, water temperature is measured at 1 and 2 meters depth using two SeaBird SBE 39 sensors operating at a frequency of 1 minute and at 18 m depth using a SBE 37 temperature and salinity sensor (foundation temperature).
The data collected at Lampedusa constitute a unique dataset to continuatively evaluate the accuracy of turbulent and radiative heat fluxes derived from satellites, models and bulk formulae and to develop of new fluxes’ parameterizations.
Our analysis reveals that the satellite estimates of the downwelling radiation components show an overestimation of the surface solar and longwave irradiances. The SEVIRI MSG3 (Meteosat Third Generation) observations overestimate the short wave irradiance by 6 W/m2 with a standard deviation of 68 W/m2 and the downward atmospheric longwave irradiance by 11 W/m2 with a standard deviation of 20 W/m2.
Similarly, based on ECMWF Interim meteorological data only, the shortwave incoming radiation computed using Reed bulk formula (1977) exceeds direct measurements by 9 W/m2, with a standard deviation of 91 W/m2, while downward atmospheric longwave irradiance (estimated using the Bignami at al. ,1995) underestimate direct measurements by 11.5 W/m2, with a standard deviation of 22.5 W/m2. Longwave irradiance still based on Bignami formula but using meteorological data measured at the buoy show an underestimation of 7 W/m2.and a RMS of 21 W/m2..
The impact of these determinations was also investigated in the framework of a 1D numerical model, General Ocean Turbulence Model (GOTM), for the evolution of the upper ocean vertical temperature. The model simulations have been compared with water temperatures recorded at 1 and 2 meters depth. The mean bias is 0.02 °C and -0.01 °C respectively, and the RMSE is 0.5 °C when the model was forced using Radiative fluxes directly measured at the mooring and turbulent fluxes estimated from in situ observations, When the model, instead, is forced by satellite based radiative fluxes the bias increased to 1.5 °C with a RMSE of about 1°C. These results confirm the importance of reducing uncertainties in satellite estimates of radiative fluxes including effects of atmospheric aerosols. Reduced uncertainties and increased space and time resolutions, thanks to a multi-satellite approach, will be essential to resolve the closure problem of the Mediterranean heat budget.

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ESA is building on almost 15 years of continuous Fiducial Reference Measurements (FRM) from UK-funded shipborne radiometers by establishing a service to provide historic and ongoing FRM measurements to the wider SST community through an International SST FRM Radiometer Network (ISFRN). The ISFRN is open for partners around the world, currently compromising of partners from the UK (University of Southampton, Rutherford Appleton Laboratory, Space ConneXions), Denmark (Danish Meteorological Institute) and France (Ifremer) and will not only collect shipborne radiometer data but also use the data to validate SLSTR and other satellite SST products with the Felyx MDB tool. Included in the service is a long term data archive of the FRM data sets at Ifremer where the data will be stored in the ISFRN netCDF L2R format. We will show examples of the ISFRN data and demonstrate its use with SLSTR validation results from the ISFRN network regions.

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The Optimal Estimation (OE) approach has recently been applied by a number of investigators to derive the sea surface skin temperature (SST) from infrared radiance measurements of satellite radiometers. The standard SST retrieval algorithm applied to MODIS data is built on the Non-Linear SST (NLSST) algorithm with a set of coefficients derived using collocated temperature measurements of from drifting buoys that form a Match-Up Data Base (MUDB). The NLSST produces accurate SST retrievals in conditions that are similar to those represented in the MUDB but when conditions deviate from typical, the errors are larger. One situation that leads to significant bias in NLSST occurs in Northern Atlantic near the African coast during Saharan Air Layer (SAL) outbreaks. Typically, the atmosphere in this region is moist and such conditions are dominantly represented in the MUDB and hence by the coefficients of the NLSST algorithm. During SAL events, moist air is replaced by a layer of very dry air; the established coefficients are no longer representative.
It has been postulated that algorithms based on the Optimal Estimation (OE) technique could be more accurate in atypical atmospheric conditions. In most cases by design, the OE also delivers estimates of the total column water vapour (TCWV) in the atmosphere above the sea surface but these TCWV are often deemed unreliable and ignored.
In fall of 2015 during a research cruise on the NATO ship R/V Alliance, we had the opportunity to take radiometric skin SST measurements for the validation of MODIS SST retrievals and simultaneous radiosonde and microwave radiometer measurements of TCWV in both standard conditions for this region, and also during a Saharan air layer (SAL) outbreak. During the SAL outbreak in the northern tropical Atlantic a typically moist tropical or sub-tropical maritime atmosphere is replaced by dry air from the African continent resulting in atypical conditions for the NLSST retrieval.
We used the ship based measurements to test the performance of the NLSST algorithm and the OE approach for the retrieval of both SST and the TCWV under both standard (moist) and atypical (dry) conditions.
For SST, we find that the RMS of the difference between the satellite and ship measured SST is smaller with the OE approach in all conditions and the improvement is greater the lower the quality satellite data.
The TCWV retrieved by OE is within 15% of the TCWV measured by radiosondes over the wide range of TCWC values encountered during the cruise. This is a promising result for the ability of OE to provide simultaneous TCWV and SST retrievals from MODIS infrared measurements.

Figures compare MODIS NLSST and OESST with ship base radiometer (M-AERI) SST and MODIS OE TCWV with a shipborne microwave radiometer (MWR) and from radiosondes and ECMWF fields. Symbols represent different quality of MODIS data QF, from the highest quality of QF=0 (squares) to lower quality QF = 2 (triangles). Generally, these use of QF=2 retrievals is not encouraged.

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There is ample evidence that the ocean has been warming throughout its depth for the past six decades, since reliable and adequate measurements have been made. This warming coincides with increases in concentrations of greenhouses gases in the atmosphere resulting from human activities. At the ocean surface, most of the incoming infrared (IR) radiation is absorbed within the top few micrometers of the ocean’s surface, in the electromagnetic skin layer, where the ocean’s thermal skin layer (TSL) also exists. Since the ocean is nearly always giving heat the atmosphere, the interface temperature of the ocean is cooler than the water beneath, resulting a mean vertical temperature gradient in the TSL, with temperature increasing with depth. Thus, the thermal energy derived by the absorption of the incident IR cannot directly heat the upper few meters of the ocean as this would require heat conduction up the TSL temperature gradient. Hyperspectral IR measurements from ships of the surface IR emission can be inverted to provide a profile of temperature in the TSL because the electromagnetic penetration depth, which equals the emission depth, has a wavelength dependence. We report the results of investigations of the physical mechanism between the absorption of IR and its effect on heat transfer at the air-sea boundary. The hypothesis is that given the heat lost through the air-sea interface is controlled by the temperature gradient in the TSL, the TSL adjusts in response to variations in incident IR to maintain the surface heat loss. This modulates the flow of heat from below, and hence controls upper ocean heat content. This hypothesis is tested using the increase in incoming IR radiation from clouds and analyzing vertical temperature profiles in the TSL retrieved from sea-surface emission spectra. We find the surplus energy from the absorption increasing IR adjusts the curvature of the TSL such that there is a smaller vertical gradient at the interface between the TSL and the water beneath. This reduces the upward conduction of heat into the TSL as the additional energy within the TSL supports a larger proportion of the surface heat loss. Thus, more heat beneath the TSL is retained leading to an increase in upper ocean heat content. This mechanism can explain the counter-intuitive observation that increasing greenhouse gasses heat the ocean.

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Parameterization of upper ocean warming is key to predicting both the vertical transport of heat and the details of air-sea heat exchange. Each of these processes contribute to uncertainties in the global heat budget which need to be narrowed in order to better quantify and model the transport and storage of heat in the climate system. The ocean gains most of its heat from incoming solar radiation, and much of that energy is absorbed very close to the surface (about 25% within the top decimeter). While significant effort has been expended on characterizing in-water absorption (e.g. due to chlorophyll), far less attention has been paid to the effect of the atmosphere on the spectrum of incoming radiation.

We have developed a new parameterization for insolation that accounts for certain atmospheric effects while retaining compatibility with in-water models for different water types. Initial tests using a 2nd-order turbulence closure scheme show that this new parameterization is able to largely resolve long-standing issues with estimating the correct magnitude of warming in different geographical locations. Previously, model tunings that work well for one region and season have resulted in either over- or under-prediction for other regions and seasons.

We are in the process of refining the insolation parameterization, including optimization of the banding and extension to account for other effects. To do this, we use a combination of modeling, radiative transfer, observed sea surface temperatures, atmospheric information, and observations of upper ocean structure. The other critical aspect is the revision of turbulence modeling parameters, primarily those that influence background mixing, including wave action and Langmuir circulation, in the light of the new insolation scheme. Use of upper-ocean information, especially from ARGO floats, is used to ascertain the validity of the new parameterizations. We will present validation results incorporating the sub-surface information combined with satellite observations of ocean skin temperature in order to provide a more complete picture.

The use of satellite-observed SSTs forms a key part of the parameterization verification because, in general, it is easier to observe diurnal warming than to model it. The vast areal coverage cf. in situ observations is, of course, a major benefit. Emerging technology on SST algorithm sensitivity allows the correct diurnal excursion to be obtained (previously it was often simply assumed that the relationship was 1:1). Thus, we will also present comparisons of observed and modeled diurnal cycles on the basin scale, taking advantage of the more accurate sea surface temperature products now available from modern geostationary imagers.

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Momentum flux (stress) and latent heat flux (evaporation) at ocean surface are transported by turbulence, which is small scale random process generated/subdued by wind shear and buoyance (vertical wind and density gradients). Turbulence is difficult to measure and historically bulk formula are used to related the fluxes to the mean parameter measured on ships, such as wind and humidity in air, and temperature and current in water. The coefficients are empirically determined by measurements in experiment at very limited sites for short durations. Starting in the 1970s, satellite measurements of the turbulent fluxes have largely been attempts to retrieve the bulk parameters from measurements by spaceborne sensors. Satellite sensors measure radiance and backscatter at the ocean surface and it is not necessary nor advantageous to reproduce ship-based meteorological and oceanic measurements. We will show direct retrieval of latent heat flux from the radiance measured by microwave radiometers, thus mitigating the multiplication of retrieval uncertainties of wind to those of temperature or humidity while facing the uncertainty of the transfer coefficient. The disadvantage of direct retrieval is that it does not allow intermediate validation using available and familiar ship and buoy measurements. We will show that scatterometer measurements represent the vector difference between wind and current, the characteristic of stress rather than wind. Retrieving winds from the scatterometer and applying them with available ocean currents to determine stress through the bulk parameters will be an overkill. Direct retrieval of stress show that stress spin-down of mesoscale eddies. We will address the uncertainty of retrieving strong wind caused by backscatter saturation of the scatterometer and the change behavior of the transfer coefficient under tropical cyclone by direct stress retrieval.

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The oceans annually absorb >25% of anthropogenic emissions of carbon dioxide (CO₂). This long-term absorption, whilst beneficial in reducing atmospheric concentrations, leads to ocean acidification and therefore impacts the ecosystems that live within the oceans. Improved understanding of this exchange, its transport and the impact on the oceans is therefore now needed to support climate and ecosystem health research. Ocean surface wind, currents and waves play a major role in governing the exchange of heat, energy and gases between the ocean and atmosphere, and its subsequent onward transport. But despite this combined control, a lack of observations means that current methods typically focus on just the wind.

Frontal regions associated with major ocean current systems including the Gulf Stream, Kuroshio and the Antarctic Circumpolar Current play key roles in modulating atmosphere-ocean CO₂ exchange. However, existing global net CO₂ sink analyses are parameterised using just wind-based gas transfer and so overlook the turbulent exchange created by the fronts themselves.

The highly heterogeneous and biologically active continental shelf seas are considered important sinks of anthropogenic CO₂, the strength of which is thought to be increasing. However, the atmosphere-ocean exchange within these seas and its onward transport to the open ocean used within annual assessments is typically characterised as a fixed term based on sparse (historical) in situ measurements.

The Sea Surface Kinematics Multiscale monitoring satellite mission (SKIM) is an Earth Explorer-9 (EE9) candidate mission and it will provide the first direct measurements of total surface ocean velocity and wave spectrum. Here we use existing observations and simulated SKIM data to investigate the impact of wind-wave-current interactions on atmosphere-ocean CO₂ gas exchange and the surface transport of carbon across continental shelves. Both of these processes are typically parameterised using wind speed measurements, despite the knowledge that wind-wave-current interactions play a major role in generating surface turbulence and transport. Our results show that i) previously overlooked turbulent exchange due to wind-wave-current interactions known to occur in strong frontal regions significantly increase regional oceanic CO₂ absorption and ii) wind, waves and currents act in unison to enhance the surface transport of water onto continental shelves, and the subsequent export of carbon from shelf seas to the deep ocean. We will present animated examples of surface exchange and transport and discuss where and how SKIM could help address other critical gaps in carbon research. This study forms part of the SKIM preparatory work. If launched SKIM will provide truly global measurements of surface currents and waves, including complete coverage of equatorial regions and continental shelves.


Figure 1: The Ekman current, geostrophic current and Stokes drift (plotted here from ESA GlobCurrent and NOAA WaveWatchIII data) across multiple depths act together to determine surface transport onto the European continental shelf, which in turn drives offshelf transport of carbon to the deep ocean. The relative importance of each of these components is temporally variable, with wind-driven Ekman currents (and thus Ekman transport) often dominating in winter (a), and geostrophic currents and Stokes drift normal to the shelf edge contributing a greater proportion during the summer months (b). The distance (in kms) along the European continental shelf is given between the coast of Norway in the North, through to the the coast of Spain in the South, and indicative regions are labelled (Norwegian Shelf, North Sea and Hebrides, Celtic Sea, Spanish coast).

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Sentinel-1 (S-1) mission is a synthetic aperture radar (SAR) satellite constellation aiming to provide high-resolution observations for Land, Marine and Atmosphere Monitoring, Emergency Management, Security and Climate Applications. Two satellites, S-1 A&B, are now routinely acquiring wave mode (WV) data over the global open ocean in all weather and day-and-night conditions. Nearly 120,000 SAR images per month are obtained by the two platforms. Each WV SAR image has a footprint of 20 km by 20 km with a spatial resolution of 5 m. These high-resolution ocean surface observations were originally designed for directional wave spectra retrieval, which is part of the operational European Space Agency (ESA) level-2 ocean product. Further exploration of these WV SAR data reveals distinct oceanic and atmospheric signatures are also routinely imaged. This provides a new and unique opportunity to investigate the air-sea processes at sub-kilometer to kilometer scales.
In this study, we classify S-1 WV SAR data for global geophysical investigations. Ten commonly occurring and distinct oceanic and atmospheric phenomena are defined in the labeled dataset TenGeoP-SARwv [1]. Based on this hand-curated training set, a classification model (CMwv), is developed by fine-tuning the Inception v3 deep convolutional neural network (CNN). This classification tool is able to distinguish the ten pre-defined geophysical phenomena: pure ocean waves, wind streaks, micro convective cells, rain cells, biological slicks, sea ice, icebergs, low wind areas, atmospheric fronts, and oceanic fronts. Performance of the developed model is evaluated by using an independent labeled dataset. Results show that the classification tool works properly, especially for six of the ten classes. To further verify the classification results, we compare the classified rain cells and sea ice with rain precipitation (from Global Precipitation Measurement, GPM) and sea ice concentration (from Special Sensor Microwave Imager, SSMI). The geophysical maps are qualitatively comparable to other data sources suggesting the S-1 WV data is an independent data source of small-scale phenomena at a global scale.
Mapping each category in time and space help us to gain a better understanding of air-sea interactions at scales of 5 m-10 km. Here, we focus on the global distribution of organized large eddies and convection (rolls & cells) in the marine atmospheric boundary layer (MABL). These processes are ubiquitous in WV imagery and can significantly contribute to the vertical transport of heat, moisture, and momentum in the MABL. Seasonal alternation between rolls and cells over the Arabian sea is found to be closely associated with the South Asia monsoon and Somalia ocean currents. We will also discuss the characteristics of MABL rolls and cells as well as the atmospheric conditions of their occurrence.

[1] Wang Chen, Mouche Alexis, Tandeo Pierre, Stopa Justin, Longépé Nicolas, Erhard Guillaume, Foster Ralph, Vandemark Douglas, Chapron Bertrand (2018). Labeled SAR imagery dataset of ten geophysical phenomena from Sentinel-1 wave mode (TenGeoP-SARwv). SEANOE. https://doi.org/10.17882/56796

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The CYGNSS constellation of eight satellites was successfully launched in December 2016 into a low inclination (tropical) Earth orbit. Each satellite carries a four-channel bi-static radar receiver which measures signals transmitted by Global Positioning System (GPS) satellites and scattered back into space by the Earth surface. Over the ocean, surface roughness, near-surface wind speed and air-sea latent heat flux are estimated from the direct measurements of surface scattering cross section. Over the land, estimates of near-surface soil moisture and imaging of flood inundation are also possible. The measurements are able to penetrate through all levels of precipitation due to the low microwave frequency at which GPS operates. The spatial density and revisit time of sampling resulting from the number of satellites in the constellation and from their continuous data-taking operation makes possible the reliable detection of tropical cyclone intensification and the resolving of diurnal cycles of tropical winds and soil moisture variability. Engineering commissioning of the constellation was completed in March 2017 and the mission is currently in the science operations phase.

Level 2 science data products have been developed for near surface (10 m referenced) ocean wind speed, ocean surface roughness (via the mean square slope statistic) and latent heat flux. Level 3 gridded versions of the L2 products are also available. A set of Level 4 products have also been developed specifically for direct tropical cyclone overpasses. These include the storm intensity (peak sustained winds) and size (radius of maximum winds), its extent (34, 50 and 64 knot wind radii), and its integrated kinetic energy. Assimilation of CYGNSS L2 wind speed data into the HWRF hurricane weather prediction model has also been studied, and their impact on forecast skill demonstrated. Level 2 science data products over land related to near-surface volumetric soil moisture content and flood inundation extent are also in development.

An overview and the current status of the mission will be presented, together with highlights of on-orbit performance and scientific results.

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The Mediterranean Basin is a climatically sensitive region as it becomes subject to water and temperature stresses while it is a crossroad of air masses, carrying pollutants of different origin including the warm dry air masses from Africa.
On the 22nd of March 2018, an intensive dust outbreak from the Saharan desert over the East Mediterranean Sea has been occurred and has been observed from space. Various satellite’s images show the Saharan dust being blown northwards across the Mediterranean Sea to Europe continent. Lifted into the atmosphere, the mineral dust was carried by the wind and pulled back down to the surface in rain and snow. It reached as far as Greece, Cyprus, Romania, Bulgaria and Russia (http://www.esa.int/spaceinimages).
The present study, using satellite observations, aims to detect the impact of dust transport to Aerosol Load (expressed in terms of optical depth, dimensionless) to the ocean colour and marine primary production of the Mediterranean Sea (using Chlorophyll-a, mg m-3, as a proxy), during this major event. For this purpose, Aerosol Optical Depth (AOD) and Chlorophyll-a (Chl-a) concentration data from Ocean and Land Colour Instrument (OLCI), onboard Copernicus Sentinel-3 satellite, have been acquired. OLCI data have been obtained in a spatial resolution of approximately 1.2 km x 1.2 km at ground (Reduced Resolution – RR), with AOD data at a given wavelength (865 nm) and a spectral dependency between 779 and 865 nm. The impact of dust deposition on the marine ecosystem has been investigated examining covariation of AOD and Chl-a for different time-lags spanning from 1 to 6 days since time needed to allow for transport and fixation of deposited nutrients by the marine ecosystems. Indeed, according to mesocosm experiments the impact of dust additions to marine ecosystem maximizes 2 days after the addition, while after 6 days the effect becomes negligible.

This work has been supported by the project “PANhellenic infrastructure for Atmospheric Composition and climatE change” (MIS 5021516) which is implemented under the Action “Reinforcement of the Research and Innovation Infrastructure”, funded by the Operational Programme "Competitiveness, Entrepreneurship and Innovation" (NSRF 2014-2020) and co-financed by Greece and the European Union (European Regional Development Fund).

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