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Oceans form Space V Symposium, 24-28 october 2022, Venice, Italy.-- 2 pages, 2 figures, Accurate high and extreme sea surface wind observations are essential for meteorological, ocean, and climate applications. A method to inter-calibrate spaceborne scatterometer and radiometer derived high and extreme winds using NOAA hurricane “hunter” data is presented. The proposed method is effective, providing highly consistent satellite-derived extreme wind datasets in the period 2009-2020. Further work is needed though to consolidate an in-situ reference for extreme wind calibration purposes, This work was supported in part by the MCIN/AEI/10.13039/501100011033 through the Project INTERACT under Grant PID2020-114623RB-C31, and in part by the European Space Agency (ESA) through the OCEAN+EXTREMES Marine Atmosphere eXtreme Satellite Synergy (MAXSS) Project under Contract 4000132954/20/I-NB

Oceans form Space V Symposium, 24-28 october 2022, Venice, Italy.-- 2 pages, 2 figures, This paper presents a new methodology to correct the land-contaminated normalized radar crosssection (σ0) measurements acquired by the scatterometer SeaWinds, which flew aboard the QuikSCAT satellite platform from 1999 to 2009, operated by the National Aeronautics and Space Administration (NASA). This method is based on the hypothesis that contaminated σ0s are linearly dependent on the Land Contribution Ratio (LCR) index, which is defined as the ratio of the footprint area contaminated by the presence of land to the total footprint area. Furthermore, the σ0 deviations from the expected contaminated σ0 values are “regularized” by homogenizing their distribution, making them independent of land contamination. The preliminary results show that this methodology is effective up to few kilometers to the coast. In addition, it prevents the presence of negative corrected σ0s, This work has been carried out in the context of the Visiting Scientist Activity ”Coastal PenWP”, (OSI VSA 21 03) issued by the Ocean Sea Ice Satellite Application Facilities (OSI-SAF) of the European Agency for the Exploitation of Meteorological Satellites (EUMETSAT)

Oceans form Space V Symposium, 24-28 october 2022, Venice, Italy.-- 2 pages, 3 figures, The ocean interacts with the atmosphere, land and ice on multiple spatial scales including fine submesoscales that are often observed in high resolution optical images. Little is known about their dynamics however. SeaSTAR is an innovative satellite mission concept that proposes to address this gap by mapping ocean current and wind vectors at 1 km resolution. In this paper, we present the OSCAR instrument - an airborne demonstrator of the SeaSTAR concept - and the first results from a scientific campaign over the Iroise Sea in May 2022. The capabilities of OSCAR are demonstrated against ground truth data with very promising first results. These results open the door to using OSCAR as a scientific tool to provide unique 2D synoptic views of ocean and atmosphere dynamics at km-scales, This work was supported by ESA/ESTEC Contract Number 4000116410/16/NL/BJ for the OSCAR development and ESA/ESTEC contract number 400017623/22/NL/IA for the campaign over Iroise Sea

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, 17-22 July 2022, Kuala Lumpur, Malaysia.-- © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-- 4 pages, 3 figures, The ERA* stress-equivalent wind (UI0S) is a correction of the ECMWF Fifth Reanalysis (ERA5) output by means of geo-Iocated scatterometer-ERA5 differences over a 3-day temporal window, in which the combined sampling of the Advanced Scatterometers on board the Metop satellite series (ASCAT-A, -B, and -C) and the SCATSat-l scatterometer (OSCAT2) have been used, for the year 2019. ERA * can correct for local, persistent NWP model output errors associated with physical processes that are absent or misrepresented by the model, e.g., strong current effects (such as western boundary current systems, highly stationary), wind effects associated with the ocean mesoscales (sea surface temperature), coastal effects (land see breezes, katabatic winds), Planetary Boundary Layer parameterization errors, and large-scale circulation effects, e.g., at the inter-tropical convergence zone, This work was supported in part by the Spanish R&D project LBAND (ESP2017-89463-C3-1-R), which is funded by MCIN/AEI/10.13039/501100011033 and “ERDF A way of making Europe”, and project INTERACT (PID2020-114623RB-C31), which is funded by MCIN/AEI/10.13039/501100011033

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, 17-22 July 2022, Kuala Lumpur, Malaysia.-- © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-- 4 pages, 3 figures, This paper describes some preliminary steps to improve the coastal winds retrieved from the Seawinds scatterometer on-board the QuikSCAT satellite platform. In particular, it describes a method for estimating the slice Normalized Radar Cross Section ( σ0 ) noise. Moreover, it shows a simple method for selecting the best-suited σ0 domain to implement a Land Contribution Ratio (LCR) based σ0 correction scheme. The preliminary results suggest that there are some non-negligible differences between the open sea and the “every kind of surface” noise characteristics, even if such differences are not reported in the QuikSCAT files. The intra-egg σ0 biases may amount to approximately ±0.6 dB for H-Pol acquisitions and half that for V-Pol, but the impact on the noise estimation amounts to less than 2%. Finally, the LCR-based σ0 correction scheme is now being tested and developed in the linear domain, This work was supported by the EUMETSAT Ocean & Sea Ice Satellite Application Facilities (OSI-SAF) Visiting Scientist projects VS20 01, VS20 03 and VS21 03 and by the Spanish R&D Plan through the Project L-BAND (reference ESP2017-89463-C3-1-R)

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, 17-22 July 2022, Kuala Lumpur, Malaysia.-- © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-- 4 pages, 2 figures, The resolution of regional numerical weather prediction (NWP) models has continuously been increased over the past decades, in part, thanks to the improved computational capabilities. At such small scales, the fast weather evolution is driven by wind rather than by temperature and pressure. Over the ocean and in the free troposphere, where global NWP models are not able to resolve wind scales below 150 km, regional models provide wind dynamics and variance equivalent to 25 km or lower. However, although this variance is realistic, it often results in spurious circulation (e.g., moist convection systems), thus misleading weather forecasts and interpretation. An accurate and consistent initialization of the evolution of the 3-dimensional (3-D) wind structure is therefore essential in regional weather analysis. The wind profiles provided by the ESA Aeolus satellite mission will help filling the observational gap in the upper air and hopefully improve regional weather forecast. For a correct assimilation into NWP models, the observations need to be characterized in terms of their spatial scales and measurement errors. To this end, the triple collocation method, widely used in scatterometry, is applied to Aeolus observations collocated with Mode-S aircraft observations and ECMWF model output. An algorithm for collocating 4D wind observations from Aeolus, Mode-S and ECMWF over a region of Western Europe will be presented, along with measurement errors obtained from triple collocation

This work is a contribution to CSIC PTI Teledetect.-- VII Encuentro de Oceanografía Física (EOF) - Expanding Ocean Frontiers Conference, VIII International Symposium on Marine Sciences, 6-8 July 2022, Las Palmas de Gran Canaria, España, In the framework of the European Space Agency (ESA) World Ocean Circulation project (WOC), the enhanced ocean wind forcing product (ERA*) has been developed to address the growing demand for accurate forcing from the ocean modelling community. The ERA* is a corrected reanalysis product that optimally combines the capacities of scatterometer observations and model reanalysis stress equivalent wind (U10S) output, by means of a geolocated scatterometer-based correction (SC) applied to the European Centre forMediumrange Weather Forecasts (ECMWF) Fifth reanalysis U10S output (ERA5). The SC consists of accumulated ERA5-scatterometer U10S component (zonal and meridional) differences over time windows of typically a few days to a month, at each ocean grid point (Trindade et al. (2020)). ERA* is able to introduce true smaller scale signal into ERA5 that corresponds to the physical processes absent or misrepresented by the latter, e.g., strong current effects (such as WBCs, highly stationary), wind effects associated with the ocean mesoscales (SST), coastal effects (land see breezes, katabatic winds), parameterization errors, and large-scale circulation effects, e.g., at the ITCZ. This is verified by comparing both products against independent scatterometer observations (e.g., HSCAT on HY-2A and HY-2B) and buoys winds. The ERA* product is generated for the period 2010-2020. An optimized configuration of ERA* in terms of the varying scatterometer constellation over the period of interest is sought. In particular, the optimal SC time window size will depend on the scatterometer sampling, i.e., the larger the number of scatterometers in orbit is, the smaller is the time window required. The ERA* reduces the vector root-mean-square difference by 10% (5%) against independent scatterometers (buoys), with respect to that of ERA5. The new ERA* product, which thus significantly outperforms ERA5, will be freely available from theWOC webpage (https://www.worldoceancirculation.org/), This work was supported in part by the ESA study entitled "World Ocean Circulation" (4000130730/20/I-NB) and in part by the Spanish R&D projects LBAND (ESP2017-89463-C3-1-R), which is funded by MCIN/AEI/10.13039/501100011033 and "ERDF A way of making Europe", and INTERACT (PID2020-114623RB-C31), which is funded by MCIN/AEI/10.13039/501100011033. We also acknowledge funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2019-000928-S)

17 pages, 1 table, The present document is the Product User Manual dedicated to the content and format description of the ERA star stress-equivalent wind vector (U10S) and wind stress product. This is the primary document that users should read before handling the product. It provides an overview of processing algorithm, technical product content and format and main validation results

42 pages, 20 figures, 4 tables, The ERA* stress-equivalent wind (U10S) and stress vector product is a correction of the ECMWF Fifth Reanalysis (ERA5) output by means of geo-located scatterometer-ERA5 differences over a few days temporal window. The version 2 products contain two different datasets: the nominal product over the period 2010-2020, which uses a temporal window of 15 days (except for 2010, in which a temporal window of 30 days is used); and an enhanced quality and resolution product for the years 2013, 2018 and 2020, which uses a temporal window of 3 days. Both products use, at any given time, all available scatterometer systems with global and continuous coverage. The enhanced product is only provided over those periods in which there is sufficient scatterometer sampling to allow the use of short temporal windows. The scatterometer-based corrections are computed from a combination of the following systems, i.e., the Advanced Scatterometers (ASCAT-A, -B, -C) onboard the EUMETSAT Metop satellite series, and the scatterometers onboard the ISRO Oceansat-2 (OSCAT) and SCATSat-1 (OSCAT2). ERA* can correct for local, persistent NWP model output errors associated with physical processes that are absent or misrepresented by the model, e.g., strong current effects (such as WBCS, highly stationary), wind effects associated with the ocean mesoscales (SST), coastal effects (land see breezes, katabatic winds), PBL parameterization errors, and large-scale circulation effects, e.g., at the ITCZ

43 pages, 35 figures, A prerequisite for a successful development of the multi-mission wind (MMW) product is to ensure good inter-calibration of the different extreme wind datasets to be integrated in the product. Since the operational hurricane community is working with the in-situ dropsondes as wind speed reference, which are in turn used to calibrate the NOAA Hurricane Hunter Stepped Frequency Microwave Radiometer (SFMR) wind data (Uhlhorn et al., 2007), MAXSS uses the latter to ensure inter-calibration among the Tier-1 medium-resolution swath-based scatterometer and radiometer systems described in Section 2.2 and listed in Tables 1 and 2 of [MAXSS Team, 2021]. In short, these are: the Advanced Scatterometers onboard the Metop series (i.e., ASCAT-A, -B, and -C), the scatterometers onboard Oceansat-2 (OSCAT) and ScatSat- 1 (OSCAT-2), and onboard the HY-2 series (HSCAT-A, -B); the Advanced Microwave Scanning Radiometer 2 onboard GCOM-W1(AMSR-2), the multi-frequency polarimetric radiometer (Windsat), and the L-band radiometers onboard the Soil Moisture and Ocean Salinity (SMOS) and the Soil Moisture Active Passive (SMAP) missions. [...]

55 pages, 36 figures, 2 tables, This study presents a refinement of the assessment of QuikSCAT normalized radar cross sections (σ0s) noise, together with an assessment of the intra-egg biases induced by the incidence angle variation and their impact on noise estimates. In addition, it describes a new implementation of Land Contribution Radio (LCR). Furthermore, it shows the implementation of an LCR-based σ0 correction scheme to reduce the impact of land contaminations. Finally, corrected σ0s are integrated in the four pol-view σ0s to be used in the retrieval step. Four different averaging methodologies are considered, which differentiate according to the weight assigned to each slice: homogeneous (boxcar), Kp dependent, lcr dependent, or Gaussian dependent on the retrieval error. The results confirm that the noise levels provided in the full resolution files have some significant differences with the estimates. In particular, external H-Pol acquisitions are noisier than expected, especially those closer to the antenna for medium-high wind regimes, while inner acquisitions are less noisy than reported in the files, especially those V-Pol. The impact of the intra-egg biases on the noise estimates is less than 7%, therefore all previous conclusions are valid. The correction of σ0s shows that the new LCR method (LCRfull) seems to provide more suitable estimates of LCR. The correction method is effective in reducing the coastal σ0 values, even if many negative values occur. This trend is expected and the main reason is due to the high σ0-dependent noise level that affects QuikSCAT measurements. A new formulation of the correction scheme that considers an additional noise-dependent regularization parameter is recommended. Finally, integration methodologies show some differences, but all show some residual contamination near the shore. These preliminary results are not sufficient to select the most suitable one. It is recommended to make this choice after the retrieval step is performed. The software structure is robust, but the LCR computation is very time-consuming. An optimization of the code is required after it is implemented in a suitable low-level programming language

3 pages, 2 figures, [EN] In 1987, Konstantin Fedorov, a prominent Soviet oceanographer of the time, dedicated one of his popular science talks to the salinity of the ocean and called it “The Cinderella of Dynamic Oceanology”. Fedorov said that “The fate of salinity as a physical parameter is closely related to the dynamics of ocean waters and is very similar to the fate of poor Cinderella in Charles Perrault’s fairy tale. And, like the fate of poor Cinderella, salinity has long cried out for justice”. […], [ES] En 1987, el Prof. Fedorov, destacado oceanógrafo soviético de la época, dedicó una de sus charlas divulgativas a la salinidad del océano y la llamó “La Cenicienta de la oceanología dinámica”. Fedorov decía que “El destino de la salinidad como parámetro físico está estrechamente relacionado con la dinámica de las aguas del océano y es muy similar al destino de la pobre Cenicienta del cuento de hadas de Charles Perrault. Y, como el destino de la pobre Cenicienta, hace tiempo que la salinidad clama justicia”. […], [CAT] El 1987, el Prof. Fedorov, destacat oceanògraf soviètic de l’època, va dedicar una de les seves xerrades divulgatives a la salinitat de l’oceà i la va anomenar “La Ventafocs de l’oceanologia dinàmica”. Fedorov deia que “El destí de la salinitat com a paràmetre físic està estretament relacionat amb la dinàmica de les aigües de l’oceà i és molt similar al destí de la pobra Ventafocs del conte de fades de Charles Perrault. I, com la pobra Ventafocs, fa temps que la salinitat clama justícia”. […]

Remote Sensing for Ocean-Atmosphere Interactions Studies and Applications Workshop, 1-3 December 2021, The traditional framework used for inferring the density driven oceanic circulation necessitates the need of air-sea flux datasets. These datasets are of coarse spatio-temporal resolution as well as highly uncertain due to the nature of their derivation. This means that we cannot take advantage of high resolution ocean surface variables (e.g. provided by satellites) in studies of oceanic circulation. In this study, we have developed an alternative framework in which deep circulation can be inferred through ocean surface variables alone via the material evolution of sea surface salinity (SSS) and sea surface temperature (SST). We showcase the performance of both the approaches over 23 years (1995-2018) in the Southern Hemisphere

2021 EUMETSAT Meteorological Satellite Conference, 20-24 September 2021, Bucharest, Romania

VI Expanding Ocean Frontiers Conference (EOF 2021), 5-7 July 2021

15th International Winds Workshop, 12-16 April 2021.-- 30 pages, High-resolution satellite-derived sea-surface wind data, such as those from scatterometers, are increasingly available for operational monitoring and forecasting of the ocean. In this presentation we present the scatterometer constellation and show first results that indicate that the scatterometer wind data assimilation process can be potentially much improved by bias correction. Belmonte & Stoffelen (2019) documented large NWP model errors on both large and small scales and on all temporal scales. Trindade et al. (2019) succeeded to compute stable gridded NWP minus scatterometer differences over a few days, which were subsequently used to correct a time series of numerical weather prediction (NWP) outputs in a product that they called ERA*. They verified ERA* against independent wind measurements, which resulted in a reduction of the observation minus NWP field, so-called o-b, global variance of 20%. An o-b reduction of 20% is very substantial. Moreover, the reduction is due to bias correction, which helps to more closely fulfill the BLUE paradigm of NWP data assimilation. BLUE stands for Best Linear Unbiased Estimate and is necessary to well inform the atmospheric state variables of the NWP model. Data assimilation of scatterometer data in NWP generally only resolves NWP spatial scales of ~150 km. Therefore, information on the wind-SST interaction, the diurnal wind cycle and the wind variability in moist convection areas is lost in such products. Moreover, known systematic NWP model (parameterization) errors and ocean currents contribute to local biases, which are rather time invariant. Such biases prevent to properly correct the meso- and large-scale NWP dynamical errors. Following ERA*, a bias correction scheme may be implemented that takes out the slow biases in o-b mentioned above, that are mostly related to the local ocean state and not resolved in NWP models. The corrections can be further used to attribute errors to the bias (and variability) source terms in order to improve the air-sea interaction modelling, which will be important in the coupling of atmosphere and ocean models of the future

International Ocean Vector Winds Science Team Meeting, 24 February - 10 March 2021

International Ocean Vector Winds Science Team Meeting, 24 February - 10 March 2021

Third International Workshop on Satellite Analysis of Tropical Cyclones (IWSATC-3), 7-10 December 2021

2021 EUMETSAT Meteorological Satellite Conference, 20-24 September 2021, Bucharest, Romania, The prime ocean vector winds user requirement is enhanced temporal coverage for the tracking of mesoscale transient features and resolving coastal air-sea breezes and their diurnal cycle. Hence, collaboration and cooperation between Europe, India and China is ongoing to elaborate our OSI SAF plans to develop high-quality services and applications, while the global virtual constellation of wind scatterometers is being extended, in order to benefit world-wide users. Besides the comprehensive and versatile quality monitoring by the wind data providers, extended quality monitoring has been performed by the Numerical Weather Prediction (NWP) centres, before relying on data assimilation techniques to improve the initial model state of the forecast model by using the actual constellation scatterometer winds. For example, first Observing System Experiments (OSE) at several European NWP centres show neutral to positive forecast impact by assimilating HY-2B winds processed by KNMI. These new winds, measured at 6:00 and 18:00 Local Solar Time (LST) are furthermore much welcomed by the marine nowcasting professionals to complement the current virtual constellation of wind scatterometer data at 8:45/20:45 and 9:30/21:30 LST from ScatSat and ASCAT-A/B/C, respectively. Later in 2021, more scatterometer systems measuring at different local times will be added (OceanSat-3 from ISRO at 12:00/0:00 LST, CMA WindRad at 6:00/18:00 LST and HY-2C at varying LST). Ground station extension is much welcomed for the European marine nowcasting and NWP applications. Access to more timely constellation winds is the single achievable requirement by our users that would bring most benefit. Concerning ocean model forcing, the HY2 data has been used to verify a new blended scatterometer and NWP wind product that exploits the virtual wind scatterometer constellation in more detail by extracting and isolating the global wind structures associated with the air-sea interface, but that are not resolved in (ocean-coupled) global NWP. The resulting improved ocean forcing and NWP bias product may be extended, inter alia, to include the information brought by the HY2 scatterometers. In particular, the sun-asynchronous HY-2C wind data would be invaluable to further develop this product. The extracted structures are stable in time and may be used to allow Best Linear Unbiased Estimation in NWP data assimilation. The bias correction structures reduce the so-called o-b variance by 20%, which is enormous and should in principle much enhance the benefits of scatterometer wind data assimilation in NWP. This remains to be tested, however., Preliminary work on using the HY-2B scatterometer backscatter data for soil moisture and accumulated rain observation over land has commenced, indicating the potential of such development. A virtual constellation is further very useful for the assessment of accumulated rain as more observations per day will become available at each ground pixel. It goes without saying that an accumulated rain product, based on land backscatter measurements is highly complementary to rain products based on microwave rain cloud measurements, as the latter cannot track the fast moist convection processes and its associated rain, while the accumulated rain acts more like a rain gauge, where all rain is collected in the measured soil wetness. In summary, the virtual constellation of wind scatterometers has already contributed to relevant processing, monitoring and application developments over sea, land and ice, where further NWP and more general application benefits are expected with the further ongoing extension of the constellation and its applications

2021 EUMETSAT Meteorological Satellite Conference, 20-24 September 2021, Bucharest, Romania, The resolution of regional numerical weather prediction (NWP) models has continuously been increased over the past decades, in part, thanks to the improved computational capabilities. At such small scales, the fast weather evolution is driven by wind rather than by temperature and pressure. Over the ocean, where global NWP models are not able to resolve wind scales below 150 km, regional models provide wind dynamics and variance equivalent to 25 km or lower. However, although this variance is realistic, it often results in spurious circulation (e.g., moist convection systems), thus misleading weather forecasts and interpretation. An accurate and consistent initialization of the evolution of the 3-dimensional (3-D) wind structure is therefore essential in regional weather analysis. The research will focus on a comprehensive characterization of the spatial scales and measurement errors for the different operational space-borne wind products currently used and/or planned to be used in regional models. In addition, a thorough investigation and improvement of the 4-D (including time) consistency between different horizontal and/or vertical satellite wind products will be carried out. Such products include the Ocean and Sea Ice Satellite Application Facility (OSI SAF) scatterometer-derived sea-surface wind fields, the Nowcasting and Very Short-Range Forecasting (NWC) SAF Atmospheric Motion Vectors (AMVs), Aeolus and/or Infrared Atmospheric Sounding Interferometer (IASI) wind profiles. Densely sampled aircraft wind profiles (Mode-S) will be used to verify and characterize the satellite products. To this end, the experience of the NWC, OSI, and NWP SAFs will be exploited. Moreover, data assimilation experiments of the consistent datasets into the HARMONIE-AROME regional model will be carried out in two different regions, i.e., the Netherlands and the Iberian Peninsula regional configurations. Regarding the characterization of the spatial scales and measurement errors, the widely used triple collocation analysis in scatterometry is further analyzed and adapted for the purpose of this project. Scatterometer winds are collocated with buoy observations and ECMWF model output during a period of 14 months on a global scale over the oceans. Different techniques to estimate the representativeness errors of the collocated data sets are inter-compared and their inconsistencies analyzed. The triple collocation method is then exploited to characterize the errors of the different sources at different scales. The analysis is performed for different oceanic regions and seasons., Finally, an algorithm for collocating 4D wind observations from Aeolus, Mode-S data, and ECMWF model output over a region of Western Europe is currently being developed. Moreover, experimental 4D wind data from IASI are analyzed to evaluate its possible use as an additional source of wind observations for regional data assimilation