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2019 Living Planet Symposium, 13-17 May 2019, Milan, Italy, Nowadays, wind speed retrieval is a topic of great interest. Most of the remote-sensing satellite radar systems are able to provide sea-surface wind field information, and they can be considered the main near sea surface wind information source. Within this context, active microwave remote sensing, in particular the scatterometer and the Synthetic Aperture Radar (SAR), is worldwide recognized as one of the best suitable tools to perform a reliable sea-surface wind speed retrieval. Radar backscatter intensity and its statistical properties contain quantitative information about sea surface roughness and, therefore, can be used to derive sea-surface wind information. Empirically derived Geophysical Model Functions (GMF) are used to relate the calibrated radar return to the wind speed at a height of 10m. GMFs usually relate the radar backscatter to wind speed and wind direction. An alternative method to retrieve wind speed from SAR is represented by the spectral based approaches, i.e.; the azimuth cut-off procedure. When dealing with SAR microwave sensors, Doppler misregistration along the azimuth is induced by gravity wave orbital motion. This issue is the major responsible of a distortion of the imaged wave spectrum and of a strong cut-off in the azimuthal direction: this is the azimuth cut-off. Originally, this technique was proposed in [1] to retrieve significant wave height (SWH), without the knowledge of any a priori wind direction information. The theory that is at the basis of the azimuth cut-off method is related to the effect of the orbital motion related to the surface waves in the SAR imaging of the ocean surface. This orbital motion results in additional Doppler shifts that distort the phase history of the backscattered signal used to synthetize the resolution in azimuth. The result is a low-pass filtered SAR image in the azimuth direction. The azimuth cut-off well correlates to the SWH because of its sensitivity to the long waves. In this study, the ACF-based λc approach is extended to high wind speed regimes, e.g.; extreme weather conditions. The key issues that need to be tackled concern the tuning with respect to pixel spacing, box size and the homogeneity of the SAR imagery. Preliminary results obtained processing a large data set of Sentinle-1 SAR imagery collected under a broad range of wind conditions show that the box size and the median filter window should be set at 1 km × 1 km and 90-120 m, respectively. Then, tailored experiments have been undertaken an actual Sentinel-1 dataset collected under high wind regimes, i.e.; tropical cyclones. The obtained λc values are compared both with the ECMWF forecasted information and with wind speed maps provided by Ifremer. Preliminary results show that there is a good agreement between λc and wind speed in some areas of the cyclone, i.e.; further enough from the cyclone eye. [1] V. Kerbaol, B. Chapron, and P.W. Vachon, “Analysis of ERS-1/2 synthetic aperture radar wave mode imagettes”, Journal of Geophysical Reserarch, vol. 103, no. C4, pp. 7833-7846, 1998.

2018 Dragon 4 Mid-term Results Symposium, 19-22 June 2018, Xi’an, P.R. China

2018 Dragon 4 Mid-term Results Symposium, 19-22 June 2018, Xi’an, P.R. China

2018 Dragon 4 Mid-term Results Symposium, 19-22 June 2018, Xi’an, P.R. China

SeaSAR 2018, Advances in SAR Oceanography Workshop, 7-10 May 2018, Frascati, Rome, Tropical cyclone is a generic term that designs a rapidly rotating storm system characterized by a low pressure center that produces strong winds and heavy rainfall. Cyclones are differently named according to the ocean basin where they develop: “Hurricanes” in the Northern Atlantic and Northeast Pacific Ocean, “Typhoons” in the Northwest Pacific Ocean, and “Cyclones” in the Indian Ocean and Southwest Pacific Ocean. Although tropical cyclones are among the most dangerous and destructive natural disasters, current models are still not able to give an accurate forecast of their intensity and track. Hence, within this context, spaceborne active microwave sensors, like the Synthetic Aperture Radar (SAR), are of paramount importance because of their all-weather and all-day capabilities together with a fine spatial resolution. In particular, SAR data can be used to directly monitor position and intensity of the storms, to analyze their structure or the rainfall-rate but also to estimate wind speed and direction. The purpose of this study is to apply the azimuth cut-off approach under extreme weather conditions. In literature, the azimuth cut-off method is used to retrieve wind speed and several studies have been carried out to analyze the dependence of λc on sea surface parameters. In particular, there is a linear relationship between λc values and geophysical parameters, like wind speed under low-to-moderate regimes and significant wave height Recently, in [1] the ACF-based λc approach has been improved to deal with high wind speed regimes, e.g.; extreme weather conditions. The key issues that allow to extend the method to high wind regimes concern the tuning of the method with respect to pixel spacing, box size and the homogeneity of the SAR imagery. In particular, the box size is set at about 1 km × 1 km and an adaptive window size is selected for the median filter to account for the pixel spacing and first results on wind speed estimation under tropical cyclone conditions are presented. In this study, an actual SAR dataset collected under tropical cyclones is used to discuss the soundness of this improved azimuth-cut-off method under extreme weather conditions . [1] M. Portabella, V. Corcione, X. Yang, Z. Jelenak, P. Chang, G. Grieco, A. Mouche, F. Nunziata, W. Li, “Analysis of the SAR-derived wind signatures over extra-tropical storm conditions”, Dragon 4 Symposium, Copenhagen, Denmark, 26-30 June

International Ocean Vector Winds Science Team Workshop (2018 IOVWST), 24-26 April 2018, Barcelona

2017 Dragon 4 Symposium, 26-30 June 2017, Copenhagen, Denmark, Satellite Earth Observation is of paramount importance for a wide range of applications. In fact, the synoptic view of the Earth offered by remotely sensed space-borne measurements allows gathering useful information on climate, environment, etc. Among those applications, the observation of oceans from space represents one of the key topics since oceans cover more than 70% of the Earth’s surface and they are responsible for life. In addition, monitoring the oceans makes us able to better understand natural and human-related processes as marine pollution, climate change, sea level rise, etc. In this context the synthetic aperture radar (SAR), being a microwave active sensor, routinely provides, information on the Earth’s surface during day and nighttime and in almost any weather condition, with fine resolution and dense revisit time if virtual constellation are exploited. In this study, European Space Agency (ESA) Sentinel-1 scanSAR Extra Wide Swath (EW) Ground Range Multilook Detected Medium Resolution (GRDM) dual-polarimetric (DP) VH-VV SAR data measurements are considered to extract information, at C-band, on hurricanes. The underpinning idea is to retrieve wind speed both with co-polar and with cross-polar channels. We used a Geophysical Model Function (GMF), the C-band Cross-Polarization Ocean (C-2PO) which is developed for cross-polarized channel and it is independent of incidence angle and wind direction, for the VH channel [1]. With respect to the VV channel, the azimuth cut-off method is studied to calculate a coefficient of linearity, that allows linking directly the azimuth cut-off with wind speed. The link between azimuth cut-off and wind speed is here investigated under extreme wind conditions

2017 Dragon 4 Symposium, 26-30 June 2017, Copenhagen, Denmark, The monitoring and forecasting of tropical and extra-tropical storm tracks and intensities are strategic for the protection of coastal infrastructures and residents. The Synthetic Aperture Radar (SAR) can potentially be very useful for such purposes. In fact, its high spatial resolution and its capability to observe the sea surface in all weather conditions and at all times (regardless of the day or night-time) makes it one of the best candidate instrument for these goals. Several empirical forward models or geophysical model functions (GMFs), which relate the normalized radar backscatter cross section to the sea surface wind vector, have been developed and successfully used for a wide variety of scatterometer and SAR systems at different frequencies and polarizations. The GMFs have high accuracy under no-rain and low-to-moderate conditions, although for C-band radar systems good-quality winds are also derived under rainy conditions. For high wind speed measurements, the accuracy rapidly decreases due to saturation of the co-polarized backscattered intensity and the reduction of friction between the sea surface and the wind. An improved high-wind GMF for C-band and SAR spatial scales (most GMF developments are based on scatterometer data) as well as new high-wind GMFs for other frequencies (e.g., X-band) are required for the successful wind retrievals under tropical and extratropical cyclone conditions. In this study, the radar backscatter sensitivity to high winds (as given by the different GMFs) is revisited for both C-band and X-band systems, as well as for co-polarized and cross-polarized beams, using the NOAA P-3 flight winter campaign data from January-February 2017. During this campaign, the NOAA P-3 plane, equipped with several sea-surface wind sensing systems, i.e., the Step Frequency Microwave Radiometer (SFMR), the Imaging Wind and Rain Profiler (IWRAP), and dropsondes, underflew both Sentinel-1 (S-1) and Cosmo-SkyMed (CSK) satellite passes under storm conditions in the North Atlantic region. These extra-tropical storms are characterized by vast areas of nearly uniform very high-wind conditions, up to 30-35 m/s. The sensitivity analysis will therefore provide a comprehensive view of the main sensitivities of the radar backscatter (e.g., co-polarized, cross-polarized, polarization difference, polarization ratio) to relatively high winds, for a variety of incidence angles. Moreover, two wind retrieval approaches commonly used by the SAR community, i.e., the azimuth cut-off method and the combined radar backscatter and doppler centroid scheme, will be used to derive the sea surface wind field for the mentioned SAR scenes and validated against the mentioned NOAA wind data sources as well as collocated scatterometer and Soil Moisture Active Passive (SMAP) derived winds