Airborne Co-polarization and Cross-Polarization Observations of the Ocean-Surface NRCS at C-Band

Sapp, Joseph; Alsweiss, Suleiman; Jelenak, Zorana; Chang, Paul; Frasier, Stephen J.; Carswell, J.

doi:10.1109/tgrs.2016.2578048

Cited by 42 publications

(30 citation statements)

References 26 publications

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“…The GFS wind directions are close to the measured ones, despite their coarse spatial grid. As expected, wind FIGURE 1 Sketch of wind speed estimation from Sentinel-1 images based on CMOD5.N (Hersbach, 2008) and the Sapp's model (Sapp et al, 2016) for VV-pol and HH-pol data, respectively speed estimates based on the Sapp's model are quite similar to the in situ measurements. The deviation of 0-0.7 m/s is largely below the reasonable threshold of 1-2 m/s, depending on wind spatial resolutions.…”

Section: Hh-pol Sentinel-1 Imagesupporting

confidence: 70%

Detection of convective systems through surface wind gust estimation based on Sentinel‐1 images: A new approach

Messager

Honnorat

et al. 2018

Atmospheric Science Letters

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Convective system (CS) tracking and identification are mainly based on the analyses of brightness temperature and precipitation. Few studies reported about the detection of CSs through surface wind gust estimation due to CS downdraft reaching sea surface. Based on high-resolution Sentinel-1 images, this study proposes the detection of CS signatures through an enhancement of surface wind magnitude in the vicinity of CSs. The CMOD5.N and Sapp's model (CMOD-like function) are used for the retrieval of surface wind speed from VV-pol and HH-pol images, respectively. Based on numerous cases, the study presents the retrieved winds from two representative Sentinel-1 images acquired over the Gulf of Mexico, on which several types of CS effect on sea surface (i.e., round form, convection line) are detected. Wind gust produced by the downdraft associated to these CSs exceeds 20-25 m/s. In order to verify whether the detected wind gust is associated to CSs, moderate/heavy precipitation extracted from the Next-Generation Radar (NEXRAD) images is used as an additional assessment. K E Y W O R D Sconvective system detection, Sentinel-1, surface wind speed estimation

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Section: Hh-pol Sentinel-1 Imagesupporting

confidence: 70%

Detection of convective systems through surface wind gust estimation based on Sentinel‐1 images: A new approach

Messager

Honnorat

et al. 2018

Atmospheric Science Letters

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“…The alternate cross polarization (here denoted VH for simplicity) on the mid beams will improve the extreme wind speed range and initial research has provided first empirical and theoretical insights on the VH sensitivity at extreme winds (e.g., [32]- [34]). Further scientific elaboration of the VH signal behavior for ocean [35], soil, and cryospheric applications will be necessary, as well as elaboration of the geophysical retrieval methodologies to include the VH sensitivity.…”

Section: Cross Polarization and Hh Copolarizationmentioning

confidence: 99%

Scientific Developments and the EPS-SG Scatterometer

Stoffelen

Aaboe

Calvet

et al. 2017

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The second-generation exploitation of meteorological satellite polar system (EPS-SG) C-band-wavelength scatterometer instrument (called SCA), planned for launch in 2022, has a direct heritage from the successful advanced scatterometer (ASCAT) flown on the current EPS satellites. In addition, SCA will represent three major innovations with respect to ASCAT, namely: 1) Cross polarization and horizontal copolarization; 2) a nominal spatial resolution of 25 km; and 3) 20% greater spatial coverage than AS-CAT. The associated expected science and application benefits that led the SCA design are discussed with respect to ocean, land, and sea ice applications for near-real time, climate monitoring, and research purposes. Moreover, an option to implement an ocean Doppler capability to retrieve the ocean motion vector is briefly discussed as well. In conclusion, the SCA instrument innovations are well set to provide timely benefits in all the main application areas of the scatterometer (winds, soil moisture, sea ice) and can be expected to contribute to new and more sophisticated meteorological, oceanographic, land, sea ice, and climate services in the forthcoming SCA era.

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“…Scatterometers, such as ASCAT or QuikSCAT, are able to reliably measure wind speeds up to ∼35 m/s, at which point they lose sensitivity and the signal begins to saturate (Donelan et al, 2004;Hwang et al, 2013;Hwang and Fois, 2015;Sapp et al, 2016). C-band scatterometers perform better in rainfall than Ku-band scatterometers, but existing C-band scatterometers sacrifice spatial coverage to do so.…”

Section: High Wind Speed Retrievalsmentioning

confidence: 99%

“…To note, the potential of both cross and co-polarization yielded to several proposals of concept missions, including the scatterometer onboard the Metop-SG series (Stoffelen et al, 2017b). C-band scatterometer cross-pol measurements obtained from hurricane flights with the NOAA WP-3D aircraft have also shown the sensitivity of the cross-polarized response to extreme winds (Sapp et al, 2016(Sapp et al, , 2018.…”

Section: High Wind Speed Retrievalsmentioning

confidence: 99%

Remotely Sensed Winds and Wind Stresses for Marine Forecasting and Ocean Modeling

et al. 2019

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Airborne Co-polarization and Cross-Polarization Observations of the Ocean-Surface NRCS at C-Band

Cited by 42 publications

References 26 publications

Detection of convective systems through surface wind gust estimation based on Sentinel‐1 images: A new approach

Detection of convective systems through surface wind gust estimation based on Sentinel‐1 images: A new approach

Scientific Developments and the EPS-SG Scatterometer

Remotely Sensed Winds and Wind Stresses for Marine Forecasting and Ocean Modeling

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