TY - GEN
T1 - A 'Track-Wise' Wind Retrieval Algorithm for the CYGNSS Mission
AU - Said, Faozi
AU - Jelenak, Zorana
AU - Park, Jeonghwang
AU - Soisuvarn, Seubson
AU - Chang, Paul S.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - The cyclone global navigation satellite system (CYGNSS), launched on December 15 2016, represents the first dedicated GNSS-R satellite mission specifically designed to retrieve ocean surface wind speeds in the Tropical Cyclone (TC) environment. The baseline wind retrieval algorithm for the CYGNSS mission makes use of two observables (the normalized bi-static radar cross section and the leading edge slope) to retrieve the average wind speed within a 25 km resolution cell. The premise of the algorithm is that these two observables are only a function of wind speed and incidence angle. Analysis of actual CYGNSS measurements during the course of the calibration and validation process, indicates that collected GNSS-R signals show a dependence on both winds and waves. This paper will present an alternative method in retrieving the wind speed from CYGNSS data, which will include the use of a geophysical model function dependent on both wind and wave data.
AB - The cyclone global navigation satellite system (CYGNSS), launched on December 15 2016, represents the first dedicated GNSS-R satellite mission specifically designed to retrieve ocean surface wind speeds in the Tropical Cyclone (TC) environment. The baseline wind retrieval algorithm for the CYGNSS mission makes use of two observables (the normalized bi-static radar cross section and the leading edge slope) to retrieve the average wind speed within a 25 km resolution cell. The premise of the algorithm is that these two observables are only a function of wind speed and incidence angle. Analysis of actual CYGNSS measurements during the course of the calibration and validation process, indicates that collected GNSS-R signals show a dependence on both winds and waves. This paper will present an alternative method in retrieving the wind speed from CYGNSS data, which will include the use of a geophysical model function dependent on both wind and wave data.
UR - https://www.scopus.com/pages/publications/85077681284
U2 - 10.1109/IGARSS.2019.8898099
DO - 10.1109/IGARSS.2019.8898099
M3 - Conference contribution
AN - SCOPUS:85077681284
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 8711
EP - 8714
BT - 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
Y2 - 28 July 2019 through 2 August 2019
ER -