Using Synthetic Cyclone Models for High Wind GNSS-R Calibration, Validation, and Algorithm Development: A CYGNSS Case Study

Al-Khaldi, Mohammad M.; Gleason, Scott; Johnson, Joel T.; Balasubramaniam, Rajeswari; Ruf, Christopher S.; McKague, Darren S.; Annane, Bachir; Wang, Tianlin; Russel, Anthony; Twigg, Dorina

doi:10.1109/TGRS.2023.3294870

i

Using Synthetic Cyclone Models for High Wind GNSS-R Calibration, Validation, and Algorithm Development: A CYGNSS Case Study

2023
By Al-Khaldi, Mohammad M. ; Gleason, Scott ; Johnson, Joel T.
Source IEEE Transactions on Geoscience and Remote Sensing, 61, 1-11

Details

Journal Title:

IEEE Transactions on Geoscience and Remote Sensing
Personal Author:

Al-Khaldi, Mohammad M. ; Gleason, Scott ; Johnson, Joel T. ; Balasubramaniam, Rajeswari ; Ruf, Christopher S. ; McKague, Darren S. ; Annane, Bachir ; Wang, Tianlin ; Russel, Anthony ; Twigg, Dorina
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; AOML (Atlantic Oceanographic and Meteorological Laboratory) ; CIMAS (Cooperative Institute for Marine and Atmospheric Studies)
Description:

This work reports a case study of the use of synthetic cyclone models for the development, assessment and validation of global navigation satellite system reflectometry (GNSS-R) wind speed remote sensing algorithms using a cyclone global navigation satellite system (CYGNSS) data record extending from 1 August 2018 to 31 December 2022. Synthetic cyclone models are shown to be useful in assessing the high wind speed sensitivity of CYGNSS’s v1.0, v2.1, v3.0, v3.1, and future v3.2 normalized bistatic radar cross Section (NBRCS) products due to the extended matchup dataset of high wind speed information that is obtained. The models are also shown useful in investigating the impacts of specific error corrections terms and in the development of level-2 geophysical model functions (GMFs) for the retrieval of ocean surface winds.
Keywords:
- General Earth and Planetary Sciences
- Electrical and Electronic Engineering
Source:

IEEE Transactions on Geoscience and Remote Sensing, 61, 1-11
DOI:

https://doi.org/10.1109/TGRS.2023.3294870
ISSN:

0196-2892 ; 1558-0644
Format:

PDF
Publisher:

Institute of Electrical and Electronics Engineers (IEEE)
Document Type:

Journal Article
Rights Information:

Accepted Manuscript
Compliance:

Submitted
Download URL:

https://repository.library.noaa.gov/view/noaa/55850/noaa_55850_DS1.pdf
File Type:

[PDF - 8.56 MB]
Collection(s):

Office of Oceanic and Atmospheric Research (OAR) ; NOAA Cooperative Institutes
Main Document Checksum:

urn:sha256:4604ab4abefb1d71c5ae4e0f5d6520a7bedccc36801647f118e6b5b05ff040ea

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