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Assessment of CYGNSS Wind Speed Retrieval Uncertainty

Ruf, Christopher S., Gleason, Scott, McKague, Darren S.·2019·IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
DOI 10.1109/jstars.2018.2825948
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Abstract

Measurements of near surface wind speed made by the Cyclone Global Navigation Satellite System (CYGNSS) constellation of GNSS-R satellites are evaluated and their uncertainty is assessed in two ways. A bottom-up assessment begins with a model for the error in engineering measurements and propagates that error through the wind speed retrieval algorithm analytically. A top-down assessment performs a statistical comparison between CYGNSS measurements and coincident “ground truth” measurements of wind speed. Results of the two approaches are compared. Overall performance, as determined by the top-down method, is decomposed using the bottom-up approach into its contributing sources of error. Overall root mean square (RMS) uncertainty in the CYGNSS retrievals is 1.4 m/s at wind speeds below 20 m/s. At higher wind speeds, an increase in the retrieval error is primarily caused by a decrease in the sensitivity of the ocean scattering cross section to changes in wind speed. In tropical cyclones, retrieval errors are compounded by unaccounted departures from a fully developed sea state. Overall RMS uncertainty in the CYGNSS retrievals is 17% at wind speeds above 20 m/s.

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Crossref · 10.1109/jstars.2018.2825948

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  • Bistatic radar data contains signatures that have been used for wide-ranging Earth Science applications, including measuring ocean surface wind speeds, soil moisture, inland water body mapping, river width and surface slope estimation.

    “The bistatic radar data contains signatures that have been used for wide-ranging Earth Science applications, including measuring ocean surface wind speeds [4], soil moisture [5][6][7], inland water body mapping [8][9][10][11][12][13][14][15], and river width [16] and surface slope [17] estimation.”

    From Characterization of River Width Measurement Capability by Space Borne GNSS-Reflectometry (2024) · cites this paper as [4]

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Research works printed but not linked: 22

  1. gleason, 0, The CYGNSS level 1 calibration algorithm and error analysis based on on-orbit measurements, IEEE J Sel Topics Appl Earth Observ Remote Sens
  2. 10.1109/TGRS.2016.2541343 · DOI
  3. ruf, 2016, CYGNSS Handbook
  4. wang, 0, Design and performance of a GPS constellation power monitor system for improved CYGNSS L1B calibration, IEEE J Sel Topics Appl Earth Observ Remote Sens
  5. ruf, 0, Development of the CYGNSS geophysical model function for wind speed, IEEE J Sel Topics Appl Earth Observ Remote Sens
  6. 10.1109/TGRS.2014.2303831 · DOI
  7. andersson, 2015, User Guide to ECMWF Forecast Products, ECMWF v2 1, 121
  8. 10.1175/MWR3454.1 · DOI
  9. 10.1016/j.ocemod.2013.12.006 · DOI
  10. 10.1109/JSTARS.2016.2643641 · DOI
  11. 10.1080/2150704X.2012.693967 · DOI
  12. 10.1002/2015GL064204 · DOI
  13. 10.1109/TGRS.2012.2230401 · DOI
  14. 10.1109/MGRS.2013.2260911 · DOI
  15. 10.1175/BAMS-D-14-00218.1 · DOI
  16. 10.1109/36.729357 · DOI
  17. 10.1029/96JC01751 · DOI · Paper page
  18. 10.1109/TGRS.2015.2502245 · DOI
  19. 10.1109/TGRS.2009.2027896 · DOI
  20. hersbach, 2008, CMOD5.N: A C-band geophysical model function for equivalent neutral wind, ECMWF Technical Memorandum
  21. 10.1109/JSTARS.2017.2685432 · DOI
  22. verhoef, 2008, CMOD5.n—The CMOD5 GMF for Neutral Winds, EUMETSAT Tech Note SAF/OSI/CDOP/KNMI/TEC/TN/165, 13

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Metadata

Authors
Ruf, C. S., Gleason, S., & McKague, D. S.
ORCID
Ruf, Christopher S.
Venue
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2019-01
Volume
12
Issue
1
Pages
87-97
ISSN
  • 1939-1404
  • 2151-1535
DOI
10.1109/jstars.2018.2825948
Cited by
128
References
0
Licence
Funders
Science Mission Directorate (NNL13AQ00C)

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