Set-up of Pencil Beam Wind Processor (PenWP) for SeaWinds-derived coastal winds

  • In the context of the OSI SAF Visiting Scientist Activities Program, Giuseppe Grieco from the Italian Institute of Marine Science (ISMAR-CNR), worked on a procedure to mitigate land contamination of the Seawinds Pencil beam scatterometer's acquisitions. This work done in 2023 was supervised by Marcos Portabella (ICM-CSIC) and Ad Stoffelen (KNMI).

    • Result of three sea-wind retrieval experiments over the North Adriatic with and without noise regularization. Result of three sea-wind retrieval experiments over the North Adriatic with and without noise regularization.
  • Figure: CTRL: stateof-the-art configuration at OSI SAF: all slices with Land Contribution Ratio (f) > 0.02 are discarded, no correction applied. | NC : “No-Correction”: all slices with f > 0.5 are discarded, and no correction was applied.| NR : “Noise Regularization”: all slices with f > 0.5 are discarded, and noise regularization was applied.| QCed : Quality Checked, MLE : Maximum Likelihood Estimation, varQC : Failed Quality Check.

  • Objectives and framework of the study

    Coastal winds are of vital importance for many applications, such as safety at sea, wind energy, coastal protection and land-sea interaction. This study presents the implementation of a procedure to mitigate land contamination of ocean scatterometer measurements for the Pencil Beam Wind Processor (PenWP) scatterometer, the fore-runner of very similar instruments from India (OceanSat) and China (HY2). The applied methodology is effective in mitigating land contamination as coastal sampling increases by 300% in the coastal band within 10 km to the coast, compared to the state-of-the-art retrieval procedure implemented at the EUMETSAT OSI SAF.

  • The applied procedure is called noise regularization, because, after it is applied, the level of noise of the corrected acquisitions is constant. The effects of noise regularization are evaluated both at the Normalized Radar Cross-Section (σ0), and wind retrieval levels.

  • Within 10 km to the coast the sampling rate improves (by ≈300%), when noise regularization is applied.

  • There appears further room for improvement by refining the wind retrieval quality control. The study also shows the implementation of a more efficient software for the calculation of the Land Contribution Ratio (f) index. Finally, the analytical model used to correct the measurements could potentially introduce an under-correction at low winds, with consequent high bias in the wind retrievals. This aspect will be more thoroughly investigated in the future.

  • Report conclusions

    This Visiting Scientist Activity, aimed at exploring solutions to refine the SeaWinds wind retrieval system. Objectives included noise regularization to mitigate land contamination of SeaWinds σ0s, software optimization, updating PenWP to retrieve wind on a 12.5 km grid, and coastal wind retrieval validation. Computational efficiency and accuracy were compared for different versions. Noise regularization significantly improved coastal sampling. Further investigations are however needed to explore increased bias of retrieved coastal wind as compared to ECMWF model. Validation against buoys and Synthetic Aperture Radar (SAR)-derived winds are suggested for further analysis.

  • Benefits for the SAF

    • This work aimed at providing Land Contribution Ratio (LCR) correction software for pencil-beam scatterometer-derived winds for the QuikSCAT mission, and to make these developments also available to other pencil-beam scatterometers.
    • The OSI SAF processors are publicly available and hence LCR correction software will aid the international Indian and Chinese partners to further collaborate and implement LCR and coastal processing in their world-wide data flows, profiting the OSI SAF users.
  • Report on this study

    Set-up of PenWP for SeaWinds-derived coastal winds

  • Authors

    Giuseppe Grieco - Istituto di Scienze Marine del Consiglio Nazionale delle Ricerche (ISMAR-CNR)

    Marcos Portabella - Barcelona Expert Centre Institut de Ciències del Mar (BEC ICM-CSIC)

    Jur Vogelzang, Anton Verhoef and Ad Stoffelen - Koninklijk Nederland Meteorologisch Instituut (KNMI)

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