QuikSCAT normalized radar cross section noise characterization for coastal wind field retrieval
In the context of the OSI SAF Visiting Scientist Program, Giuseppe Grieco from the Instituto di Scienze Marine (ISMAR-CNR) in Napoli, worked on the estimation of the QuikSCAT slice Normalized Radar Cross Section (NRCS) noise. This work took place in 2021 and was supervised by Marcos Portabella (ICM-CSIC) and Ad Stoffelen (KNMI).
Objectives and framework of the study
One of the main outcomes of the recent OSI SAF Visiting Science Activity VSA 20 01 shows that the QuikSCAT slice NRCSs are very noisy, especially along the coastline. An accurate estimation of the NRCS noise is essential for accurate wind field retrievals. This study aims to thoroughly characterize the QuikSCAT slice NRCS noise and compare it with the noise information provided in the QuikSCAT full resolution Level 1B (L1B) files.
The large amount of pencil-beam scatterometers from NASA’s QuikScat to the Indian OSCAT and the Chinese scatterometers on HY make coastal winds production from this type of scatterometer particularly interesting for the OSI SAF users for both near real time (NRT) and climate applications.
The slice NRCS noise, called Kp, is estimated using its common definition, and is then compared to the values provided in the L1B files, which are estimated from relevant instrument parameters. Some sensitivity analysis is carried out in order to verify the dependency on the wind regime, the dependency on the kind of surface (sea or any other kind), the dependency on the slice position with respect to (w.r.t.) the full footprint (egg) centroid, and on the view angle (aft or fore), the presence of any slice biases and their dependency on the acquisition azimuth angle.
Figure 1: Blue (red) circles: median of the Kp values (in percentage) provided in the file with orbit number 40651 vs the slice index for every kind of surface (marked with subscript A) (sea, marked with subscript S)) and for each of the 4 flavours pol-view, namely H-Pol Aft (HHA), H-Pol Fore (HHF), V-Pol Aft (VVA) and V-Pol Fore (VVF). Blue (red) crosses: estimated values of Kp for every kind of surface (sea). The number in blue (red) by the flavour label represents the total number of samples for every kind of surface (sea). This plot refers to a σ0 level corresponding to a wind speed of approximately 5 m/s .
The comparison shows that:
- the values provided in the files are significantly different from those estimated, especially for what concerns the outer slices of the QuikSCAT footprint. In particular, the noise of the closest slices w.r.t. the antenna appears to be underestimated, while it appears to be lower for the farthest ones;
- due to the lower signal, H-Pol acquisitions are generally noisier than V-Pol ones, while for the same backscatter value, the noise properties are very similar; • Kp decreases w.r.t. the wind speed and no differences are found w.r.t. the view, in line with the expectations;
- Kp over sea is generally lower w.r.t. any other kind of surfaces;
- the NRCS biases may reach 0.8 dB for H-Pol measurements and 0.3 dB for V-Pol ones, in line with the general GMF sensitivity as a function of incidence angle. Since this sensitivity is quasi-linear at any wind speed or direction, it suggests that slice incidence angles should be weighted in the same way as the contributing backscatter values in each view.
Benefits for the SAF
- NRCS noise characterization is essential for accurate wind field retrievals. This aspect, together with the implementation of a Land Contribution Ratio (LCR) based NRCS correction scheme is fundamental to improve the coastal sampling of scatterometer derived winds and satisfy the demand for coastal winds by OSI SAF users.
- The large amount of pencil-beam scatterometers from NASA’s QuikScat to the Indian OSCAT and the Chinese scatterometers on HY make coastal winds production from this type of scatterometer particularly interesting for the OSI SAF users for both near real time (NRT) and climate applications.
Noise characterization is essential for accurate wind field retrievals.
Report on this study
G. Grieco from Institute of Marine Sciences (ISMAR-CNR)
M. Portabella from Barcelona Expert Center (BEC ICM-CSIC)
J. Vogelzang, A. Verhoef, A. Stoffelen from Koninklijk Nederlands Meteorologisch Instituut (KNMI)