Current Science

Open Access Open Access  Restricted Access Subscription Access

SCATSAT-1 Scatterometer Data Processing


Affiliations
1 Space Applications Centre, ISRO, Ahmedabad 380 015, India
2 National Remote Sensing Centre, ISRO, Hyderabad 500 625, India
 

SCATSAT-1 carries a Ku-band scatterometer with a scanning pencil beam configuration. It deploys two beams, a vertically polarized outer beam and a horizontally polarized inner beam, to cover a swath of 1800 km. The mission mainly caters to oceanographic applications and weather forecasting, with the data being extensively used for cyclogenesis predictions across the globe and specifically, the tropical region. Since the launch of SCATSAT-1 in September 2016, the satellite and payload performances as well as mission and ground segment operations have been found to be nominal and satisfactory. This article highlights various levels of operational data products as well as algorithms used for deriving radar backscatter and retrieving wind vector data from scatterometer measurements.

Keywords

Data Products, Footprint, Scatterometer, Slices, Wind Vector.
User
Notifications
Font Size

  • Misra, T. et al., Oceansat-II scatterometer: sensor performance evaluation, σ0 analyses and estimation of biases. IEEE Trans. Geosci. Remote Sensing, 2014, 52, 3310–3315.

  • Bhowmick, S. A., Kumar, R. and Kiran Kumar, A. S., Cross calibration of the OceanSAT-2 scatterometer with QuikSCAT scatterometer using natural terrestrial targets. IEEE Trans. Geosci. Remote Sensing, 2014, 52, 3393–3398.

  • Kumar, R., Chakraborty, A., Parekh, A., Sikhakolli, R., Gohil, B. S. and Kiran Kumar, A. S., Evaluation of Oceansat-2-derived Ocean surface winds using observations from global buoys and other scatterometers. IEEE Trans. Geosci. Remote Sensing, 2013, 51, 2571–2576.

  • Chakraborty, A., Deb, S. K., Shikakolli, R., Gohil, B. S. and Kumar, R., Intercomparison of OSCAT winds with numericalmodelgenerated winds. IEEE Geosci. Remote Sensing Lett., 2013, 10, 260–262.

  • Ulaby, F. T., Moore, R. K. and Fung, A. K., Microwave Remote Sensing – Active and Passive, Vols. 1 and 2, Addison-Wesley Publ. Co, Reading, Mass, USA, 1981.

  • Long, D. G. and Spencer, M., Radar backscatter measurement accuracy for a spaceborne pencil-beam wind scatterometer with transmit modulation. IEEE Trans. Geosci. Remote Sensing, 1997, 35, 102–114.

  • Fischer, R. E., Standard deviation of scatterometer measurements from space. IEEE Trans. Geosci. Electron., 1972, 10, 106–113.

  • Schroeder, L., Boggs, D. H., Dome, G., Halberstam, I. M., Jones, W. L., Pierson, W. J. and Wentz, F. J., The relationship between the wind vector and the normalized radar cross section used to derive Seasat-A satellite scatterometer winds. J. Geophys. Res., 1982, 87, 3318–3336.

  • Pierson Jr, W. J., Probabilities and statistics for backscatter estimates obtained by a scatterometer. J. Geophys. Res., 1989, 94, 9743–9759.

  • Long, D. G. and Mendel, J. M., Identifiability in wind estimation from scatterometer measurements. IEEE Trans. Geosci. Remote Sensing, 1991, 29, 268–276.

  • Wentz, F. J. and Smith, D. K., A model function for the oceannormalized radar cross-section at 14 GHz derived from NSCAT observations. J. Geophys. Res., 1999, 104(11), 499–514.

  • Gohil, B. S., Sikhakolli, R. and Gangwar, R. K., Development of geophysical model functions for Oceansat-2 scatterometer. IEEE Geosci. Remote Sensing Lett., 2013, 10, 377–380.

  • Uppala, S. M. et al., The ERA-40 re-analysis. Q. J. R. Meteorol. Soc., 2005, 131, 2961–3012.

  • Stoffelen, A. and Anderson, D., Scatterometer data interpretation: measurement space and inversion. J. Atmos. Ocean Technol., 1997, 14, 1298–1313.

  • Stoffelen, A. and Portabella, M., On Bayesian scatterometer wind inversion. IEEE Trans. Geosci. Remote Sensing, 2006, 44, 1523– 1533.

  • Gohil, B. S. and Pandey, P. C., An algorithm for retrieval of oceanic wind vectors from the simulated SASS normalized radar cross‐section measurements. J. Geophys. Res., 1985, 90, 7307–7311.

  • Gohil, B. S., Extraction of ocean surface wind field from simulated ERS-1 scatterometer data. Int. J. Remote Sensing, 1992, 13, 3311–3327.

  • Gohil, B. S., Sarkar, A. and Agarwal, V. K., A new algorithm for wind-vector retrieval from scatterometers. IEEE Geosci. Remote Sensing Lett., 2008, 5, 387–391.

  • Gohil, B. S., Sharma, P., Sikhakolli, R. and Sarkar, A., Directional stability and conservation of scattering (DiSCS) based directionalambiguity removal algorithm for improving wind-fields from scatterometer: a QuikSCAT example. IEEE Geosci. Remote Sensing Lett., 2010, 7, 592–595.

  • Stiles, B. W., Polland, B. D. and Dunbar, R. S., Direction interval retrieval with thresholded nudging: a method for improving the accuracy of QuikSCAT winds. IEEE Trans. Geosci. Remote Sensing, 2002, 40, 79–89.

  • Huddleston, J. N. and Stiles, B. W., Multidimensional histogram rain-flagging technique for sea winds on QuikSCAT. In Proceedings of International Geoscience and Remote Sensing Symposium – 2000, vol. 3, pp. 1232–1234.

  • Stiles, B. W. and Yueh, S. H., Impact of rain on spaceborne Kuband wind scatterometer data. IEEE Trans. Geosci. Remote Sensing, 2002, 40, 1973–1983.

  • Gohil, B. S., Sikhakolli, R., Gangwar, R. K. and Kiran Kumar, A. S., Oceanic rain-flagging using radar backscatter and noise measurements from Oceansat-2 scatterometer. IEEE Trans. Geosci. Remote Sensing, 2016, 54, 2050–2055.


Abstract Views: 468

PDF Views: 118




  • SCATSAT-1 Scatterometer Data Processing

Abstract Views: 468  |  PDF Views: 118

Authors

Devang Mankad
Space Applications Centre, ISRO, Ahmedabad 380 015, India
Rajesh Sikhakolli
National Remote Sensing Centre, ISRO, Hyderabad 500 625, India
Puja Kakkar
Space Applications Centre, ISRO, Ahmedabad 380 015, India
Qamer Saquib
Space Applications Centre, ISRO, Ahmedabad 380 015, India
Krishna Murari Agrawal
Space Applications Centre, ISRO, Ahmedabad 380 015, India
Suresh Gurjar
Space Applications Centre, ISRO, Ahmedabad 380 015, India
Dinesh Kumar Jain
Space Applications Centre, ISRO, Ahmedabad 380 015, India
V. M. Ramanujam
Space Applications Centre, ISRO, Ahmedabad 380 015, India
Pradeep Thapliyal
Space Applications Centre, ISRO, Ahmedabad 380 015, India

Abstract


SCATSAT-1 carries a Ku-band scatterometer with a scanning pencil beam configuration. It deploys two beams, a vertically polarized outer beam and a horizontally polarized inner beam, to cover a swath of 1800 km. The mission mainly caters to oceanographic applications and weather forecasting, with the data being extensively used for cyclogenesis predictions across the globe and specifically, the tropical region. Since the launch of SCATSAT-1 in September 2016, the satellite and payload performances as well as mission and ground segment operations have been found to be nominal and satisfactory. This article highlights various levels of operational data products as well as algorithms used for deriving radar backscatter and retrieving wind vector data from scatterometer measurements.

Keywords


Data Products, Footprint, Scatterometer, Slices, Wind Vector.

References





DOI: https://doi.org/10.18520/cs%2Fv117%2Fi6%2F950-958