Refine your search
Collections
Co-Authors
Journals
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Thapliyal, Pradeep
- Geostationary Satellite-Based Observations for Ocean Applications
Abstract Views :181 |
PDF Views:76
Authors
Neeraj Agarwal
1,
Rashmi Sharma
1,
Pradeep Thapliyal
1,
Rishi Gangwar
1,
Prateek Kumar
1,
Raj Kumar
1
Affiliations
1 Earth, Ocean, Atmosphere and Planetary Sciences Area, Space Applications Centre, Indian Space Research Organisation, Ahmedabad 380 015, IN
1 Earth, Ocean, Atmosphere and Planetary Sciences Area, Space Applications Centre, Indian Space Research Organisation, Ahmedabad 380 015, IN
Source
Current Science, Vol 117, No 3 (2019), Pagination: 506-515Abstract
The study presents assessment and potential oceanographic applications of sea-surface temperature (SST), ocean net shortwave radiation (SWR) and chlorophyll concentration (CC) observations obtained from various geostationary platforms. SST and SWR from imager on-board Indian National Satellite (INSAT- 3D) and CC from Global Ocean Color Imager (GOCI) on-board communication ocean and meteorological satellite (COMS) have been used in the analysis. Relative advantages of high temporal resolution obtained from the geostationary platform compared to polar orbiting platforms are demonstrated. Comparison of INSAT-3D SST with observations gives a correlation of 0.85 and RMSE of 0.81 K. These platforms definitely provide a highly reliable source of continuous observations, which is useful in monitoring dynamic oceanic features such as thermal fronts, chlorophyll blooms, air–sea exchange fluxes, etc. on diurnal to daily timescales.Keywords
Chlorophyll Concentration, Geostationary Satellites, INSAT-3D, Sea-surface Temperature, Shortwave Radiation.Full Text
References
- CGMS-46, Report of the 46th Plenary Session of the Coordination Group for Meteorological Satellites, CGMS-46, Bengaluru, 3–8 June 2018.
- Murakami, H., Ocean color estimation by Himawari-8/AHI, 2016; doi:10.1117/12.2225422.
- Kurihara, Y., Murakami, H. and Kachi, M., Sea surface temperature from the new Japanese geostationary meteorological Himawari8 satellite. Geosphys. Res. Lett., 2015; doi:10.1002/2015 GL067159.
- Nigam, R., Bhattacharya, B. K., Gunjal, K. R., Padmanabhan, N., and Patel, N. K., Formulation of time series vegetation index from Indian geostationary satellite and comparison with global product. J. Indian Soc. Remote Sensing, 2011, 40(1), 1–9.
- Temimi, M., Romanov, P., Ghedira, H., Khanbilvardi, R. and Smith, K., Sea-ice monitoring over the Caspian Sea using geostationary satellite data. Int. J. Remote Sensing, 2011, 32(6), 1575– 1593.
- Legeckis, R. and LeBorgne, P., EUMETSAT geostationary satellite monitors the sea surface temperatures of the Atlantic and Indian Oceans since 2004. Environ. Res. Eng. Manage., 2009, 3(49), 4–9.
- Clayson, C. A. and Weitlich, D., Variability of tropical diurnal sea surface temperature. J. Climate, 2007; https://doi.org/10.1175/JCLI3999.1.
- Wang, M., Son, S., Jiang, L. and Shi, W., Observations of ocean diurnal variations from the Korean geostationary ocean color imager (GOCI). Proc. SPIE 9111, Ocean Sensing and Monitoring VI, 911102, 2014; doi:10.1117/12.2053476.
- Qi, L., Hu, C., Visser, P. M. and Ma, R., Diurnal changes of cyanobacteria blooms in Taihu Lake as derived from GOCI observations. Limnol. Oceanogr., 2018; doi:10.1002/lno.10802.
- Lou, X. and Chuanmin, H., Diurnal changes of a harmful algal bloom in the East China Sea: observations from GOCI. Remote Sensing Environ., 2014, 140, 562–572; https://doi.org/10.1016/j.rse.2013.09.031.
- Park, J.-E., Park, K.-A., Ullman, D. S., Cornillon, P. C. and Park, Young-Je, Observation of diurnal variations in mesoscale eddy sea-surface currents using GOCI data. Remote Sensing Lett., 2016; https://doi.org/10.1080/2150704X.2016.1219423,1131-1140.
- Lukas, R., Observations of air–sea interaction in the western Pacific warm pool during WEPOCS. In Paper presented at the Western Pacific International Meeting and Workshop for TOGA COARE, Institut francais de Recherche scientifique pour le Developpement en Cooperation (ORSTOM), NOUMEA, New Caledonia, 1989.
- Shinoda, T., Hendon, H. H. and Glick, J., Intraseasonal variability of surface fluxes and sea surface temperature in the tropical western Pacific and Indian Oceans. J. Climate, 1998, 11, 1685–1702.
- Sengupta, D., Goswami, B. N. and Senan, R., Coherent intraseasonal oscillations of ocean and atmosphere during the Asian summer monsoon. Geophys. Res. Lett., 2001, 28, 4127–4130.
- Shahi, N. R., Thapliyal, P. K., Sharma, R., Pal, P. K. and Sarkar, A., Estimation of net surface shortwave radiation over the tropical Indian Ocean using geostationary satellite observations: algorithm and validation. J. Geophys. Res., 2011, 116, C09031; doi:10.1029/ 2011JC007105.
- Le Traon, P.-Y. et al., Use of satellite observations for operational oceanography: recent achievements and future prospects. J. Operational Oceanogr., 2015, 8(s12–s27); doi:10.1080/1755876X.2015.1022050.
- Minnett, P. J., Zhu, X., Hendee, J., Manfrino, C. and Berkelmans, R., Diurnal heating of shallow water – implications for satellite remote sensing of sea-surface temperature and monitoring coastal environments. In IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012, Munich, Germany, 22–27 July 2012.
- Stuart‐Menteth, A. C., Robinson, I. S. and Challenor, P. G., A global study of diurnal warming using satellite‐derived sea surface temperature. J. Geophys. Res. (Oceans), 2003, 108(C5), 3155; doi:10.1029/2002JC001534.
- Mathur, A., Srinivasan, I., Gohil, B. S., Sarkar, A. and Agarwal, V. K., Development of sea surface temperature retrieval algorithm for INSAT-3D. In Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions, International Society for Optics and Photonics, Goa, India, December 2006, vol. 6404, p. 64040E.
- Martin, M. et al., Group for High Resolution Sea Surface temperature (GHRSST) analysis fields inter-comparisons. Part 1: a GHRSST multi-product ensemble (GMPE). Deep Sea Res. II, 2012, 77–80, 21–30; doi.org/10.1016/j.dsr2.2012.04.013.
- Schmetz, J. and Liu, Q., Outgoing longwave radiation and its diurnal variation at regional scales derived from Meteosat. J. Geophys. Res., 1988, 93(11), 192–204.
- Venkatesan, R., Lix, J. K., Phanindra Reddy, A., Arul Muthiah, M. and Atmanand, M. A. Two decades of operating the Indian moored buoy network: significance and impact. J. Oper. Oceanogr., 2016, 9(1), 45–54.
- Shukla, M. V., Thapliyal, P. K., Bisht, J. H., Mankad, K. N., Pal, P. K. and Navalgund, R. R., Intersatellite calibration of Kalpana thermal infrared channel using AIRS hyperspectral observations. IEEE Geosci. Remote Sensing Lett., 2012, 9(4), 687–689; doi:10.1109/LGRS.2011.2178813.
- Casey, K. and Cornillon, P., A comparison of satellite and in situ– based sea surface temperature climatologies. J. Climate, 1999, 12(6), 1848–1863.
- Marra, J., Houghton, R. and Garside, C., Phytoplankton growth at the shelf-break front in the middle Atlantic bight. J. Mar. Res., 1990, 48(4), 851–868; doi:https://doi.org/10.1357/002224090784988665.
- Weller, R. A. and Anderson, S. P., Surface meteorology and air– sea fluxes in the western equatorial Pacific Warm Pool during the TOGA Coupled Ocean–Atmosphere Response Experiment. J. Climate, 1996, 9, 1959–1990; doi:10.1175/1520-0442(1996)009< 1959:SMAASF>2.0.CO;2.
- SCATSAT-1 Scatterometer Data Processing
Abstract Views :282 |
PDF Views:72
Authors
Devang Mankad
1,
Rajesh Sikhakolli
2,
Puja Kakkar
1,
Qamer Saquib
1,
Krishna Murari Agrawal
1,
Suresh Gurjar
1,
Dinesh Kumar Jain
1,
V. M. Ramanujam
1,
Pradeep Thapliyal
1
Affiliations
1 Space Applications Centre, ISRO, Ahmedabad 380 015, IN
2 National Remote Sensing Centre, ISRO, Hyderabad 500 625, IN
1 Space Applications Centre, ISRO, Ahmedabad 380 015, IN
2 National Remote Sensing Centre, ISRO, Hyderabad 500 625, IN
Source
Current Science, Vol 117, No 6 (2019), Pagination: 950-958Abstract
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.Full Text
References
- 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.