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Impact of Saharan Dust on Ocean Surface Wind Speed Derived by Microwave Satellite Sensors

  • Thomas Ohde
Article
  • 128 Downloads

Abstract

In the present paper ground truth and remotely sensed datasets were used for the investigation and quantification of the impact of Saharan dust on microwave propagation, the verification of theoretical results, and the validation of wind speeds determined by satellite microwave sensors. The influence of atmospheric dust was verified in two different study areas by investigations of single dust storms, wind statistics, wind speed scatter plots divided by the strength of Saharan dust storms, and wind speed differences in dependence of microwave frequencies and dust component of aerosol optical depth. An increase of the deviations of satellite wind speeds to ground truth wind speeds with higher microwave frequencies, with stronger dust storms, and with higher amount of coarse dust aerosols in coastal regions was obtained. Strong Saharan dust storms in coastal areas caused mean relative errors in the determination of wind speed by satellite microwave sensors of 16.3% at 10.7 GHz and of 20.3% at 37 GHz. The mean relative errors were smaller in the open sea area with 3.7% at 10.7 GHz and with 11.9% at 37 GHz.

Keywords

Ocean surface wind speed Saharan dust METAR QuikSCAT TMI MODIS MERIS 

Notes

Acknowledgements

The author thanks the Leibniz Institute for Baltic Sea Research for support of this investigation. METAR - Data are provided by NCAR/EOL under sponsorship of the National Science Foundation (http://data.eol.ucar.edu).

QuikSCAT and TMI data are produced by Remote Sensing Systems and sponsored by the NASA Ocean Vector Winds Science Team as well as by the NASA Earth Science REASON DISCOVER Project. The data are available at http://www.remss.com.

The MODIS aerosol data were provided by NASA’s Giovanni, an online data visualization and analysis tool maintained by the Goddard Earth Sciences (GES) Data and Information Services Center (DISC), a part of the NASA Earth-Sun System Division (http://giovanni.gsfc.nasa.gov).

The MODIS RGB images were taken from MODIS Rapid Response Project (http://rapidfire.sci.gsfc.nasa.gov).

This research was based on MERIS RGB images provided by ESA (European Space Agency). MERIS data are available from MERCI system (http://merci-srv.eo.esa.int).

Many thanks for helpful comments on the manuscript to the anonymous reviewers.

References

  1. 1.
    Wu, C., Graf, J., Freilich, M., Long, D. G., Spencer, M., Tsai, W., Lisman, D., Winn, C., 1994. The SeaWinds scatterometer instrument, in Proceedings International Geoscience and Remote Sensing Symposium, Pasadena, CA, Aug. 8–12, 1994, M. W. Spencer, C.Google Scholar
  2. 2.
    Kummerow C., Barnes, W., Kozu, T., Shiue, J., Simpson, J., 1998. The Tropical Rainfall Measuring Mission (TRMM) sensor package. Journal of Atmospheric and Oceanic Technology, 15, 809–817.CrossRefGoogle Scholar
  3. 3.
    Wentz, F. J., 1997. A well-calibrated ocean algorithm for special sensor microwave/imager. Journal Geophysical Research, 102, 8703–8718.CrossRefGoogle Scholar
  4. 4.
    Wentz, F. J., 1998. Algorithm theoretical basis document: AMSR Ocean Algorithm. Tech. Rep. 110398, Remote Sensing Systems, Santa Rosa, CA, 65 pp. (Available online at http://www.remss.com.)
  5. 5.
    Wentz, F. J., Gentemann, C. L., Smith, D., 2000. Satellite measurements of sea surface temperature through clouds. Science 288 (5467), 847–850.CrossRefGoogle Scholar
  6. 6.
    Gentemann, C. L., Wentz, F. J., Mears, C. A., Smith, D. K., 2004. In situ validation of Tropical Rainfall Measuring Mission microwave sea surface temperature. Journal of Geography Research 109, C04021 pp., doi: 10.1029/2003JC002092.
  7. 7.
    Portabella, M., Stoffelen, A., 2002. A comparison of KNMI quality control and JPL rain flag for SeaWinds. Canadian Journal of Remote Sensing 28, 424–430.Google Scholar
  8. 8.
    Rapp, A. D., Kummerow, C., Elsaesser, C., 2008. On the effects of warm rain clouds in the tropics. In: Third TRMM NASA/JAXA International Science Conference.Google Scholar
  9. 9.
    Owen, M. P., Long, D. G., 2008. Progress Toward Validation of Quikscat Ultra-High-Resolution Rain Rates using TRMM PR. Geoscience and Remote Sensing Symposium, IGARSS 2008. IEEE International Volume 4, Issue, 7–11 July 2008 Page(s):IV-299–IV-302, doi: 10.1109/IGARSS.2008.4779717.
  10. 10.
    Marzano, F. S., Mugnai, A., Turk, F. J., 2002. Precipitation Retrieval From Spaceborne Microwave Radiometers and Combined Sensors, in Remote Sensing of Atmosphere and Ocean from Space: Models, Instruments and Techniques, F.S. Marzano and G. Visconti (eds.), Kluwer Academic Publishers, 107–126.Google Scholar
  11. 11.
    Wentz, F. J., Spencer, R. W., 1998: SSM/I rain retrievals within a unified all-weather ocean algorithm. Journal Atmospheric Science, 55, 1613–1627.CrossRefGoogle Scholar
  12. 12.
    Mears, C. A., Smith, D. K., Wentz, F. J., 2001. Comparison of Special Sensor Microwave Imager and buoy-measured wind speeds from 1987 to 1997. Journal Geophysical Research, 106, 11719–11729.CrossRefGoogle Scholar
  13. 13.
    Kaufman, Y. J., Koren, I, Remer, L. A., Tanré, D., Ginoux, P., Fan, S., 2005. Dust transport and deposition observed from the Terra-Moderate Resolution Imaging Spectroradiometer (MODIS) spacecraft over the Atlantic Ocean. Journal Geophysical Research 110, D10S12 pp., doi: 10.1029/2003JD004436.
  14. 14.
    Comparetto, G., 1993. The impact of dust and foliage on signal attenuation in the millimeter wave regime, Journal Space Communication 11, 13–20.Google Scholar
  15. 15.
    Altshuler, E. E., 1983. The Effects of a Low-Altitude Nuclear Burst on Millimeter Wave Propagation, Rome Air Development Center, Report, RADC-TR-83-286, 1–19.Google Scholar
  16. 16.
    Ghobrial, S. I., 1980. Effect of hygroscopic water on dielectric constant of dust at X-band, Electron Letters 16, 393–394.CrossRefGoogle Scholar
  17. 17.
    Ansari, A. J., Evans, B. G., 1982. Microwave propagation in sand and dust storms, IEE Proceedings, Part F - Communications, Radar and Signal Processing 129, 315–322.CrossRefGoogle Scholar
  18. 18.
    Yan, Y., 2001. Multiple scattering solution of millimeter wave propagation in strong sandstorms, International Journal of Infrared and Millimeter Waves 22(2), 361–371.CrossRefGoogle Scholar
  19. 19.
    Prospero, J. M., Carlson, T. N., 1972. Vertical and areal distribution of Saharan dust over the Western Equatorial North Atlantic Ocean. Journal Geophysical Research 77, 5255–5265.CrossRefGoogle Scholar
  20. 20.
    Kalu, A. E., 1979. The African dust plume: Its characteristics and propagation across West Africa in winter, SCOPE, 14, 95–118.Google Scholar
  21. 21.
    Chiapello, I., Moulin, C., 2002. TOMS and METEOSAT satellite records of the variability of Saharan dust transport over the Atlantic during the last two decades (1979–1997). Geophysical Research Letter 29(8), 1176 pp, doi: 10.1029/2001GL013767.
  22. 22.
    Baker, A. R., Kelly, S. D., Biswas, K. F., Witt, M., Jickells, T. D., 2003. Atmospheric deposition of nutrients to the Atlantic Ocean. Geophysical Research Letter 30(24), 2296 pp., doi: 10.1029/2003GL018518.
  23. 23.
    Jickells, T. D., An, Z. S., Anderson, K. K., Baker, A. R., Bergametti, G., Brooks, N., Cao, J. J., Boyd, P. W., Duce, R. A., Hunter, K. A., Kawahata, H., Kubilay, N., La Roche, J., Liss, P. S., Mahowald, N., Prospero, J. M., Ridgwell, A. J., Tegen, I., Torres, R., 2005. Global Iron Connections between desert dust, ocean biogeochemistry and climate. Science 308, 67–71.CrossRefGoogle Scholar
  24. 24.
    Gao, Y., Kaufman, Y. J., Tanré, D., Kolber, D., Falkowski, P. G., 2001. Seasonal distributions of aeolian iron fluxes to the global ocean. Geophysical Research Letter 28, 29–32.CrossRefGoogle Scholar
  25. 25.
    Prospero, J. M., Lamb, P. J., 2003. African droughts and dust transport to the 638 Caribbean: Climate change implications. Science, 302, 1024–1027.CrossRefGoogle Scholar
  26. 26.
    Schepanski, K., Tegen, I., Macke, A., 2009. Saharan dust transport and deposition towards the tropical northern Atlantic, Atmos. Chem. Phys., 9, 1173–1189.CrossRefGoogle Scholar
  27. 27.
    Pérez-Marrero, J., Llinás, O., Maroto, L., Rueda, M. J., Cianca, A., 2002. Saharan dust storms over the Canary Islands during winter 1998 as depicted from the advance very high-resolution radiometer, Deep-Sea Research II 49, 3465–3479.CrossRefGoogle Scholar
  28. 28.
    Bourassa, M. A., Legler, D., O’Brian, J. J., Smith, S. R., 2003. SeaWinds validation with research vessels. Journal of Geophysical Research 108(C2), 3019 pp.Google Scholar
  29. 29.
    Ebuchi, N., Graber, H. C., Caruso, M. J., 2002. Evaluation of wind vectors observed by QuikSCAT/SeaWinds using ocean buoy data. American Meteorological Society 19, 2049–2062.Google Scholar
  30. 30.
    Chelton, D. B., Freilich, M. H., 2005. Scatterometer-based assessment of 10 m wind analysis from the operational ECMWF and NCEP numerical weather prediction models. Monthly Weather Review 133, 409–429.CrossRefGoogle Scholar
  31. 31.
    Hoffman, R. N., Leidner, S. M., 2005. An introduction to the near-real-time QuikSCAT data. Weather and Forecasting 2005, 20, 476–493.CrossRefGoogle Scholar
  32. 32.
    Sharma, N., D’Sa, E., 2008. Assessment and Analysis of QuikSCAT Vector Wind Products for the Gulf of Mexico: A Long-Term and Hurricane Analysis, Sensors 2008, 8, 1927–1949.Google Scholar
  33. 33.
    Li, C. C., Liu, G. R., 2006. An Empirical Study of Surface Wind Retrievals using the TMI over the South China Sea in the Summer Monsoon Season. TAO 17(2), 447–459.Google Scholar
  34. 34.
    Senan, R., Anith, D. S., Sengupta, D., 2001. Validation of SST and wind speed from TRMM using north Indian Ocean moored buoy observations. Indian Institute of Science Tech. Memo. CAOS Rep. 2001 ASl, 29 pp.Google Scholar
  35. 35.
    Jones, T. A., Christopher, S. A., 2007. MODIS derived fine mode fraction characteristics of marine, dust, and anthropogenic aerosols over the ocean, constrained by GOCART, MOPITT, and TOMS, Journal Geophysical Research, 112, D22204 pp., doi: 10.1029/2007JD008974.
  36. 36.
    Tanré, D., Kaufman, Y. J., Herman, M., Mattoo, S., 1997. Remote sensing of aerosol over oceans from EOS-MODIS, Journal Geophysical Research, 102, 16,971–16,988.Google Scholar
  37. 37.
    Tanré, D., Herman, M., Kaufman, Y. J., 1996. Information on aerosol size distribution contained in solar reflected radiances, Journal Geophysical Research, 101, 19,043–19,060.Google Scholar
  38. 38.
    Remer, L. A., Tanré, D., Kaufman, Y. J., Ichoku, C., Mattoo, S., Levy, R., Chu, D. A., Holben, B., Dubovik, O., Smirnov, A., Martins, J. V., Li, R. R., Ahmad, Z., 2002. Validation of MODIS aerosol retrieval over ocean. Geophysical Research Letters 29(12), 8008 pp.Google Scholar
  39. 39.
    Parekh, A., Sharma, R., Sarkar, A., 2007. A Comparative Assessment of Surface Wind Speed and Sea Surface Temperature over the Indian Ocean by TMI, MSMR, and ERA-40. Journal of Atmospheric and Oceanic Technology 24(6), 1131–1142CrossRefGoogle Scholar
  40. 40.
    Prandtl, L., 1904. Über Flussigkeitsbewegung bei sehr kleiner Reibung. Verhandlg. III Int. Math. Kong. (Heidelberg: Teubner), pp 484–491; Also available in translation as: Motion of fluids with very little viscosity. NACA TM 452 (March 1928).Google Scholar
  41. 41.
    Haddad, S., Salman, M. J. H., Jha, R. K., 1983. Effects of Dust/Sandstorms on Some Aspects of Microwave Propagation, Proc. URSI Commission F Symposium, Louvain-la-Neuve: ESA publication 194, 153–161.Google Scholar
  42. 42.
    He, Q. S., Zhou, Y. H., Zheng, X. J., 2006. Attenuation of electromagnetic wave propagation in sandstorms incorporating charged sand particles, Science in China: Series G Physics, Mechanics & Astronomy 49(1), 77–87. doi: 10.1140/epje/i2004-10138-5.MATHCrossRefGoogle Scholar
  43. 43.
    Jankowiak, I., Tanré, D., 1992. Satellite climatology of Saharan dust outbreaks. Journal of Climate 5, 646–656.Google Scholar
  44. 44.
    Karyampudi, M. V., Palm, S. P., Reagen, J. A., Hui Fang, William, B., Grant, W. B., Hoff, R. M., Moulin, C., Pierce, H. F., Torres, O., Browell, E. V., Melfi, H. S., 1999. Validation of the Saharan dust plume conceptual model using Lidar, METEOSAT, and ECMWF data. Bulletin of the American Meteorological Society 80, 1045–1076.CrossRefGoogle Scholar
  45. 45.
    Zender, C. S., Newman, D., 2003. Spatial heterogeneity in aeolian erodibility: Uniform, topographic, geomorphic, and hydrologic hypotheses. Journal Geophysical Research, 108, 4543 pp., doi: 10.1029/2002JD003039.
  46. 46.
    Mahowald, N. M., Baker, A. R., Bergametti, G., Brooks, N., Duce, R. A., Jickells, T., Kubilay, N., Prospero, J. M., Tegen, I., 2005. Atmospheric global dust cycle and iron inputs to the ocean. Global Biogeochemical Cycles, 19, GB4025 pp., doi: 10.1029/2004GB002402.

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Leibniz Institute for Baltic Sea ResearchWarnemündeGermany

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