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A new algorithm for sea fog/stratus detection using GMS-5 IR data

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Abstract

A new algorithm for the detection of fog/stratus over the ocean from the GMS-5 infrared (IR) channel data is presented. The new algorithm uses a clear-sky radiance composite map (CSCM) to compare the hourly observations of the IR radiance. The feasibility of the simple comparison is justified by the theoretical simulations of the fog effect on the measured radiance using a radiative transfer model. The simulation results show that the presence of fog can be detected provided the visibility is worse than 1 km and the background clear-sky radiances are accurate enough with known uncertainties. For the current study, an accurate CSCM is constructed using a modified spatial and temporal coherence method, which takes advantage of the high temporal resolution of the GMS-5 observations. The new algorithm is applied for the period of 10–12 May 1999, when heavy sea fog formed near the southwest coast of the Korean Peninsula. Comparisons of the fog/stratus index, defined as the difference between the measured and clear-sky brightness temperature, from the new algorithm to the results from other methods, such as the dual channel difference of NOAA/AVHRR and the earth albedo method, show a good agreement. The fog/stratus index also compares favorably with the ground observations of visibility and relative humidity. The general characteristics of the fog/stratus index and visibility are relatively well matched, although the relationship among the absolute values, the fog/stratus index, visibility, and relative humidity, varies with time. This variation is thought to be due to the variation of the atmospheric conditions and the characteristics of fog/stratus, which affect the derived fog/stratus index.

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References

  • Anthis, A. L., and A. P. Gracknell, 1998: Fog detection and forecast of fog dissipation using both AVHRR and METEOSAT data. 9th Sat. Met/OCEAN, p2.42B, 270–273.

  • Anderson, G. P., and coauthors, 1995: FASCODE/ MODTRAN/LOWTRAN: Past/Present/Future, 18th Ann. Rev. Conf. Atm. Transmission Models.

  • Coakley, J. A., and F. P. Bretherton, 1982: Cloud cover from high resolution scanner data: Detection and allowing for partially filled fields of view.J. Geophys. Res.,87, 4917–4932.

    Article  Google Scholar 

  • Coakley, J. A., and D. G. Baldwin, 1984: Towards the objective analysis of clouds from satellite imagery.J. Climate Appl. Meteor.,23, 1065–1099.

    Article  Google Scholar 

  • Croft, P. J., R. L. Pfost, J. M. Meldin, and G. A. Johnson, 1997: Fog forecasting for the southern region: A conceptual model approach.Weather and Forecasting,12, 535–556.

    Article  Google Scholar 

  • Ellrod, G. P., 1995: Advances in the detection and analysis of fog at night using GOES multispectral infrared imagery.Weather and Forecasting,10, 606–619.

    Article  Google Scholar 

  • Ernst, J. A., 1975: Fog and stratus “invisible” in meteorological satellite infrared (IR) imagery.Mon. Wea. Rev.,103, 1024–1026.

    Article  Google Scholar 

  • Eyre, J. R., J. L. Brownscombe, and R. J. Allam, 1984: Detection of fog at night using Advanced Very High Resolution Radiometer.Meteor. Mag.,113, 266–271.

    Google Scholar 

  • Inoue, T., 1985: On the temperature and effective emissivity determination of semi-transparent cirrus cloud by bi-spectral measurements in the 10 m window region.J. Meteor. Soc. Japan,63, 88–99.

    Google Scholar 

  • Kim, M. O., 1998: The characteristics of the sea fog around the Korean Peninsula. M. S. thesis, Chonnam National University, 64pp.

  • Lee, T. F., F. J. Turk, and K. Richardson, 1997: Stratus and fog products using GOES-8-9 3.9-m data.Weather and Forecasting,12, 664–677.

    Article  Google Scholar 

  • Masuda, K., T. Takashima, and Y. Takayama, 1988: Emissivity of pure and sea waters for the model sea surface temperature in the infrared regions.Remote Sens. Environ.,24, 313–329.

    Article  Google Scholar 

  • METRI, 1999: Study on sea fog detection using GMS-5 satellite data (II). Meteorological Research Institute of Korea, Seoul, 73pp.

    Google Scholar 

  • MSC, 1997: The GMS User’s Guide. Meteorological Satellite Center of Japan, 190pp.

  • Park, K. -A., 1996: Spatial and temporal variability of sea surface temperature and sea level anomaly in the East Sea using satellite data (NOAA/AVHRR, TOPEX). Ph. D. dissertation, Seoul National University, 294pp.

  • Roden, G. I., 1975: On the North Pacific temperature, salinity, sound velocity and density fronts and their relation to the wind and energy flux field.J. Phys. Oceanogr.,4, 168–182.

    Article  Google Scholar 

  • Roozekrans, J. N., and G. J. Prangsma, 1986: Cloud clearing algorithms without AVHRR channel 3. Summary Proceeding of Second AVHRR Users Meeting, April 1986.

  • Saunders, R. W., and K. T. Kriebel, 1988: An improved method for detecting clear sky and cloudy radiance from AVHRR data.Int. J. Remote Sens.,9, 123–150.

    Article  Google Scholar 

  • Yasuda, H., and Y. Shirakawa, 1999: Improvement of the derivation method of sea surface temperature from GMS-5 data.Meteorological Satellite Center Technical Note,37, 19–33.

    Google Scholar 

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Correspondence to Myoung-Hwan Ahn.

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Ahn, MH., Sohn, EH. & Hwang, BJ. A new algorithm for sea fog/stratus detection using GMS-5 IR data. Adv. Atmos. Sci. 20, 899–913 (2003). https://doi.org/10.1007/BF02915513

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  • DOI: https://doi.org/10.1007/BF02915513

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