Journal of Korean Society for Geospatial Information Science (대한공간정보학회지)

Korea Spatial Information Society (대한공간정보학회)
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Development of Estimation Algorithm of Near-Surface Air Temperature for Warm and Cold Seasons in Korea

온난 및 한랭시즌의 우리나라 지상기온 평가 알고리즘 개발

  • Kim, Do Yong (Department of Environmental Engineering, Mokpo National University)
  • 김도용 (목포대학교 환경공학과(기후변화연구소))
  • Received : 2015.07.28
  • Accepted : 2015.10.27
  • Published : 2015.12.31
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Abstract

Spatial and temporal information on near-surface air temperature is important for understanding global warming and climate change. In this study, the estimation algorithm of near-surface air temperature in Korea was developed by using spatial homogeneous surface information obtained from satellite remote sensing observations. Based on LST(Land Surface Temperature), NDWI(Normalized Difference Water Index) and NDVI(Normalized Difference Vegetation Index) as independent variables, the multiple regression model was proposed for the estimation of near-surface air temperature. The different regression constants and coefficients for warm and cold seasons were calculated for considering regional climate change in Korea. The near-surface air temperature values estimated from the multiple regression algorithm showed reasonable performance for both warm and cold seasons with respect to observed values (approximately $3^{\circ}C$ root mean-square error and nearly zero mean bias). Thus;the proposed algorithm using remotely sensed surface observations and the approach based on the classified warm and cold seasons may be useful for assessment of regional climate temperature in Korea.

시공간적 기온정보는 지구온난화와 기후변화의 이해에 있어서 중요한 기상요소이다. 본 연구에서는 인공위성 원격탐사로부터 획득된 공간적으로 균질한 지표면 정보를 이용하여 우리나라 지상기온 평가 알고리즘을 개발하였다. LST(Land Surface Temperature), NDWI(Normalized Difference Water Index), NDVI(Normalized Difference Vegetation Index)를 독립변수로 하는 지상기온 추정을 위한 다중회귀모형을 제안하고, 우리나라의 지역기후변화를 고려하기 위하여 온난시즌과 한랭시즌에 대한 모형의 회귀상수 및 회귀계수를 도출하였다. 개발된 기온 추정 알고리즘에 의해 산출된 온난 및 한랭시즌의 기온정보는 지상관측기온과 비교하여 우수한 상관관계를 보였고, $3^{\circ}C$ 미만의 RMSE와 거의 0에 가까운 BIAS로 매우 높은 일치성을 보였다. 따라서 인공위성 지표면 원격탐사자료를 활용하고 온난 및 한랭시즌의 구분을 적용한 기온 평가 알고리즘은 우리나라의 지역기후를 평가하는데 있어서 간략하고 유용한 수단이 될 수 있으리라 기대된다.

Keywords

References

  1. Darecki, M. and Stramski, D., 2004, An evaluation of MODIS and SeaWiFS bio-optical algorithms in the Baltic Sea, Remote Sensing of Environment, Elsevier Inc., Vol. 89, No. 3, pp. 326-350. https://doi.org/10.1016/j.rse.2003.10.012
  2. Florio, E.N., Lele, S.R., Chang, Y.C., Sterner, R., Glass, G.E., 2004, Integrating AVHRR satellite data and NOAA ground observations to predict surface air temperature: A statistical approach, International Journal of Remote Sensing, Taylor & Francis, Vol. 25, No. 15, pp. 2979-2994. https://doi.org/10.1080/01431160310001624593
  3. Han, K.-S., Viau, A.A., Kim, Y.-S., Roujean, J.-L., 2005, Statistical estimate of the hourly near-surface air humidity in eastern Canada in merging NOAA/AVHRR and GOES/IMAGER observations, International Journal of Remote Sensing, Taylor & Francis, Vol. 26, No. 21, pp. 4763-4784. https://doi.org/10.1080/01431160500177711
  4. IPCC, 2007, Climate Change 2007, The Physical Science Basis, Contribution of Working Group I to Fourth Assessment Report of the Intergovernmental Panel on Climate change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 996 pp.
  5. Kim, D.Y., Han, K.S., 2012, Temporal and Spatial Wind Information Production and Correction Algorithm Development by Land Cover Type over the Republic of Korea, Journal of the Korean Society for Geospatial Information System, Korean Society for Geospatial Information System, Vol. 20, No, 3, pp. 19-27.
  6. Kim, D.Y., Han, K.S., 2013, Remotely sensed retrieval of midday air temperature considering atmospheric and surface moisture conditions, International Journal of Remote Sensing, Taylor & Francis, Vol. 34, No. 1, pp. 247-263. https://doi.org/10.1080/01431161.2012.712235
  7. KMA, Korea Meteorological Administration, http://www.kma.go.kr/
  8. Lakshmi, V., Czajkowski, K., Dubayah, R., Susskind, J., 2001, Land surface air temperature mapping using TOVS and AVHRR. International Journal of Remote Sensing, Taylor & Francis, Vol. 22, No. 4, pp. 643-662. https://doi.org/10.1080/01431160050505900
  9. Mostovoy, G.V., King, R.L., Reddy, K.R., Kakani, V.G., Filippova, M.G., 2006, Statistical estimation of daily maximum and minimum air temperatures from MODIS LST data over the state of Mississippi, GIScience and Remote Sensing, V. H. Winston & Son, Inc., Vol. 43, No. 1, pp. 78-110. https://doi.org/10.2747/1548-1603.43.1.78
  10. Nieto, H., Sandholt, I., Aguado, I., Chuvieco, E., Stisen, S., 2011, Air temperature estimation with MSG-SEVIRI data: Calibration and validation of the TVX algorithm for the Iberian Peninsula, Remote Sensing of Environment, Elsevier Inc., Vol. 115, No. 1, pp. 107-116. https://doi.org/10.1016/j.rse.2010.08.010
  11. Stisen, S., Sandholt, I., Norgaard, A., Fensholt, R., Eklundh, L., 2007, Estimation of diurnal air temperature using MSG SEVIRI data in West Africa, Remote Sensing of Environment, Elsevier Inc., Vol. 110, No. 2, pp. 262-274. https://doi.org/10.1016/j.rse.2007.02.025
  12. Vancutsem, C., Ceccato, P., Dinku, T., Connor, S.J., 2010, Evaluation of MODIS land surface temperature data to estimate air temperature in different ecosystems over Africa, Remote Sensing of Environment, Elsevier Inc., Vol. 114, No. 2, pp. 449-465. https://doi.org/10.1016/j.rse.2009.10.002
  13. Yan, H., Zhang, J., Hou, Y., HE, Y., 2009, Estimation of air temperature from MODIS data in east China, International Journal of Remote Sensing, Taylor & Francis, Vol. 30, No. 23, pp. 6261-6275. https://doi.org/10.1080/01431160902842375
  14. Yu, Y., Tarpley, D., Privette, J.L., Goldberg, M.D., Raja, M.K.R.V., Vinnikov, K.Y. and Xu, H., 2009, Developing algorithm for operational GOES-R land surface temperature product, IEEE Transactions on Geoscience and Remote Sensing, IEEE GRSS, Vol. 47, No. 3, pp. 936-951. https://doi.org/10.1109/TGRS.2008.2006180
  15. Zhao, T.X.-P., Stowe, L.L., Smirnov, A., Crosby, D., Sapper, J. and Mcclain, C.R., 2002, Development of a global validation package for satellite oceanic aerosol optical thickness retrieval based on AERONET observation and its application to NOAA/NESDIS operational aerosol retrievals, Journal of the Atmospheric Sciences, AMS, Vol. 59, No. 3, pp. 294-312. https://doi.org/10.1175/1520-0469(2002)059<0294:DOAGVP>2.0.CO;2