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시공간평균 기준기후에 기인한 농업기상특보의 불확실성

Uncertainty of Agrometeorological Advisories Caused by the Spatiotemporally Averaged Climate References

  • Kim, Dae-jun (National Center for Agro-Meteorology, Seoul National University) ;
  • Kim, Jin-Hee (National Center for Agro-Meteorology, Seoul National University) ;
  • Kim, Soo-Ock (National Center for Agro-Meteorology, Seoul National University)
  • 투고 : 2017.08.31
  • 심사 : 2017.09.18
  • 발행 : 2017.09.30

초록

고해상도 전자기후도 기반의 농가맞춤 조기경보서비스를 구현하기 위해서는 실측기상자료가 없는 곳의 평년기후를 복원해야 한다. 일별 기상자료 복원에 드는 시간과 노력을 절약하기 위해 간이산출방식이 널리 사용되어 왔는데, 본 연구에서는 이렇게 간소화된 방식을 통해 제작된 평년 기후값이 어느 정도의 오차를 수반하는지를 분석하기 위하여, 평년기간(1981-2010)에 대한 일별 기상 값을 모두 복원하고, 이를 '시간적', '공간적' 간소화를 진행한 평년기후값과의 비교를 통해 기상위험의 예측 결과의 차이에 대해 분석하였다. 이를 위해 여러 재해관련 지수 중에서 많은 종류의 기상자료를 필요로 하는 농업가뭄지수를 이용하였으며, 섬진강 유역 일대의 10개 시군을 선정하였다. '시간'규모를 간소화한 평년 값은 30개년(1981-2010)에 대해 일별로 평균한 값을 이용하여 고해상도 분포를 제작하였으며, '공간'규모를 간소화 평년 값은 실험지역에 대하여 집수역 단위로 제작한 평년 값을 이용하였다. 먼저 '잔여수분지수'의 경우 '시간'규모 간소화 평년 값의 경우 과대 추정되었으며, '공간'규모 간소화 평년 값의 경우 과소 추정되는 경향을 나타냈다. 또한 2017년 1월부터 7월까지의 가뭄지수를 제작한 결과, 평년 자료 별로 가뭄의 정도를 모의한 결과에 차이가 있었으며, 지역적인 편차 또한 확인 되었다. 본 연구를 통하여 '간소화'된 제작방식을 통한 평년 기후 값이, 이를 이용해 재해위험을 산출한 결과에 영향을 미칠 수 있음을 확인하였다.

Agrometeorological advisories for farms and orchards are issued when daily weather exceeds a predefined range of the local reference climate, which is a long-term average of daily weather for the location. The reference climate at local scales is prepared by various simplification methods, resulting in uncertainty in the agrometeorological advisories. We restored daily weather data for the 1981-2010 period and analyzed the differences in prediction results of weather risk by comparing with the temporal and spatial simplified normal climate values. For this purpose, we selected the agricultural drought index (ADI) among various disaster related indices because ADI requires many kinds of weather data to calculate it. Ten rural counties within the Seomjin River Basin were selected for this study. The normal value of 'temporal simplification' was calculated by using the daily average value for 30 years (1981-2010). The normal value of 'spatial simplification' is the zonal average of the temporally simplified normal values falling within a standard watershed. For residual moisture index, temporal simplification normal values were overestimated, whereas spatial simplification normal values were underestimated in comparison with non-simplified normal values. The ADI's calculated from January to July 2017 showed a significant deviation in terms of the extent of drought depending on the normal values used. Through this study, we confirmed that the result of weather risk calculation using normal climatic values from 'simplified' methods can affect reliability of the agrometeorological advisories.

키워드

참고문헌

  1. Allen, R. G., L. S. Peretira, D. Raes, and M. Smith, 1998: Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements. FAO irrigation and drainage paper 56, UN-FAO, Rome, Italy.
  2. Byun, H. R., and D. A. Wilhite, 1999: Objective quantification of drought severity and duration. Journal of Climate 12, 2747-2756. https://doi.org/10.1175/1520-0442(1999)012<2747:OQODSA>2.0.CO;2
  3. Chung, U., H.-C. Seo, J. I. Yun, S.-J. Jeon, K. H. Moon, H.-H. Seo, and Y. S. Kwon, 2009: Extrapolation of daily maximum temperature in a mountainous terrain. Asia-Pacific Journal of Atmospheric Science 45(4), 473-482.
  4. Chung, U., H. H. Seo, K. H. Hwang, B. S. Hwang, J. Choi, J. T. Lee, and J. I. Yun, 2006: Minimum temperature mapping over complex terrain by estimating cold air accumulation potential. Agricultural and Forest Meteorology 137(1-2), 15-24. https://doi.org/10.1016/j.agrformet.2005.12.011
  5. Chung, U., K. Yun, K.-S. Cho, J. H. Yi, and J. I. Yun, 2009: The PRISM-based rainfall mapping at an enhanced grid cell resolution in complex terrain. Korean Journal of Agricultural and Forest Meteorology 11(2), 72-78. (in Korean with English abstract) https://doi.org/10.5532/KJAFM.2009.11.2.072
  6. Kim, D.-J., and J. I. Yun, 2013: Improving usage of the Korea Meteorological Administration's digital forecasts in agriculture: 2. refining the distribution of precipitation amount. Korean Journal of Agricultural and Forest Meteorology 15(3), 171-177. (in Korean with English abstract) DOI: 10.5532/KJAFM.2013.15.3.171
  7. Kim, D. J., S.-O. Kim, J.-H. Kim, K-M. Shim, and J. I. Yun, 2015: A drought index designed for field-scale water management. Asia-Pacific Journal of Atmospheric Sciences 51(3), 197-203. https://doi.org/10.1007/s13143-015-0070-9
  8. Kim, S. J., 2006: Agricultural disasters. Journal of the Korean Society of Hazard Mitigation 6(4), 87-102. (in Korean)
  9. Kim, S.-O., and J. I. Yun, 2011: A quantification method for the cold pool effect on nocturnal temperature in a closed catchment. Korean Journal of Agricultural and Forest Meteorology 13(4), 176-184. (in Korean with English abstract) DOI: 10.5532/KJAFM.2011.13.4.176
  10. Kim, S.-O., J.-H. Kim, D.-J. Kim, and J. I. Yun, 2012: Wind effect on the distribution of daily minimum temperature across a cold pooling catchment. Korean Journal of Agricultural and Forest Meteorology 14(4), 277-282. (in Korean with English abstract) DOI:10.5532/KJAFM.2012.14.4.277
  11. Kim, S.-O., J.-H. Kim, D.-J. Kim, K. M. Shim, and J. I. Yun, 2015: Combined effects of wind and solar irradiance on the spatial variation of midday air temperature over a mountainous terrain. Asia-Pacific Journal of Atmospheric Science 51(3), 239-247. DOI:10.1007/s13143-015-0074-5
  12. KMA, 2011: Climatological normal of Korea (한국기후 표). 158pp. (in Korean)
  13. McKee, T. B., N. J. Doesken, and J. Kleist 1993: The relationship of drought frequency and duration to time scale. 8th Conference on Applied Climatology, Anaheim, CA, American Meteorological Society, 179-184.
  14. MOLIT (Ministry of Land, Infrastructure and Transport), 2017: Water Resource Management Information System (www.wamis.go.kr) 2017.08.01
  15. National Institute of Agricultural Sciences, 2017: Agrometeorological Early Warning System (http://new.agmet.kr) 2017.08.01.
  16. National Institute of Horticultural and Herbal Science, 2002: Fruit Disaster Patterns and Countermeasures (과수 재해양상과 대책). Rural Development Administration. 140pp. (in Korean)
  17. Proebsting, E. L., and H. H. Mills, 1978: Low temperature resistance of developing flower buds of six deciduous fruit species. Journal of the American Society for Horticultural Science 103, 192-198.
  18. Shin, Y. S., J. H. Park, S. K. Kim, W. S. Kang, K. M. Shim, and E. W. Park, 2015: An operational site-specific early warning of weather hazards for farmers and extension workers in a mountainous watershed. Korean Journal of Agricultural and Forest Meteorology 17(4), 290-305. (in Korean with English abstract) DOI: 10.5532/KJAFM.2015.17.4.290.
  19. Sievers, U., and W. G. Zdunkowski, 1986: A micro-scale urban climate model. Beitrage zur Physik der Atmosphare 69(1), 13-40.
  20. Son, C., S. J. Kim, and S. O. Han, 2013: Impact based weather warning using probability of high impact weather and past disaster weather information. Proceeding of 2013 Korean Society of Hazard Mitigation Conference, Ansan, Korea, Korean Society of Hazard Mitigation, 218p.
  21. Wilhite, D. A., M. J. Hayes, C. Knutson, and K. H. Smith, 2000: Planning for drought: moving from crisis to risk management. Journal of the American Water Resources Association 36(4), 697-710. https://doi.org/10.1111/j.1752-1688.2000.tb04299.x
  22. Yun, J. I., 2004: Visualization of local climates based on geospatial climatology. Korean Journal of Agricultural and Forest Meteorology 6(4), 272-289. (in Korean with English abstract)
  23. Yun, J. I., 2007: Applications of "high definition digital climate maps" in restructuring of Korean agriculture. Korean Journal of Agricultural and Forest Meteorology 9(1), 1-16. (in Korean with English abstract) https://doi.org/10.5532/KJAFM.2007.9.1.001
  24. Yun, J. I., 2013: User-specific agrometeorological service to local farming community: a case study. Korean Journal of Agricultural and Forest Meteorology 15(4), 320-331. (in Korean with English abstract) DOI: 10.5532/KJAFM.2013.15.4.320
  25. Yun, J. I., 2014: Agrometeorological early warning system: a service infrastructure for climate-smart agriculture. Korean Journal of Agricultural and Forest Meteorology 16(4), 403-417. (in Korean with English abstract) DOI: 10.5532/KJAFM.2014.16.4.403