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기후자료 판별분석에 근거한 나주 배 생산지 서리발생 예측

Frostfall Forecasting in the Naju Pear Production Area Based on Discriminant Analysis of Climatic Data

  • 한점화 (국립원예특작과학원 배시험장) ;
  • 최장전 (국립원예특작과학원 배시험장) ;
  • 정유란 (경희대학교 생태시스템공학과) ;
  • 조광식 (국립원예특작과학원 배시험장) ;
  • 천종필 (충남대학교 식물자원학부 원예학)
  • 발행 : 2009.12.30

초록

기상요인을 근거로 서리를 예측할 수 있다면 농작물의 서리피해 경감에 매우 유용할 것이다. 이와 관련하여 본 연구에서는 나주지역 배 개화기인 4월 동안 일 최고기온 $20^{\circ}C$ 이하인 날 중 다음날 서리가 내린 날과 내리지 않은 날의 야간의 공기 냉각율과 기온 변화를 분석하였다. 야간 공기 냉각율은 서리 내습일이 비내습일에 비해 높았으며, 특히 19시부터 24시까지의 평균 공기 냉각율은 $1.7^{\circ}C$로 비내습일의 $0.7^{\circ}C$보다 높았다. 야간 기온은 서리내습일이 비내습일에 비해 현저히 낮았으며, 24시의 기온은 $3.9{\pm}1.5^{\circ}C$로 비내습 일의 $10.1{\pm}2.9^{\circ}C$에 비해 $6.2^{\circ}C$ 낮았다. 독립변수는 구름량, 24시 기온, 전날 5일간의 강우량으로 하고, 종속변수는 다음날 서리내습여부로 하여 판별분석을 실시한 결과 분류대상 32일 중 30일이 정확히 분류되었으며, 판별함수 검증 결과 적중률은 86.9%로 높았다. 따라서 전날 일 최고기온, 24시 기온, 구름량, 전날 5일간의 강우량에 의해 다음날 서리 발생 예측 가능성이 높은 것으로 판단되었다.

In order to predict frostfall, nocturnal cooling rate and air temperature changes were analyzed on days with and without frost when the maximum temperature was lower than $20^{\circ}C$. In general, the nocturnal cooling rates on frosty days were higher than those on non-frosty days. The cooling rates averaged from 19:00 to 24:00 on frosty and non-frosty days were $1.7^{\circ}Ch^{-1}$ and $0.7^{\circ}Ch^{-1}$ respectively. As expected, the nocturnal temperature on frosty days was lower than that on non-frosty days. Especially, the midnight air temperature averaged about $3.9{\pm}1.5^{\circ}C$ on frosty days, which was lower than that on non-frosty days (i.e., $10.1{\pm}2.9^{\circ}C$). The discriminant analysis using three independent variables (i.e., total cloud amount, air temperature at 24:00, and 5-day rainfall amount) successfully classified the presence of frost with 87% accuracy.

키워드

참고문헌

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피인용 문헌

  1. Effect of Shade Net on Reduction of Freezing Damage at a Tea Garden vol.16, pp.2, 2014, https://doi.org/10.5532/KJAFM.2014.16.2.146
  2. Spatiotemporal variability of the latest frosts in Korean Peninsula and causes of atmospheric circulation vol.128, pp.5, 2016, https://doi.org/10.1007/s00703-016-0439-z
  3. Improving Usage of the Korea Meteorological Administration's Digital Forecasts in Agriculture: I. Correction for Local Temperature under the Inversion Condition vol.15, pp.2, 2013, https://doi.org/10.5532/KJAFM.2013.15.2.076