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Çѱ¹¼öÀÚ¿øÇÐȸ / v.42, no.9, 2009³â, pp.681-690
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±â»óÀÎÀÚ¸¦ ÀÌ¿ëÇÑ ¿ì¸®³ª¶óÀÇ È®·ü°¼ö·® Æò°¡
( Evaluation of Probability Precipitation using Climatic Indices in Korea ) |
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º» ¿¬±¸¿¡¼´Â ±â»óÀÎÀÚ¸¦ ¹Ý¿µÇÏ¿© È®·ü°¼ö·®À» »êÁ¤ÇÏ°í ºÒÈ®½Ç¼ºÀ» Æò°¡ÇÏ¿´´Ù. ±â»óÀÎÀÚ´Â ¹üÁö±¸ÀûÀ¸·Î °üÃøµÇ°í ÀÖ´Â ÇØ¼ö¸é¿Âµµ¿Í ½ÀÀ±Áö¼ö ÀڷḦ ÀÌ¿ëÇÏ¿´´Ù. ºÐ¼® ¹æ¹ýÀº ±â»óÀÎÀÚ¿Í ¿¬ÃÖ´ë½Ã°£°¼ö·® »çÀÌÀÇ Áöü»ó°ü°è¼ö¸¦ »êÁ¤ÇÏ¿© ºñ±³ÇÔÀ¸·Î½á, ¿ì¸®³ª¶óÀÇ ½Ã°£ÃÖ´ë°¼ö·®°ú »ó°ü°ü°è°¡ Å« ±â»óÀÎÀÚÀÇ °üÃøÁö¿ª°ú Áöü½Ã°£À» ¼±Á¤Çϰí Áö¿ª°¡Áß´ÙÇ×½ÄÀ» ÀÌ¿ëÇÏ¿© ȸ±Í°ü°è¸¦ ¼³Á¤ÇÏ¿´´Ù. ´ÙÀ½À¸·Î ±â»óÀÎÀÚ¸¦ º¯µ¿ÇٹеµÇÔ¼ö¸¦ ÀÌ¿ëÇÏ¿© È®·ü ¹ÐµµÇÔ¼ö¸¦ ÃßÁ¤ÇÏ¿© ¸ðÀǹ߻ýÀ» ¼öÇàÇÏ¿´´Ù. ¸¶Áö¸·À¸·Î ¸ðÀÇµÈ ±â»óÀÎÀÚ¸¦ Áö¿ª°¡Áß´ÙÇ×½ÄÀ» ÅëÇØ °¼ö·®À» ÃßÁ¤ÇÏ¿© È®·ü°¼ö·®À» »êÁ¤ÇÏ¿´´Ù. ºÐ¼® °á°ú¿¡¼ ±â»óÀÎÀÚ¸¦ ¹Ý¿µÇÑ È®·ü°¼ö·®Àº °¼öÀڷḦ ºóµµÇؼ®ÇÑ È®·ü°¼ö·®°ú Å« Â÷À̸¦ º¸ÀÌÁö ¾Ê´Â °ÍÀ¸·Î ³ªÅ¸³µ´Ù. ¶ÇÇÑ Áö±¸¿Â³È¿Í °°Àº ±âÈĺ¯È¸¦ ¹Ý¿µÇÏ´Â ±â»óÀÎÀÚ¸¦ ¹Ý¿µÇÑ È®·ü°¼ö·® »êÁ¤ÀÇ ±âÃÊÀÚ·á·Î Ȱ¿ëÇÒ ¼ö ÀÖÀ» °ÍÀ¸·Î ÆÇ´ÜµÈ´Ù. |
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In this research, design precipitation was calculated by reflecting the climatic indices and its uncertainty assessment was evaluated. Climatic indices used the sea surface temperature and moisture index which observed globally. The correlation coefficients were calculated between the annual maximum precipitation and the climatic indices. and then climatic indices which have the larger correlation coefficient were selected. Therefore, the regression relationship was established by a locally weighted polynomial regression. Next, climatic indices were generated by montecarlo simulation using kernel function. Finally, the design rainfall was calculated by the locally weighted polynomial regression using generated climatic indices. At the result, the comparison of design rainfall between the reflection of the climatic indices and the frequency analysis did not indicate a significant difference. Also, this result can be used as basic data for calculation of probability precipitation to reflect climate change. |
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ºóµµÇؼ®;È®·ü°¼ö·®;±â»óÀÎÀÚ;º¯µ¿ÇٹеµÇÔ¼ö;Áö¿ª°¡Áß´ÙÇ×½Ä;frequency analysis;probability precipitation;climatic index;variable Kernel function;locally weighted polynomial regression; |
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Çѱ¹¼öÀÚ¿øÇÐȸ³í¹®Áý / v.42, no.9, 2009³â, pp.681-690
Çѱ¹¼öÀÚ¿øÇÐȸ
ISSN : 1226-6280
UCI : G100:I100-KOI(KISTI1.1003/JNL.JAKO200927941501009)
¾ð¾î : Çѱ¹¾î |
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³í¹® Á¦°ø : KISTI Çѱ¹°úÇбâ¼úÁ¤º¸¿¬±¸¿ø |
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