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Çѱ¹¼öÀÚ¿øÇÐȸ / v.35, no.6, 2002³â, pp.763-777
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½Ã°£°¼ö°è¿ÀÇ °¼ö·® ¸ðÀǹ߻ýÀ» À§ÇÑ Ãß°èÇÐÀû ¸ðÇü
( A Stochastic Simulation Model for the Precipitation Amounts of Hourly Precipitation Series ) |
| ÀÌÁ¤½Ä;ÀÌÀçÁØ;¹ÚÁ¾¿µ; ±Ý¿À°ø°ú´ëÇб³ Åä¸ñ, ȯ°æ ¹× °ÇÃà°øÇкÎ;±Ý¿À°ø°ú´ëÇб³ Åä¸ñ, ȯ°æ ¹× °ÇÃà°øÇкÎ;±Ý¿À°ø°ú´ëÇб³ Åä¸ñ, ȯ°æ ¹× °ÇÃà°øÇкÎ;
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| º» ¿¬±¸ÀÇ ¸ñÀûÀº °£Çæ ¼ö¹®»ç»óÀÎ ½Ã°£°¼ö°è¿ÀÇ ±¸Á¶Àû Ư¼ºÀ» °íÂûÇÏ¿© °¼ö·® ¸ðÀǹ߻ýÀ» À§ÇÑ Ãß°èÇÐÀû ¸ðÇüÀ» °³¹ßÇÏ´Â °ÍÀÌ´Ù. À̸¦ À§ÇÏ¿© º» ¿¬±¸¿¡¼´Â °¼ö¹ß»ý°úÁ¤¿¡ ´ëÇÑ Ãß°èÇÐÀû ¸ðÇüÀº ÀÌÀçÁذú ÀÌÁ¤½Ä(2002)ÀÌ °³¹ßÇÑ Ãß°èÇÐÀû ¸ðÇüÀ» ÀÌ¿ëÇÏ¿´À¸¸ç, °¼ö·®°úÁ¤À» À§ÇÏ¿© »ç»ó³»ÀÇ ½Ã°£°¼ö·®À» ºñÁ¤»ó 1Â÷ ÀÚ±âȸ±Í¸ðÇüÀ¸·Î ±â¼úÇÏ¿´´Ù. ½Ã°£°¼ö°è¿ÀÇ °¼ö¹ß»ý°úÁ¤°ú °¼ö·®°úÁ¤À» Á¶ÇÕÇÏ¸é ½Ã°£°¼ö»ç»óÀÇ ¹ß»ýÆÐÅϰú »ç»ó±â°£³»ÀÇ °¼öÀÇ Á¾¼Ó±¸Á¶¸¦ ¸ðÀÇÇÒ ¼ö ÀÖ´Â ½Ã°£°¼ö°è¿¿¡ ´ëÇÑ ¸ðÀǸðÇüÀÌ ¾ò¾îÁö¸ç, ÀÌ ¸ðÇüÀÇ ÀûÇÕ¼ºÀ» ±¸¸íÇϱâ À§ÇØ ¼¿ïÀ» ´ë»óÀ¸·Î ÇÏ¿© ½ÇÀû°¼öÀڷḦ ºÐ¼®ÇÏ¿´´Ù. Monte Carlo ¸ðÀǰá°ú´Â ¸ðÇüÀÌ »ç»ó±â°£³»ÀÇ °¼ö°µµ, Áö¼Ó ±â°£, Å©±âÀÇ ÁÖº¯ ¹× Á¶°ÇºÎ ºÐÆ÷¸¦ Àß ÀçÇöÇϰí ÀÖÀ½À» º¸¿©ÁÖ¾ú´Ù. ½ÇÀû ¹× ¸ðÀÇ ÀÚ·á¿¡ ´ëÇÑ ÀÚ±â»ó°üÇÔ¼öµµ ºñ±³Àû ÀÛÀº ½Ã°£Áöü¿¡¼´Â À¯»çÇÏ¿´´Ù |
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| The objective of this study is to develop computer simulation model that produces precipitation patterns from stochastic model. The hourly precipitation process consists of the precipitation occurrence and precipitation amounts. In this study, an event cluster model developed by Lee and Lee(2002) is used to describe the occurrence process of events, and the hourly precipitation amounts within each event is described by a nonstationary form of a first-order autoregressive process. The complete stochastic model for hourly precipitation is fitted to historical precipitation data by estimating the model parameters. An analysis of historical and simulated hourly precipitation data for Seoul indicates that the stochastic model preserves many of the features of historical precipitation. The autocorrelation coefficients of the historical and simulated data are nearly identical except for lags more than about 3 hours. The precipitation intensity, duration, marginal distributions, and conditional distributions for event characteristics for the historical and simulated data showed in general good agreement with each other. |
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| Ű¿öµå |
| ½Ã°£°¼ö°è¿;°¼ö·®°úÁ¤;ºñÁ¤»ó 1Â÷ ÀÚ±âȸ±Í°úÁ¤;Á¶°ÇºÎºÐÆ÷;ÁÖº¯ºÐÆ÷;Hourly precipitation series;Process of precipitation amounts;Nonstationary 1st order AR process;Conditional distribution;Marginal distribution; |
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Çѱ¹¼öÀÚ¿øÇÐȸ³í¹®Áý / v.35, no.6, 2002³â, pp.763-777
Çѱ¹¼öÀÚ¿øÇÐȸ
ISSN : 1226-6280
UCI : G100:I100-KOI(KISTI1.1003/JNL.JAKO200211921477235)
¾ð¾î : Çѱ¹¾î |
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| ³í¹® Á¦°ø : KISTI Çѱ¹°úÇбâ¼úÁ¤º¸¿¬±¸¿ø |
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