{"title":"巴基斯坦北部丘陵地区夏季季风降雨的模拟与模拟","authors":"M. Tufail, Saqib-ur-Rehman, B. Usmani","doi":"10.1109/INMIC.2008.4777786","DOIUrl":null,"url":null,"abstract":"This study assesses the inter-annual variability of summer monsoon rainfall of Northern Hilly Area of Pakistan, which includes Balakot, Chitral, Murree, Gilgit, Skardu, Chilas, Muzaffarabad and Dir. The region receives a heavy rainfall, the total annual rainfall being 1000 mm or more. We attempt to model the rainfall process of the data from 1971-2000. Initially we use twelve predictors out of which only four, viz., sea surface temperature (SST-10a), temperature of Hyderabad city of Pakistan (HT-5) and pressure of Kakul (KP-10)and Lahore (LP-3), are selected with the help of stepwise multiple linear regression. The mean square error of the regression model is found to be 13.8%. Since the entire modeling procedure is based on selected predictors, we suggest that the selected predictors, which are selected here according to their correlation, should be refined by using more sophisticated technique such as principal component analysis, or nonlinear correlations.","PeriodicalId":112530,"journal":{"name":"2008 IEEE International Multitopic Conference","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling and simulation of summer monsoon rainfall for Northern Hilly Area of Pakistan\",\"authors\":\"M. Tufail, Saqib-ur-Rehman, B. Usmani\",\"doi\":\"10.1109/INMIC.2008.4777786\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study assesses the inter-annual variability of summer monsoon rainfall of Northern Hilly Area of Pakistan, which includes Balakot, Chitral, Murree, Gilgit, Skardu, Chilas, Muzaffarabad and Dir. The region receives a heavy rainfall, the total annual rainfall being 1000 mm or more. We attempt to model the rainfall process of the data from 1971-2000. Initially we use twelve predictors out of which only four, viz., sea surface temperature (SST-10a), temperature of Hyderabad city of Pakistan (HT-5) and pressure of Kakul (KP-10)and Lahore (LP-3), are selected with the help of stepwise multiple linear regression. The mean square error of the regression model is found to be 13.8%. Since the entire modeling procedure is based on selected predictors, we suggest that the selected predictors, which are selected here according to their correlation, should be refined by using more sophisticated technique such as principal component analysis, or nonlinear correlations.\",\"PeriodicalId\":112530,\"journal\":{\"name\":\"2008 IEEE International Multitopic Conference\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE International Multitopic Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INMIC.2008.4777786\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Multitopic Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INMIC.2008.4777786","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling and simulation of summer monsoon rainfall for Northern Hilly Area of Pakistan
This study assesses the inter-annual variability of summer monsoon rainfall of Northern Hilly Area of Pakistan, which includes Balakot, Chitral, Murree, Gilgit, Skardu, Chilas, Muzaffarabad and Dir. The region receives a heavy rainfall, the total annual rainfall being 1000 mm or more. We attempt to model the rainfall process of the data from 1971-2000. Initially we use twelve predictors out of which only four, viz., sea surface temperature (SST-10a), temperature of Hyderabad city of Pakistan (HT-5) and pressure of Kakul (KP-10)and Lahore (LP-3), are selected with the help of stepwise multiple linear regression. The mean square error of the regression model is found to be 13.8%. Since the entire modeling procedure is based on selected predictors, we suggest that the selected predictors, which are selected here according to their correlation, should be refined by using more sophisticated technique such as principal component analysis, or nonlinear correlations.
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