{"title":"孟加拉国迪纳杰普尔气候变量的预报","authors":"J. Syeda","doi":"10.3329/JESNR.V10I2.39030","DOIUrl":null,"url":null,"abstract":"An attempt was made to forecast the 17 monthly climatic variables for 2005-2012 of Dinajpur using the univariate Box-Jenkin’s ARIMA (autoregressive integrated moving average) modeling techniques for 1948-2004. The 8 years data for 1973-1980 were missing and those data were replaced with the 4 years monthly forecasted data for 1948-1972 and 1981-2004 (reversing the years). The well fitted ARIMA (autoregressive integrated moving average) models were selected from the possible 16 ARIMA models based on the minimum root mean square forecasting errors (RMSFE) with the last 24 observations for all the cases and the residuals followed stationarity and normality. Several outliers were detected in the data which were replaced by the forecasted value. The fitted model for sunshine data (1989-2004) was found ARIMA (1, 1, 1)(1, 1, 1)12 and for evaporation data (1987-2000) was ARIMA (1, 1, 2)(1, 1, 1)12. . The findings supports that the changing term of the climatic variables may have adverse impacts on the crop production in this country.J. Environ. Sci. & Natural Resources, 10(2): 163-170 2017","PeriodicalId":15768,"journal":{"name":"Journal of Environmental Science and Natural Resources","volume":"37 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Forecasting of Climatic Variables in Dinajpur of Bangladesh\",\"authors\":\"J. Syeda\",\"doi\":\"10.3329/JESNR.V10I2.39030\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An attempt was made to forecast the 17 monthly climatic variables for 2005-2012 of Dinajpur using the univariate Box-Jenkin’s ARIMA (autoregressive integrated moving average) modeling techniques for 1948-2004. The 8 years data for 1973-1980 were missing and those data were replaced with the 4 years monthly forecasted data for 1948-1972 and 1981-2004 (reversing the years). The well fitted ARIMA (autoregressive integrated moving average) models were selected from the possible 16 ARIMA models based on the minimum root mean square forecasting errors (RMSFE) with the last 24 observations for all the cases and the residuals followed stationarity and normality. Several outliers were detected in the data which were replaced by the forecasted value. The fitted model for sunshine data (1989-2004) was found ARIMA (1, 1, 1)(1, 1, 1)12 and for evaporation data (1987-2000) was ARIMA (1, 1, 2)(1, 1, 1)12. . The findings supports that the changing term of the climatic variables may have adverse impacts on the crop production in this country.J. Environ. Sci. & Natural Resources, 10(2): 163-170 2017\",\"PeriodicalId\":15768,\"journal\":{\"name\":\"Journal of Environmental Science and Natural Resources\",\"volume\":\"37 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Environmental Science and Natural Resources\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3329/JESNR.V10I2.39030\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Environmental Science and Natural Resources","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3329/JESNR.V10I2.39030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Forecasting of Climatic Variables in Dinajpur of Bangladesh
An attempt was made to forecast the 17 monthly climatic variables for 2005-2012 of Dinajpur using the univariate Box-Jenkin’s ARIMA (autoregressive integrated moving average) modeling techniques for 1948-2004. The 8 years data for 1973-1980 were missing and those data were replaced with the 4 years monthly forecasted data for 1948-1972 and 1981-2004 (reversing the years). The well fitted ARIMA (autoregressive integrated moving average) models were selected from the possible 16 ARIMA models based on the minimum root mean square forecasting errors (RMSFE) with the last 24 observations for all the cases and the residuals followed stationarity and normality. Several outliers were detected in the data which were replaced by the forecasted value. The fitted model for sunshine data (1989-2004) was found ARIMA (1, 1, 1)(1, 1, 1)12 and for evaporation data (1987-2000) was ARIMA (1, 1, 2)(1, 1, 1)12. . The findings supports that the changing term of the climatic variables may have adverse impacts on the crop production in this country.J. Environ. Sci. & Natural Resources, 10(2): 163-170 2017