Application to import climate data into CLIMSOFT (import-App)

The focus of this study is to find the relationship between El Nino and dengue fever cases in the study area.Mosquito density was recorded with the help of light traps and through aspirators collection. Climate data were obtained from National Meteorology and Environment centre. (Year wise El Nino and La Nina data are according to NOAA & Golden Gate Weather Services). Statistical methods were used to establish the correlation coefficient between different factors. A high significant relationship was observed between Relative Humidity and Dengue fever cases, but Aedes abundance had no significant relationship with either Relative humidity and Temperature. Our conclusion is that the El Nino does not affect the dengue transmission and Aedes mosquito abundance in this region, which is supported by earlier works.

Download Full-text

Rainfall Prediction in South-Eastern Part of Bangladesh by Linear Regression Method

International Journal of Emerging Research in Management and Technology ◽

10.23956/ijermt.v6i6.255 ◽

2018 ◽

Vol 6 (6) ◽

pp. 119

Author(s):

Mohammad Shohidul Islam ◽

Sultana Easmin Siddika ◽

S M Injamamul Haque Masum

Keyword(s):

Linear Regression ◽

Correlation Coefficients ◽

Rain Gauge ◽

Regression Method ◽

Linear Regression Method ◽

Climate Data ◽

Rainfall Forecasting ◽

Statistical Parameters ◽

Time Duration ◽

Rainfall Prediction

Rainfall forecasting is very challenging task for the meteorologists. Over the last few decades, several models have been utilized, attempting the successful analysing and forecasting of rainfall. Recorded climate data can play an important role in this regard. Long-time duration of recorded data can be able to provide better advancement of rainfall forecasting. This paper presents the utilization of statistical techniques, particularly linear regression method for modelling the rainfall prediction over Bangladesh. The rainfall data for a period of 11 years was obtained from Bangladesh Meteorological department (BMD), Dhaka i.e. that was surface-based rain gauge rainfall which was acquired from 08 weather stations over Bangladesh for the years of 2001-2011. The monthly and yearly rainfall was determined. In order to assess the accuracy of it some statistical parameters such as average, meridian, correlation coefficients and standard deviation were determined for all stations. The model prediction of rainfall was compared with true rainfall which was collected from rain gauge of different stations and it was found that the model rainfall prediction has given good results.

Download Full-text