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Trend Analysis of Changing Temperature in Bangladesh Due to Global Warming

R. Zaman
Wheat Research Centre, Bangladesh Agricultural Research Institute, Dinajpur-5200, Bangladesh

P. K. Malaker
Wheat Research Centre, Bangladesh Agricultural Research Institute, Dinajpur-5200, Bangladesh

K. F. I. Murad
Wheat Research Centre, Bangladesh Agricultural Research Institute, Dinajpur-5200, Bangladesh

M. A. Sadat
Wheat Research Centre, Bangladesh Agricultural Research Institute, Dinajpur-5200, Bangladesh

Abstract/ Executive Summary:

Long term changes in near-surface air temperature over Bangladesh was studied using the available historical data of maximum and minimum daily temperature for the last 60 years (1949-2008) collected by the Bangladesh Meteorological Department (BMD). Analysis was done by using MAKESENS trend model. It has been observed that the temperature increased significantly at the rate of 0.00569^oC Yr^-1 for AMXT, 0.014498^oC Yr^-1 for AMNT and 0.010262^oC Yr^-1 for AMT. It is evident that AMXT and AMT raised to maximum levels during November by 0.023^oC Yr^-1 and 0.02597^oC Yr^-1 respectively. However, AMNT increased to its maximum during February at 0.0308^oC Yr^-1. It was also found that maximum increase in AMXT occurred at Shitakundu (0.058102^oC Yr^-1), in AMNT at Madaripur (0.042^oC Yr^-1) and in AMT at Kutubdia (0.031113^oC Yr^-1). Southern parts of the country showed higher increasing trends of daily AMXT than other parts. Northern and north-western parts had higher rate of increase in daily AMNT, whereas the daily AMT has increased more in the southern and south-western parts. During Rabi season AMNT increased by 0.023^oC Yr^-1 and AMT by 0.013^oC Yr^-1. In Kharif-1 AMNT increased by 0.012^oC Yr^-1 and AMT by 0.006^oC Yr^-1, whereas in Kharif-2 AMXT increased at 0.011^oC Yr^-1, AMNT at 0.005^oC Yr^-1 and AMT at 0.008^oC Yr^-1. Besides, the temperature of winter season (December to February) has been raised at much higher rate than summer season (June to August). This study also showed that temperature has been increased to much higher levels over the last 30 years (1979-2008) than the last 60 years (1949-2008).

Keywords: Climate, Temperature, Trend, Change, Prediction

Location: Wheat Research Centre, Bangladesh Agricultural Research Institute, Dinajpur

Start Date: 00-00-1949

End Date: 00-00-2008

Program Area: Risk Management in Agriculture

Non-commodity: Temperature

Objectives:

The study was conducted to investigate the long term changes and prediction of future status of near surface air temperature, by using data from historic period up to recent year, with the MAKESENS trend model.

Methodology:

Maximum and minimum daily temperature data of last 60 years (1949-2008) were collected from different stations of BMD. These stations are mainly located at the city centres of urban districts. The trend of changes in temperature was computed monthly, yearly and crop yearly and analyzed by using MAKESENS trend model for all the stations. User’s manual of MAKESENS model was introduced. The MAKESENS is a software computer model which was developed using Microsoft Excel 97 and macros were coded with Microsoft Visual Basic. MAKESENS performed two types of statistical analyses. First, the presence of monotonic increasing and decreasing trend was tested with the nonparametric Mann-Kendall test and secondly, the slope of linear trend was estimated with the nonparametric Sen’s method. These methods are used in their basic forms; the Mann-Kendall test is suitable for cases where the trend may be assumed to be monotonic and thus no seasonal or other cycle is present in the data. The Sen’s method uses a linear model to estimate the slope of the trend and the variance of the residuals should be constant in time. These methods offer many advantages that have made them useful in analyzing atmospheric chemistry data. Missing values are allowed and the data need not to be conformed to any particular distribution. Besides, the Sen’s method is not greatly affected by single data errors or outliers. In MAKESENS test, the significant levels alphas (α) were 0.001, 0.01, 0.05 and 0.10. For the four tested significance levels the following symbols were used in the template: *** if trend at α = 0.001 level of significance, ** if trend at α = 0.01 level of significance, * if trend at α = 0.05 level of significance, + if trend at α = 0.1 level of significance. If the cell is blank, the significance level is greater than 0.1. Changes were calculated based on trend analysis results as Change = (last data yr – first data yr) *Q. Actual values were calculated by the equation, Actual value = (change + B) and Prediction was calculated based on trend analysis results as equation of the lines: f (year) = Q*(last data yr-first data yr) + B. Here, B = Intercept, Q = Rate of change per year.

Source of Information: Journal of Biodiversity and Environmental Sciences (JBES); ISSN: 2220-6663 (Print) 2222-3045 (Online); Vol. 3, No. 2, p. 32-38, 2013

Article Link (Online Journal): http://www.innspub.net

Funding Source:

Budget:

Total Budget (Tk.) :

Achievement/Findings:

Daily average temperature (maximum, minimum and mean) showed positive trends over Bangladesh. Temperature increased significantly at the rate of 0.00569** ^oC Yr^-1 for AMXT, 0.014498*** ^oC Yr^-1 for AMNT and 0.010262***^oC Yr^-1 for AMT. After 60 years (2068) the predicted temperature will be 30.85 ^oC for AMXT, 22.32 ^oC for AMNT and 26.60 ^oC for AMT. The highest increase in AMXT occurred at Shitakundu (0.058102 ^oC *** Yr^-1), in AMNT at Madaripur (0.042 ^oC Yr^-1) and in AMT at Kutubdia (0.031113** ^oC Yr^-1). It was also found that temperature increased dramatically over the last 30 years (1979-2008). Finally the study shows changes in climatic behaviour of the entire study area due to drastic changing temperature. During winter season, cold loving Rabi crops are mainly planted in the northern parts of the county. It is evident that Rabi crops during winter will be highly affected because of global warming

Knowledge Management: Journal