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Performance Study of Global Circulation Model Hadcm3 Using Sdsm for Temperature and Rainfall in North-eastern Bangladesh

A. H. Nury
Department of Civil and Environmental Engineering, Shahjalal University of Science and Technology, Sylhet-3114, Bangladesh

M. J. B. Alam
Department of Civil and Environmental Engineering, Shahjalal University of Science and Technology, Sylhet-3114, Bangladesh

Abstract/ Executive Summary:

This paper describes application of a statistical downscaling model to study the performance of the global circulation model HADCM3 (Hadley centre coupled model, version 3) for the Sylhet and Moulvibazar districts (North-eastern region) of Bangladesh. Predictors of HADCM3 have been downscaled by statistical downscaling model (SDSM). Daily observed temperature and rainfall data from 1981 to 2006 was used to conduct the calibration and 2007 to 2011 was used for validation using SDSM. Percent of bias (PBIAS), Nash-Sutcliffe efficiency (NSE) and modified index of agreement are also used for the assessment of downscaled temperature and rainfall data. PBIAS of downscaled temperature is the least (-0.30%), NSE (0.80) and modified index of agreement (0.83) is the highest for daily maximum temperature at Sylhet station. Among five rainfall stations, PBIAS of downscaled rainfall is the least (1.31%), NSE (0.76) and modified index of agreement (0.79) is the highest at Kanairghat station. The down scaled temperature and rainfall data approximately agree with the observed data.

Keywords: Temperature; Rainfall; SDSM; Downscaling; Validation; PBIAS; NSE.

Location: Sylhet district and Chandbagh, Sreemangal and Manu railway bridge are located in Moulvibazar district.

Start Date: 00-00-1981

End Date: 00-00-2006

Program Area: Knowledge Management

Non-commodity: Performance

Objectives:

The objective of this study is to evaluate the performance of the global circulation model HADCM3 using SDSM at Sylhet and Moulvibazar districts in Bangladesh.

Methodology:

Climate data: Monthly temperature and rainfall data covering the Sylhet (24053'40" latitude, 24053'40" longitude) and the neighboring Moulvibazar (24018'31" latitude, 91043'49" longitude) district have been collected from the Bangladesh Meteorological Department (BMD). The temperature and rainfall data cover a period of 30 years from 1981 to 2011. Rainfall stations Tajpur and Kanairghat are located in Sylhet district and Chandbagh, Sreemangal and Manu railway bridge are located in Moulvibazar district. Downscaling of climate change data was conducted using SDSM. Before downscaling process, quality control was ensured. The empirical relationship between gridded predictors (such as mean sea level pressure) and single site predictands (such as station precipitation) was then evaluated. After finding suitable predictor variables, calibration process was performed. By using calibration parameter obtained from calibration process, climate scenarios were produced with ensembles of synthetic daily weather series derived from atmospheric predictor variables. Calibration: The calibration of downscaling models was based on solving multiple regression equations, by given daily weather data (the predictand) and regional–scale atmospheric (predictor) variables. To initiate the calibration process it is prerequisite to define calibration time period. The observed time period 1981 to 2006 was used to conduct the calibration of temperature and rainfall. Percent of bias (PBIAS) measurNash-Sutcliffe efficiency (NSE):The Nash-Sutcliffe efficiency (NSE) is a normalized statistic that determines the relative magnitude of the residual variance compared to the measured data variance.NSE indicates how well the plot of observed versus simulated data fits. NSE ranges between −∞ and 1.0 (1 inclusive), with NSE = 1 being the optimal value. Values between 0.0 and 1.0 are generally viewed as acceptable levels of performance, whereas values <0.0 indicates that the mean observed value is a better predictor than the simulated value, which indicates unacceptable performance.es the average tendency of the simulated data to be larger or smaller than their observed counterparts. The optimal value of PBIAS is 0.0, with low-magnitude values indicating accurate model simulation. Positive values indicate model underestimation bias, and negative values indicate model overestimation bias.

Source of Information: J. Sci. Res. 6 (1), 87-96 (2014)

Article Link (Online Journal):

Funding Source:

Total Budget (Tk.) :

Achievement/Findings:

Statistical downscaling of GCM (global circulation model) for temperature and rainfall data can easily be understood and adopted in order to minimize climate changes and its relevant impacts. There are some biases in downscaled temperature and rainfall. Such biases were comparatively less for downscaled temperature in comparison to rainfall. PBIAS (percent of BIAS) of downscaled daily maximum temperature at Sylhet station was the least (-0.30%). NSE (Nash-Sutcliffe model efficiency) and index of agreement of downscaled daily maximum temperature at Sylhet station was 0.80 and 0.83 respectively. As a result, the downscaled daily maximum temperature was fitted well to the observed data at Sylhet station. PBIAS (percent of BIAS) was the least (1.31%) of daily rainfall at Kanairghat station. NSE (Nash-Sutcliffe model efficiency) and index of agreement of downscaled daily rainfall at Kanairghat station was 0.76 and 0.79 respectively. Moreover, the agreement between downscaled daily rainfall and observed one was impressive at Kanairghat station. Finally, it was evident that performance of GCM model HADCM3 using SDSM was successively promising to temperature and rainfall data. It might be used effectively for estimation and prediction of missing temperature and rainfall values and investigation of long term temperature and rainfall changes.

Knowledge Management: Journal