Author | Mahmood, Rashid |
Note | A research study submitted in partial fulfillment of the requirements for the degree of
Master of Engineering in Water Engineering and Management, School of Engineering and Technology |
Publisher | Asian Institute of Technology |
Abstract | The fundamental rationale of downscaling methods is to assess the impacts of climate
change on land surface processes at regional level by using the outputs of General
Circulation Model (GCM) which cannot be used directly in assessing the effects of climate
change on local scale due its coarse resolution of about 200 to 600 km. The overall
objective of this study is to compare the two downscaling techniques, Delta Change and
Regression based Statistical downscaling, and to analyze the future trend of temperature
and precipitation in Ping River Basin by using the most advance tool-HadCM3.
Delta Change Approach uses simulated future and current climate data from the HadCM3
along with observed time series to find out the future trend. The SDSM model is developed
by using the daily observed station data and NCEP reanalysis data. Then the climate
variables (Temperature and Precipitation) are simulated for current and future period (2050
and 2080) by using the Predictors from HadCM3.
Both methods are validated by using correlation coefficient and standard error for the same
period (1991-2000). The correlation coefficients for the validation of Delta Change are
98% and 97% for temperature and precipitation respectively and of SDSM are 99% and
97% for temperature and precipitation respectively. The future scenarios are simulated for
the period of 2050 and 2080. According to Delta Change the temperature will be raised by
2.23°C and 3.89°C in 2050 and 2080 respectively, and precipitation will be increased 53%
and 91% in 2050 and 2080 respectively with respect to baseline period. The SDSM shows
that temperature will be raised by 1.77°C and 3.23°C in 2050 respectively, and
precipitation will be increased by 19.68% and 22.84% in 2080 respectively with respect to
baseline period.
The results from both methods are compared by using the six statistical parameters
(Correlation coefficient, Standard error, Standard deviation, Min, Max and Mean values)
with observed data for the period of 1991-2000. Both present high correlation above than
96% and low standard error below than 0.84 both for temperature and precipitation. The
SDSM gives a little good correlation in case of temperature but same in case of
precipitation. |
Year | 2009 |
Type | Research Study Project Report (RSPR) |
School | School of Engineering and Technology (SET) |
Department | Department of Civil and Infrastucture Engineering (DCIE) |
Academic Program/FoS | Water Engineering and Management (WM) |
Chairperson(s) | Babel, Mukand S. ; |
Examination Committee(s) | Sutat Weesakul ;Clemente, Roberto S. ; |
Scholarship Donor(s) | Higher Education Commission (HEC), Pakistan ;AIT Fellowship; |