The main objective of this study is to develop
algorithms for calculating the air surface temperature (AST). This
study also aims to analyze and investigate the effects of greenhouse
gases (GHGs) on the AST value in Peninsular Malaysia. Multiple
linear regression is used to achieve the objectives of the study.
Peninsular Malaysia has been selected as the research area because
it is among the regions of tropical Southeast Asia with the greatest
humidity, pockets of heavy pollution, rapid economic growth, and
industrialization. The predicted AST was highly correlated
(R = 0.783) with GHGs for the 6-year data (2003–2008). Comparisons
of five stations in 2009 showed close agreement between
the predicted AST and the observed AST from AIRS, especially in
the wet season (within 1.3 K). The in situ data ranged from 1 to
2 K. Validation results showed that AST (R = 0.776–0.878) has
values nearly the same as the observed AST from AIRS. We found
that O3 during the wet season was indicated by a strongly positive
beta coefficient (0.264–0.992) with AST. The CO2 yields a reasonable
relationship with temperature with low to moderate beta
coefficient (-0.065 to 0.238). The O3, CO2, and environmental
variables experienced different seasonal fluctuations that depend on
weather conditions and topography. The concentration of gases and
pollution were the highest over industrial zones and overcrowded
cities, and the dry season was more polluted compared with the wet
season. These results indicate the advantage of using the satellite
AIRS data and a correlation analysis to investigate the effect of
atmospheric GHGs on AST over Peninsular Malaysia. An algorithm
that is capable of retrieving Peninsular Malaysian AST in all
weather conditions with total uncertainties ranging from 1 to 2 K
was developed.
جاسم محمد رجب حسين | Jasim Mohammed Rajab | 1581