Author/Authors :
Limsakul، نويسنده , , Atsamon and Goes، نويسنده , , Joaquim I. and Mouw، نويسنده ,
Abstract :
The spatio-temporal variations of monthly averaged maximum, mean and minimum surface air temperatures (Tmax, Tmean, Tmin) in Thailand for the period between 1951 and 2003 have been examined using Principal Component Analysis. The objective of this study was to determine the dominant patterns of interannual and longer period variability and illustrate their connection to large-scale climate variability.
sults reveal that the dominant variability in Tmax, Tmean and Tmin can be explained in large measure by the first principal component (PC1), which accounts for 60%, 61% and 62% of the total variance, respectively. The coefficient time series associated with PC1 appear to have oscillated in relation to the primary global climate variability. There are significant indications that El Niٌo-Southern Oscillation (ENSO) events are an important source of interannual/interdecadal variability in Thailand surface air temperatures. On an interannual timescale, surface air temperatures in Thailand were anomalously higher (lower) than normal during the El Niٌo (La Niٌa) years. In addition, the overall warming trends of Tmax, and Tmin in the 1980s and 1990s were consistent with the tendency for more frequent El Niٌo events and fewer La Niٌa events since the late 1970s.
long-term perspective, the data suggest that Tmin has been on the rise at an unprecedented rate since the early 1950s, consistent with the patterns of globally and hemispherically-averaged air temperatures in the 20th century. The change in Tmin has been occurring at faster rate than Tmax. One consequence of differential changes in maximum and minimum temperatures is the progressive narrowing of temperature ranges over most parts of Thailand. These results are consistent with the well-documented evidence, illustrating that diurnal temperature range in most parts of the world are continuing to decrease because minimum temperatures are increasing at about twice the rate of maximum temperatures.