Variability of GPS water vapor associated with warming activity in Peninsular Malaysia during the period of 2008–2011

Warming activity is an indicator of climate change impact on a particular region. As the warming increases, the impact on socio-economic and political behavior increases and this is seen most keenly in environmental issues, therefore, it has become a major concern for the international community and stake holders during the last few decades. The occurrence of warming can be understood by considering two unbalanced energies. If the balance between the radiation energy from the Sun and the thermal radiation from the Earth and the atmosphere to outer space is disturbed, it can be restored by an increase in the Earth's surface temperature (Houghton 2009). This occurs when heat is trapped inside the Earth's atmosphere after the sun's rays are reflected from the Earth's surface. The surface of the Earth and the atmosphere heat up, and this causes changes in the climate throughout the world. In the 20th century, studies on global warming and climate change have been attracting a great deal of attention due to its huge impact on human habitats. However, the scope of exploring the impact of warming phenomena and climate change from the perspective of Malaysia is still limited compared with other countries in Asia.

One way to analyze the effects of warming is to study the trend and alterations of Earth's surface temperature. Meng et al. (2005) and Tangang et al. (2007) show that in every 100 years in Peninsular Malaysia, there is a rise in average temperature, which ranges from 1 to 4 °C. Other studies have investigated that the effect of warming is higher in the northern part of Peninsular Malaysia (Deni et al. 2008) where dry spells occur earlier than the other parts due to influence of the easterlies that cause a drying of the atmosphere. NAHRIM (2011) observed that the coastal areas in the northern part are experiencing rising sea levels compared with other parts. In a quantitative study, Shaffril et al. (2011) found out that besides the sea level rise (SLR), warming is threatening coastal areas by changing the geography, raising sea surface temperatures, changing flows of ocean currents and acidifying the seawater which directly impacts on the fishery sector. Using a downscaling technique, Tangang et al. (2012) reported an increment in average surface temperature and SLR over Peninsular Malaysia towards the end of the 21st century. They projected the average of surface temperature would be approximately 29 to 30 °C and the increment of SLR would be approximately 0.25 to 0.52 m. In addition to the increase in surface temperature trends, greenhouse gases such as methane (CH₄) possess the highest percentage of emissions that are produced in Peninsular Malaysia. The emission of CH₄ rises during the Northeast monsoon mainly in the northern region (latitude above 4°) throughout the year (Rajab et al. 2012). One of the most abundant greenhouse gases that plays a crucial role in warming activity is water vapor. Although the amount of greenhouse gases produced by humans in this region may seem small from a certain perspective, their potential is amplified by the water vapor positive feedback loop (NASA 2008), allowing them to cause significant warming and climate change.

The objective of this study is to analyze precipitable water vapor (PWV) variability derived from global positioning system (GPS) to detect the effects of warming activity in Peninsular Malaysia. We used statistical analysis to explain the changes in PWV variation with response to warming activity during the period of 2008–2011. We compare the PWV variability with Radiosonde, or radio sounding (RS), PWV data and their trend with accumulated precipitation taken from NASA's Tropical Rainfall Measuring Mission (TRMM). The anomaly of PWV trend obtained can be considered for future mitigation of climate change across the country as well as an early warning for stake holders.

GPS is a powerful tool and as such has been employed in atmospheric studies, and Bevis et al. (1992) utilised PWV for climate studies. However, this parameter is difficult to characterize in equator regions due to the humidity and irregular weather patterns. For Malaysia, the installation of a GPS receiver by the government is mostly for the purposes of surveying and mapping. This further complicates the study of climate change which requires the installation of a GPS receiver co-located with the meteorological sensors. Indeed, long-term data provided with high temporal and spatial resolution are also limited.

The geographical locations regarding the GPS, MET and RS stations used in this study are compiled in Tables 1 and 2. In this study, the GPS data were supplied by the Department of Survey and Mapping Malaysia (DMSS). The MET data were provided by Malaysian Meteorological Department (MMD), while the RS data were provided by the Department of Atmospheric Sciences, University of Wyoming. The GPS receiver records the data every 15 seconds and temporal resolution for MET data was recorded at hourly intervals, while the RS data were collected twice a day (00:00 UTC and 12:00 UTC), and comprise of temperature, pressure, humidity, wind information and PWV. For studying the irregularity or warming effects, we compared the variability of PWV with monthly precipitation rates taken from NASA's TRMM website.

From Figure 4 and Table 3, the GPS PWV agreed very well with RS PWV and displays the potential to measure PWV as well as monitoring the warming activity. The difference values between both techniques are possibly due to the GPS stations not being co-located with the RS stations. As can be seen on the right hand column of Table 3, the difference in height (ΔH_GPS&RS) between GPS and RS varied from 3.83 to 15.91 m. This difference coincidently corresponded with the correlation of PWV between GPS and RS, where the higher the position of the station, the lower the correlation. This indicates that the altitude of the station is very important because it has affected the variability of pressure and temperature. In the range of that altitude difference, many events from unknown meteorological parameters, especially the winds and the atmospheric pressure, can influence the coordinates of the system. For example, the vertical profile of a balloon can move away from the launching point with extreme weather events.

Table 4 compiles the mean value of PWV and STD for the region as defined. As shown in the table, KUAL station shows more than a 5% increment and decrement in annual PWV average, while in the other five stations the increment was less than 5%. Small changes can be seen at JHJY with annual mean and STD less than 1% and 15%, respectively. For the year 2008 and 2009, at KUAL unlike the other stations the increment of STD was more than 40% while the others are less than 20%. From a PWV and STD point of view, the southern part is seen to be more stable than the other parts. The western and northern parts give similar increment or decrement. However, the PWV values in the eastern part (KUAL) are more dynamic from year to year, especially across 2009 and 2010, where PWV variations showed flutter within a large range from 35 to 55 mm compared with GETI and PEKN.

From the figure, one could see that the possibilities of differences in PWV content in the observed region are due to topographic and local terrain features factors, which result in different evaporation rates. More than that, stations in the northern and western parts, which lie between 13 and 15 km from the coast, are more influenced by the Strait of Malacca and the urban city, while the stations located in the eastern part situated a distance less than 9 km from the South China Sea (SCS) have less precipitation. On the other hand, the southern part which is located away from the ocean (more than 45 km), receives a lower PWV compared with the western and eastern parts. The evaporation process of the ocean is probably higher than in mainland, where the sun via outgoing longwave radiation (OLR) has a significant influence (e.g., Hall & Manabe 2000).

To clarify the information of PWV affected by the warming activity, monthly accumulated precipitation from TRMM with same period as in Figure 6(a) is plotted in Figure 6(b). The maximum and the minimum peaks of this parameter are opposite to those of GPS PWV. Moreover, accumulated precipitation in November and December of every year in the eastern part is observed to be high, while the other parts were lower at about 500 mm. As seen in the figure, average accumulated precipitation for the 4 years of observation is 248.48 mm, with the minimum and the maximum values of 45.43 mm and 643.22 mm, respectively. Although the variability of accumulated precipitation is opposite to that of PWV, their trend is increasing by 11.76 mm per year. Referring to Figure 6, both trend GPS PWV and accumulated precipitation for the period of study are increased by 2.40 mm and 47.04 mm, respectively. Both parameters bring lower PWV to this region when precipitation is high. Based on these figures, the precipitation was higher every year at November and PWV is lower in the next month. The high of this precipitation is due to the beginning of the Northeast monsoon and much of the water vapor content in this season is precipitated as rain. On the other hand, the Northeast monsoon brings cool temperatures and water vapor is cumulated and forms cloud, then is transformed to raindrops. The PWV on the next month will be lower when heavy rain falls. This phenomenon affected the east coast of Peninsular Malaysia, where the eastern stations (GETI, KUAL and PEKN) showed high accumulations of precipitation.

Comparing the variation of surface temperature in Figure 2, their maximum peak for MAM (March, April, and May) of 2010 was similar to that of PWV in Figure 6(a). During this period, the trend of surface temperature and GPS PWV increased about 0.18% per year and 1.35% per year, respectively. In addition, the average PWV always drastically dropped in DJF months every year with the exception of DJF 2009/2010 when the drop was smaller. This behavior gives the warmest year for this study. As the climate warms, the temperature in the atmosphere is higher, and relative humidity is opposite to that of temperature pattern, hence PWV is expected to naturally increase (Trenberth 2011). In other words, a warmer atmosphere will hold more moisture than colder air. This clarifies the Clausius-Clapeyron equation for the relationship between temperature and water vapor changes.

This paper has shown the potential use of GPS PWV to detect warming activity in Peninsular Malaysia for the period of 2008–2011. The PWV trend in this region is in agreement with the surface temperature trend, and its natural variability was significantly dominated by the annual cycle. We found that the PWV variation is in opposite pattern to the distribution of accumulated precipitation. At the six selected stations, the northern part of Peninsular Malaysia is observed warmer, and the eastern part faced heavy rainfall during the monsoon. However, PEKN and USMP are consistently the warmest stations recorded in this study. JHJY and GETI experienced moderate warming, and KUAL the weakest. In conclusion, the results show that the warming activity has a high impact on our climate patterns with an annual cycle noted at all the stations in Peninsular Malaysia, mostly due to summer and winter monsoons. These results imply that GPS PWV with high temporal and spatial resolution is a reliable parameter to be used for studying these warming effects.

From 4 years of analysis, the trend of warming activity detected from PWV variability significant affects the region. Although the trend of surface temperature for the 8-year observation showed a smaller increase (0.05 °C per year), almost all the regions in Peninsular Malaysia are affected by global warming. To clearly measure the warming long-term effect, good quality GPS and MET data should be provided with complete time series. The comparison of warming effects in other places in Southeast Asia is also important to observe a regional pattern. The effect of warming, which can aid the forecast model, will be studied in future work by providing long-term data for detailed analysis.

This research is funded by Malaysian Ministry of Higher Education (MOHE), through Universiti Kebangsaan Malaysia (UKM) under the Long-Term Research Grant Scheme (LRGS-TD/2011/UKM/PG/01). The researcher would like to convey appreciation to Department of Survey and Mapping (JUPEM) for supplied GPS data and the Malaysian Meteorological Department (MMD) for providing the surface meteorological data. Thanks also to Department of Atmospheric Sciences, University of Wyoming for supporting the RS PWV data and NASA's Tropical Rainfall Measuring Mission (TRMM) for accumulated precipitation data.