Topography In Southeast Asia

[Orville Marquez]

SoutheastAsia provides an interesting example of some of the basic physicalfactors influencing population distribution. The two maps aboveshow the combined continental and submarine topography of southeast Asia(top) and the distribution of population (bottom). It is apparent from theelevation map that the present position of the coastline (heavy black line)is quite different from the steep submarine slope that marks the actualedge of the continent where the South China Sea deepens from 200 to 1000meters. This map emphasizes the point that coastlines areephemeral features and move significantly when sea level changes.The rugged topography of the Wuliang Shan mountains in the northwest extendssouthward into Vietnam creating a very narrow coastal plain in contrastto the much wider coastal plains to the north and east of the Gulf of Thailand.These major physiographic features in the elevation map are reflected somewhatin the adjacent population density map. Most, but not all, of the ruggedmountainous regions are very sparsely populated. The densest concentrationsof people are located along the coast and on low lying river deltas. A significantchange in regional population density can also be seen across the borderbetween Vietnam and China, north of Hainan Island.

Some of the information contained in these maps can be combined and condensedinto elevation histograms shown on the right. The distribution of populationwith elevation is quite dramatic, showing that 80 million people inSoutheast Asia live within 25 meters of sea level. It is difficultto predict the impact that a gradual 1 meter increase in sea level wouldhave on this region but it is clear that a 6 meter storm surge could bedevastating in a number of areas. Several of these areas are currently experiencingrapid population growth. The distribution of occupied land area with elevationshows that the population distribution is accommodated somewhat by the hypsographyof the continent; there is more land area available near sea level thanat any other elevation. When the population distribution is adjusted forthe available land area we can determine how average population densityvaries with elevation. Overall, sea level is still the "elevation ofchoice" with far more people per available area than any other elevationrange. Population densities in the large cities are actually much higherthan average population densities.

In summer, the TP is a heat source; it heats the atmosphere and amplifies the thermal gradient between itself and ocean to the south. One school of thought attributes the TP-induced strengthening of the Indian monsoon circulation and precipitation to this summer heating (Hahn and Manabe 1975; Kutzbach et al. 1989; Wu and Zhang 1998; Wu et al. 2012). In these studies, the changes in the thermal conditions over the TP and the importance of sensible heating on the Indian summer monsoon have formed the major focus (e.g., Yanai et al. 1992; Yanai and Li 1994; Rajagopalan and Molnar 2013). Latent heat from the Bay of Bengal also contributes to the anomalous high-tropospheric warming center around the TP (Tamura et al. 2010).

From a mechanical perspective, the TP forces the westerly jet into two branches, and it also blocks the northward transport of moisture from the Indian Ocean (Kutzbach et al. 1989; Manabe and Broccoli 1990; Broccoli and Manabe 1992). In contrast to the thermal effect, it is difficult to quantify the mechanical effect of the TP precisely. Based on numerical experiments, the Himalaya Mountains are believed to act as a barrier in isolating the northern cold dry air and thus potential thermal influence of the TP on the Indian monsoon circulation (Boos and Kuang 2010), emphasizing that the blocking effect of the Himalayas or the southern TP may be more significant than the thermal effect. Except for the mature period of the Indian monsoon, the mechanical impact of the TP is also evident in its onset and seasonal evolution (Park et al. 2012).

In most numerical experiments, the defined topography is so coarse that only the main TP can be resolved. The real TP topography is simplified and idealized, ignoring the small mountains at the margin of, and around, the main TP, which might lead to an inaccurate estimate of the real effect of the TP. For instance, the Mongolian Plateau, a smaller area of terrain located to the north of the TP, can have a marked effect on the stationary planetary wave pattern and the winter monsoon system over East Asia (Shi et al. 2015; Sha et al. 2015). Facilitated by its more northerly location, the Mongolian Plateau forces the westerly winds flowing around it to shift more northward and ultimately exerts a larger influence on the westerly jet than the TP (Shi et al. 2015). These analyses tell us that the effects of smaller terrains at sensitive locations for specific climate systems may be unexpectedly important. Given that it would be difficult for these mountains to exert similar thermal influences as the main TP because of their smaller size, we can speculate that any noticeable response of the climate system might come primarily from the mechanical effect.

In this study, the effect of the YG Plateau on the Indian summer monsoon circulation and associated precipitation, as well as its comparison to the entire TP, was evaluated using climate model experiments. The response of the anomalous heating center over the TP during the monsoon onset is also examined. The experimental design is introduced in section 2. The results are presented and discussed in sections 3 and 4, respectively. Section 5 provides a summary of the key findings.

Three numerical experiments using a general circulation model were conducted to evaluate the orographic effect of the YG Plateau on the Indian monsoon and its relative contribution compared to the TP. The model used was the Community Atmosphere Model, version 3 (CAM3), developed by the National Center for Atmospheric Research. CAM3 is an atmospheric model in which a land surface model (Community Land Model, version 3) is coupled. It performs well in its simulation of the Asian monsoon and is widely employed in monsoon research, including the examination of monsoon sensitivity to mountain topography (Shi et al. 2011; Sha et al. 2015). However, CAM3, like most climate models, is biased in its simulation of the thermodynamic structure of the Indian summer monsoon, including both the upper-tropospheric temperature and surface air moist static energy. This bias has been shown in other models to be associated with the overly smoothed topography west of the TP (Boos and Hurley 2013).

In the control experiment (TP1YG1), the modern global topography was employed. Then, in the other two runs, the entire TP topography including the YG (TP0YG0) and only the YG topography, not Tibet (TP1YG0), were removed from the global topography in sensitivity experiments. In TP0YG0, we flattened all the TP-related high terrains in the model to 400 m. In TP1YG0, we flattened only the southeastern margin of the TP where the height is greater than 800 m and less than 2000 m, flattening a maximum height of 800 m (Fig. 2). All boundary conditions except the elevation of topography and the atmospheric carbon dioxide concentration were set to present-day values in the three experiments. The Hadley Centre global sea surface temperature (SST) data (Rayner et al. 2003) are employed as the climatologically averaged SST. The atmospheric carbon dioxide concentration was kept at 280 ppmv, the preindustrial value. The changes in the vegetation cover and the boundary layer roughness associated with the modified topography and their potential climatic feedbacks are not taken into consideration. The gravity wave drag is also not altered. The horizontal resolution was T85, corresponding to approximately 1.4 1.4, which resolves the smaller YG Plateau but does not capture its details. All experiments were integrated for 15 model years after a 5-yr spinup period. The 15-yr-mean outputs were calculated and analyzed in order to evaluate the response of the Indian monsoon to the YG topography.

The control experiment performance with respect to the Indian summer monsoon, including the monsoonal circulation and precipitation, was examined first using ERA-Interim with a resolution of 0.75 0.75 (Dee et al. 2011; Fig. 1). In the TP1YG1 experiment, the simulated 850-hPa wind vectors presented a similar circulation pattern as observed over the Indian monsoon region, with a few notable differences. In the northern Bay of Bengal, the simulated westerly winds turned northward to the YG Plateau (Fig. 1b), but they turn too far northward such that they are southerly with almost no branched westerly component. These southerly winds appear to intersect the TP and get branched toward the YG rather than flowing straight to the YG. This bias might somewhat affect our evaluation of the YG topography. Another bias is that the main westerly winds observed around the southwestern TP were not captured by the model; instead it simulates easterly winds in this region. However, overall the model can successfully capture the relevant circulation phenomena, in particular that the Indian monsoonal winds flow around the YG Plateau when facing it, allowing us to evaluate the climatic effect of this topography. The modeled and observed distribution of summer precipitation rates, associated with the Indian monsoon circulation, were also in general qualitative agreement. The modeled absolute value of the simulated precipitation maximum was larger over the eastern Arabian Sea, and the precipitation center over the Bay of Bengal is located too far to the southwest.

The responses of seasonal precipitation over the Indian monsoon region to the YG topography and the entire TP were examined first (Fig. 3). Compared to that in the TP1YG0 experiment, April to August precipitation is consistently suppressed in the TP1YG1 experiment (Fig. 3a), indicating that the YG topography weakens the Indian monsoon precipitation during both the mature monsoon period and the monsoon onset. However, the precipitation anomalies between the TP1YG1 and TP1YG0 experiments become positive in the non-summer-monsoon months (September to November and January to March) other than December. As a result, the seasonality of the Indian monsoon climate is amplified in the TP1YG0 experiment, compared with TP1YG1. This effect of the YG topography is different from that of the entire TP, shown as the difference between the TP1YG1 and TP0YG0 experiments, which tends to intensify the precipitation throughout the whole year. The most sensitive response of precipitation to the TP occurs mainly during the monsoon onset (May and June), which supports the view that the onset of the Indian monsoon is closely associated with the thermal and mechanical change of the TP (Yanai et al. 1992; Wu and Zhang 1998; Park et al. 2012; Tamura et al. 2010).

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