Figure 11-7: Spatial distribution of changes in monsoon rainfall over Indian subcontinent as simulated by Hadley Centre's global and regional climate models at the time of doubling of CO2 in the atmosphere.
Figure 11-7: Spatial distribution of changes in monsoon rainfall over Indian subcontinent as simulated by Hadley Centre's global and regional climate models at the time of doubling of CO2 in the atmosphere. |
Although these AOGCMs treat the complex interactions of atmospheric physics and planetary-scale dynamics fairly well, coarse horizontal resolution in the models restricts realistic simulation of climatic details on spatial variability. For example, tropical precipitation has high temporal and spatial variability, which cannot be resolved realistically in currently available AOGCMs. Many investigations on the ability of GCMs to simulate the Asian monsoon have been reported in the literature (e.g., Meehl and Washington, 1993; Chakraborty and Lal, 1994; Bhaskaran et al., 1995; Lal et al., 1995a, 1997, 1998a,b). These studies suggest that although most GCMs are able to simulate the large-scale monsoon circulation well, generally they are less successful with the summer monsoon rainfall. Since the SAR, nested modeling approaches have been followed to generate high-resolution regional climate scenarios (Jones et al., 1995; Lal et al., 1998c; Hassell and Jones, 1999) with more realistic mesoscale details and the response of GHG forcings to the surface climatology over the Asian monsoon region.
Large-scale patterns of temperature change simulated by GCMs and nested regional climate models (RCMs) are found to be generally similar under 2xCO2 forcing, but the regional model results present some additional details associated with coastline and local topographical features (Hirakuchi and Giorgi, 1995). In addition, projected warming over eastern China region in the summer is less pronounced in the RCM than in the GCM and is characterized by a different spatial pattern. This is related to an increase in monsoon precipitation simulated by the RCM there and associated surface cooling induced by evaporation and cloudiness. Nonetheless, the GCM and RCM simulations suggest a general increase in warming toward higher latitudes and greater warming in winter than in summer. The RCM produces a more pronounced increase in winter precipitation over southeastern China than does the GCM in response to orographic lifting of stronger low-level southerly onshore winds. The RCM also simulates increased precipitation in the monsoon rain belt over east China, Korea, and Japan during the summer.
The increase in surface air temperature simulated by the RCM over central and northern India is not as intense as in the GCM and does not extend as far south (Lal et al., 1998c; Hassell and Jones, 1999). These anomalies are linked with changes in surface hydrological variables. Summer precipitation exhibits a more complex pattern of increases and decreases. Whereas an increase in rainfall is simulated over the eastern region of India, northwestern deserts see a small decrease in the absolute amount of rainfall in RCM simulation (Figure 11-7). Changes in soil moisture broadly follow those in precipitation except in eastern India, where they decrease as a result of enhanced drainage from the soil. The largest reductions (precipitation reduced to <1 mm day-1; 60% decline in soil moisture) are simulated in the arid regions of northwest India and Pakistan. The projected increase in precipitation in flood-prone Bangladesh is approximately 20%. Nested RCM simulations have the potential to simulate the onset of the summer monsoon and its active/break cycle over India. The RCM captures the observed precipitation maximum over the southern tip of India during weak monsoon conditions, whereas the GCM does not.
Given the current state of climate modeling, projections of future regional climate have only limited confidence. The degree of confidence that could be attributed to RCM responses in terms of temporal and spatial changes resulting from GHG forcings would depend on more accurate simulation of the space and time evolution of large-scale monsoon circulation features in AOGCMs, as well as additional long-term RCM simulations with better skill. Current efforts on climate variability and climate change studies increasingly rely on diurnal, seasonal, latitudinal, and vertical patterns of temperature trends to provide evidence for anthropogenic signatures. Such approaches require increasingly detailed understanding of the spatial variability of all forcing mechanisms and their connections to global, hemispheric, and regional responses. Because the anthropogenic aerosol burden in the troposphere would have large spatial and temporal variations in the atmosphere, its future impact on regional scale would be in striking contrast to the impact from GHGs. It has also been suggested that aerosols produced by tropical biomass burning could lead to additional negative radiative forcing (Portmann et al., 1997). Considerable uncertainty prevails about the indirect effect of aerosols on tropospheric clouds, which could strongly modulate the climate. The implications of localized radiative forcing on deep convection in tropical Asia and on Hadley circulation are still not understood (Lal et al., 2000).
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