1. Introduction
Tropical vegetation controls the physical and biogeochemical interactions over climatically influential areas on the earth and plays important roles in the formation of the regional and global climates. Until recently, there have been numerous studies concerning the impact of vegetation change in the tropical region. There have been, however, few numerical impact studies that target the influence of vegetation change in the Asian tropical region.
In the present study, using a global climate model that includes a realistic land surface model, several numerical simulations were performed to investigate the impact of Asian tropical vegetation change on the climate. Henderson-Sellers et al. (1993) and Zhang et al. (1996a,b) conducted examinations of the impact of the deforestation of the moist forest in Southeast Asia. The resolution of the model used in the experiments, however, was coarse, and the period of model integration for the experiment was short compared with the present study.
The control simulation, under conditions of the actual vegetation, and three vegetation-change impact simulations were performed in the present study. The results of the impact experiments were compared with those of the control run. The horizontal resolution of the model was 1.875°. The time periods of the control and each experimental integration were 30 yr, with the last 20 yr of model data analyzed.
In Mabuchi et al. (2005, hereafter referred to as Part I), which is a companion of this paper, the results of the Northern Hemisphere summer (June–July–August) were described. In the present paper, the results of the analysis concern the Northern Hemisphere winter, that is, the December–January–February (DJF) case. The possibility of the influence of vegetation change on the midlatitude atmospheric circulation is also discussed. Hereafter, the present paper is referred to as Part II.
Section 2 briefly describes the model and experimental design used in Part II. Section 3 presents several results, and the overall discussion is given in section 4.
2. Model description and experimental design
In this section, the model structure and the experimental design of the study are briefly reviewed. For further details, the reader should refer to Part I.
The atmospheric model used in the present experiment is the spectral general circulation model developed by the Japan Meteorological Agency (JMA). This general circulation model has a triangular truncation at wavenumber 63 (T63) and employs hybrid vertical coordinates at 21 levels. The horizontal resolution is 1.875° (192 × 96 grid points). The basic equations adopted in the model are the primitive equations. The prognostic variables of the atmosphere are temperature, specific humidity, divergence and vorticity of the wind, the carbon dioxide concentration in each atmospheric layer, and surface pressure. The model includes the short- and longwave radiation processes. Large-scale precipitation and convective precipitation are estimated separately, with convective precipitation calculated by the Kuo (1974) scheme. Vertical diffusion is calculated by the turbulent closure model (level 2.0) proposed by Mellor and Yamada (1974).
The Biosphere–Atmosphere Interaction model (BAIM), a land surface model (Mabuchi et al. 1997), was integrated into the general circulation model. The type of vegetation at each model grid point is specified, and the interactions between the land surface vegetation and the atmosphere are estimated by the BAIM at each grid point. The BAIM has two vegetation layers and three soil layers and predicts the temperature and stored moisture in each layer. The photosynthesis processes for C3 and C4 plants are adopted in the model. The model can also predict the ground accumulation and melting of snow and the freezing and melting of water in the soil.
The vegetation type of each model grid point was fundamentally derived from the Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation dataset (Olson et al. 1983) (see Fig. 1 of Part I). The actual vegetation of a given global land surface grid point was classified into 1 of 12 types, including the desert and cryosphere. In the present experiment, crop-type vegetation was regarded as the grassland type of vegetation. The major parameter values (e.g., leaf area index or vegetation height, etc.) for each vegetation type were derived from Dorman and Sellers (1989). Several modifications were made to these parameter values to conform to the general circulation model.
To investigate the impact of Asian tropical vegetation changes on the climate, three experimental areas were defined, namely, the Indian subcontinent area (IND), the Indochina peninsula area (ICP), and the Maritime Continent area (MTC; see Fig. 1 of Part I). The IND, ICP, and MTC areas are covered mainly by grassland, tropical seasonal forest, and tropical rain forest types of vegetation, respectively. The photosynthesis process for the grass of the actual vegetation in the experimental areas is assumed as the C3 type.
Prior to the vegetation-change impact experiments, a control time integration was performed. In this control integration (CN), the actual global vegetation and the climatic SST values were used. To estimate the initial values of soil water content, including the ice content in the soil and soil temperature, a 10-yr model spinup calculation was carried out. Using the soil values obtained by the spinup calculation, the control time integration was continued for 20 yr.
After the control time integration, three vegetation-change impact experiments, namely, the bare soil (BS), C4 grass (C4), and green-less (GR) experiments, were carried out. In the GR experiment, the types of vegetation in the experimental areas were not changed, but the greenness values of the vegetation in these areas were all set to zero. In the other two experiments, the actual types of vegetation in the experimental areas (the IND, ICP, and MTC areas) were changed to a single vegetation type for each of the impact experiments. In each impact experiment, a 10-yr spinup calculation was first performed, starting from the conditions in the soil at the end of the control run, and then the main experimental impact time integration was continued for 20 yr under the changed vegetation conditions. The results of these three 20-yr impact time integrations were compared with the results from the 20-yr control integration. The analysis is generally performed on the 20-yr mean values of the DJF seasonal mean values.
3. Results
a. Verification of the results of the model control integration
Figures 1 and 2 indicate the comparison of the results of the model control integration with the analysis data for the DJF mean. The analysis data used in the verification is the global objective analysis data compiled by the JMA. The grid resolution of the analysis data is 1.875°.
In Fig. 1, the model sea surface pressure in the Northern Hemisphere is somewhat lower over the Aleutian Islands and higher on the Asian continent than those found in the analysis data. In the Southern Hemisphere, the model values are somewhat lower on the Antarctic continent and higher over the ocean. In general, as was found in the JJA case (Part I), the contrast of the pressure values of the model between the ocean and continent is clearer than those in the analysis data. For the surface wind vectors (Fig. 2), the differences between the model results and the analysis data reflect the differences in the values of sea surface pressure.
Although the figures are not shown, the 500-hPa geopotential heights of the model exhibit slightly higher values over the low latitudes and lower values over the Aleutian Islands than those found in the analysis data. The distribution patterns of the model results, however, are reasonable. Although there are a number of differences that reflect the geopotential height differences, the model wind vector patterns at 500 hPa are also reasonable (not shown).
Figure 3 indicates the comparison of the model precipitation with the Center for Climate Prediction (CPC) Merged Analysis of Precipitation (CMAP) data (Xie and Arkin 1997). Compared with the CMAP data, the values of model precipitation are generally small over the Indian Ocean to the area over the South Pacific convergence zone (SPCZ). The precipitation distribution pattern of the model, however, roughly agrees with the CMAP data and the consistency found in the DJF results is better than that in JJA (Part I).
b. Impact of the vegetation change on the climate
1) Changes of the surface albedo and roughness length
The results of the three impact experiments, the BS, C4, and GR, are compared with the results of the control run. Table 1 indicates the comparison of experimental-area mean values of the vegetation parameters employed in the control and each impact experiment. Table 2 indicates the comparison of the experimental-area means of the calculated physical values for each simulation. The parameter values of transmittance and reflectance of the vegetation used in the simulations can be found in Table 1 of Part I.
The general features of the change in vegetation from the actual vegetation (CN) to BS for DJF are almost the same as those found in JJA (Part I). The surface albedo values significantly increase in the areas where the actual vegetation was the forest type and significantly decrease in the areas where the actual vegetation was grassland. In the IND area, the actual vegetation was mainly grassland, and the albedo values decrease over the entire area. In the ICP area, the albedo values in the areas where the actual vegetation type was seasonal rain forest increase, and those in the areas where the original vegetation type was grassland decrease. In the MTC area, the main vegetation type was tropical rain forest, and albedo values increase in most places when changed to bare soil. In the present study, the value of soil surface reflectance for the BS experiment was set to the value for soil in a forest (not for desert). Therefore, the albedo values decreased when changed from grassland to bare soil.
The difference pattern in the DJF when changing the vegetation from CN to C4 is also similar to that in JJA. The albedo values in the area where the actual vegetation type was grassland do not change, while those in the area where the actual vegetation type was forest significantly increase. The area mean albedo in the IND area of the C4 experiment is almost the same as that of the CN, while those in the ICP and MTC areas are greater than that in the CN.
In the CN of this study, the greenness values of the grassland and seasonal forest were reduced to almost zero during DJF in the Northern Hemisphere. Therefore, in the GR experiment, the albedo values in the IND and ICP areas were almost the same as those in the CN. These results may be somewhat extreme compared with the actual situation. In the MTC area, originally covered mainly by evergreen tropical rain forest, the GR albedo values significantly decrease for the same reason as in the JJA case. Although the reflectance of a dead leaf or stem for visible radiation is greater than that of a green leaf, the reflectance of a dead leaf or stem for near-infrared radiation is less than that of a green leaf. In addition, the transmittances of a dead leaf or stem are very small (see Table 1 of Part I). As a result of these effects, the albedo value for the forest of the MTC area in the GR experiment decreases as a whole compared with that in the control.
The roughness length difference patterns between each experiment and the control for DJF are almost the same as those found in the JJA case. By the change of vegetation from the actual vegetation to bare soil (BS experiment), the roughness lengths in the MTC and ICP areas decrease significantly. Although the value of the change is small, the roughness length in the IND area also significantly decreases. In the C4 experiment, while the roughness length values in the area where the vegetation was grassland do not change, those in the area where the vegetation was the forest type significantly decrease. Consequently, the changes in the roughness length in the C4 experiment are similar to those in the BS experiment. In the GR experiment, the morphological parameter values of the vegetation are not changed. Therefore, the roughness lengths do not change in each experimental area.
2) Impact on the heat and water balances at the land surface
Impacts on the heat and water balances for each experimental area were examined. From the results of Student’s t test, the changes that appeared in each area were generally statistically significant.
In the BS experiment, the net radiation values in the areas where the actual vegetation type was forest decrease because of the increased albedo values in these areas (Table 2). On the other hand, the net radiation values in the areas where the actual vegetation type was grassland increase because of decreased albedo values. This difference pattern is fundamentally the same as that found in the JJA case. The latent heat fluxes in the experimental areas have a tendency to increase because of the fact that while the fluxes by transpiration and interception decrease, the flux by direct evaporation from the soil surface increases. The increase in the direct evaporation from the soil surface is related to the increase in the surface wind speed over the land in the experimental areas. This feature is the same as that in the JJA case (Part I). The difference found in the ICP area is small compared with the JJA case, because of the relatively small DJF latent heat flux in this area. However, the overall patterns in the results are the same as those in the JJA case. The pattern of change in the sensible heat fluxes in the experimental areas is generally opposite to that of the latent heat fluxes. In the MTC area, soil surface temperatures increase as a result of the increase in the radiation that reaches the soil surface from the increase in the shortwave radiation (decrease in precipitation), and the removal of the canopy. The increase in the IND area is due to both the decreased albedo and the removal of the canopy. The temperature increase in the ICP area is relatively small because of the advection of cold air from the northern inland region. This DJF temperature difference pattern in the ICP area differs from that found in the JJA case. The pattern of change in the soil water content fundamentally corresponds with that of precipitation. The changes in the soil water content vary according to locality, and in the IND area the effects of the precipitation change in JJA also remain. The mean values increase in all experimental areas.
In the C4 experiment, the same as in JJA, the decreases in the net radiation in the areas where the actual vegetation was forest are significant because of the increased albedo values. The changes in the areas where the actual vegetation was grassland are not significant. The latent heat fluxes in the forest areas generally decrease as a result of the decreased net radiation and decreased roughness lengths. The change in the latent heat fluxes in the IND area is not significant, since the physiological activity of vegetation is weak during DJF. The decreases in the sensible heat fluxes in the ICP and MTC areas are due to the decreases in the net radiation. The change in the IND area is not significant. In DJF, the patterns of changes in the canopy temperature and the soil surface temperature are almost the same. The decreases of temperatures in the ICP and IND areas are due to the decreased net radiation. The cold-air advection from the northern inland region also influences the temperature in the ICP area. In the MTC, the latent heat fluxes by the transpiration and the evaporation of intercepted water decrease; consequently the canopy temperature increases. Although the net radiation over the total vegetation layer in the MTC area decreases, the radiation absorbed by the soil surface increases. Therefore the soil surface temperature increases. The IND area mean soil water content decreases because of the decrease in the northwestern part of the IND. It is considered that the effects of the increased latent heat flux in JJA in this area continue into DJF. In the MTC area, the soil water content decreases as a result of the decrease in precipitation. In the ICP, precipitation and the latent heat flux both decrease; consequently the change in the soil water content in the area is small when compared with that in the control run. The tendency of the change in the DJF soil water content in each experimental area is generally the same as in JJA (Part I).
In the GR experiment, the greenness values were all set to zero, while the greenness values of the grassland and seasonal forest in the IND and ICP areas decrease in DJF during the control run. Therefore, the changes in the net radiation fluxes, the latent and sensible heat fluxes in the IND and ICP areas, are generally not significant. In the MTC area, precipitation significantly increases and the downward shortwave radiation decreases. Therefore, although the albedo decreases, the net radiation decreases. The latent heat flux in the MTC area decreases as a result of the decrease in transpiration from the leaves of vegetation, while the sensible heat flux increases because of the decreases in transpiration. While the temperature changes in the canopy and soil surface of the IND and ICP area are not significant, in the MTC area, these temperatures clearly increase as a result of the decrease in the latent heat flux. The soil water content in the MTC increases because of the increase in precipitation and the decrease in the latent heat flux. The change in soil water content in the ICP is small. In the northwestern part of the IND, the soil water content increases as a result of the increased precipitation during JJA. In each experimental-area mean, the values of soil water in the MTC and IND areas significantly increase, and the change of that in the ICP is small. The tendency of the change in soil water content in each experimental area in DJF is generally the same as that in the JJA case (Part I).
3) Impact on the atmospheric circulation
In this section, the impact of the three vegetation changes on the DJF atmospheric circulation is discussed. The possibility of an influence on the midlatitude circulation is also discussed.
(i) Impact on the low-latitude atmospheric circulation
Although the figure is not shown, the global-scale distribution patterns of the divergent/convergent wind by the model control integration are as follows. In the DJF season, at the lower atmospheric level, core convergence areas are found over the western equatorial Pacific in the Southern Hemisphere (the SPCZ), over the South American continent, and over the southern part of the African continent. Convergence into the Aleutian low also exists over the northern part of the North Pacific. At the upper atmospheric level, core divergence areas are found in the areas corresponding to the lower-atmospheric-level convergence areas. These patterns of the model atmospheric circulation generally agree with those of observed data (not shown).
Figures 4 –9 show the comparisons of the DJF mean atmospheric circulations simulated by the impact experiments with those of the control integration (impact–control). Figures 4 and 5 indicate the differences between the BS experiment and the CN (BS–CN), Figs. 6 and 7 those between C4 and CN (C4–CN), and Figs. 8 and 9 those between GR and CN (GR–CN). Furthermore, the comparisons of the DJF mean precipitation for the impact experiments with that of the control integration (impact–control) are indicated in Figs. 10–12.
In Fig. 4 (BS–CN), the direct effect of the vegetation change is revealed as the strengthening of the northeasterly wind over the ICP area, the westerly wind over the islands of the MTC area, and the easterly wind over the northern equatorial Pacific. This strengthening of the winds is due to the decrease in the roughness lengths by the vegetation change in the experimental areas (see Table 2). These difference patterns also exist at the 850-hPa level and remain over the MTC area at the 700-hPa level (figures are not shown). The strengthening of the winds induces the strengthening of the low-level atmospheric convergence over the central equatorial Pacific and over the SPCZ (upper panel in Fig. 5). Over the ICP and MTC, although not significant, divergence anomalies are found. At the 250-hPa level (lower panel in Fig. 5), the areas where the divergence strengthens spread from the central equatorial Pacific to over Japan. These anomalies are related to the strengthening of the low-level convergence. Although the figures are not shown, ascending anomalies exist at the 500-hPa level over the low-level areas of stronger convergence, and descending anomalies are found over the islands of the MTC. These changes in the atmospheric circulation induce changes in the precipitation. In Fig. 10, the precipitation significantly increases over the western part of the Indochina peninsula, the central equatorial Pacific, and the SPCZ. On the other hand, the precipitation significantly decreases over the eastern part of the Indochina peninsula and the islands of the MTC.
In Fig. 6 (C4–CN), although areas of significant differences of the winds are less than those in Fig. 4, the wind anomaly pattern in the C4 experiment is fundamentally the same as in the BS case. Difference patterns also exist over the MTC area at the 850-hPa level. As in the BS experiment, the roughness lengths in the C4 experimental areas also decrease when compared with the control run, especially in the ICP and MTC areas. Compared with the BS case, the low-level convergence anomalies and upper-level divergence anomalies over the central equatorial Pacific and SPCZ are weaker, while the low-level divergence anomalies and the upper-level convergence anomalies over the ICP and MTC areas are more intense (Fig. 7). The effects of the change in the roughness length on the wind field in the C4 experiment are weaker than those in the BS experiment, as a result of the magnitude of the roughness length decrease in the C4 experiment being less than that in the BS experiment. The pattern of the change in precipitation in the C4 case is also fundamentally the same as that in the BS case (Fig. 11). The magnitudes of the decreases in the ICP and MTC precipitation are greater than those in the BS case. The reason for these results is considered as follows. The albedo values in these areas significantly increase in the C4 experiment. The net radiation, the latent heat flux, and the sensible heat flux all decrease. Therefore, the local convective activity is suppressed. These results were also found in the JJA case (Part I).
In Fig. 8 (GR–CN), the DJF pattern of the change in atmospheric circulation differs from those of the other experiments. In the GR experiment, wind anomalies such as those in the BS and C4 experiments do not exist, while wind anomalies are mainly found over the islands of the MTC. These anomalies remain at the 850-hPa level. In Fig. 9, the GR anomaly pattern of the atmospheric circulation is fundamentally the same as in JJA, but the low-level convergence and upper-level divergence anomalies that are considered as direct effects of the vegetation change are limited to over the islands of the MTC. The reason for this is considered that the influence of vegetation change in the GR experiment on the DJF circulation is mainly confined to the islands of the MTC (see Table 2). In Fig. 12, GR precipitation increases over the islands of the MTC and decreases over the surrounding areas. This precipitation anomaly over the MTC is opposite of those anomalies found in the BS and C4 experiments. The reason for this precipitation anomaly is considered to be the same as that in JJA. In the GR experiment, the roughness lengths in the experimental areas do not change. Therefore, the effects due to changes in the roughness length on the wind field such as in the BS or C4 experiments are not found. On the other hand, the temperatures of the canopy and the soil surface both increase, and the sensible heat flux increases, as a result of the decrease in the latent heat flux by transpiration from the leaves of vegetation in the forest areas of the MTC. The islands of the Maritime Continent are surrounded by the ocean and have a sufficient supply of water vapor. Under these conditions, the low-level convergence strengthens over the Maritime Continent islands, and convective precipitation increases.
(ii) Impact on the midlatitude atmospheric circulation
There have been several studies on the effects of vegetation changes on the atmospheric circulation. The studies of Chase et al. (1996, 2000 and Zhao et al. (2001) investigated the effect of land cover change on the global atmospheric circulation. These studies simulated the impacts of the difference between actual vegetation conditions and potential vegetation conditions on climate. These studies indicated that the land cover changes in the Tropics induce changes in the extratropic atmospheric circulation, especially in the winter season. Gedney and Valdes (2000) showed that complete Amazonian deforestation could result in changes in the climate far afield from the region of deforestation. In particular, the model predicted statistically significant changes to winter rainfall over the North Atlantic, extending toward western Europe. Werth and Avissar (2002) also detected a noticeable impact of the Amazon deforestation in several other regions of the world, several of which showed a reduction in rainy season precipitation that exhibited a high signal-to-noise ratio.
Among other vegetation-change studies, Zhang et al. (1996a,b) performed numerical simulations of the potential impact of tropical deforestation in South America, Africa, and Southeast Asia using a climate model coupled with a realistic land surface model. Zhang et al. (1996b) discussed the influence of tropical deforestation on the large-scale climate system. It was concluded that the modification of the model surface parameters to simulate tropical deforestation produced significant modifications in both the Hadley and Walker circulations. A mechanism for the propagation of disturbances arising from tropical deforestation to middle and high latitudes was proposed, based on the mechanisms of Rossby wave propagation.
These mechanisms are similar to those associated with extratropical influences of ENSO events. There have been numerous studies of the global teleconnections associated with the tropical sea surface temperatures (SSTs), for example, Horel and Wallace (1981), Trenberth and Hurrell (1994), Latif and Barnett (1994), Hurrell (1996), Zhang et al. (1997), Mantua et al. (1997), Renshaw et al. (1998), Gershunov and Barnett (1998), Enfield and Mestas-Nunez (1999), Livezey and Smith (1999), and Kobayashi et al. (2000). In the tropical atmosphere, anomalous SSTs force anomalies in convection and large-scale overturning, with subsidence in the descending branch of the local Hadley circulation. The resulting strong upper-tropospheric divergence in the Tropics and convergence in the subtropics act as a Rossby wave source. The climatological stationary planetary waves and associated jet streams, especially in the Northern Hemisphere, can make the total Rossby wave sources somewhat insensitive to the position of the tropical heating that induces them and thus can create preferred teleconnection response patterns, such as the Pacific–North American (PNA) pattern. Anomalous SSTs and tropical forcing have tended to be strongest in the northern winter, and teleconnections in the Southern Hemisphere are weaker and more variable and thus more inclined to be masked by the natural variability of the atmosphere (Trenberth et al. 1998).
In the present study, impacts of the deforestation in the Asian tropical region on the midlatitude atmospheric circulation were also examined. The C4 experiment in this study is the most realistic case of deforestation among the three impact experiments. Therefore the influences of the vegetation changes in the C4 experiment on the midlatitude atmospheric circulation were examined. In the C4 experiment, which differs from previous studies, the vegetation changes were only applied in the Asian tropical region, while the vegetation in South America and Africa were maintained as the actual vegetation. There is, however, the possibility of an influence of the vegetation changes of only those in the Asian tropical region on the midlatitude atmospheric circulation.
In Fig. 7 (C4–CN), additional results are found of changes in the midlatitude circulation that may be considered as resulting from the vegetation change in the Asian tropical region. There are areas of significant differences of the wind, not only over the ICP and MTC, but also around Japan and over the Atlantic Ocean. At the lower atmospheric level, with significant convergence anomalies found over the central equatorial Pacific and divergence anomalies over the ICP and MTC areas, there are significant divergence anomalies over the Atlantic Ocean that coincide with significant wind differences over the same area. At the upper atmospheric level, although not statistically significant, convergence anomalies also exist over the Atlantic Ocean. The same anomaly patterns exist more clearly in Fig. 5 (BS–CN) but are not found in Fig. 9 (GR–CN). Therefore, it is considered that these atmospheric circulation anomalies are due to modifications of the Hadley and Walker circulations and are induced by the vegetation changes (morphological, physiological, and physical changes from forest to grassland or bare soil) in the Asian tropical region. In particular, the divergence/convergence anomaly pattern that appears at the upper atmospheric level in the C4 experiment (lower panel in Fig. 7) is very similar to that of an ENSO event (see Fig. 3 of Trenberth et al. 1998).
Figure 13 indicates the DJF differences of the 500-hPa geopotential heights between C4 and CN (C4–CN). Over the Northern Hemisphere, areas of positive difference exist from Japan to Europe, and areas of negative difference are found over the Aleutian Islands to Greenland. Statistically significant areas of positive differences exist over the western part of the northern midlatitudes of the Pacific Ocean and the northern midlatitudes of the Atlantic Ocean. Over Greenland, an area of statistically significant negative differences can be seen. These height anomalies at the 500-hPa level are similar to those found during an ENSO event. Therefore, the possibility exists that the deforestation in the Asian tropical region induces teleconnections similar to those associated with ENSO events.
4. Summary and discussion
In the present paper, as a companion paper to Part I, the results of the analysis of the Northern Hemisphere winter (DJF) case were discussed as Part II. The possibility of an influence of vegetation change on the midlatitude atmospheric circulation was also discussed.
The general features of the DJF mean surface albedo, roughness lengths, and energy balances for the change of vegetation from the actual vegetation (CN) to bare soil (BS) were similar to those in the JJA case. The temperature increase in the ICP area was relatively small because of the advection of cold air from the northern inland region. This DJF temperature difference pattern in the ICP differed from that found in the JJA case. The pattern of change in the soil water content fundamentally corresponded with that of precipitation. In the IND area, the effect of changes in the JJA precipitation also remained. The surface winds over the experimental areas were generally stronger because of the decreased roughness lengths in the experimental areas. This strengthening of the winds induced strengthening of the low-level convergence over the central equatorial Pacific and over the SPCZ. These patterns differed from those in the JJA case. These atmospheric circulation changes induced changes in precipitation. Precipitation significantly increased over the western part of the Indochina peninsula, the central equatorial Pacific, and the SPCZ. On the other hand, precipitation significantly decreased over the eastern part of the Indochina peninsula, and over the islands of the MTC. The decreased precipitation over the islands of the MTC was the same as that found in the JJA case.
In the C4 experiment, the vegetation was changed from the actual vegetation to C4 grassland. Among the three impact experiments conducted in the present study, the assumptions applied in this experiment were most similar to those in other deforestation experiments, except that the C4 photosynthesis process was used. In the results from Henderson-Sellers et al. (1993), during the dry season (January), significant decreased evaporation and net radiation were indicated over land points. The changes in the surface temperatures and precipitation, however, were not statistically significant. In their experiment, the impact of the vegetation change in Southeast Asia on the atmospheric circulation was also weak. Zhang et al. (1996a) found that the evapotranspiration and net radiation indicated statistically significant decreases, but precipitation changes were not statistically significant. These results were almost the same as those of Henderson-Sellers et al. (1993). The present results for DJF are somewhat different from those of the above-mentioned studies. The results of the present C4 experiment indicated statistically significant differences. The net radiation and the latent heat fluxes in the forest areas generally decreased. The temperatures in the ICP and IND areas decreased. Cold-air advection from the northern inland region also influenced the temperature in the ICP area. In the MTC area, the latent heat fluxes decreased; consequently the temperature increased. Although the areas of significant differences in the winds were smaller, the wind anomaly pattern in the C4 experiment was fundamentally the same as that in the BS case. The pattern of change in precipitation in the C4 experiment was also fundamentally the same as that in the BS case. The magnitudes of the decreases in precipitation in the ICP and MTC areas were greater than those in the BS case.
In the GR experiment, precipitation significantly increased and the downward shortwave radiation decreased in the MTC area. Therefore, the value of the net radiation decreased. The latent heat flux in the MTC area decreased as a result of the decreased transpiration from the leaves of vegetation, while the sensible heat flux increased due to the decreased transpiration. In the MTC area, the temperatures clearly increased as a result of the decreased latent heat flux. The soil water content in the MTC area increased due to the increased precipitation and the decreased latent heat flux. Also in the GR experiment, wind anomalies were mainly found over the islands of the MTC. The low-level convergence anomalies and the upper-level divergence anomalies, considered as direct effects of the vegetation changes, were limited to the islands of the MTC. The reason for these results was that the influences of vegetation change in the GR experiment for DJF mainly existed over the islands of the MTC.
Over the islands of the MTC, precipitation in the BS and C4 experiments indicated statistically significant decreases, and that in the GR experiment indicated statistically significant increases compared with the CN. These tendencies were the same in the JJA and DJF cases and are characteristic results of the present study.
In Fig. 3, compared with the CMAP data, the values of model precipitation were generally small over the area of the Indian Ocean to over the South Pacific convergence zone (SPCZ). The precipitation distribution pattern of the model, however, roughly agreed with the CMAP data, and the consistency in the DJF results was better than that in JJA (Part I). The model was found to reproduce the potential pattern of precipitation in the tropical area, and it was also possible that the model reproduced the precipitation mechanism in that area. Therefore, it was considered that the results of the impact experiments indicated mechanisms of the potential effect of vegetation changes on the atmospheric circulation.
In the present C4 experiment, vegetation changes were assumed only in the Asian tropical region. However, it was possible that the vegetation changes influenced the midlatitude atmospheric circulation. In the comparison of the wind field between the C4 experiment and CN run, it was considered that the atmospheric circulation anomalies that appeared in the C4 experiment were due to modifications of the Hadley and Walker circulations. These modifications were induced by the vegetation change from forest to grassland in the Asian tropical region. In particular, the divergence/convergence anomaly pattern that appeared at the upper atmospheric level in the C4 experiment was very similar to that of an ENSO event. In the differences of the DJF mean 500-hPa geopotential heights between the C4 and CN, the height anomalies at the 500-hPa level were similar to those of an ENSO event. Although the figure was not shown, the DJF surface temperatures over the sea area near the Japanese islands were higher than those of the control run. This result also corresponded to the feature found during an ENSO event. Although it is difficult to determine a clear view of the interaction mechanism, the possibility exists that the deforestation of the Asian tropical region could induce similar teleconnections as those associated with an ENSO event.
In the present studies (Part I and Part II), the investigation was focused on meteorological phenomena. The carbon balance at the land surface, and the carbon dioxide circulation between the land surface and the atmosphere are also strongly influenced by vegetation change. A study of the carbon circulation will be performed in a future paper.
A more detailed investigation using a fine-resolution regional climate model will be useful in order to understand the mechanisms of the heterogeneous land surface and to examine local influences. An investigation concerning the mechanisms of the feedback impact of climate change on the vegetation change is also necessary. The interactions between the land surface ecosystem and climate are nonlinear and very complicated. Therefore, it is of great importance to continue research on the interactions between the land surface and the atmosphere.
Acknowledgments
The authors wish to thank Prof. Takehisa Oikawa of the University of Tsukuba, Prof. Tatsuo Sweda of Ehime University, Dr. Susumu Yamamoto, and Dr. Nobuko Saigusa of the National Institute of Advanced Industrial Science and Technology for many helpful suggestions and discussion. Special thanks are extended to Prof. Tetsuzo Yasunari of Nagoya University and Prof. Masahiro Amano of Waseda University for helpful suggestions. Two anonymous reviewers provided helpful comments for improving the quality of this paper. This research was partially supported by the Funds for the Promotion of Surveys and Research in Earth Science and Technologies and Ocean Development of the Science and Technology Agency and was also supported by the Grants-in-Aid for Scientific Research 14208062 of the Ministry of Education, Culture, Sports, Science and Technology. The model computations were performed on the HITACH S3800 and SR8000 computers.
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Comparison of the DJF mean sea surface pressure (hPa) calculated by the model control integration with that of the analysis data. (top) The analysis data and (bottom) the model results. Values greater than 1015 hPa are shaded.
Citation: Journal of Climate 18, 3; 10.1175/JCLI-3274.1
The same as in Fig. 1, except for the surface wind vectors.
Citation: Journal of Climate 18, 3; 10.1175/JCLI-3274.1
Comparison of the DJF mean precipitation (mm day−1) calculated by the model control integration with that of the CMAP data. (top) The CMAP data and (bottom) the model results. Values greater than 6 mm day−1 are shaded.
Citation: Journal of Climate 18, 3; 10.1175/JCLI-3274.1
Comparison of the DJF mean results of the impact experiments with those of the control integration (impact–control). The differences in the surface wind vectors between BS and CN are indicated. The areas where the Student’s t-test values indicate statistically significant differences (at the 95% level) are shaded.
Citation: Journal of Climate 18, 3; 10.1175/JCLI-3274.1
The same as in Fig. 4, except for the velocity potential (10 6 m 2 s–1) and the divergence/convergence of wind vectors. The results at the (top) surface and (bottom) 250-hPa level.
Citation: Journal of Climate 18, 3; 10.1175/JCLI-3274.1
The same as in Fig. 4, except for the differences between C4 and CN.
Citation: Journal of Climate 18, 3; 10.1175/JCLI-3274.1
The same as in Fig. 5, except for the differences between C4 and CN.
Citation: Journal of Climate 18, 3; 10.1175/JCLI-3274.1
The same as in Fig. 4, except for the differences between GR and CN.
Citation: Journal of Climate 18, 3; 10.1175/JCLI-3274.1
The same as in Fig. 5, except for the differences between GR and CN.
Citation: Journal of Climate 18, 3; 10.1175/JCLI-3274.1
Comparison of the DJF mean values of precipitation of the impact experiments with those of the control integration (impact–control). The differences between BS and CN are indicated. The results for the experimental areas and the surrounding areas are indicated. The colors toward red indicate relatively large values. The areas where the Student’s t-test values indicate statistically significant differences (at the 95% level) are hatched.
Citation: Journal of Climate 18, 3; 10.1175/JCLI-3274.1
The same as in Fig. 10, except for the differences between C4 and CN.
Citation: Journal of Climate 18, 3; 10.1175/JCLI-3274.1
The same as in Fig. 10, except for the differences between GR and CN.
Citation: Journal of Climate 18, 3; 10.1175/JCLI-3274.1
Latitude–longitude distribution of the differences in the DJF 500-hPa geopotential heights (m) between C4 and CN (C4–CN). The positive difference areas are shaded. The areas where the Student’s t-test values indicate statistically significant differences (at the 95% level) are densely shaded.
Citation: Journal of Climate 18, 3; 10.1175/JCLI-3274.1
Comparison of the values of the vegetation parameters used in the experimental areas. Values are DJF means and are listed for IND, ICP, and MTC area means. Numbers in parentheses are gridpoint numbers located in each experimental area. The values are also for leaf area index (LAI), green leaf fraction (Grn), and vegetation height (V-H) (m). The experiments are CN, BS, C4, and GR. The differences of the vegetation parameter values from the CN are also indicated (Diff).
Comparison of the calculated physical values at the land surface in the experimental areas. Values are DJF means and are listed for IND, ICP, and MTC area means. Numbers in parentheses are gridpoint numbers located in each experimental area. The values are also for the surface albedo (ALB), the roughness length (Z0) (m), the net radiation (RNET) (MJ m−2 day−1), the latent heat flux (E) (MJ m−2 day−1), the sensible heat flux (H) (MJ m−2 day−1), the canopy temperature (TC) (°C), the soil surface temperature (TG) (°C), the soil water content (WA) (cm), and the precipitation (P) (mm day−1). The experiments are CN, BS, C4, and GR. The difference values from the CN are also indicated (Diff).
