3.1. LULCC sensitivity experiments: current versus natural vegetation scenario

3.1.1. Vegetation characteristics Two main areas with vegetation changes are identified in Figure 1d). The largest converted area is located in southern Brazil, where broadleaf trees were assumed to be replaced by corn in 42% of the modified grid cells and by soybean in 15% (Table I). The other area is located over the Pampas region, with a 20 and 12% of the changed grid cells converted from tall grass to soybean and wheat, respectively (Table I). These conversions have associated changes in vegetation characteristics, like albedo, LAI, roughness length (zo) and rooting depth (zr) (Table I and Figure 2). Figure 2 Open in figure viewer PowerPoint (a) Spatial changes CTRL ‐ NAT of albedo (unitless) averaged for the three periods for spring; (b) Idem (a) for summer; (c) Spatial changes CTRL—NAT of LAI (m2 m−2) averaged for the three periods for spring; (d) Idem (c) for summer. (e) Differences between 1997–1998 and 1999–2000 of LAI CTRL—NAT changes for spring. (f) Idem (e) for summer. (g) Spatial changes CTRL—NAT of sensible heat (SH, W m−2) averaged for the three periods for spring; (h) Idem (g) for summer. (i) Idem (g) for latent heat (LH, W m−2); (j) Idem (i) for LH (W m−2); (k) Differences between 1997–1998 and 1999–2000 of LH CTRL—NAT changes for spring. (l) Idem (k) for summer. Contoured are the differences with statistical significance greater than 95%. This figure is available in colour online at wileyonlinelibrary.com/journal/joc Overall, albedo of current vegetation was higher than that of natural vegetation (Figure 2a), b)). Area‐averaged albedo differences between the CTRL and NAT experiments were higher in summer than in spring, except for the grid cells with wheat. This is a consequence of the growing cycle of the crops. Wheat harvest occurs from mid‐December to early January. As summer progresses, the number of grid cells in the CTRL experiment with similar albedo to the NAT experiment increases, and therefore, the averaged albedo differences for the wheat‐tall grass conversion area decreases from 0.057 in spring to 0.018 in summer (Table I). Conversely, in the case of summer crops, which are sowed around early to mid‐October, the number of grid cells in the CTRL experiment with different albedo than the natural vegetation increases through January leading to an increase in the area‐averaged albedo differences between CTRL and NAT experiments from spring to summer (Table I). Different crop phenology is also reflected in LAI differences between CTRL and NAT experiments in spring and summer (Table I and Figure 2c) and d)). Conversion from natural vegetation to wheat increased LAI during spring and decreased LAI in summer due to the harvest starting around mid December. Within the grid cells that converted from tall grass to soybean (Table I), two areas of opposite behaviour were found (Figure 2d)) and Table I). In the northern part (4N in Table I), where grasslands were assumed to have a C 4 photosynthetic pathway, LAI was slightly lower under current conditions than with natural vegetation (Figure 2d)). On the other hand, in the southern part, where grasslands were assumed to be C 3 (4S in Table I) LAI was higher in the CTRL than in NAT experiment. For both 4N and 4S areas the average LAI differences (in absolute values) were higher during summer as more grid cells shift to soybean. A shift from broadleaf tree or wooded grasslands to soybean and corn resulted in lower LAI values (conversions 3, 5, and 6 in Table I, respectively, and Figure 2c) and d)). Overall, a shift from natural to current vegetation resulted in decreased zo and zr. The largest decreases were concentrated in Brazil, associated with the tree‐to‐crop conversion (conversions 3 and 6 in Table I), and followed by the wooded grasslands‐to‐crop conversion (conversions 2 and 5 in Table I). There was also a seasonal variation, related to the different crop phenology. Interannual variability. We now look at how the changes in the vegetation characteristics with the shift to an agricultural scenario could be affected by different precipitation patterns in two ENSO years. Similar spatial patterns of albedo changes CTRL–NAT were found for the two extreme ENSO years and interannual differences of those changes were small (not shown). LAI differences CTRL‐NAT between 1997–1998 and 1999–2000 are within the 3‐years average differences range (compare Figure 2c) and d) with Figure 2e) and f)). The direction of the LAI CTRL–NAT changes remains the same for both periods, but in some areas the signal is enhanced during the overall 1999–2000 dry period (Figure A.1 in the Appendix). In the areas where the 3‐years average LAI CTRL–NAT differences are negative, i.e. north and central part of the domain (Figure 2c)) and d)), those differences become more negative during 1999–2000, i.e. positive values in Figure 2e) and f). This indicates that LAI for the current vegetation decreases more than for the natural vegetation during dry conditions. In other areas, like in the southern Pampas, the signal is also enhanced during the same 1999–2000 period but under wet conditions: e.g. during summer in this area, precipitation is actually higher in 1999–2000 than in 1997–1998 (Figure A.1 in the Appendix). The higher precipitation increases the LAI of the natural vegetation (tall grass), and because wheat is being harvested during that time of the year, the LAI CTRL‐NAT differences are larger in absolute value during the period 1999–2000 than during 1997–1998.

3.1.2. LULCC effects on near‐surface sensible and latent heat fluxes A replacement of natural vegetation by crops decreased SH in most of the simulation domain in both seasons (Figure 2g) and h), and Table II). The largest statistically significant SH differences between the CTRL and NAT experiments were found in the southern portion of the grid cells that converted from tall grass and evergreen broadleaf tree to soybean throughout the simulation (areas 4S and 3, Table II), and in the ones converted to wheat in the southern Pampas during spring (conversion 1, Table I). Small areas with statistically significant positive SH differences were found in the centre and northeastern part of the domain throughout the simulation and non‐significant in the southern Pampas during summer (Figure 2g) and h), Table II). Table II. Changes (CTRL–NAT) of sensible (SH) and latent heat (LH) fluxes (W m−2), and Bowen ratio (β = SH/LH) averaged for each of the vegetation conversions (see Figure ) for spring and summer. The vegetation conversion corresponds to the current and natural land‐cover. The conversions 4N and 4S are the northern and southern grid cells of the conversion 4. Statistical significant differences (P < 0.05) between CTRL and NAT experiments using the Student t‐test are shown in bold Vegetation conversion Spring Summer SH LH β SH LH β Wheat‐tall grass (1) −43 38 −47 2 −21 14 Wheat‐wooded grasslands (2) − 2 − 12 10 −22 1 − 10 Soybean‐evergreen broadleaf tree (3) − 23 − 1 − 19 − 21 − 10 − 15 Soybean‐tall grass (4) 4N 8 − 18 16 − 1 − 20 8 4S −40 35 − 45 −50 38 − 45 Soybean‐wooded grasslands (5) − 7 − 22 21 − 5 − 21 5 Corn‐evergreen broadleaf tree (6) − 5 −11 − 2 − 2 −20 4 Corn‐tall grass (7) 2 − 21 18 − 10 − 9 − 4 The changes in LH showed the opposite pattern of SH changes in grid cells that converted from wheat and soybean to grasses (Figure 2i) and j), Table II). LH values were higher over crops when shift was from C 3 grasslands (conversion 1 and 4S, Table II). The increase in albedo decreases the available energy (SH plus LH), and in these converted areas the LAI increase led to higher LH and lower SH in the current vegetation, i.e. a shifting in the energy partitioning toward LH. In the rest of the LULCC areas, average LH was lower in the current vegetation (i.e. crops) than in natural vegetation (Table II). In most of these areas, SH also showed a decrease (when trees and wooded grasslands were involved, conversions 2, 3, 5, or 6). The lower amount of available energy combined also with lower LAI and rooting depth in the current vegetation, lead to a decrease in LH and SH in the CTRL experiments. In other areas, SH slightly increased when conversion was from C 4 grasses (4N and 7, Table II). Seasonal variation in the LH and SH CTRL–NAT differences appeared associated with the crops growing cycle, through the LAI and rooting depth seasonal evolution. Bowen ratio (β) values, the ratio between SH and LH, indicates how the available energy is partitioned between LH and SH. Changes in β for each of the vegetation conversion are shown as a percentage with respect to natural cover in Table I. The largest relative changes in β were 47% and negative, indicating that more energy is now being used in transpiration and evaporation than in heating the near‐surface atmosphere; therefore a net cooling effect is expected in that region. The largest positive change, of 26%, was found in spring in the few grid cells that shifted from wooded grasslands to soybean (Table II). There was also a seasonal variation in β changes, with values generally lower in summer than in spring. Interannual variability. Latent heat differences CTRL–NAT between 1997–1998 and 1999–2000 are shown in Figure 2k) and l) and in Table III. Similar to LAI, the changes are within the average LH differences, and tended to be higher and more spatially coherent during summer. In most of the simulation domain, the direction of the LH changes is the same for both periods and seasons, but the response to wet or dry conditions varies depending on the LULCC. For example, in Brazil around 20°S, 50°W, during wet conditions in summer 1997–1998, LH for trees increased more than corn, leading to an area‐average CTRL‐NAT difference of − 32 W m−2 versus − 22 W m−2 during 1999–2000 (conversion 6, Table III). This can be due to a combination of factors: deeper rooting depth, larger canopy conductance, and higher roughness length in the natural vegetation compared to crops. Also in summer, in the southern Pampas (conversion 1, Table III), LH changes were larger in 1999–2000 during slightly wetter conditions than in the drier 1997–1998 conditions (Figure A.1 in the Appendix). Wheat is being harvested during summer; therefore the wetter conditions affect more the natural vegetation. On the other hand, in the central part of the domain, during the summer dry period 1999–2000 area‐average LH for both current and natural vegetation decrease, but LH for soybean decreased more than for grasslands (conversion 5, Table III). This leads to larger LH absolute differences CTRL–NAT during 1999–2000 (−32 Wm−2) than in 1997–1998 (−18 Wm−2) (Table III). Slightly low canopy conductance in soybean and deeper rooting depth for wooded grasslands were the main factors that could explain this pattern. Table III. Austral spring and summer changes (CTRL–NAT) of sensible (SH) and latent heat (LH) fluxes (W m−2), two‐metre temperature (2 mt, °C) and precipitation (PR, mm), averaged for each of the vegetation conversions (see Figure ) for the El Niño (1997–1998) and La Niña years (1999–2000). The vegetation conversion corresponds to the current and natural land‐cover. The conversions 4N and 4S are the northern and southern grid cells of the conversion 4. Statistical significant differences (P < 0.05) between CTRL and NAT experiments using the Student t‐test are shown in bold 1997–1998 1999–2000 Vegetation conversion Spring Summer Spring Summer SH LH 2 mt PR SH LH 2 mt PR SH LH 2 mt PR SH LH 2 mt PR Wheat‐tall grass (1) −40 35 −1.0 − 2 − 6 − 14 − 0.1 − 2 − 50 45 − 1.1 1 − 5 − 5 0.0 10 Wheat‐wooded grasslands (2) 7 −28 0.5 − 1 19 −50 1.2 0 12 − 1 0.3 − 3 −21 28 0.2 1 Soybean‐evergreen broadleaf tree (3) − 3 − 2 0.5 − 2 − 5 − 8 0.5 − 6 − 4 10 0.6 9 − 4 − 10 0.6 2 Soybean‐tall grass (4) 4N 3 − 18 − 0.1 0 0 −26 − 0.2 − 3 12 − 15 0.1 4 9 −16 0.1 12 4S −41 35 −0.8 − 1 −57 37 −1.0 − 8 − 41 41 − 0.7 2 −63 67 −1.0 10 Soybean‐wooded grasslands (5) 7 −45 0.8 − 4 −25 − 18 0.2 − 15 24 − 33 0.8 4 6 −32 0.4 10 Corn‐evergreen broadleaf tree (6) − 1 − 15 0.7 2 − 6 −32 0.6 − 4 10 − 25 0.6 19 5 −22 0.5 11 Corn‐tall grass (7) − 3 − 15 0.0 − 1 −18 − 6 − 0.3 − 6 4 − 19 0.3 1 − 8 3 − 0.1 8

3.1.3. LULCC effects on near‐surface temperature and humidity Changes in near‐surface fluxes led to changes in near‐surface temperature and water vapor (Figure 3 and Table III). With a current land cover, a cooler near‐surface atmosphere was found associated with higher LH and lower SH fluxes, and vice versa, warming was associated with lower LH and SH fluxes. Near‐surface temperatures decreased when crops (wheat and soybean) replaced C 3 grasslands, as in the southern Pampas (Figure 3a), b) and Table III). Increases in temperature were found when vegetation shifted from evergreen trees, wooded grasslands (e.g. in Brazil), and C 4 grasslands (e.g. in the central region of the Pampas) to crops (Figure 3a), b)). This is the result of the simulated higher LAI and therefore LH in C 4 grasslands than in C 3 grasslands and crops due to a higher dry matter growth rate related to their different photosynthetic rates (Chen and Coughenour, 1994; Larcher, 1995). The coolest (up to − 0.8 °C) and warmest (higher than 0.6 °C) two‐metre average temperature differences appeared during spring in the southern and northern part of the domain, respectively. Temperature differences between current and natural cover became smaller at the first model level (approximately at 57 m) but changes were statistically significant up to 1000 m (not shown). Figure 3 Open in figure viewer PowerPoint (a) Two‐metre temperature ( °C) differences CTRL—NAT for spring averaged for the three simulated periods; (b) Idem (a) for summer. (c) Differences between 1997–1998 and 1999–2000 of temperature CTRL—NAT changes for spring; (d) Idem (c) for summer. (e) Water vapor mixing ratio (g kg−1) differences CTRL—NAT for spring averaged for the three simulated periods; (f) Idem (l) for spring. (g) Two‐metre maximum (15 Local Standard Time, LST) temperature ( °C) differences between CTRL—NAT for spring averaged for the three simulated periods; (h) Idem (g) for summer. (i) Idem (g) for minimum (06 LST) temperature ( °C); (j) Idem (i) for summer. (k) Temporal series of two‐metre maximum, minimum and their differences (i.e., diurnal temperature range) for wheat—tall grass conversion; (l) Idem (k) for soybean—C 3 grassland. (m) Idem (k) for corn—evergreen broadleaf tree. Contoured are the differences with statistical significance greater than 95%, in (a), (b) and (e) to (j). This figure is available in colour online at wileyonlinelibrary.com/journal/joc The warming or cooling was consistent for both seasons for most of the areas with the LULCC, except for the southern Pampas. In this region, a net cooling was found in spring while a small net warming was present in summer. As mentioned before, this is a consequence of the phenology of the crop in this area, wheat. This is the harvesting period, and vegetation was assumed tall grass after harvest, same as the natural vegetation, but with a lower LAI and vegetation cover; therefore LH was higher in NAT than in CTRL experiments during summer in this area. A similar response was found in the observed temperature and humidity for the Oklahoma's winter wheat belt in the US (McPherson et al., 2004). They found that during the wheat growing season maximum temperatures were statistically significantly cooler and wetter than the neighboring grasslands. After the wheat has been harvested, the temperature becomes warmer. Similarly, Ge (2010) over Oklahoma and Kansas wheat areas, found that during the growing season wheat was 2.3 °C cooler and after harvest was 1.6 °C warmer than the grasslands. Changes in water vapor mixing ratio were small and only statistically significant in a few areas with LULCC (Figure 3e), f)). They tended to be consistent with the changes in LH fluxes: a more humid near‐surface atmosphere was found with increases in LH and vice versa. Interannual variability. The impact of LULCC on near‐surface temperature was similar for the extreme ENSO years, 1997–1998 and 1999–2000, and the direction of the changes was the same for both periods and seasons (Figure 3c) and d), and Table III). Spatially the variations closely follow the LH interannual variability map (Figure 2k) and l)): temperature changes are enhanced concurrently with enhanced LH differences. Similar to LH, the wet or dry conditions affect the temperature response. In the conversions broadleaf tree to corn (conversion 6) and tall grass to wheat (conversion 1), wetter conditions amplified the temperature CTRL‐NAT differences (Table III). In the centre of the domain, the response is augmented during relatively dry conditions in 1999–2000 (Table III). The patterns are consistent during both seasons, slightly more spatially coherent during summer. Diurnal variation. Temperature changes between current and natural vegetation experienced a diurnal variation. Figure 3g) to j) show the two‐metre temperature differences between CTRL and NAT experiments at 15 Local Standard Time (LST) and at 6 LST, which can be assumed to be the maximum and minimum values during the day, respectively. With a shift from grass to crops, maximum temperatures significantly decreased in the southern Pampas during spring and in central Pampas during both seasons (Figure 3g) and h), and Figure 4c) and d)). During spring, those changes were collocated with a large decrease of SH and an increase of LH (Figure 4f), g)). In the southern Pampas, during summer, changes were small and no statistically significant (Figure 3h)). In this case, the seasonality of the wheat plays a key role in these differences: the seasonal variation of LAI leads to a shift of the available energy towards transpiration and evaporation in spring. Figure 4 Open in figure viewer PowerPoint (a) Diurnal temperature range (DTR, °C) differences CTRL ‐ NAT for spring averaged for the three simulated periods; (b) Idem (a) for summer. (c) Two metre‐temperature ( °C) averaged for conversion area 1 for CTRL and NAT experiments; the differences CTRL ‐ NAT are shown in the bottom; (d) Idem (c) for conversion area 4S; (e) Idem (c) for conversion area 6. (f) Latent (LH) and sensible heat (SH) fluxes (W m−2) averaged for conversion area 1 for CTRL; the differences CTRL ‐ NAT are shown in the bottom; (g) Idem (f) for conversion area 4S; (h) Idem (f) for conversion area 6. This figure is available in colour online at wileyonlinelibrary.com/journal/joc Maximum temperatures significantly increased in southern Brazil in both seasons where crops (corn) replaced trees and a few cells in Chile and in central Argentina (Figure 3g) and h), and Figure 4e)). These changes can be explained mostly by the daytime decrease in LH (Figure 2i) and j), and Figure 4h)), complemented with a small positive SH differences (Figure 2g) and h), and Figure 4h)). Although in an area‐averaged basis, daytime SH is lower over corn and soybean than on evergreen broadleaf trees (conversions 3 and 6, Table I), there are some corn and soybean grid cells with a slightly higher daytime‐averaged SH than trees. LH shows lower values on crops than on trees starting at 9 LST, reaching maximum averages differences of 60 W m−2 at 15 LST (Figure 4h)). The differences in minimum temperatures were statistically significant only in few grid cells, with cooler temperatures in central Argentina and warmer temperatures in central Chile under current vegetation conditions (Figure 3i), j)). Over Oklahoma and Kansas, Ge (2010) also found that at night temperature differences between wheat and adjacent grasslands were smaller, especially after harvest. In summer, there is an overall slight increase in the minimum temperature in the CTRL experiments over much of the simulation domain (Figure 3j)). In most of the areas, nighttime warming or cooling coincides with areas that experienced also daytime warming or cooling. In some areas, e.g. southern of the Pampas in summer, slight nighttime warming coincides with slight daytime cooling (Figure 3j)). That extra warming is supplied by a slight increase of SH during the night under current vegetation conditions. Over most of the domain, and particularly in the Pampas, the shift to an agricultural scenario resulted in a decrease in the diurnal temperature range (DTR), i.e. daily maximum minus minimum temperature, especially during spring, because maximum temperatures presented a larger decrease than minimum temperatures (Figure 4a) and b)). As an example for this case, the DTR area‐average for the wheat‐tall grass and soybean‐C 3 grasslands conversions 1 and 4S, respectively, are shown in Figure 3k) and l). A seasonal shift in the temperature differences for the conversion area 1 can be seen clearly in Figures 3k) and 4a) and b): the decrease in DTR is due in spring to a larger decrease of maximum temperatures (Figure 4c)), and in summer to a larger increase of minimum temperatures. During summer, DTR differences between CTRL and NAT become smaller (Figures 3k) and 4b)). Figure 3l) (and Figure 4d) for summer) shows that for the soybean‐C 3 grassland conversion the decrease in DTR was mostly due to lower maximum temperatures under current vegetation conditions. In the northern part of the domain, DTR shows an increase under current vegetation conditions (Figure 4a) and b)) mainly due to a larger increase of maximum temperature than of minimum temperatures (Figure 3m)). Rusticucci and Barrucand (2004) found a negative trend in observed maximum temperatures in summer over the period 1959–1998, especially in the centre of the Pampas region. They also found a strong and generalized increase in minimum temperatures but the simulations showed a slight increase. Our results in general agree with estimations of the impact of LULCC over Argentina for the period 1961–2000 using the ‘observation minus reanalysis’ (OMR) differences between the trends in the surface temperature (Nuñez et al., 2008). The OMR differences can be assumed to include in part the effects of the land surface characteristics. On a domain average, they found an average decrease in the OMR diurnal temperature range. Spatially (in an annual basis), the trends were negative in the central part of the domain and positive over the western and northeastern part of Argentina, consistent with our results (except for the slight non‐statistically significant increase that we found in the grid cells with a C 4 grassland to soybean conversion). The area with the strong decrease in the DTR coincides with the location of the soybean production area in the centre of Argentina.