4.1 The signal of the asymmetric LH flux
Some may concern whether the asymmetric LH flux in CL is a signal of climatological average with daily maximum happens in different timing in the morning, or the peak of LH flux does frequently happen at 9 a.m. Figure 4.1 shows the occurrence probability of daily maximum LH flux in CL and LHC. The high occurrence probability of daily maximum LH flux in the two places both happens at the timing of the climatological peak of LH flux. The highest occurrence probability of daily maximum LH flux in CL is at 8:30 a.m., and the maximum of the diurnal cycle of LH flux happens at 9:30 a.m. In LHC, the highest occurrence probability of daily maximum LH flux is at 11:30 a.m., and the maximum of the diurnal cycle of LH flux happens at noon. To sum up, the asymmetric diurnal cycle of LH flux does result from the frequent peak timing around 9 a.m.
4.2 The sensitivity test of maximum allowed canopy water
To show the modelling impact of maximum allowed canopy water on the asymmetry of LH flux in CL, the sensitivity test according to the coefficient of maximum allowed dew were conducted: CTR, max_cw_0.2, max_cw_0.1, max_cw_0.05. The coefficient of maximum allowed dew regulates maximum allowed canopy water by multiplying the coefficient with LAI in the model. In these four simulations, the atmospheric forcing and the land type are fixed as CTR, but the coefficient of the maximum allowed dew were conducted to 0.2533, 0.2, 0.1, 0.05 mm in 1𝑚2⁄𝑚2 of LAI, respectively.
Figure 4.2 displays the comparison of the diurnal cycle of canopy water, LH flux and the partition of LH flux among CTR, max_cw_0.2, max_cw_0.1, max_cw_0.05. The
daily mean canopy water in the four simulations are 0.68, 0.56, 0.32, 0.18mm, respectively. Although the daily mean canopy water becomes smaller when the value of the coefficient of maximum allowed dew gets smaller, the pattern of the diurnal cycle does not change significantly. The canopy water in all simulations starts to increase in the afternoon, reach the peak at dawn and soon decrease before 9 a.m. (Fig. 4.2a) Compared max_cw_0.05 with CTR, the total LH flux decreases by 23%. The ratio of the decrement in total LH flux in max_cw_0.1 and max_cw_0.2 are 15% and 4%, respectively (Fig.
4.2b). The decrements in the total LH flux are mainly derived from the decreases in canopy evaporation. In max_cw_0.05, the peak value of canopy evaporation is less than that in CTR by 28.6% because of less canopy water at dawn. The decrement ratio of canopy evaporation in max_cw_0.1 and max_cw_0.2 are 13.5% and 3.6%, respectively compared with CTR (Fig. 4.2c). Although less canopy water at dawn cause less canopy evaporation in the morning, the peak value of canopy evaporation still outweighs the peak value of transpiration. Therefore, the asymmetric LH flux with peaks at about 9 or 10 a.m.
can be found in the four simulations.
4.3 The drizzle’s effect on the asymmetry of LH flux
In the comparison of the observed precipitation between CL and LHC, CL rains more frequently and the drizzle in CL (the precipitation is less than 5mm) is more likely to happen than that in LHC. Figure 4.3 indicates the comparison of probability density function in precipitation between CL and LHC. The zero category shows the probability of no-rain data, which is 0.85 in CL and 0.92 in LHC. Aside from 0 mm, the probability of precipitation less than 5 mm, with 0.5 as an interval of the category, is larger in CL than in LHC. From the sensitivity tests of the atmospheric forcing, precipitation was found to be the controlling factor to the asymmetric LH flux. The storage of canopy water
increases the most in LHCatm_CL_precip. Compared LHCatm_CLsurf with LHCatm_CL_precip, more frequent drizzle input on the canopy in LHCatm_CL_precip results in the larger storage of the averaged canopy water. More canopy water is capable of evaporating in the early morning in LHCatm_CL_precip although the solar radiation forcing remains the same as LHCatm_CLsurf. Therefore, the frequent drizzle phenomenon in CL may be highly associated with the increase in the diurnal cycle of canopy water.
To investigate the effect of frequent drizzle on the asymmetry of LH flux, we conducted a more idealized simulation. We calculated the climatological diurnal cycle of precipitation from 2009 to 2011 LHC atmospheric forcing. This climatological diurnal cycle differed every month but repeated every day in each month. We replaced the original precipitation forcing by this climatological diurnal cycle, and let the rest of the atmospheric forcing remained the same as observations. We also use the same land surface as CL (Table 4.2) in this experiment. In this simulation named LHCatm_Clim_precip, drizzle always happens and the probability of precipitation under 1 mm is much higher than LHCatm_CLsurf (Fig 4.4a). With the drizzle’s effect, the averaged canopy water becomes approximately twice more than that in LHCatm_CLsurf (Fig 4.4b). The accumulating rate is higher, especially at night, making the peak value of canopy water become twice higher, compared to LHCatm_CLsurf. Despite the twice higher peak of the canopy water, the peak of canopy evaporation reaches 3 times larger in the early morning. Also, 29% of total transpiration is reduced (Fig 4.4c). Thus, the diurnal cycle of LH flux becomes more asymmetric with an early peak at about 10 a.m.
(Fig 4.4d)
Based on the two simulations, if the frequency of drizzle is significantly reduced, we will lose the characteristics of the asymmetric LH flux because of the disappearance of
high canopy evaporation in the early morning. Therefore, whether CL can hold the characteristics of the frequent drizzle may be essential to the asymmetric LH flux, even the effect on fog formation.
4.4 The diurnal LH flux and the fog under climate change:
a risk or a benefit to the ecosystem in CL?
The small diurnal temperature range, frequent fog, precipitation, and plentiful canopy water plays a vital role in the asymmetric LH flux. How these variables affected by climate change and the corresponding response of the characteristics of hydro-climatology in CL worth further discussion. First, the presence of the canopy water may result in the emergence of the asymmetric LH flux. If the canopy water is absent, the diurnal cycle of the LH flux will be in the same phase with net radiation, likewise the pattern of LH flux and net radiation in the non-cloud-fog forest. This situation indicates if the canopy loses the ability to store the water or the water storage on the canopy is insufficient, the canopy evaporation in the early morning will become lower. In CL, although the no-canopy scenario may be impossible to happen since it is a national protected area, the amount of canopy water may probably vary under climate change due to the change in atmospheric water input.
Second, the amount of the canopy water would influence the asymmetry pattern of LH flux. In montane cloud-fog forests, the canopy water in the early morning is derived from fog, dew, and precipitation accumulation since the previous afternoon or night.
Recent studies have shown a decrease in fog frequency due to anthropogenic activities.
The rising temperature in daytime might cause the water vapor to reach saturation difficultly in the afternoon (Foster, 2001; Still et al., 1999). Besides, the nighttime temperature may influence dew formation. High temperature at night will decrease
relative humidity and have negative impacts on the condensation. Furthermore, precipitation pattern may alter under climate change, such as “wet get wetter and dry get drier” (Dore, 2005). The change in both precipitation frequency and intensity might impact the storage of canopy water (Foster, 2001). Complex topography at which cloud-fog forests are located may shed large uncertainties on the change in precipitation. Both precipitation and fog occurrence might be altered by the change in mountain-valley wind circulation. When the temperature gradient varies between mountain top and valley, the wind magnitude may change. Although the contribution of advection to the water vapor accumulation in CL in the daytime remains unknown, the change in advection might affect water vapor supply, which then change the fog or precipitation climatology, thus influencing the amount of canopy water. If the amount of canopy water is unable to allow canopy evaporation to outweigh transpiration in daytime, the diurnal cycle of LH flux may become symmetric. Such symmetric LH flux will, in turn, enlarge the diurnal temperature range, possibly unfavorable to the afternoon fog formation.
Last but not least, some have concerns the disappearance of fog may have negative impacts on the growth of plants, but a lack of fog might be a benefit to Taiwan’s montane cloud-fog forests. In some seasonal dry regions, the interception of fog is essential to plant water use, especially to the top of canopy. Research has found that fog could support the growth of trees because of their direct water use through foliar water uptake (Dawson &
Goldsmith, 2018; Limm et al., 2012). However, in Taiwan’s montane cloud-fog forests where annual precipitation usually exceeds 3000mm, the water probably is not a limiting factor to the ecosystem. When fog disappears, wet leaves can still exist if the precipitation pattern does not change significantly. The lack of fog seems not to negatively influence the available water for the trees, but can significantly increase the available energy for photosynthesis or tree growth. Mildenberger et al. (2009) indicate fog can block about
64% of solar radiation. Without the immersion of fog, the acquisition of solar energy and vapor pressure deficit will become larger and might favor the open of stomata and CO2
uptake.
4.5 The importance of fog description in models
Fog is a source of canopy water that contributes to the asymmetric LH flux. Without fog’s effects on the energy and water cycle, the land will receive excess solar radiation, and LH flux will be overestimated. Furthermore, CO2 uptake in the cloud-fog forest may have bias without fog. Figure 4.5 displays the effect of fog on LH flux and CO2 flux in the CL montane cloud-fog forest. Approximately 56% of LH flux and 48% of CO2 flux are reduced under foggy conditions. As a result, if the fog is not considered in models, we may have overestimation on simulating the water exchange between land and atmosphere and the carbon uptake in the montane cloud-fog forests.