Summary and Discussion - 以系統追蹤分析探討雲凝結核對於臺灣複雜地形夏季日夜降雨之影響

In this study, the impact of CCN on the diurnally developed deep convection over complex topography in Taiwan is investigated, specifying the meteorological regime

of weak synoptic-scale weather forcing. TaiwanVVM, a framework of VVM with high-resolution Taiwan terrain, was applied to resolve fine-scale atmospheric processes over complex topography. We selected 13 cases to perform semi-realistic LESs, in which both the clean and the normal scenarios were simulated. Object-based tracking analyses

are conducted, providing novel and useful insights to the understanding of the responses resulting from increasing CCN to the diurnally developed deep convection.

The regime-dependence essence of ACPI depicted in Stevens and Feingold (2009) was mainly focused on clouds and their environments. Here, we propose that the orographic regime is also crucial. We focus on the most significant hotspot of the composite precipitation on Taiwan Island, the AMR region, for our analyses, which further emphasizes the role of complex topography. In the AMR region, we identify two different types of precipitation patterns by the regional-averaged rain rate evolution:

the STRONG type and the WEAK type. The composite precipitation in the AMR region mainly occurs over the mountain ridges. For the STRONG type, increasing CCN leads to an expansion in the area of heavy precipitation. The composite initiation time of precipitation shows an earlier start of precipitation over the mountain ridges and later

in the river valleys. These overall results demonstrate the first-order relationship between the precipitation and the topography, and highlight that increasing CCN could have different responses on diurnally developed deep convection over complex topography, depending on the strength of convective precipitation.

The cloud object analyses provide further information on the differences between the two types of precipitation patterns. For the STRONG type, increasing CCN leads to

a notably higher probability of occurrence of the clouds that can produce heavy rain rates, while the probability of those clouds is less affected by CCN concentration for

the WEAK type. Rain cell tracking analyses present additional characteristics for the two types of precipitation patterns from the perspective of the life cycle of the diurnal precipitating systems. For the STRONG type, increasing CCN leads to a larger total

rain contribution from the diurnal precipitating systems that can produce heavy rain rates, while the total rain contribution from those diurnal precipitating systems is less

affected by CCN concentration for the WEAK type. Increasing CCN delays the initiation and the ending time of the diurnal precipitating systems, especially for the STRONG type. Furthermore, for the STRONG type, the maximum rain rate, rain area, cloud depth, and cloud size during the lifetime of the diurnal precipitating systems become considerably stronger when CCN concentration rises. Increasing CCN also results in more concentrated and more vigorous updraft regions in the clouds for the

STRONG type. These results reveal a significant “strong get stronger” response to the diurnal precipitating systems when CCN concentration increases, viewed from the perspective of rain properties, cloud macro-scale characteristics, and cloud dynamical

features (Figure 15).

The difference between the two types of precipitation patterns might result from

the upstream wind field of the AMR region. Figure 16b and Figure 16c demonstrate the local circulation one hour before the initiation of precipitation in the mountain part of the blue box in Figure 16a under the clean scenario on July 7^th, 2009 (a case belonged to the STRONG type) and on July 21^st, 2006 (a case affiliated with the WEAK type).

The local circulation before the initiation of precipitation on July 7^th, 2009 is weaker than that on July 21^st, 2006. The average near-coast low-level southwesterly one hour

before the initiation of precipitation for all 13 cases are listed in Table 2. The result reveals that the near-coast low-level southwesterly before the initiation of precipitation is generally weaker (less than 1.5 m·s^-1) for the STRONG type (also shown in Figure 15 by the purple translucent arrows). Figure 17 illustrates the local circulation 10

minutes before the initiation of precipitation in the mountain part of the blue box in Figure 16a on July 7^th, 2009 under different CCN concentration scenarios. Increasing CCN delays the initiation of precipitation, which prevents the local circulation from being disturbed by the convection and allows the local circulation to be further

intensified. Thus, when CCN concentration rises, the strength of the convection could be stronger owing to the maintenance and development of local circulation.

Table 2 also shows that the low-level southwesterly of the initial sounding is

generally weaker for the STRONG type. Although experiencing several hours of

evolution, the near-coast low-level southwesterly before the initiation of precipitation is still related to the initial sounding. Once this relationship is further confirmed, sensitivity tests on the initial low-level southwesterly should provide further information on the relationship between the intensity of terrain-related local circulation and the strength of diurnal precipitation. Among all 13 cases, June 29^th, 2010 (a case being categorized as the WEAK type) is the case with the maximum regional-averaged

rain rate closest to 4 mm·hr^-1, and has the weakest near-coast low-level southwesterly

before the initiation of precipitation among the 7 cases of the WEAK type, indicating that it bears marginal features of the two types of precipitation patterns and could be the suitable candidate to conduct the sensitivity tests.

In this study, 13 semi-realistic LESs serve as an ensemble of simulations. Although the initial atmospheric conditions bear some common features, including high CAPE, high CWV, and low-level southwesterly flow, they are still distinct from each other.

Other factors could affect the development of the diurnally developed deep convection as well, including low-level moisture (Lin et al., 2011), the depth of southwesterly flow,

and temperature inversion. To minimize the complication from meteorological factors, idealized simulations could be practiced. A composite summertime sounding, such as the one provided in Chen et al. (2009), could be adopted as the initial condition for the idealized simulations. Thus, the influence of CCN on the diurnally developed deep convection over complex topography could be investigated without other disturbances of meteorology.

Comparing to the analyses simply based on regional averaging, the influence of CCN on the diurnally developed deep convection over complex topography can be more precisely identified by object-based tracking analyses. Besides the AMR region, object-based tracking analyses can be applied to other precipitation hotspots in Taiwan as well. Complex topography also appears in these regions, including the northern tip of CMR and the western slope of SMR (Figure 3). Object-based tracking analyses can also be practiced when studying how increasing CCN affects the diurnally developed deep convection on the other islands with complex topography, such as Maritime Continent (Hodzic and Duvel, 2018; Lee and Wang 2020). Overall, we consider object-based tracking analyses as useful diagnostic packages when investigating the diurnally developed deep convection over complex topography.

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Figures

Figure 1. Vertical profiles of the initial environmental conditions presented by Skew-T log-P diagrams. These profiles are adapted from the observational soundings of Central Weather Bureau Banqiao Station (World Meteorological Organization station number 46692) at 08:00 Taiwan Standard Time. The blue and the red lines represent temperature and dew point temperature, respectively. The red and blue translucent shading areas represent the positive areas and the negative areas, respectively. High convective available potential energy (greater than 900 J·kg^-1), high column water vapor (greater than 44 mm), and low-level southwesterly are common features shown in these profiles.

Figure 1. Continued.

Figure 2. The domain of TaiwanVVM and its terrain height. The center of the domain is set around Mount Jade, the highest mountain on Taiwan Island.

Figure 3. The composite precipitation of all 13 cases under (a) the clean scenario and (b) the normal scenario on Taiwan Island. The red box represents the Alishan Mountain Range region, which is the most significant precipitation hotspot and the region where this research is focusing.

Figure 4. (a) The topographic map and (b) the three-dimensional terrain of the Alishan Mountain Range region. Several major drainage systems in Taiwan are located in this region, including the Chenyoulan River, the Qingshui River, the Qishan River, and the Laonong River. The Zengwen Reservoir and the Nanhua Reservoir, the main reservoirs that support the water consumption of southern Taiwan, are situated in this region as well.

Figure 5. The Alishan Mountain Range regional-averaged rain rate evolution from 08:00 to 20:00 for (a) the STRONG type (6 cases) and (b) the WEAK type (7 cases).

The blue and the red lines represent the clean and the normal scenarios, respectively.

Figure 6. The composite total precipitation in the Alishan Mountain Range region for (a) STRONG/clean, (b) STRONG/normal, (c) WEAK/clean, and (d) WEAK/normal situations. The terrain height is presented by the hatching.

Figure 7. The composite initiation time of precipitation in the Alishan Mountain Range region for (a) STRONG/clean, (b) STRONG/normal, (c) WEAK/clean, and (d) WEAK/normal situations. The terrain height is presented by the hatching.

Figure 8. The number of the rain tracks by different maximum rain rate during their lifetime for (a) the STRONG type and (b) the WEAK type. The blue translucent bars and the red-edge hollow bars represent the clean and the normal scenarios, respectively.

Figure 9. The probability density functions of the clouds with various maximum rain rates for (a) the STRONG type and (b) the WEAK type, along with the critical cloud size. The critical cloud size is defined as the minimum cloud size that can produce the corresponding rain rate, presented by the size of the hollow dots. The blue and the red dots represent the clean and the normal scenarios, respectively.

Figure 10. The rain contribution of the clouds with different maximum rain rates for (a) the STRONG type and (b) the WEAK type, presented by the cumulative density functions. The blue and the red lines represent the clean and the normal scenarios, respectively.

Figure 11. The box-whisker plots of (a) the initiation time, (b) the ending time, and (c) the duration of the rain tracks. The red and the blue boxes represent the clean and the normal scenarios, respectively. The upper edge, the middle line, and the lower edge of a box represent the 3^rd quartile, the median, and the 1^st quartile, respectively.

The dot represents the mean. The upper and the lower tip of a whisker represents the maximum and the minimum value. The significance of the difference of the means is shown by the asterisks: ** indicates a value smaller than 0.01, while * indicates a p-value smaller than 0.05.

Figure 12. The box-whisker plots of (a) the maximum rain rate and (b) the maximum rain area (shown by effective radius r = √𝐴 𝜋⁄ ) during the lifetime of the rain tracks.

The blue and the red boxes represent the clean and the normal scenarios, respectively.

The upper edge, the middle line, and the lower edge of a box represent the 3^rd quartile, the median, and the 1^st quartile, respectively. The dot represents the mean. The upper and the lower tip of a whisker represent the 99^th percentile and the 1^st percentile, respectively. The significance of the difference of the means is shown by the asterisks:

** indicates a p-value smaller than 0.01, while * indicates a p-value smaller than 0.05.

Figure 13. The box-whisker plots of (a) the maximum cloud depth and (b) the maximum cloud size (shown by effective radius r = √3𝑉 4𝜋³ ⁄ ) during the lifetime of the rain tracks. The details are the same as Figure 12.

Figure 14. The box-whisker plots of (a) the maximum in-cloud vertical velocity and (b) the maximum core ratio during the lifetime of the rain tracks. The core ratio is defined as the proportion of the clouds with a vertical velocity greater than 0.5 m·s^-1, indicating the updraft region. The details are the same as Figure 12.

Figure 15. The schematic diagram of the influence of cloud condensation nuclei on the diurnal precipitating systems over complex topography. The life cycle is shown by the left-to-right sub-figures, representing the growing stage, the mature stage, and the dissipation of the diurnal precipitating systems. For the STRONG type, the diurnal precipitating systems initiate over the mountain ridges and then occupy the whole mountain area during their development. However, for the WEAK type, the initiation of the diurnal precipitating systems has less relationship with the terrain. The middle sub-figures further illustrate the features of the diurnal precipitating systems. The number of the slant dashed lines per each cloud represents the rain rate, while the total number of the slant dashed lines shows the rain area. The figures also visually present the size and depth of the clouds. The length of the black arrows in the clouds indicates the strength of the in-cloud vertical velocity, while the number of them displays the size

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