1.State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China 2.School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610225, China 3.Zhuzhou Meteorological Observatory, Zhuzhou 412000, China 4.Qinhuangdao Meteorological Observatory, Qinhuangdao 066000, China Manuscript received: 2019-12-30 Manuscript revised: 2020-07-03 Manuscript accepted: 2020-07-07 Abstract:To develop an objective standard for defining binary tropical cyclones (BTCs) in the western North Pacific (WNP), two best-track datasets, from the China Meteorological Administration and the Joint Typhoon Warning Center, were adopted for statistical analyses on two important characteristics of BTCs—two TCs approaching each other, and counterclockwise spinning. Based on the high consistency between the two datasets, we established an objective standard, which includes a main standard for defining BTCs and a secondary standard for identifying typical/atypical BTCs. The main standard includes two requirements: two coexisting TCs are a pair of BTCs if (i) the separation distance is ≤ 1800 km, and (ii) this separation maintains for at least 12 h. Meanwhile, the secondary standard defines a typical BTC as one for which there is at least one observation when the two TCs approach each other and spin counterclockwise simultaneously. Under the standard, the ratio of typical BTCs increases as the BTC duration increases or the minimum distance between the two TCs decreases. Then, using the JTWC dataset, it was found that there are 505 pairs of BTCs during the period 1951?2014, including 328 typical BTCs and 177 atypical BTCs, accounting for 65.0% and 35.0% of the total, respectively. In addition, a study of two extreme phenomena—the maximum approaching speed and the maximum counterclockwise angular velocity in typical BTCs—shows that the configuration of the circulation conditions and the distribution of the BTCs favor the formation of these extreme phenomena. Keywords: objective standard, binary tropical cyclones, Western North Pacific 摘要:为了发展客观标准来定义西北太平洋双台风活动(BTC),采用中国气象局(CMA)和联合台风预警中心(JTWC)两个热带气旋最佳路径数据集对BTC的两个重要参数——两者相互靠近和逆时针互旋——进行统计分析。基于两个数据集统计结果的高度一致性,我们建立了BTC客观定义标准——包括定义BTC的主要标准和识别典型/非典型BTC的二级标准。主要标准要求BTC应具备两个条件:(i)两TC中心距离≤1800km且(ii)至少维持12 h;二级标准要求典型BTC应满足至少有一次观测同时出现两TC彼此靠近且逆时针旋转。根据该标准,典型BTC的比率随BTC持续时间的增加或两个TC之间的最小距离的减小而增加。在此基础上,使用JTWC数据集,发现在1951年至2014年期间共有505对BTC,包括328个典型BTC和177个非典型BTC,分别占总数的65.0%和35.0%。此外,对两个极端现象(典型BTC中的最大接近速度和最大逆时针角速度)的研究显示,环流配置和BTC的地理分布有利于这些极端现象的形成。 关键词:西北太平洋, 双台风活动, 客观标准
HTML
--> --> --> -->
2.1. Data
Different datasets show clear differences in the intensity and location of TCs in the WNP basin (Yu et al., 2007; Knapp and Kruk, 2009; Song et al., 2010; Ren et al., 2011). We therefore used two different best-track datasets—one from the China Meteorological Administration (CMA) and the other from the Joint Typhoon Warning Center (JTWC)—to develop an objective standard for defining BTCs. Both datasets contain information on the six-hourly track and intensity of TCs in the period 1951?2014. We also used the monthly mean National Centers for Environmental Prediction reanalysis geopotential height dataset with a spatial resolution of 2.5° × 2.5° for the same period.
2 2.2. Methods -->
2.2. Methods
The basic features of BTCs are “mutual counterclockwise spinning and moving closer to each other” (Fujiwhara, 1921, 1923, 1931). We therefore designed a statistical analysis method to analyze the observations. Three parameters—the distance (d) between the centers of two coexisting TCs, the change in this distance ($ \Delta d $), and the mutual angular velocity (r)—need to be calculated for any two coexisting TCs. The value of d can be approximately calculated according to the formula for the distance between two points on a plane. $ \Delta d$ can be calculated as: where t is the number of records for two coexisting TCs and dt and dt?1 represent the distances at time t and time t?1, respectively. $ \Delta d $ < 0 means that the two TCs are approaching each other, whereas $ \Delta d $ > 0 means that they are moving apart. Figure 1 shows the schematic for calculating the mutual angular velocity between the two coexisting TCs. The value of r can be calculated as: Figure1. Schematic for calculating the mutual angular velocity between two coexisting TCs.
where $ {\theta }_{t} $ and $ {\theta }_{t-1} $ represent the angles between the line connecting the two TCs and the weft at time t and time t?1, respectively. $ {r}_{t} $ > 0 means that the rotation is counterclockwise, whereas $ {r}_{t} $ < 0 means that the rotation is clockwise. Equations (1) and (2) show that calculations can only be performed when t ? 1 ≥ 1 (i.e. t ≥ 2); that is, the duration T ≥ 12 h (12 = 2 × 6). Therefore, the duration of coexistence T should be at least 12 h and the three parameters only make sense when t ≥ 2.
3. An objective standard for BTCs Considering that the basic features of BTCs are “mutual counterclockwise spinning and moving closer to each other”, we focus on the behavior of interaction between two coexisting TCs. Figure 2 presents frequency?distance distributions of two-TC coexistence for the CMA and the JTWC TC datasets. It can be seen that the frequencies in the two datasets both show a unimodal distribution with a peak at 2100 km, while the frequency in the JTWC dataset shows a weak secondary peak at 1900 km. In addition, as the CMA dataset contains more independent TCs than the JTWC dataset (Ren et al., 2011), the frequency of two coexisting TCs in the CMA dataset is greater than that in the JTWC dataset. Figure2. Frequency?distance distributions of two-TC coexistence for the CMA and the JTWC TC datasets. Here, “distance” is the amount of space between two TC centers, while “frequency” means the number of TC pairs. The distance interval for the statistics is 100 km, with the maximum value representing the interval, e.g., 1500 for (1400, 1500].
Figure 3 shows the ratio?distance distributions of TCs that are moving apart and approaching each other for the two datasets. The CMA dataset (Fig. 3a) shows that the ratio for two TCs approaching each other increases as the distance decreases, with a ratio of 0.387 at 3000 km and 0.701 at 500 km. By contrast, the ratio for two TCs that are moving apart decreases as the distance decreases. The two ratio lines intersect over a range from 1800 to 2300 km, in which the ratios for both TCs approaching each other and TCs that are moving apart oscillate around 0.5, which means that the probabilities of occurrences for approaching and escaping are equivalent. The JTWC dataset (Fig. 3b) shows similar features with the same range of intersection. The range of intersection means that within a separation distance of 1800 km, the ratio for TCs approaching each other is > 0.5, which means that the probability of occurrence for approaching becomes dominant and increases as the distance decreases. Figure3. Approaching and escaping ratio?distance distributions of two TCs coexisting in the CMA and the JTWC datasets. Here, “ratio” means the ratio of number of coexisting TC pairs approaching or escaping to the total number of coexisting TC pairs. The distance interval for the statistics is 100 km, with the maximum value representing the interval, e.g., 1500 for (1400, 1500]. (a) CMA dataset. (b) JTWC dataset.
Figure 4 depicts the counterclockwise and clockwise ratio?distance distributions and can be used to examine the mutual angular velocity between two coexisting TCs. The JTWC dataset (Fig. 4b) shows that the counterclockwise ratio increases as the distance decreases, with a ratio of 0.416 at 3000 km and 0.846 at 500 km. By contrast, the clockwise ratio decreases as the distance decreases, with a ratio of 0.558 at 3000 km and 0.154 at 500 km. The counterclockwise and clockwise ratios intersect over a range from 1800 to 2000 km, in which both ratios oscillate around 0.5, which means that the probabilities of occurrences for counterclockwise and clockwise are equivalent. The CMA dataset (Fig. 4a) also displays highly consistent features with the same range of intersection. The intersection range also means that within a separation distance of 1800 km, the counterclockwise ratio is > 0.5, which means that the probability of occurrence for counterclockwise becomes dominant and increases as the distance decreases. Figure4. As in Fig. 3 but for counterclockwise and clockwise ratio?distance distributions. Here, “ratio” indicates the ratio of number of coexisting TC pairs with counterclockwise rotation or clockwise rotation to the total number of coexisting TC pairs. (a) CMA dataset. (b) JTWC dataset.
Based on these analyses, the two datasets both show that 1800 km is a key distance in defining BTCs: within a separation distance of 1800 km, the approaching ratio and counterclockwise ratio are both > 0.5 and increase as the distance decreases. As a result, 1800 km was selected as the threshold distance to define a BTC in Eq. (3). Taking into consideration the requirement for the duration T in Eq. (4), an objective standard for a BTC in the WNP can be established. If the distance between the centers of two coexisting TCs is ≤ d0 (1800 km) and the duration is at least 12 h, then they can be defined as a BTC: where $ \Delta t $ is the time interval (6 h) between two adjacent observations of a tropical cyclone and $ m $ ($ m\geqslant 2 $) is the number of consecutive observations with d ≤ d0. The distance threshold, 1800 km, which is larger than those of the three existing definitions of BTCs, is a key parameter in the objective standard. The distance between the centers of the two TC centers defines 900 km as an important TC size. According to Chavas et al. (2016), the median and mean sizes of the outer radius of a TC in the WNP are 957.6 and 993.5 km, respectively. These three TC sizes are clearly of the same order of magnitude. This suggests that the distance threshold, 1800 km, can be understood to be twice the mean outer radius within which two TCs easily interact with each other and show clear characteristics of BTCs. Our results are consistent with previous studies (Brand, 1970; Dong, 1980, 1981; Dong and Neumann, 1983; Kuo et al., 2000; Wu et al., 2011) in which the significance of the Fujiwara effect in a pair of TCs is dependent on the distance between the centers of two TCs. Other factors include the size, structure, and the intensity of the two TCs, as well as the environmental steering currents. However, an approaching ratio and counterclockwise ratio both > 0.5 does not mean that the two TCs will simultaneously perform a mutual counterclockwise spin and approach each other. It is necessary to introduce a secondary standard to distinguish whether a particular example is a typical BTC. For this purpose, we consider two different conditions: (1) there is at least one observation of $ \Delta d $ < 0 and at least one observation of $ {r}_{t} $ > 0 during the duration of the BTC; and (2) there is at least one simultaneous observation of both $ \Delta d $ < 0 and $ {r}_{t} $ > 0 during the duration of the BTC. Table 1 presents the statistics of typical BTCs with the two different conditions. It is revealed that, though the BTC frequencies are considerably different between the CMA and JTWC datasets, the typical BTC ratios are highly consistent with each other, being 0.680?0.689 under condition 1 and 0.642?0.650 under condition 2. Based on the comparison, condition 2, which means both $ \Delta d $ < 0 and $ {r}_{t} $ > 0 are observed simultaneously, and the ratios under which for the CMA and JTWC datasets are more consistent than those under condition 1, is selected as the standard for defining typical BTCs. Accordingly, a BTC that does not satisfy condition 2 is defined as an atypical BTC.
CMA
JTWC
Frequency
Ratio
Frequency
Ratio
Condition 1
481
0.680
348
0.689
Condition 2
454
0.642
328
0.650
BTC
707
?
505
?
Table1. Statistics of typical BTCs with two different phenomena. Condition 1: at least one observation of $ \Delta d $ < 0 and at least one observation of $ {r}_{t} $ > 0 exists during the BTC’s duration. Condition 2: at least one observation of both $ \Delta d $ < 0 and $ {r}_{t} $ > 0 exists simultaneously during the BTC’s duration.