Meteorological Regimes of the Most Intense Convective Systems Along the Southern Himalayan Front

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Meteorological Regimes of the Most Intense Convective Systems along the Southern Himalayan Front

XUEKE WU College of Atmospheric Sciences, Lanzhou University, Lanzhou, China

XIUSHU QIE Key Laboratory of Middle Atmosphere and Global Environment Observation (LAGEO), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, and Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China

TIE YUAN AND JINLIANG LI College of Atmospheric Sciences, Lanzhou University, Lanzhou, China

(Manuscript received 8 December 2014, in ﬁnal form 18 January 2016)

ABSTRACT

Based on 16 years of Tropical Rainfall Measuring Mission (TRMM) data and NCEP Climate Forecast System Reanalysis data, the most intense convective systems (ICSs) along the southern Himalayan front (SHF) are studied using the multivariate techniques of principal component analysis in T mode and k-means cluster analysis. Three clusters, classified according to the near-surface fields of wind, specific humidity, convective available potential energy, and convective inhibition, correspond to the premonsoon (March– May), the establishment of the monsoon (late May–early June), and the Indian summer monsoon itself (June– September), respectively. The location of ICSs along the SHF is closely related to the establishment of the transport passage from the eastern SHF to the northwestern SHF along the Himalayas. During the premonsoon, the southwesterly wind is weak and moist air from the Bay of Bengal is transported to the eastern SHF, where ICSs are densely distributed. The oceanic southwesterly wind is enhanced and the transport passage extends to the central SHF during the monsoon establishment period, when ICSs distribute over the whole SHF homogeneously. The southwesterly wind is the strongest and the transport passage extends to the westernmost SHF after the monsoon is established, when ICSs mainly concentrate over the concave indentation region. Backward trajectory analysis confirms that, besides the local environment, the moisture transport from the Arabian Sea (17%) and the Bay of Bengal (9%) are two important long-range transport pathways for the summer monsoon ICSs at the western end of the SHF.

1. Introduction and encounters the Himalayas, the low-level warm and moist flow is obstructed by the steep mountain barrier The Tibetan Plateau is the largest and highest and then capped by warm and dry air from the Iranian or mountain barrier in the world. During boreal summer, Tibetan Plateaus (Sawyer 1947; Houze et al. 2007), strong sensible heating leads to an upward motion over which could prevent the premature release of instability the plateau and the Himalayan southern slope, which and lead to the accumulation of unstable energy. drives the surrounding surface air to converge toward Together with the strong topographic lifting by the Hi- the plateau, like a sensible-heat-driven air pump (Wu malayas, the low-level warm and moist flow is lifted to et al. 2007). When the air mass flows from the Arabian become saturated and breaks through the stable layer, Sea and the Bay of Bengal over the Indian subcontinent so intense convective systems frequently occur in this region (Houze et al. 2007; Romatschke et al. 2010; Qie Corresponding author address: Dr. Xueke Wu, College of At- et al. 2014). mospheric Sciences, Lanzhou University, Lanzhou 730000, China. The southern Himalayan front (SHF), especially its E-mail: [email protected] western and eastern ends, is also the region known to

DOI: 10.1175/JCLI-D-14-00835.1

Ó 2016 American Meteorological Society Unauthenticated | Downloaded 10/06/21 03:57 AM UTC 4384 JOURNAL OF CLIMATE VOLUME 29 yield the most vigorous convection on Earth (e.g., Qie Sea meets the dry air flowing off the Afghan plateau et al. 2003; Liu and Zipser 2005; Zipser et al. 2006; Liu (Houze et al. 2007), the midlevel dry air provides a et al. 2007; Qie et al. 2014). Some of the most frequent capping inversion that prevents the release of convec- lightning activity occurs at the westernmost tip of tive instability until the air is lifted along small foothills the SHF as seen by the Tropical Rainfall Measuring of the northwestern Himalayas (Medina et al. 2010). Mission (TRMM), where lightning density exceeds Severe convection is more likely to occur in regions 2 2 70 flashesÁkm 2Áyr 1 (Cecil et al. 2014), almost the same as with a large low-layer moisture gradient—namely, that in central Africa. Compared with deep convective drylines (Weston 1972; Wu et al. 2013). The compre- systems [DCSs; with 20-dBZ echo-top height exceeding hensive study of DCSs (Qie et al. 2014) shows that the 14 km; unless otherwise stated, all heights in the paper intensity of deep convection over the SHF is the most are above mean sea level (MSL)], intense convective intense, followed by the deep convection over the Indian systems (with 40-dBZ echo-top height exceeding 10 km) subcontinent. This is consistent with the result obtained occur more frequently and densely along the southern from CloudSat and the Cloud–Aerosol Lidar and Infrared slope of the Himalayas than over the adjacent regions Pathfinder Satellite Observations (CALIPSO)data(Luo (e.g., the Tibetan Plateau and the Indian subcontinent; et al. 2011). Qie et al. 2014). The average 20-dBZ echo-top height of The location of the most extreme convection is closely intense convective systems can reach 16 km, and some related to the unique topography of the region and its even exceed 18 km (Qie et al. 2014). Meanwhile, the interaction with southwest monsoon winds. Houze et al. anticyclonic circulation over the Asian monsoon region, (2007) and Romatschke et al. (2010) showed that the one of the largest upper-level anticyclones on Earth terrain plays an important role in releasing and en- (named the South Asian high or Tibetan high), is an hancing the convection. The moisture sources of con- important pathway for water vapor and pollutants to vective systems (e.g., deep convection and rainstorm) in enter the stratosphere (Park et al. 2007; Randel et al. the concave indentation have been discussed widely in 2010; Bian et al. 2012). This means that the intense recent years. For example, Houze et al. (2007) and convective systems along the SHF also play an impor- Medina et al. (2010) showed that convective systems tant role in the stratosphere–troposphere exchange. with intense radar echoes (e.g., 40-dBZ echo top ex- The TRMM Precipitation Radar (PR) (Kummerow ceeding 10 km or 40-dBZ echo area exceeding 1000 km2) et al. 1998, 2000) data provide a unique opportunity to tend to occur near the western indentation. The low- study the vertical structure of convection in remote re- level flow is moistened over the Arabian Sea and heated gions of complex terrain (Cecil et al. 2002; Nesbitt and by the sensible heat flux when it passes over the Thar Zipser 2003). The radar echo maximum heights (Zipser Desert, and the convective system is triggered by the et al. 2006), horizontal structures (Hirose and Nakamura orographic lifting when the low-level flow arrives at the 2004), and both vertical and horizontal structures Himalayan foothills. Afterward, the studies of rain- (Houze et al. 2007; Romatschke et al. 2010) of convec- storms over Pakistan (Houze et al. 2011) and India tion in the region have been analyzed. Deep convection (Rasmussen and Houze 2012) showed that low- to is more likely to occur over the east coast of the Indian midlevel air is brought into the region along the Hima- subcontinent during the premonsoon and move north- layan foothills by the southeasterly flow. Recently, ward to the SHF during the monsoon (Romatschke et al. based on 14 years of TRMM observational data and 2010; Romatschke and Houze 2011; Wu et al. 2013; Qie NCEP reanalysis data, Qie et al. (2014) confirmed that et al. 2014). However, it should be noted that the con- the occurrence of deep convection over the westernmost vective systems with different intensity show a different southern slope of the Himalayas is also closely corre- seasonal variation over the southern Himalayan slope— lated to the establishment of moisture transport passage for example, the maximum occurrence frequency of along the foothills of the Himalayas from the Bay of deep convective systems appears in August, while that Bengal, in addition to that from the Arabian Sea directly of intense deep convective systems appears in May (Qie (Houze et al. 2007; Medina et al. 2010). However, the et al. 2014). On a diurnal scale, convective systems form trajectory fraction from the Bay of Bengal versus from preferentially in the evening over land, as near-surface the Arabian Sea for forming intense convective systems moist flow is capped by dry air aloft (Romatschke et al. (ICSs) over the concave indentation region is still 2010). Studies of the monsoon convection (during not clear. June–September) in 2002 and 2003 showed that deep To better understand the physical processes that de- and wide intense convective cores over the north- termine the occurrence of intense convection along the western Indian subcontinent tend to occur where the SHF, this study investigates the meteorological regimes low-level moist layer of monsoon air from the Arabian for the onset of intense convection along the SHF using

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16 years of TRMM observational data and the NCEP Climate Forecast System (CFS) Reanalysis data. Data and methods are described ﬁrst, and then the temporal variation and geographical distribution of the most ICSs over the domain of interest are investigated. Further, the atmospheric environment and possible causes of ICSs under three clusters are discussed in detail based on multivariate analysis methods. Finally, the conclusions are summarized.

2. Data and methods a. Data FIG. 1. Illustration of the topography of the study area. The black The data used in this paper include the observational and gray contour lines around the Tibetan Plateau represent the data from the TRMM satellite and the NCEP CFS 2000- and 3000-m elevation, respectively. Reanalysis data from 1998 to 2013. However, data from August 2001, when the TRMM satellite’s orbit was lightning flashes are observed by the LIS. Therefore, boosted to lengthen its mission, are excluded since according to the most extreme 0.1% PFs of different there are some doubts about data quality (Zipser et al. parameters from Zipser et al. (2006), after applying a 2006). The TRMM PR data provide powerful in- 10-km criterion for 40-dBZ echo-top height, the 1000 formation for analyzing the 3D structure of convection, most ICSs for this study are selected as those having the 2 especially in collaboration with other sensors. The highest flash rate ($32 flashes min 1), regardless of object of this paper is to study the most intense con- horizontal size. vection along the SHF (the inner rectangle region in The data used to characterize the atmospheric re- Fig. 1,208–368N, 658–958E, with elevation ,3 km) and gimes before or at the onset of the ICS are the 6-hourly to analyze the cause of ICS based on their atmospheric product, extracted from the NCEP CFS Reanalysis regimes of mesoscale parameter configurations and data (Saha et al. 2010) from 1998 to 2010 and the NCEP synoptic patterns based on the cluster analysis, for CFS, version 2 (CFSv2), from 2011 to 2013 (Saha et al. which it is necessary to first identify convection from 2014). The occurrence and development of convection TRMM PR orbital data. Hence, the TRMM pre- depend on the distribution and evolution of the syn- cipitation feature (PF) database from the University of optic environment as well as to the mesoscale factors, Utah (Liu et al. 2008) is employed. The definition of which are closely related to triggering and enhancing radar projection precipitation features (Nesbitt et al. the development of convection, such as low-level wind, 2000; Liu et al. 2008) uses grouping the area of the humidity, and atmospheric instability. Therefore, to ground projection of radar reflectivity $20 dBZ;this investigate the possible causes of ICSs along the SHF, precipitation feature is adopted in order to fully cap- four atmospheric parameters are adopted to represent ture the 3D information from PR reflectivity profiles. the mesoscale atmospheric situation just before or at After grouping PR pixels, maximum echo tops, mini- the onset of the ICSs: mum brightness temperatures, flash counts, view time, 1) wind flow at 0.995 model sigma level F0.995, etc., inside features are calculated from collocated or- 21 2) specific humidity at 1000 hPa Q1000 (kg kg ), bital data. Some erroneous TRMM Precipitation Fea- 2 3) convective inhibition (CIN; J kg 1) above ground or ture cases described by Qie et al. (2014) are excluded. water surface, and Lightning flash rate is an excellent indicator of con- 2 4) convective available potential energy (CAPE; J kg 1) vective intensity (Ávila et al. 2010; Zipser et al. 2006). above ground or water surface. The lightning data are obtained from the TRMM Lightning Imaging Sensor (LIS), which is a highly so- The horizontal resolution of these four mesoscale phisticated instrument that detects and locates light- factors is 0.5830.58. In addition, the geopotential height ning over the tropical region of the globe. However, and temperature fields at 500 and 850 hPa with the same because the imager’s field of view allows the sensor to resolution are utilized to represent the atmospheric observe a point on Earth or a cloud for about 80 s, some conditions on a synoptic scale. To study the occurrence convection is observed by the TRMM PR with a strong of ICS, this study focuses on the atmospheric situation convective intensity (referring to 40-dBZ echo-top before the ICS was observed by TRMM PR. When the height only) while almost no lightning or only few ICS was observed by TRMM PR during 0000–0600,

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0600–1200, 1200–1800, or 1800–0000 UTC, the corresponding reanalysis data at 0000, 0600, 1200, or 1800 UTC were used, respectively. A larger domain (158–408N, 608– 1008E; as shown in Fig. 1)ischosentorepresentthe atmospheric conditions before ICSs were observed by TRMM. b. Multivariate analysis methods The multivariate analysis techniques used here have been widely used to establish patterns or configurations with atmospheric fields in meteorology and climatology (e.g., FIG. 2. Geographical distribution of the most intense convective Merino et al. 2014; Wang et al. 2015). To obtain mesoscale systems over the southern Himalayan front. The color shading configurations from the selected four mesoscale fields be- represents the number of ICSs within the 0.5830.58 box, and black fore the ICS occurs, a principle components analysis (PCA) and gray contour lines along the Himalayas represent 2000- and 3000-m elevation, respectively. in T mode was performed to extract the principal components, followed by a cluster analysis of the extracted components using the k-means method (Anderberg 1973). 3. Results The PCA is designed not only as a data reduction a. Climatological characteristics technique but also to ensure that only the fundamental variation modes of the data are retained (Richman The geographical distribution of the 1000 ICSs within 1986; Yarnal 1993). Huth et al. (2008) proposed that the the study region, observed by the TRMM PR from 1998 performance of the T-mode PCA is the best in terms of to 2013, is shown in Fig. 2. The ICSs are distributed over its reproduction of predefined types, its temporal and the continental region and are more likely to appear spatial stability, and its reduced dependence on preset over the region near the foothills of Himalayan barriers. parameters. Hence, before the k-means cluster analy- They rarely appear over the central Indian subcontinent sis, the PCA was applied in T mode (Huth et al. 2008) region, and almost no ICSs occur over the oceanic re- with a correlation matrix, using the ICS days as vari- gion. The density of ICSs is the largest over the west- ables and the grid points as observations. Several ernmost SHF, followed by the southeastern SHF. This is studies (Preisendorfer 1988; Jolliffe 2002; Merino et al. consistent with the distribution of lightning flashes 2014) have used different criteria to decide the number (Houze et al. 2007; Kumar and Kamra 2012; Cecil et al. of principal components to retain to discriminate be- 2014). The distribution of ICSs in the study area is tween signal and noise. In this case, only the most im- consistent with the distribution of the intense convection portant extracted components that account for at least shown in many studies (e.g., Zipser et al. 2006; Houze 90% of the total variance are considered in the cluster et al. 2007; Romatschke and Houze 2011; Qie et al. 2014) analysis. while different from that of deep convective systems The k-meansclusteranalysisisemployedtoclassify (Wu et al. 2013; Qie et al. 2014). data into several clusters, maximizing similarity within Figure 3 shows the seasonal variation (Fig. 3a) and clusters and minimizing similarity between clusters, diurnal cycle (Fig. 3b) of the ICSs over the SHF. From while identities of the data are unknown previously. Fig. 3a it is clear that ICSs mainly occur between March The k-means method is commonly used to establish and October and that the occurrence of ICSs is more patterns, configurations, or climatologies of atmo- likely in April and May than in the monsoon months spheric fields (Bettolli and Penalba 2012; Merino et al. (June–September). The ICSs occur most frequently in 2014; Wang et al. 2015). The nonhierarchical k-means May, in contrast with the deep convective systems, algorithm (Anderberg 1973) classifies groups of data which peak in August (Qie et al. 2014). During the according to their similarity using Euclidean distance. monsoon, the occurrence frequency of ICSs reduces One of the key points in this method is the group gradually. From Fig. 3b, it is seen that the diurnal cycle number k. The group number of k can be selected of ICSs undergoes three stages. The occurrence fre- objectively, examining the intragroup distances D in a quency of ICSs is low in the morning [0600–1200 local way that selects a k value such that the reduction of D time (LT)] and then begins to increase and is especially is not significant. However, the final choice for k is active between 1600 and 2200 LT, when more than half assigned with a certain degree of subjectivity, since it of ICSs are seen during this period by TRMM. This is should allow the results to have a correct physical in- correlated with the solar radiation, and the low-level air terpretation (Merino et al. 2014). mass heated by land surface becomes strongest in the

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FIG. 3. (a) Seasonal and (b) diurnal variations of the 1000 most intense convective systems. afternoon. Strong thermal forcing of the Tibetan Pla- summer monsoon itself (June–September), respectively. teau and its southern slope leads to an upward motion This indicates that the occurrence and location of ICSs near the slope, which contributes to the occurrence of over the SHF is closely related to the Indian summer ICSs. In addition, the interaction of the low-level air monsoon. The patterns of cluster 1 and cluster 3 seem to mass with the Himalayan terrain is also conducive to the be consistent with the distributions of extreme convec- occurrence and enhancement of the ICS. However, it tion during premonsoon and monsoon seasons from can be found that the afternoon maximum hourly fre- Romatschke et al. (2010). Although cluster 2 has the quency of the ICS is nearly 9%, which is less than that of shortest duration, its period is important to ICSs in this deep convective cores in South Asia (12% and 13% region when referring to the seasonal variation shown in during the premonsoon and monsoon; Romatschke Fig. 3 and is special compared with the previous study et al. 2010) and that of tropical and subtropical over- periods, the premonsoon and monsoon seasons (Houze shooting convection over land (;13%; Liu and Zipser et al. 2007; Romatschke et al. 2010; Wu et al. 2013). In 2005). It should be noted that the hourly frequency of this section, the mean spatial distribution and cumula- ICSs in the late night (0000–0500 LT) is about 4%, which tive distribution functions of four parameters and the is consistent with the result of Qie et al. (2014) but sig- corresponding synoptic charts in three clusters will be nificantly higher than that of deep convective cores in investigated in detail, as well as the spatiotemporal South Asia (Romatschke et al. 2010) and global tropical characteristics of ICSs. and subtropical overshooting convection over land (Liu 1) CLUSTER 1 and Zipser 2005), both of which are only about 2%. Such a different temporal variation indicates that the The mean distribution of the atmospheric parameter occurrence and development of ICSs along the SHF is configuration of cluster 1 is shown in Figs. 4a–c, as well unique and requires more detailed study in the future. as the spatial and temporal variations—namely, the geographical distribution of the 315 ICSs and their b. Cluster analysis corresponding lightning flash count seen by the TRMM Based on the four atmospheric parameters described LIS (Fig. 4d), seasonal variation (Fig. 4e), and diurnal in section 2a, the most important components, ac- cycle (Fig. 4f). The result reveals that ICSs in cluster 1 counting for at least 90% of total variance, were mainly occur during the premonsoon period (as shown extracted by using the T-mode PCA method. The prin- in Fig. 4e) and more than half of them occur in April. cipal component numbers of the four factors of F0.995, During this period, the Indian subcontinent begins to be Q1000, CAPE, and CIN are 378, 12, 17, and 97, re- dominated by the subsidence of the Hadley circulation spectively. These principal components grouped to- from the intertropical convergence zone upwelling far gether to form a new matrix. By employing the k-means equatorward, the skies are generally cloud free, and the cluster analysis on the matrix, three clusters with 315, temperature is increasing (Williams et al. 1992; Qie et al. 287, and 398 ICSs were obtained. Another cluster 2014). Hot weather over the Indian subcontinent means analysis, based on 850-hPa wind flow, 850-hPa specific large sensible heat flux, and the atmosphere is condi- humidity, CAPE, and CIN, shows similar characteristics tionally unstable, which is consistent with the same be- and will not be shown here. It is particularly noteworthy havior in Australia found by Williams et al. (1992). From that the three clusters (clusters 1, 2, and 3) correspond to the mean distribution of near-surface wind flow (F0.995) the premonsoon (March–May), monsoon establishment and wind speed (contour shading) as shown in Fig. 4a, period (late May and early June), and the Indian the dominant wind is southwesterly over the western

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21 21 FIG. 4. For cluster 1, (a) the average F0.995 (streamlines) and wind speed (color shading; m s ), (b) Q1000 (color shading; kg kg ), and 2 2 (c) CAPE (color shading; JÁkg 1) and CIN (contour lines; J kg 1) before the ICSs are observed by the TRMM satellite. (d) Location of the ICSs (black dots) and the distribution of total lightning flash counts seen by the TRMM LIS corresponding to ICSs (color shading); (e) seasonal and (f) diurnal (local time) variations of ICSs. study region and southerly over the eastern region. Bay of Bengal, the specific humidity over the eastern Nevertheless, wind speed during this period is weak, SHF is higher than the other parts of the subcontinent. especially over land. Specific humidity in Fig. 4b reveals The region with a large specific humidity also corre- that the Indian subcontinent (not including the shoreline sponds to a high CAPE (i.e., the eastern SHF). The area) is dominated by dry continental air, that the at- distribution of CIN in Fig. 4c reveals that the CIN is mosphere is drier where the mean specific humidity is very weak over the Indian subcontinent. The strongest 2 less than 0.006 kg kg 1, and that only a small amount of CIN is over the Arabian Sea, and there exists a strong ICSs occur over the central and western SHF (Fig. 4c). CIN gradient near the western coast of the Indian Together with the moister conditions over the ocean subcontinent. (the Bay of Bengal and the Arabian Sea), this forms a It is possible that the details could be washed out and strong humidity gradient near the coast of the Indian the maxima and minima could be underestimated during subcontinent. Because of the slightly stronger southerly the field composite, so the corresponding maximum wind and higher specific humidity over the northwestern specific humidity, maximum CAPE, and minimum CIN

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FIG. 5. Cumulative distribution functions of (a) maximum Q1000, (b) maximum CAPE, and (c) minimum CIN of the ICSs in cluster 1. Dashed lines mark the 25%, 50%, and 75% fractions and the corresponding values, respectively. near the ICSs are calculated and their cumulative dis- concentrate over the eastern end of the SHF. Compar- tribution functions are shown in Fig. 5. Figure 5 shows ing the distributions of humidity (Fig. 4b), temperature that the maximum specific humidity near the ICS ranges at 850 hPa (Fig. 6d), and CAPE (Fig. 4c), it is found that 2 from 0.008 to 0.035 kg kg 1 with a median of approxi- the moister conditions correspond to a higher CAPE, 2 mately 0.02 kg kg 1. Correspondingly, the range of even though the temperature may be lower (e.g., at the 2 CAPE is from 0 to 4000 J kg 1, while half of the ICSs northern part of the Bay of Bengal). There are also some 2 show a maximum CAPE less than 700 J kg 1. The min- regions with less moisture (e.g., the central Indian sub- 2 imum CIN is between 0 and 2700 J kg 1 with a median continent) where the CAPE is smaller even though its 2 of 2200 J kg 1. Such an atmospheric environment temperature may be higher, which is consistent with the eventually leads to a situation where most of the ICSs of conclusions from Riemann-Campe et al. (2009) and Wu cluster 1 distribute densely over the southeastern SHF as et al. (2013) that CAPE relies more on humidity and less shown in Fig. 4d. Only a few ICSs are distributed over on temperature. During this period, the geopotential the central and western SHF where mean specific hu- height at 500 hPa decreases from south to north and the 2 midity is about 0.006–0.01 kg kg 1 (refer to Fig. 4b). The atmospheric pressure is high. South of the Tibetan Pla- geographical distribution of the corresponding lightning teau the geopotential height at 500 hPa is between 5790 flashes (Fig. 4d) is consistent with the distribution of and 5850 gpm and the contours are denser, which ICSs. The major diurnal variation feature in Fig. 4f is means a stronger pressure gradient force and stronger similar to that of the total ICSs and mainly occurs in the winds. The temperature decreases from south to north at afternoon and night, with a peak at around 1700 LT. The 500 hPa, and there is a weak warm center over the Ti- ICSs occur more frequently in late night (0000–0040 LT) betan Plateau. than the total ICSs in Fig. 3b. 2) CLUSTER 2 The corresponding mean geopotential height and temperature fields at 500- and 850-hPa isobaric surface The atmospheric parameters for cluster 2 and the are shown in Fig. 6. The geopotential height at 850 hPa climatology characteristics of ICSs are shown in Fig. 7. (Fig. 6a) shows a decreasing trend from south to north, ICSs in this cluster occur mainly during the monsoon with a low pressure (,1490 gpm) area along the Hima- establishment period, from late May to early June layas. It is notable that the temperature field at 850 hPa (Fig. 7e). Over 60% of ICSs in cluster 2 occur in May and (Fig. 6b) shows a wide and closed high-temperature re- account for approximately 73% of total ICSs in May, gion over the Indian subcontinent, with the maximum which is a vital contribution to the maximum frequency temperature exceeding 298 K. This corresponds to the in May as shown in Fig. 3a. During this period, the mean hot and dry weather over the Indian subcontinent, near-surface wind is more intense than in cluster 1, 2 meanwhile forming a strong temperature gradient along with a maximum wind speed exceeding 8 m s 1 over the the coastline. The hot condition may provide sensible ocean (Fig. 7a). The mean specific humidity in Fig. 7b heat flux for the formation and development of the ICS. indicates that the humidity increases and the atmo- The strong temperature gradient near the northwest sphere is wetter than that during the premonsoon coastline with the Bay of Bengal, together with the (cluster 1) both over ocean and land. The atmospheric strong humidity gradient (Fig. 4b), results in deep conditions over the inland region are still relatively dry convection occurring frequently along the east coastline compared to the ocean and coastal areas, with mean 2 of the Indian subcontinent during the premonsoon specific humidity of about 0.008–0.012 kg kg 1. Note (Romatschke et al. 2010; Qie et al. 2014). Within the that the southwesterly wind, originating from the Ara- study region (inner rectangle in Fig. 1), more ICSs bian Sea, is able to maintain a higher speed even when it

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FIG. 6. Cluster 1 average (white contour lines) and standard deviation (shading) of (a),(c) geopotential height (gpm) and (b),(d) temperature (K) at (top) 850 and (bottom) 500 hPa. reaches over land, resulting in the southwest of the study The distribution of CAPE (shown in Fig. 7c) over this region being dominated by southwesterly wind with an region is consistent with the specific humidity and 2 average speed of 4–8 m s 1. However, the western In- features a gradient from southeast to northwest along dian subcontinent remains less moist than the northeast, the Himalayas. Over the northeastern Arabian Sea and even though the southwesterly wind from the Arabian adjacent continent, the CIN is strong, especially over the Sea is stronger (Figs. 7a,b). Conversely, over the sea, while the specific humidity and CAPE are weaker northeastern Indian subcontinent, the southerly wind compared with those over the Bay of Bengal. This re- over the Bay of Bengal transports plenty of oceanic veals that the atmosphere over the Arabian Sea is more moisture to land, even though the wind is weaker there stable and drier than that over the Bay of Bengal, than over the western subcontinent. This may be related leading to the air mass transported from the Arabian Sea to the difference of near-surface temperature over dif- to the western Indian subcontinent containing stronger ferent sides of the land, which results from the sensible CIN and less water vapor. Over the Bay of Bengal, since heating of land surface. The northwestern Bay of Bengal the wind is stronger than in cluster 1, when the low-level is adjacent to the east coast of the Indian subcontinent, southerly wind encounters the steep Himalayas, it be- and its near-surface temperature is considered to be gins to turn left and flows northwest along the Himala- warmer than that over the easternmost Arabian Sea. A yan foothills, forming a transport passage along the warmer atmosphere has a greater potential for main- Himalayas to the west. It should be noted that the taining water in the atmosphere as vapor. transport passage only extends to the central SHF

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FIG.7.AsinFig. 4, but for cluster 2. during this period. With this configuration of atmo- 50%, and 75% are approximately 200, 450, and 2 spheric parameters, ICSs locate over the whole SHF 1250 J kg 1, respectively, also less than that in cluster 1. somewhat evenly and without a significant dense center It should be noted that CAPE values in this cluster are compared to the other two clusters, as do the corre- especially small and over half of ICSs occur in the en- 2 sponding lightning flashes. The diurnal variation in vironment with CAPE less than 450 J kg 1, which is in- Fig. 7f indicates that the most active period of ICSs is conceivable for the occurrence of an intense storm with around 1900 LT in this cluster, and the occurrence fre- 40-dBZ echo-top height reaching 10-km altitude and 2 quency of ICSs in the late night (0000–0400 LT) is less with lightning of at least 32 flashes min 1. Further study than in Fig. 3. The cumulative distribution functions of is needed to obtain the physical interpretation. The CIN corresponding maximum humidity, maximum CAPE, is slightly weaker than that in cluster 1. and minimum CIN are presented in Fig. 8. Figure 8 re- On the 850-hPa isobaric surface, the geopotential veals that the maximum specific humidity range is nar- height (Fig. 9a) near the SHF is about 25 gpm lower than rower than that in cluster 1 and the maximum humidity in the cluster-1 condition (1490 gpm), and there is a 2 is 0.029 kg kg 1. The humidity with proportions of 25%, trough (the Bay of Bengal depression) located at the 50%, and 75% are all less than that in cluster 1. And eastern SHF. It occurs as a part of the intraseasonal correspondingly, the CAPE with proportions of 25%, oscillation (Hoyos and Webster 2007) and in connection

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FIG.8.AsinFig. 5, but for cluster 2. with the mesoscale convective systems over this region region over the eastern SHF where the specific hu- (Houze et al. 2007). This decrease is also conducive to midity is even greater than over the ocean, as shown in the development of the easterly wind flow along the Fig. 10b, and the maximum specific humidity exceeds 2 Himalayas, as well as the formation of the transport 0.02 kg kg 1. The cumulative distribution functions of passage. The temperature over the continent is higher humidity as shown in Fig. 11a indicate that the maxi- than before, especially in the northwestern Indian sub- mum specific humidity is highly concentrated in cluster continent, which shows a strong northwest–southeast 3, and over 80% of ICSs occur with the maximum hu- 2 distribution feature. The weather during this period is midity between 0.018 and 0.024 kg kg 1. Meanwhile, the hottest over the Indian subcontinent, and the max- the geopotential height at 850 hPa (Fig. 12a) reveals imum surface temperature can reach even about 508Cin that the air pressure decreases along the SHF com- India (De et al. 2005). The standard deviation of tem- pared with the previous result, with the minimum perature over land is larger than over ocean. At the geopotential height lower than 1455 gpm, which is 500-hPa level, both the geopotential height (Fig. 9c) and significantly smaller than the 1465 gpm in cluster 2 and temperature (Fig. 9d) increase more than in cluster 1. 1480 gpm in cluster 1. The strong low pressure center The geopotential height south of the Himalayas exceeds is conducive to the cyclonic deflection of the wind di- 5800 gpm, about 20 gpm higher than in cluster 1, and rection. In addition, denser contour lines over the south- contours are more sparse. A trough is located at the ern region at 850 hPa indicate a stronger pressure gradient eastern SHF, and its location is farther eastward than force and larger wind speed, especially over the ocean that at 850 hPa. Temperature at 500 hPa is warmer, and (refer to Fig. 10a). Together with the distribution of spe- the warm center over the Tibetan Plateau is also en- cific humidity (refer to Fig. 10b), decreasing from south- hanced. These all indicate that the atmospheric condi- east to northwest along the Himalayan foothills and tion of cluster 2 corresponds to the adjustment period reaching the westernmost SHF during this period, it is from the premonsoon to summer monsoon. revealed that the westward transport passage from the Bay of Bengal along the Himalayas is further enhanced 3) CLUSTER 3 compared to previous periods. Also, the transport passage Cluster 3 has the most ICSs, and there are 398 ICSs in provides water vapor supply for the formation of ICSs total. Figure 10 shows the mean atmospheric configu- over the western SHF. ration and the climatology characteristics of the ICSs in The distribution of CAPE is consistent with specific this cluster. ICSs in this cluster mainly occur during the humidity as shown in Figs. 10b,c. It can be found in monsoon season (June–September) with the peak oc- Fig. 11b that the number of ICSs with smaller CAPE currence frequency appearing in July as shown in values is less than that in cluster 1 (Fig. 5b) and cluster 2 Fig. 10e. With the Indian summer monsoon established, (Fig. 8b). Over 75% of ICSs in cluster 3 show CAPE 2 the intertropical convergence zone moves from the greater than approximately 1200 J kg 1, while only the Southern Hemisphere to the Northern Hemisphere, and top 25% of ICSs in cluster 2 show CAPE greater than 2 most parts of the Indian subcontinent are dominated by approximately 1200 J kg 1. The mean distribution of strong summer monsoon winds (Fig. 10a). The wind is CIN in Fig. 10c shows that the strongest CIN still ap- further enhanced, with the maximum wind speed over pears over the northern Arabian Sea, extending north- 2 the ocean exceeding 10 m s 1, and larger than that in the ward to land and affecting the adjacent continental area. other two clusters. The previous dry and hot weather The cumulative distribution functions of CIN (Fig. 11c) over the Indian subcontinent is replaced by the monsoon show a similar distribution characteristic in the three rainy weather. Moisture is transported from the Bay of clusters. Although the moisture over the southwestern Bengal northward to land and forms a high-humidity part of the analysis region increases noticeably (cf.

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FIG.9.AsinFig. 6, but for cluster 2.

Figs. 7b and 10b), the moisture transport capacity is period of the monsoon, and the contour lines become slightly weaker compared with that along the Hima- more sparse than before. As a result, ICSs in cluster 3 layas. The air parcel flows from the Arabian Sea east- are mainly located over the western SHF, especially the ward to the Indian subcontinent and then turns concave indentation region. A stronger low pressure northwest to the western SHF region. system at 850 hPa (the Bay of Bengal depressions) with The atmosphere at 850 hPa (Fig. 12b) becomes sig- higher temperature at 500 hPa and abundant near- nificantly cold compared to the previous periods be- surface water vapor content lies over the eastern SHF, cause of the monsoon rainfall during this period. which is conducive to the occurrence of broad stratiform However, the atmosphere is still warmer over the con- echoes or a mixture of stratiform and convective pre- cave indentation region than elsewhere in the study re- cipitation (Houze et al. 2007; Medina et al. 2010; Houze gion because of the warm airflow from the Afghan et al. 2015). Only a few ICSs are sparsely located in the plateau (a hot and dry elevated desert), and the geo- central and eastern portions of the SHF. The distribu- potential height shows a depression of about 1455 gpm tion of lightning flashes is closely consistent with the (Fig. 12a). Atmospheric conditions at 500 hPa are ICSs. ICSs mainly occur from afternoon to late night warmer than in cluster 1 and cluster 2 because of the (0400 LT) and are more frequent in the late night (0000– enhancement of the solar radiation and the strong sen- 0400 LT) than the total ICSs in Fig. 3b, which is similar sible heat flux over the Tibetan Plateau in boreal sum- to that in cluster 1. mer. The geopotential height at 500 hPa is reduced Although the most vigorous convection and the most compared to the premonsoon and the establishment frequent lightning activity on Earth occurs in the

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FIG. 10. As in Fig. 4, but for cluster 3. westernmost SHF (e.g., Liu and Zipser 2005; Zipser local air mass, and 34% of them show a long-range et al. 2006; Liu et al. 2007; Cecil et al. 2014), there is still transport within 96 h. Previous studies looking at no consensus on the moisture sources of convective ﬂooding scenarios in both India and Pakistan (Houze systems in this region. To further track the moisture et al. 2011; Rasmussen and Houze 2012; Rasmussen sources and their transport pathway of ICSs over the et al. 2015) showed that long-range transport was very western end of the SHF, 96-h hourly backward trajec- important for bringing extra moisture into the region tories at 1000 m above ground level (AGL) coinciding supporting ﬂoods. The ICSs with the water vapor with the locations of 129 ICS cases, which occur in the transport pathway from the Arabian Sea account for concave indentation region (north of 328N), are simu- 17% of simulated cases, and the ICSs with the moisture lated by using the NOAA/ARL HYSPLIT model (see transport from the Bay of Bengal account for 9%. Ac- http://ready.arl.noaa.gov/HYSPLIT_traj.php) combined tually, air parcels may undergo multiple cycles of with NCEP Global Data Assimilation System (GDAS) moisture uptake and release along their way before meteorological data. The cluster-mean trajectories of reaching the target region. Therefore, because of the four groups obtained by using trajectory cluster anal- precipitation during parcel transport, earlier moisture ysis are shown in Fig. 13. It is revealed that 66% of uptake will contribute less and less to the precipitation simulated ICS cases in this region are supported by the within the target region (Sodemann et al. 2008). Water

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FIG. 11. As in Fig. 5, but for cluster 3. vapor to feed ICSs is mainly provided by the local en- the deep convective systems over the same region occur vironment, which means that the formation of most ICSs in July. ICSs mainly occur in the afternoon, while the is closely related to the geographical distribution of hourly frequency at late night (0000–0400 LT) is larger humidity. From the evolution of mean spatial distri- than elsewhere because of the unique terrain condition, butions of the wind and specific humidity fields from especially during the premonsoon (cluster 1) and mon- cluster 1 to cluster 2, and then to cluster 3, it can be soon (cluster 3) found in this paper. found that the water vapor transport passage along the The occurrence and geographical distribution of Himalayas from the Bay of Bengal extends to the ICSs along the SHF are closely related to the estab- central SHF (corresponding to cluster 2) and reaches lishment of water vapor transport passage from the the westernmost region of the SHF (corresponding to northern Bay of Bengal along the Himalayas to the cluster 3) step by step. This provides water vapor for west, strongly depending on the intensity of south- the formation of ICSs over the western SHF during the westerly wind over the Bay of Bengal during different monsoon season. In addition, the distribution of wind periods of the Indian summer monsoon. With the sea- flow and humidity in Figs. 10a,b shows that the air son transition from the premonsoon to the establish- parcels originated from the Arabian Sea are trans- ment period of monsoon and the monsoon itself, the ported eastward to the central Indian subcontinent southwesterly wind over the Bay of Bengal is gradually first, then turn to the northwest, and finally reach the enhanced. Before the summer monsoon is established, western SHF, which also can contribute to the forma- the Indian subcontinent is dominated by the dry and tion of ICSs over the western SHF. hot continental air mass, which means a strong sensible heat flux to near-surface atmosphere. The major de- ficiency is the moisture in cluster 1 and cluster 2 to 4. Conclusions forming ICSs over the SHF . The moisture over the Bay Based on the 16-yr TRMM satellite observational of Bengal is blown northward to the eastern SHF by the data and the NCEP CFS Reanalysis data from 1998 to southwesterly wind during the premonsoon; hence, 2013, the climatology characteristics of ICSs along the ICSs mainly occur over the eastern SHF. Then, during SHF are investigated, and some possible causes are an- the monsoon establishment period, the oceanic south- alyzed by using the multivariate analysis methods of westerly wind enhances more than before, and the PCA and cluster analysis. The main results are sum- water vapor is transported northwestward along the marized as follows. Himalayas, extending to the middle of the SHF. Also, Based on the wind flow and specific humidity at near- ICSs in cluster 2 are located somewhat evenly along the surface level, including CAPE and CIN above ground Himalayascomparedtoinclusters1and3.Afterthe and water surfaces, ICSs are classified into three clusters Indian summer monsoon establishes, the southwesterly corresponding to the premonsoon (March–May), the wind over the ocean is the strongest, and the transport monsoon establishment period (late May and early passage along the SHF arrives at the western end of the June), and the South Asian summer monsoon (June– SHF, together with the warm and dry air from the September), respectively. The geographical distribution Afghan plateau, which results in most of the ICSs in shows that most ICSs occur over land, especially the cluster 3 being concentrated at the concave indentation eastern SHF region during the premonsoon and the of the westernmost SHF. Backward trajectory analysis westernmost SHF region during the monsoon. The ICSs confirms that most of the ICSs (66%) over the concave along the SHF mainly occur during March–October, and indentation region are supported by the local envi- the maximum monthly frequency appears in May, while ronment. It is found that 17% of the ICSs have long- convective activity over the Northern Hemisphere and distance water vapor transport from the Arabian Sea

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FIG. 12. As in Fig. 6, but for cluster 3. and 9% of them from the Bay of Bengal along the to cluster 3, and over 80% of ICSs have a maximum 2 Himalayas. humidity between 0.018 and 0.024 kg kg 1 in cluster 3. The mean spatial distributions of wind flow and spe- The monsoon establishment period (late May and cific humidity reveal that ICSs are more likely to occur early June) is an adjustment stage of atmospheric cir- over the continental region with a moderate humidity culation from the premonsoon to the monsoon. Over 60% and strong humidity gradient condition, where dry and of ICSs appear in May during this period, which con- moist air masses interact frequently. Neither too humid tribute about 73% of total ICSs over the SHF in May. The nor too dry conditions are conducive to the formation of occurrence frequency of ICSs in cluster 2 at late night the ICS. There is not enough water vapor to support the (0000–0400 LT) is significantly smaller than that in cluster formation of ICSs in drier conditions (e.g., the central 1 and cluster 3. Half of the maximum CAPE values are 2 regions of the subcontinent during the premonsoon). In lower than approximately 450 J kg 1, and 75% of them 2 the most humid environments, the instability is fre- are lower than 1200 J kg 1 in cluster 2, which is especially quently released by weak-to-moderate convection and smaller than those in the other two clusters. All these cannot build up to greater amounts to support ICS for- differences suggest that the monsoon establishment mation. There are significant differences for specific period (cluster 2) is an important period and should be humidity in the three clusters. The maximum specific given more attention in future study, instead of the 2 humidity has a wide value range of 0.008–0.035 kg kg 1 premonsoon and monsoon only. 2 with a median of about 0.02 kg kg 1 in cluster 1. The The analysis results of the present paper are based on ranges become narrower from cluster 1 to cluster 2, then 16 years of TRMM observational data and reanalysis

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