Journal of Climate. Convective Variability associated with the Boreal Summer Intraseasonal Oscillation in the South China Sea Region

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1 Journal of Climate Convective Variability associated with the Boreal Summer Intraseasonal Oscillation in the South China Sea Region --Manuscript Draft-- Manuscript Number: Full Title: Article Type: Corresponding Author: Corresponding Author's Institution: First Author: Order of Authors: JCLI-D Convective Variability associated with the Boreal Summer Intraseasonal Oscillation in the South China Sea Region Article Weixin Xu Colorado State University Fort Collins, UNITED STATES Colorado State University Weixin Xu Weixin Xu Steven Rutledge Abstract: This study investigates the convective cloud population, precipitation microphysics, and lightning activity associated with the Boreal Summer Intraseasonal Oscillation (BSISO) over the South China Sea (SCS) and surrounding landmasses. SCS rainfall shows a marked 30-60d intraseasonal variability. This variability is less evident over land. The population of mesoscale convective systems (MCSs) and the stratiform rain fraction over the SCS, Philippines, and Indochina increase remarkably after the onset of BSISO. Convection over the SCS during inactive periods exhibits a trimodal population including shallow cumulus, congestus and deep convection, mirroring the situation over tropical open oceans. The shallow mode is absent over land. Shallow cumulus clouds rapidly transition to congestus clouds over the SCS under active BSISO conditions. Over land, deep convection and lightning lead total rainfall and MCSs by 2-3 BSISO phases, while they are somewhat in phase over the SCS. Though convective instability over the SCS is larger during active periods compared to inactive periods, variability in convective intensity and precipitation microphysics is minimal, with active periods showing only higher frequency of moderate ice scattering and 30- dbz heights extending to -10 oc. Over the Philippines and Indochina, inactive phases exhibit substantially stronger ice scattering signatures, robust mixed-phase microphysics, and higher lightning flash rates, possibly due to greater convective instability and a stronger convective diurnal cycle. Total rainfall, convective environments, and convective structures over Borneo are all out of phase with that over Philippines and Indochina, while Southern China shows little BSISO variability on convective intensity and lightning frequency. Powered by Editorial Manager and ProduXion Manager from Aries Systems Corporation

2 Convective Variability associated with the Boreal Summer Intraseasonal Oscillation in the South China Sea Region Weixin Xu and Steven A. Rutledge Department of Atmospheric Sciences, Colorado State University, Fort Collins, CO Submitted to: Journal of Climate Submitted: February 26, 2018 Revised: June 7, 2018 Accepted: June 11, Corresponding Author Address: Dr. Weixin Xu, Department of Atmospheric Sciences, Colorado State University, 3915 West Laporte Avenue, Fort Collins, CO

3 ABSTRACT This study investigates the convective cloud population, precipitation microphysics, and lightning activity associated with the Boreal Summer Intraseasonal Oscillation (BSISO) over the South China Sea (SCS) and surrounding landmasses. SCS rainfall shows a marked 30-60d intraseasonal variability. This variability is less evident over land. The population of mesoscale convective systems (MCSs) and the stratiform rain fraction over the SCS, Philippines, and Indochina increase remarkably after the onset of BSISO. Convection over the SCS during inactive periods exhibits a trimodal population including shallow cumulus, congestus and deep convection, mirroring the situation over tropical open oceans. The shallow mode is absent over land. Shallow cumulus clouds rapidly transition to congestus clouds over the SCS under active BSISO conditions. Over land, deep convection and lightning lead total rainfall and MCSs by 2-3 BSISO phases, while they are somewhat in phase over the SCS. Though convective instability over the SCS is larger during active periods compared to inactive periods, variability in convective intensity and precipitation microphysics is minimal, with active periods showing only higher frequency of moderate ice scattering and 30-dBZ heights extending to -10 o C. Over the Philippines and Indochina, inactive phases exhibit substantially stronger ice scattering signatures, robust mixed-phase microphysics, and higher lightning flash rates, possibly due to greater convective instability and a stronger convective diurnal cycle. Total rainfall, convective environments, and convective structures over Borneo are all out of phase with that over Philippines and Indochina, while Southern China shows little BSISO variability on convective intensity and lightning frequency

4 Introduction The Asian summer monsoon (ASM) is one of the strongest components of the global monsoon system (Chang et al. 2011). The strong ASM circulation impacts a large region of the tropics and subtropics in the eastern hemisphere. The ASM is thought to be driven by large-scale thermal contrast between the Eurasian continent and Indo-Pacific Ocean (Yanai et al. 1992; Li and Yanai 1996; Wu and Zhang 1998). The initial onset of the ASM occurs in the Bay of Bengal (BOB) and the South China Sea (SCS) during early-to-mid May (Tao and Chen 1987; Wu et al. 1998). As the monsoon trough over the SCS deepens and extends northward, the ASM marches northward and establishes itself over southern China and the northern SCS, marking the beginning of the Meiyu/Baiu rainy season in East Asia (Wu et al. 1998; Chen 2004; Ding and Chan 2005). After the ASM onset, active and break monsoon periods are largely determined by the boreal summer intraseasonal oscillation (BSISO), a specific mode of the tropical intraseasonal oscillation (ISO) prevailing in boreal summer (Wang and Xie 1997). While the ISO in boreal winter is of course the Madden-Julian Oscillation (MJO) dominated by eastward propagation of deep convection in the tropics, the BSISO exhibits an additional northward propagating feature due to effects of monsoonal vertical wind shear (Wang and Xie 1997; Jiang et al. 2004) and air-sea coupling (Kemball-Cook and Wang 2001, Fu et al. 2003). The BSISO consists of two major modes, the day mode and the day oscillation (Wang et al. 2005; Waliser 2006; Kikuchi et al. 2012; Chu et al. 2012; Lee et al. 2013). The dominant day mode (similar time scales to the MJO) features prominent eastward and northward/northeastward propagation, and is identified by a northwestsoutheastward tilted rain band between BOB and the SCS (Wang and Xie 1997). The day oscillation mainly shows northward/northwestward progression and a southwest-northeast 3

5 elongated frontal-like rain band (Lee et al. 2013). The BSISO has broad impacts on the ASM including monsoon onset (Wang and Xie 1997; Kang et al. 1999), active and break monsoon periods (Goswami 2005; Hoyos and Webster 2007; Ding and Wang 2009), seasonal mean rainfall (Krishnamurthy and Shukla 2007, 2008), and precipitation extremes (Hsu et al. 2016; Gao et al. 2016; Chen and Zhai 2017; Lee et al. 2017). Virts and Houze (2016) showed that mesoscale organization, vertical cloud structure, and lightning activity within convection over and around the BOB all vary significantly across the BSISO cycle (particularly the day mode). The BSISO also influences the midlatitude weather and climate by interacting with the midlatitude circulation directly or indirectly (Ding and Wang 2005, 2007; Lee et al. 2011; Moon et al. 2013). Unfortunately, our ability to simulate and predict the BSISO is severely limited (Waliser et al. 2003; Kim and Kang 2008; Sabeerali et al. 2013), due to model misrepresentation of processes key to the BSISO. Model improvement requires a more complete understanding that can only be obtained by extensive observations of the BSISO, e.g., evolution and structure of cloud and precipitation processes, vertical profiles of tropospheric moistening and heating, surface fluxes, atmospheric boundary-layer processes, upper-ocean mixing and air-sea interaction. Indeed these outstanding problems have motivated the Propagation of the Intraseasonal Tropical Oscillation (PISTON) field experiment to be held in late summer-early fall 2018 ( The South China Sea Monsoon Experiment (SCSMEX) held in May-June 1998 collected a rich dataset of radar, atmospheric sounding, and surface observations for studying convection and convective environments associated with the SCS monsoon onset (Lau et al. 2000). SCSMEX observations have been extensively used to investigate the organization and propagation characteristics of convection, convective structures and precipitation microphysics, 4

6 regional variability of convection (southern versus northern SCS), convective heating profiles, and the diurnal cycle (Johnson and Ciesielski 2002; Wang 2004; Johnson et al. 2005; Wang and Carey 2005; Ciesielski and Johnson 2006; Aves and Johnson 2008). SCSMEX studies suggested that SCS convection generally resembled other tropical oceanic systems in terms of convective organization, e.g., shear-parallel convective lines (Wang 2004; Johnson et al. 2005), convective intensity (Wang and Carey 2005), and ensemble precipitation microphysics (Wang and Carey 2005). However, some unique features of SCS convection were also identified. Two unique convective organizational modes were found for the SCS convection possibly owing to its interaction with subtropical frontal systems propagating from southern China (Johnson et al. 2005). The stratiform rain fraction within precipitation systems over the northern SCS (25%) was substantially smaller compared to general tropical oceanic convection (40-50%), possibly due to reduced atmospheric instability, low sea surface temperatures (SSTs), and relatively dry upper tropospheric conditions during SCSMEX (Johnson et al. 2005; Wang and Carey 2005). While SCSMEX focused on convection occurring before and during the onset of the SCS monsoon in May-June, SCSMEX did not observe mid-to-late summer convection over the SCS nor consider the BSISO cycles (or active-break monsoon cycles). Many studies have showed contrasting convective intensities and structures between active and break periods of various monsoons (e.g., Williams et al. 1992; Petersen and Rutledge 2001; Cifelli and Rutledge 1998; Xu and Zipser 2012), and between the low-level westerly and easterly wind regimes in the Amazon (Petersen et al. 2002; Cifelli et al. 2002; Williams et al. 2002). Convection during monsoon breaks and easterly regime in the Amazon is more intense, containing strong mixed-phase processes (owing to higher CAPE and stronger updrafts) resulting in frequent lightning activity (Mohr and Zipser, 1996; Petersen and Rutledge 2001; Williams and 5

7 Stanfill 2002; Xu and Zipser 2012). Monsoon (or the Amazon westerly regime) convection resembles maritime convection characterized by weak to moderate intensity, significant warmrain processes, and only weak mixed-phase precipitation growth (Petersen and Rutledge 2001; Williams and Stanfill 2002; Xu and Zipser 2012). Lightning is markedly reduced during this phase. These regime-based variations in convective intensity and mixed-phase microphysics are attributed to thermodynamic variability (Williams et al. 1992; Rosenfeld and Lensky 1998; Petersen and Rutledge 2001) or aerosol loading (Rosenfeld and Lensky 1998; Williams and Stanfill 2002), or both processes working in concert (Williams and Stanfill 2002; Stolz et al. 2015). Over the SCS, convective intensity is stronger before the monsoon onset than after, as indicated by larger flash rates (Yuan and Qie 2008). Ho et al. (2008) showed that inactive ISO periods (easterly conditions) exhibited more intense radar structures compared to the active ISO periods (westerly conditions). Furthermore they showed that convection over the SCS during the inactive ISO was more land-based, i.e., peak convection was mainly initiated over land in the afternoon and migrated offshore in the evening. Similarly, convection over the SCS was stronger than open ocean convection (i.e., Philippine Sea) as indicated by more intense radar reflectivity structures and microwave ice scattering signatures (Park et al. 2007). Convection over the SCS might be best described by a combination of continental and oceanic regimes, possibly impacted by aerosols advected from adjacent continents/islands or the migration of continental convective systems from land (Takayabu 2006; Park et al. 2007; Ho et al. 2008). Nevertheless, the full spectrum of the convective cloud population and microphysical structures associated with the BSISO cycles over the SCS and surrounding landmasses warrants further study. This study provides a large-scale climatological context of the convective cloud populations and microphysical characteristics throughout the BSISO cycles over the SCS and 6

8 adjacent land areas. Sixteen years of measurements from the Tropical Rainfall Measuring Mission (TRMM) are used to quantify convective structures as a function of BSISO phase (30-60 day mode), specifically, convective organization, precipitation type, cold cloud top characteristics, vertically integrated ice content, vertical precipitation structures, and lightning flash rates. These TRMM-based convective parameters are also related to environmental variables derived from reanalysis data to determine how major environmental factors may modulate convective structures throughout the day cycles. We also examine variability in precipitating cloud populations and precipitation microphysics between regions along the active BSISO rain band (i.e., the SCS, Philippines, Indochina Peninsula) and areas outside the rain band (Borneo and Southern China) Data and Methodology Data used in this study include a multi-satellite rainfall product, large-scale reanalysis, TRMM precipitation features (PFs), and TRMM Lightning Imaging Sensor (LIS) orbital lightning observations during BSISO peak periods (June-September) from 1998 to These data are stratified by BSISO phase defined by the BSISO index (Lee et al. 2013). This study focuses on the key BSISO region over the SCS and surrounding landmasses [5S-30N; E], including the Indochina peninsula (INDO), Philippines (PHIL), Borneo (BORN), and Southern China (SCH) as marked in Fig a. Large-scale rainfall maps and environmental variables To study the large-scale rainfall patterns as a function of BSISO phase, we use the TRMM Multi-satellite Precipitation Analysis surface rainfall product (version 7) called 3B42 (Huffman et al. 2007). The 3B42 rainfall data have a 3 h temporal resolution and a 0.25 o spatial resolution, 7

9 available from 50 S to 50 N during This dataset mainly uses passive-microwave measurements from low-earth orbit satellites, which were first calibrated by the TRMM PR. This study examines a set of environmental variables including SST, near surface (2 m) temperature, low-level (850 hpa) winds, mid-level (500 hpa) geopotential height, relative humidity at these two levels, vertical wind shear ( hpa), and convective available potential energy (CAPE). SST data are taken from the TRMM Microwave Imager and Advanced Microwave Scanning Radiometer for EOS (Gentemann et al. 2010). SST data are on daily time scales, the same scale as the BSISO index data. The atmospheric environmental variables are derived from the ancillary data of TRMM PF database (Liu et al. 2008). The ancillary data are based on European Centre for Medium-Range Weather Forecasts re-analysis Interim (ERA- Interim) reanalysis data (Dee et al. 2009), which have a horizontal spatial resolution of 1 o by 1 o, temporal resolution of 6 h and mean vertical resolution of 25 hpa. Reanalysis data were interpolated into locations of PFs using linear interpolation methodology (Liu et al. 2008). Specifically, atmospheric variables including near surface air temperature at 2 m, convective available potential energy (CAPE), relative humidity (RH), and deep vertical wind shear are analyzed. CAPE is accumulated from the near-surface level (1000 hpa over ocean and 925 hpa over land) up to the level of neutral buoyancy. RH is averaged over lower troposphere ( hpa) and mid-troposphere ( hpa) levels. Deep vertical wind shear is defined as the wind shear between hpa (V150 V700). Deep shear was thought to be an important factor for convective vigor and development of stratiform precipitation during the upscale growth of convective systems (Saxen and Rutledge 2000)

10 b. TRMM observations Two different levels of TRMM data are used in this study, specifically, the TRMM PF database (Liu et al. 2008), and orbital lightning observations from TRMM LIS (both version 7). LIS flash data (from all orbits) are used to calculate the lightning flash density over the entire study region [5S-30N; E]. During each TRMM overpass, LIS detects total lightning (both intracloud and cloud-to-ground lightning) events (radiance-based), employing a 5 km horizontal resolution and a temporal resolution of 2 ms (Christian 1999). LIS lightning events are grouped into flashes (a flash is identified as events within 6 km of one another and occurring within a 330 ms interval). The flash detection efficiency of LIS has been established to be 70% 90% (Boccippio et al. 2002; Christian et al. 2003). The PF database utilizes various instruments on TRMM (Kummerow et al. 1998) including the PR, LIS, TRMM Microwave Imager (TMI), and Visible and IR Scanner (VIRS). These multiple sensor measurements were grouped into PFs as described by Liu et al. (2008). PFs are first defined as clusters of PR raining pixels (5 km horizontal res.) at the near surface level, with the centroid (based on elliptical fitting) of the cluster as the location of each PF. PR vertical profiles (250 m vertical res.), as well as measurements of various resolutions from VIRS, TMI, and LIS, are then collocated into the PR pixels of each PF. Therefore, a PF contains quantities such as precipitation area, fraction of convective/stratiform rain, radar echo top height, frequency of radar reflectivity values as a function of altitude, microwave brightness temperature (Tb), lightning flash rate, etc. Horizontally and vertically polarized Tb at 85 GHz from TMI is converted into the polarization corrected temperature (PCT). PCT at 85 GHz (PCT85) is a good proxy for ice scattering (Spencer et al. 1989) or vertically integrated ice content (Vivekanandan et al. 1991). Frequencies of precipitation (PR pixels) relative to PF size, stratiform rain fraction, 9

11 dBZ echo-top height, infrared (IR) Tb, and PCT85, as well as 30-dBZ occurrence in the mixed-phase region and PDF of flash rates, are all derived from the PF database. Temperatures at PR vertical range heights (above sea level) are calculated through the interpolation of pressure-level temperatures and geopotential heights from ERA-Interim reanalysis data. c. BSISO indices A primary goal of this study is to examine convection as a function of BSISO phase in the day mode. For this purpose, we use the BSISO indices developed by Lee et al. (2013) (hereafter, Lee index), which is available from 1981 to present ( The Lee index is derived from the Multivariate empirical orthogonal functions (MV-EOFs) of 850-hPa zonal wind and outgoing long-wave radiation over the entire ASM region [10S-40N, E]. The day mode is represented by the first and second EOF principal components (PC). The Lee index better captures BSISO features in the ASM region compared to previous BSISO indices (e.g., Waliser et al. 2004; Annamalai and Sperber 2005; Kikuchi et al. 2012) and the MJO index (Wheeler and Hendon 2004). BSISO index is on a daily timeframe and has eight phases, indicating various states of the ISO over the ASM region. In order to focus on major BSISO conditions, BSISO data are inclusive to days with significant amplitude, i.e., (PC1 2 + PC2 2 ) 1/2 > 1 during June-September. The total number of days, TRMM overpasses, and PFs in specific BSISO phases is listed in Table 1. Obviously, there are a large number of data samples in each BSISO phase (e.g., sample days with over 1000 TRMM overpasses in each phase). These statistics provide confidence for the phase composites used in this study

12 Overview of Days Variability a. Large-scale rainfall and synoptic conditions Figure 2 shows the composites of rainfall and 850-hPa winds as a function of BSISO phase during June-September. Generally, precipitation and low-level winds are suppressed over the SCS during phases 1-3 (Figs. 2a-c), whereas phases 5-7 feature bands of heavy rain and accompanying strong westerlies over the BOB, SCS, and Philippine Sea (Figs. 2e-g). In contrast, BORN and SCH, to the south and north of the SCS, show a nearly opposite rainfall pattern to the SCS (also shown in Fig. 3). Specifically, phases 1-2 mark the most suppressed conditions of precipitation (< 5 mm d -1 ) and winds (southwesterlies at 850 hpa < 5 m s -1 ) over the SCS. During these same phases, heavy rainfall is located over the eastern Indian Ocean, or immediately west of Sumatra, as well as western BORN (Figs. 2a-b). The BSISO convective envelope begins propagating eastward and northward (to northern BOB) during phase 3 (Fig. 2c), and forms a northwest-southeastward oriented rain band between the BOB and the tropical western Pacific by phase 4 (Fig. 2d). A southwest-northeast oriented rain band accompanied by strong low-level southwesterlies (> 10 m s -1 ) develops along the northern edge of an anticyclonic circulation (the western Pacific subtropical high) between southern China and Japan (phases 3-4). Heavy precipitation accompanied by strong low-level westerly winds (~15 m s -1 ) over the southern SCS and western Pacific propagates further northward during phases 5-7, and produces peak rainfall over the central and northern SCS areas. During phases 5-7, precipitation over BORN and SCH (outside the BSISO rain band) is generally suppressed possibly owing to enhanced subsidence adjacent to the intense rain band. The heavy BSISO rain band (phases 5-7) tends to be interrupted by landmasses, i.e., the INDO and the islands of the PHIL. Figure 3 clearly shows that both maximum rainfall and intraseasonal variability of precipitation are reduced over land 11

13 (INDO and PHIL) compared to over ocean (SCS). Previous studies suggested that the low thermal inertial of the land surface could suppress intraseasonal surface fluxes that help to promote the intraseasonal oscillation (Maloney and Sobel 2004; Sobel et al. 2010). Furthermore, the strong diurnal cycle over land could release the atmospheric instability on the diurnal timescale and compete with the intraseasonal timescale (BSISO) for instability (Neale and Slingo 2003; Sobel et al. 2010). Analysis of the geopotential height at 500 hpa (Fig. 4) shows that precipitationsuppressed conditions (phases 1-3) over the SCS is dominated by the western Pacific subtropical high (Figs. 4a-c), whereas the active BSISO rain band (phases 5-7) over the BOB, SCS, and tropical western Pacific is associated with a train of low-pressure circulations (Figs. 4e-g). The subtropical high has maximum westward extent and is the strongest during phase 3, prior to retreating eastward in phase 4. A low-pressure circulation initiates over the central SCS in phase 5, accompanied by strong low-level westerlies. The strongest westerlies during active phases (5-7) are to the south of the low-pressure systems, along the zone of large pressure gradients. The northward propagation of the active BSISO rainfall maxima (phase 5 to phase 7) over the SCS and the western Pacific region corresponds closely to the northward movement of monsoon lows. Previous studies suggested that land surface heat fluxes into the boundary layer could destabilize the atmosphere ahead of the ascending zone and cause a northward shift of convective activity (Webster, 1983; Srinivasan et al., 1993). Similarly, positive SST anomalies to the north of the BSISO convective center could induce boundary layer convergence and promote northward propagation of the intraseasonal disturbance (Back and Bretherton 2009; Hsu and Li 2012). Of course, many other propagation mechanisms for BSISO have been proposed (summary in DeMott et al. 2012). 12

14 b. Precipitation features and lightning activity Locations of PFs categorized by PF size in each BSISO phase are shown in Fig. 5. In Fig. 6, the quantitative PF population (density) as a function of BSISO phase is shown. In general, phases 1-2 feature the most suppressed convective condition (minimum population of PFs by all metrics) over the SCS (Figs. 5a-b and Fig. 6), while phases 5-6 are characterized by maximum number of MCSs and cold clouds over the SCS (Figs. 5e-f and Figs. 6b-c). Behaviors of the PF population, especially mesoscale convective systems (MCSs) with PF areas > 2000 km 2 (Nesbitt et al. 2000; Liu et al. 2008), are consistent with rainfall patterns (shown in Fig. 2) over both the SCS and surrounding landmasses. During phases 1-3, PF frequency is relatively small and MCSs are infrequent over the SCS, INDO, and the PHIL, marking suppressed conditions in these areas (Figs. 5a-c). However, during these same periods MCSs occur more frequently over BORN and the most southern portions of the SCS. Many of the MCS over the southern SCS west of BORN may originate from convection over Borneo, given the pronounced nocturnal offshore propagation from BORN (Ichikawa and Yasunari 2006). In the wake of active BSISO conditions (phase 5, Fig. 5e), MCSs increase substantially over INDO, the SCS, and PHIL, and exhibit a northward propagating pattern (phases 6-7, Figs. 5f-g). As will be shown in Sec. 4a, MCSs contribute over 80% of the total rainfall during active periods, therefore, the propagation of these MCSs constitutes the main BSISO rain band. During these phases (5-7), BORN and SCH become convectively suppressed, marked by the minimum population of all types of PFs in these regions (Figs. 5e-f and Figs. 6b-c). Populations of deep convection (min IR Tb < -60 o C, Fig. 6c) and intense convection (20- dbz echo-tops exceeding 12 km, Fig. 6d) reveal a different pattern compared to MCSs (Fig. 6b), especially over land. The deepest convection over PHIL and INDO leads the frequent MCS 13

15 period by 1-2 phases, whereas deep convection and MCSs are more in phase over SCS and regions outside the BSISO rain band (BORN and SCH). For example, deep/intense convection frequently develops over PHIL and INDO during phases 2-3 (Figs. 6c-d), whereas MCSs are less frequent during these same periods (Fig. 6b). Following onset of active periods associated with BSISO over the SCS (phase 5), deep convective clouds increase over the SCS (Fig. 6c), but decrease over land including INDO, PHIL, and BORN. However, intense convection (e.g., 20- dbz echo-top > 12 km) over SCS only increases slightly during active periods of the BSISO, possibly because deep convection (producing cold IR Tb) over ocean have only moderate updraft that is not able to lift precipitation size particles (20-dBZ) to high altitudes (12 km). Figure 7 shows the distribution of lightning flash density (unconditional) in each BSISO phase. Lightning activity over land is most robust during suppressed conditions (phases 2-3, figs. 7a-c), corresponding to the presence of intense convection (Figs. 6d). However, during inactive BSISO periods, lightning activity is highly suppressed over the SCS, although there are indeed a significant population of deep convective clouds (Figs. 6c-d). This is due to the fact that lightning production is more related to the mixed-phase physics (e.g., 30-dBZ echo-top height) rather than the cloud-top height (Zipser and Lutz 1994; Petersen et al. 1996, 1999). [Note: the frequency of 30 dbz above the freezing level is very low during the inactive periods over the SCS as will be shown in Sec. 4c] The increase of lightning activity over the SCS during active periods may be partially attributed to larger CAPE (will be shown in Sec. 3c), which may in fact be enhanced by stronger heat and moisture fluxes from the ocean (discussed in Sec. 3c). The increase in MCS organization over SCS during active periods may also promote lightning (Bang and Zipser 2015; Bang and Zipser 2016). As shown previously, deep convective systems over the SCS during inactive BSISO periods are relatively isolated, therefore, buoyant updrafts in the 14

16 convective cores of these systems are more likely to be diluted by ambient air (Bang and Zipser 2016). After the onset of the BSISO (phase 5), flash density increases over the SCS corresponding to an increase in the MCS population. During active BSISO phases, flash density over land (i.e., PHIL and INDO) decreases substantially, consistent with reduced CAPE (will be shown in Sec. 3c) c. Composites of inactive versus active BSISO periods Figure 8 shows composites of rainfall, 850-hPa winds, and lightning density during inactive (phases 1-3) and active periods (phases 5-7). Obviously, inactive periods are characterized by minimum rainfall (Fig. 8a) and infrequent lightning activity (Fig. 8c) over the SCS, while a remarkable west-eastward rain band spanning over INDO, SCS, and PHIL marks the active phases (Fig. 8b). However, BORN and SCH show a rainfall pattern opposite to INDO, SCS, and PHIL, as these locations are outside the BSISO rain band region. Figure 9 shows mean values of several environmental variables during inactive and active BSISO periods as a function of location (marked in Fig. 1). SST (SCS only) and surface air temperature in the BSISO rain band regions (SCS, INDO, and PHIL) are reduced (by o C) during active periods compared to inactive phases, likely owing to cloud shading, precipitation cooling, and stronger upper-ocean mixing owing to enhanced low level winds (Fig. 9a). As a result, the inactive BSISO induces larger CAPE relative to the active phases, particularly for the INDO and PHIL regions (Fig. 9b), likely due to stronger surface heating over land. It is intriguing that SCS shows higher CAPE during active periods even though SST/air temperature is lower compared to inactive periods. A possible mechanism is that higher sea surface fluxes (due to stronger surface winds) and stronger low-level moisture convergence during active BSISO phases (as in active MJO phases, Johnson and Ciesielski 2013) lead to 15

17 larger CAPE during these periods. Petersen et al. (1996) found that CAPE was highly correlated to the mixing ratio (wm) of the lowest 50 hpa (i.e., CAPE = 747.7*wm b) over the tropical western Pacific Ocean, suggesting that CAPE over warm oceans is largely moisture driven. Over SCS, mixing ratio in the lowest 50 hpa is 17.6 g kg -1 during inactive periods and 18.2 g kg -1 during active periods. Using the relationship reported by Petersen et al. (1996), the derived CAPE differences are ~400 J kg -1 between active and inactive periods, consistent to the difference shown in Fig. 9b. Relative humidity in the lower-to-mid troposphere and vertical wind shear over SCS, INDO, and PHIL are all enhanced during active periods (Figs. 9c-d) with influences from rain bands, low-pressure circulations, and strong low-level westerly winds. Convective environments over BORN also vary significantly between inactive and active periods, showing patterns opposite to INDO and PHIL, e.g., higher air temperature and larger CAPE during active BSISO periods. Note that active BSISO periods correspond to dry periods over BORN (and SCH), vice versa. So it is not surprising the CAPE over BORN is high during active periods as there is little convection to remove the CAPE. Deep shear over BORN during active phases becomes exceptionally large (25 m s -1 ), as the South-Asia upper-level anticyclonic circulation is enhanced by active BSISO deep convection leading to strengthened upper-level easterlies/northeasterlies over BORN. In contrast, SCH shows the minimum BSISO-related variability in most of the environmental variables. Compared to other regions, SCH shows lower rainfall maxima and less variability in total precipitation between active and inactive periods (Fig. 3 and Figs. 8a-b), therefore minimal variability in cloud shading, precipitation cooling, and condensational heating across the BSISO cycle

18 BSISO Variations on Convective and Microphysical Structures While Sec. 3 provided a large-scale overview of the variability in synoptic conditions, convective environments, rainfall, precipitation features, and lightning activity over the BSISO cycle, we now discuss the detailed convective and microphysical structures during inactive and active BSISO periods. Specifically, we compare convective organization, radar echo-top heights, IR Tb frequency, vertically integrated ice content, mixed-phase microphysical properties, and lightning flash rates of convective clouds over various regions impacted by the BSISO including SCS, INDO, PHIL, BORN, and SCH. a. Convective organization Convective organization is examined in terms of the size and convective/stratiform proportions of precipitation systems. Figure 10 shows the frequency of precipitation occurrence (PR raining pixels) as a function of precipitation area and areal fraction of stratiform precipitation (FSP) of PFs. Generally, precipitation systems over SCS, PHIL, and INDO are larger and consist of larger FSP during active phases compared to inactive periods, possibly due to greater shear and more moist mid-tropospheric environments during active periods (Fig. 9). Isolated systems contribute 20-30% of precipitation frequency (similar contribution from mostly convective systems with FSP < 20%) over SCS, PHIL, and INDO during inactive periods, which is twice that during active phases. This is consistent with higher CAPE, reduced deep shear, and drier mid-tropospheric conditions over SCS, PHIL, and INDO during inactive phases (Fig. 9). In these same regions, large systems with broad stratiform precipitation (e.g., PF size > 10,000 km 2 and FSP > 50%) are responsible for nearly 40% of the precipitation frequency during active phases, yet comprise only 15-25% of the precipitation frequency during inactive periods. The precipitation contribution from large MCSs during active BSISO phases is similar to what has 17

19 been observed by shipborne radar during active MJO periods over the Indian Ocean (Xu and Rutledge 2014) and the western Pacific warm pool (Rickenbach and Rutledge 1998). BORN and SCH exhibit an opposite trend regarding precipitation area and FSP to the SCS, as the wet and dry periods in these regions correspond to inactive and active BSISO phases over the SCS, respectively b. Convective echo-top heights Figure 11 shows the probability distribution function (PDF) of 20-dBZ echo-top heights (ETH20) of convective cells (within rain areas identified as convective). Generally, ETH20 maximizes near the freezing level (5 km), corresponding to the congestus mode over the tropical oceans (Johnson et al. 1999). The congestus mode is caused by the near 0 o C stable layer, owing to cooling and moistening effects associated with extensive regions of melting within MCSs. SCS exhibits a broad peak (2-5 km) of ETH20 during inactive BSISO periods (Fig. 11a). The lower-level (2-3 km) echo-top maximum represents the shallow cumulus mode, as reported over the Pacific warm pool/western Atlantic (Johnson et al. 1999), Manus Is. (Hollars et al. 2004), and the central Indian Ocean (Powell et al. 2015). It is not surprising that this shallow cumulus mode disappears over land (Figs. 11b-e), given the strong surface heating and greater instability over land. The shallow cumulus mode is better defined over more open oceans during inactive periods, i.e., western tropical Pacific (WPC, Fig. 11f). An examination of stability profiles shows that a low-level stable layer ( hpa) associated with trade inversion apparently exists over both SCS and WPC (Fig. 12). Of course, the mid-level stable layer is also evident over these regions. The mid-level stable layer over the SCS is stronger during active periods (Fig. 12a), due to the substantial increase of MCS population in active BSISO thus enhanced cooling and subsidence within broad stratiform regions. 18

20 During active BSISO periods, the frequency of shallow cumulus over the SCS (e.g., MAXHT20 < 3 km) decreases (Fig. 11a), as the large-scale BSISO disturbance likely disrupts the trade stable layer near 2 km (reduction of stability as shown in Fig. 12a), promoting the growth of cumulus into congestus. The modulation of the shallow cumulus cloud population due to active BSISO is even more evident over WPC (Fig. 11f). During inactive periods, convective echo tops over WPC show a clear bimodal structure with maxima at 2-3 km and 5 km. After the onset of BSISO, shallow cumulus decreases substantially and congestus clouds (with tops at 4-6 km) increase correspondingly. Hence the shallow cumulus mode virtually disappears There is little variability of shallow cumulus and congestus echo tops over land between inactive and active periods (Figs. 11b-e). Over land, especially PHIL and INDO, the frequency of deep convection (e.g., ETH20 > 8 km) is higher during inactive periods compared to active periods. Nevertheless, ETH20 does not show a deep convective mode (cloud tops > 12 km, Johnson et al. 1999), possibly because ETH20 does not represent actual cloud tops (which may be closer to 0 dbz as in Johnson et al. 1999). Xu and Rutledge (2016) compared convective top heights from 20 dbz, 0 dbz, and IR Tb using shipborne radar data and satellite imagery collected during DYNAMO. They found that the discrepancies between these heights increase as a function of altitude, e.g., these proxies are near in height for shallow to medium convection (< 5-6 km), but 20 dbz echo-top height could be 4-5 km lower than 0 dbz echo-top height or IRbased cloud-top height when the cloud top reaching above 10 km. In fact, the deep convective mode could be seen in cold IR Tb (< -60 o C or 213 K) as shown in IR Tb distribution (Fig. 13). The frequency of IR-inferred deep convection is 30-40% over ocean and 20-30% over land

21 451 c. Precipitation microphysics and lightning flash rates Precipitation microphysics is investigated in terms of microwave-based vertically integrated ice content and radar structures in the mixed-phase region. Figure 14 shows the PDF of microwave PCT85, a close proxy for vertically integrated ice content. In general, oceanic convection exhibits substantially lower frequencies of cold PCT85 (e.g., < 200 K, a threshold for significant ice content suggested by Mohr and Zipser 1996) compared to land-based convection, presumably due to reduced updraft speeds in oceanic convection. Recall that SCS convection produces the coldest IR-inferred cloud tops of all regions (Fig. 13). These opposite PCT85 and IR Tb patterns suggest that convective clouds over SCS may indeed have a deep ice column but columnar ice contents are low. Oceanic convection also shows smaller variability on PCT85 between inactive and active periods. Over SCS, active periods correspond to a slight increase in the frequency of moderate PCT85 ( K) compared to inactive periods (Fig. 14a). In contrast, land-based convection can induce large PCT85 depressions (e.g., PCT85 < 175 K) due to strong ice scattering (Mohr and Zipser 1996), suggesting a very deep column of significant ice water contents, or the presence of large ice particles in a portion of the column. PHIL and INDO exhibit the greatest BSISO-related variability on PCT85 (Figs. 14b-c), i.e., inactive periods have substantially higher frequency (~20%) of convection with large PCT85 depression (< 200 K) compared to active periods (~5%). Over BORN, convection during active BSISO periods induces slightly higher frequencies of moderate-to-cold PCT85 (Fig. 14c). Distributions of PCT85 are very similar between inactive and active periods over SCH (Fig. 14d). Fig. 15 depicts the frequency of 30-dBZ radar echoes at sub-freezing temperatures within convective precipitation areas, an accepted proxy for the existence of precipitation-sized ice particles and/or mixed-phase precipitation production (Zipser and Lutz 1994; Petersen et al. 20

22 ). Over the SCS (Fig. 15a), active-bsiso convection exhibits a higher frequency of 30 dbz echoes at temperatures between 0 and -10 o C compared to convection during inactive periods. However, SCS convection exhibits only marginal values and little BSISO variation regarding the frequency of 30 dbz at temperatures colder than -10 o C, a pseudo-threshold for lightning production (Petersen et al. 1996). These mixed-phase 30-dBZ patterns are consistent to patterns of PCT85 (Fig. 14a). Together they suggest that active BSISO convection over the SCS may have slightly stronger updrafts relative to inactive BSISO convection (consistent with higher CAPE in active periods, Fig. 9b), but the active-bsiso updrafts are evidently not strong enough to loft precipitation-sized ice particles to temperatures colder than -10 o C. In contrast, PHIL and INDO show the largest BSISO variations in mixed-phase 30-dBZ frequency with inactive periods twice that of the active phases (Figs. 15b-c). This finding is consistent with observed stronger surface heating, higher CAPE, and drier mid-tropospheric conditions denoting inactive periods (Figs. 9a-c). Another intriguing point is that during the same BSISO active periods, distributions of 30-dBZ frequency above the freezing level are almost identical across INDO, SCS, and PHIL, suggesting very little land-sea contrast in mixed-phase microphysics (convective intensity) along the active BSISO rain band (further discussions will be provided in Sec. 5). For regions outside the BSISO rain band, BORN (Fig. 15d) exhibits a higher mixed-phase 30-dBZ frequency during active BSISO periods (locally drier condition) compared to inactive periods (locally wetter condition), consistent with the higher CAPE over BORN during active phases (Fig. 9b). Again, SCH shows almost no change in mixed-phase 30-dBZ frequency throughout the BSISO cycle (Fig. 15e), possibly due to marginal BSISO variability in thermodynamic conditions over this region (Fig. 9). 21

23 Distributions of PFs with lightning (as a function of flash rate; Fig. 16) mimic the mixed-phase 30-dBZ patterns discussed above. Flash rates over the SCS are overall lower in comparison to surrounding landmasses (e.g., PHIL and INDO, by roughly a factor of two), which is expected due to the substantially lower 30-dBZ frequencies at altitudes colder than -10 o C (a well-accepted threshold for lightning production, Petersen et al. 1996) over ocean. Over SCS, convection during active BSISO periods produces slightly higher flash rates relative to inactive periods (Fig. 16a), consistent with slightly stronger convective intensities during the active periods (indicated by PCT85 and mixed-phase 30-dBZ frequency). Flash rates during inactive periods over PHIL and INDO are a factor of two larger than during active periods (Figs. 16b-c), reflecting the previously demonstrated stronger convection over land areas during inactive periods. Flash rates over BORN shows an opposite trend to PHIL and INDO (Fig. 16d). It is not surprising that inactive and active BSISO periods in SCH have the same flash rate patterns (Fig. 16e), given their similar 30-dBZ frequencies in the mixed-phase region (Fig. 15) Summary and Conclusions The BSISO is the most dominant intraseasonal mode in the SCS and surrounding landmasses during the summer monsoon. Rainfall patterns, large-scale circulations, precipitation extreme, monsoon onset, and monsoon active/break periods have previously been shown to vary substantially over the BSISO cycle. However, the full spectrum of the convective cloud population and microphysical structures associated with the BSISO cycles in these regions were relatively unknown prior to the current study. Using 16 years of TRMM satellite convective measurements and reanalysis data, this study investigated the BSISO-associated intraseasonal and regional variations in convective environments, convective cloud populations, precipitation 22

24 microphysics, and lightning activity over the SCS and surrounding landmasses. For this purpose, large-scale satellite rainfall, environmental variables, TRMM PFs, and TRMM lightning data were stratified by BSISO indices (focusing on the day mode). Figure 17 summarizes the convective structures and microphysical properties in regions across the BSISO rain band during inactive and active BSISO periods. Generally, land-sea contrasts of convective structures and microphysical properties are substantial during inactive periods. Land-sea contrasts in these parameters are only marginal during active periods (right panels in Fig. 17). For example, during inactive periods land convection induces higher echo-tops, stronger microwave ice scattering and higher 30-dBZ heights in the mixed phase zone compared to convection over the SCS. However, during active periods, all these convective/microphysical metrics are almost identical across INDO, SCS, and PHIL, suggesting very little land-sea contrast in the convective intensity and mixed-phase microphysics. One explanation for this is related to impact of the BSISO on the diurnal cycle of convection over land (left panels in Fig. 17). During inactive periods, convection over land shows a remarkable diurnal cycle with copious amounts of intense convection. In contrast, the diurnal cycle amplitude over land is reduced significantly during active BSISO conditions (perhaps owing to cloud shading, weaker surface heating, and reduced instability). As a result, intense convection is infrequent during these periods. In conclusion, major findings from this study are summarized as follows: 1) Active periods of the BSISO (30-60 day mode) are characterized by a NW-SE tilted rain band between the BOB and the tropical western Pacific, but this rain band is somewhat disrupted over land (rainfall over land show less variability). 2) During the active BSISO phases (phases 5-7), precipitation systems over the rain band regions (SCS, PHIL, and INDO regions) are larger in size and contain larger fractions of 23

25 stratiform precipitation. We suggest that this behavior is due to greater shear and more moist mid-tropospheric environments in active periods. 3) The deepest convection over PHIL and INDO leads the frequent MCS period by 1-2 phases, whereas deep convection and MCSs are more in phase over SCS and regions outside the BSISO rain band (BORN and SCH). 4) Convection over the SCS during inactive periods exists in a trimodal population including shallow cumulus, congestus and deep convection, whereas land convection only shows the congestus and deep convection modes. Shallow cumulus clouds over the SCS decrease substantially under active BSISO conditions. The shallow cumulus and congestus modes over SCS are consistent to stable layers at 2-3 km and 0 o C. 5) Although active BSISO periods over the SCS has higher CAPE compared to inactive periods, convection in active periods is only slightly more intense as revealed by PCT85, 30-dBZ frequency at sub-freezing temperatures, and lightning flash rates. 6) Convection over PHIL and INDO induces substantially higher 30-dBZ heights, stronger PCT85 depressions, and larger flash rates during inactive periods than active periods. We suggest that enhanced surface heating and drier mid-troposphere conditions lead to stronger convection during inactive phases. 7) Total rainfall, convective environments, and convective structures over BORN are out of phase with convection over the BSISO rain band regions. Specifically, BORN convection is stronger and exhibits more robust mixed-phase microphysics during active BSISO periods than inactive periods. 24

26 ) SCH shows little BSISO variability in system size, convective intensity, and mixedphase microphysics, even though rainfall amounts and atmospheric circulations over SCH are significantly different between active and inactive BSISO periods. Acknowledgements This research was supported by the ONR PISTON program (grant #N ) and the NASA PMM program (grant #NNX16AD85G). We thank the three anonymous reviewers for their constructive comments and suggestions. We thank Professors Edward Zipser (University of Utah) and Chuntao Liu (TAMU-CC) for providing the TRMM precipitation feature dataset as well as science discussions. Thanks also go to Prof. June-Yi Lee for providing the BSISO index data. We also thank colleagues for insightful discussions of this work, especially Dr. Timothy Lang from NASA MSFC and Prof. Eric Maloney from CSU. The TRMM precipitation features and orbital lightning data can be downloaded from NASA Goddard Earth Sciences Data and Information Services Center ( and BSISO index data from

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37 Table 1. Data samples used in this study over [5S-30N; E] from June to September during : number of BSISO periods (days), TRMM overpasses (orbits), and TRMM precipitation features (PFs) as a function of BSISO phases (phases 1 to 8). Samples are exclusive to days with BSISO index amplitude > P 1 P 2 P 3 P 4 P 5 P 6 P 7 P 8 Days Orbits PFs

38 Figures Fig. 1. Geography map of elevation (color shaded) overlaid with low-level winds at 925 hpa (arrows) from June to September in the South China Sea and Indo-Pacific regions. Study regions are marked by boxes, including South China Sea (SCS), Philippines (PHIL), Indochina (INDO), Borneo (BORN), Southern China (SCH), and Western Pacific (WPC)

39 Fig. 2. Mean rainfall (mm d -1 ) from TRMM 3B42 (color shaded) overlaid with winds at 850 hpa (arrows) derived from reanalyses as a function of BSISO phase during June-September

40 Fig. 3. Mean rainfall (mm d -1 ) time series for five study regions derived from TRMM 3B42 as a function of BSISO phase

41 Fig. 4. Geopotential heights at 500 hpa (contours) and winds at 850 hpa (arrows) as a function of BSISO phase. Colorbar represents geopotential height

42 Fig. 5. Distribution of Precipitation Features (PFs) categorized by PF area (color) as a function of BSISO (30-60 days oscillation) phase during June-September, Small PFs with area < 100 km 2 are not displayed

43 Fig. 6. PF population as a function of BSISO phase: (a) all PFs, (b) PFs with area > 2000 km 2, (c) PFs with minimum IR Tb < -60 o C, and (d) PFs with 20dBZ echo-top height > 12 km. PF numbers are normalized by area of study region and number of days in each BSISO phase

44 Fig. 7. Distribution of lightning flash density (fl km -2 yr -1 ) derived from orbital TRMM LIS data as a function of BSISO phase. Flash density is unconditional, including both raining and not raining times sampled by LIS

45 Fig. 8. Mean rainfall overlaid with 850 hpa winds and lightning flash density during inactive (phases 1-3) and active (phases 5-7) BSISO periods: (a) rainfall during inactive, (b) rainfall during active, (c) lightning during inactive, and (d) lightning during active. White boxes in panels (a) and (b) mark the selected study regions

46 Fig. 9. Environmental variables during inactive (blue) and active (red) BSISO periods: (a) SST and 2-m air temperature, (b) convective available potential energy (CAPE), (c) relative humidity (RH) at lower-levels ( hpa) and mid-to-upper levels ( hpa), and (d) vertical wind shear between 700 and 150 hpa. Error bars represent 0.5 standard deviation

47 Fig. 10. Joint PDF of TRMM PR raining pixels as a function of PF area and PF stratiform rain fraction during (a)-(e), inactive BSISO, and (f)-(j), active BSISO periods. Number within each box represents the percentage of occurrence in the specific value ranges of PF area and stratiform rain fraction

48 Fig. 11. PDF of 20-dBZ echo-top height over convective area of precipitation systems observed by TRMM PR during inactive (blue bars) and active (red bars) BSISO periods. Frequency is relative to convective rain pixels near the surface

49 Fig. 12. Cumulative frequency (%) of stability (dt/dz) greater than -5 o C km -1 over ocean for (a) SCS and (b) WPC. The frequency is calculated in every 50 hpa bin

50 Fig. 13. Frequency of infrared brightness temperature during inactive (blue bars) BSISO and active (red bars) BSISO periods observed by TRMM VIRS during

51 Fig. 14. Frequency of TRMM TMI microwave polarization-corrected brightness temperature at 85 GHz during inactive (blue bars) BSISO and active (red bars) BSISO periods. Frequency is relative to TMI raining pixels near the surface

52 Fig. 15. Occurrence frequency of PR 30-dBZ radar reflectivity above the freezing altitude during inactive (blue bars) BSISO and active (red bars) BSISO periods. Frequency is relative to PR convective rain pixels at 2 km

53 Fig. 16. Accumulated frequency of precipitation features as a function of PF s lightning flash rates during inactive (blue bars) BSISO and active (red bars) BSISO periods. All PFs are included for the frequency calculation

54 Fig. 17. Conceptual model (left panels) of convective structures and microphysical properties across the BSISO rainband region (INDO, SCS, and PHIL) during suppressed conditions and active BSISO periods, and corresponding diurnal variations (right panels) on 30-dBZ occurrence frequency above 6 km in convective precipitation areas