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Kinematic and Precipitation Characteristics of Convective Systems Observed by Airborne Doppler Radar during the Life Cycle of a Madden-Julian Oscillation in the Indian Ocean [Monthly Weather Review](Monthly Weather Review Via Acquire Media NewsEdge) ABSTRACT This study presents characteristics of convective systems observed during the Dynamics of the Madden-Julian oscillation (DYNAMO) experiment by the instrumented NOAA WP-3D aircraft. Nine separate missions, with a focus on observing mesoscale convective systems (MCSs), were executed to obtain data in the active and inactive phase of a Madden-Julian oscillation (MJO) in the Indian Ocean. Doppler radar and in situ thermodynamic data are used to contrast the convective system characteristics during the evolution of the MJO. Isolated convection was prominent during the inactive phases of the MJO, with deepening convection during the onset of the MJO. During the MJO peak, convection and stratiform precipitation became more widespread. A larger population of deep convective elements led to a larger area of stratiform precipitation. As the MJO decayed, convective system top heights increased, though the number of convective systems decreased, eventually transitioning back to isolated convection. A distinct shift of echo top heights and contoured frequency-by-altitude diagram distributions of radar reflectivity and vertical wind speed indicated that some mesoscale characteristics were coupled to the MJO phase. Convective characteristics in the climatological initiation region (Indian Ocean) were also apparent. Comparison to results from the Tropical Ocean and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) in the western Pacific indicated that DYNAMO MCSs were linearly organized more parallel to the low-level shear and without strong cold pools than in TOGA COARE. Three-dimensional MCS airflow also showed a different dynamical structure, with a lack of the descending rear inflow present in shear perpendicularly organized TOGA COARE MCSs. Weaker, but deeper updrafts were observed in DYNAMO. 1. Introduction A dominant component of intraseasonal tropical vari- ability is the Madden-Julian oscillation (MJO; Madden and Julian 1971, 1972), characterized by an eastward- moving envelope of organized, deep convection (and precipitation) and westerly winds. The MJO has been shown to influence monsoon systems (e.g., Asia, Africa, and Australia), tropical cyclones in all cyclone basins, midlatitude weather (e.g., rainfall and temperature variability), and other atmospheric and ocean phenom- ena (e.g., El Nin~o-Southern Oscillation, North Atlantic Oscillation, Indian Ocean dipole); discussed further in Lau and Waliser (2005) and Zhang (2005). Given the extensive impact of the MJO on global circulations, it is important to correctly simulate the MJO in forecast and climate models. However, current model simulations do not represent the MJO well (Lin et al. 2006; Benedict and Randall 2009). This is due in part to an incomplete understanding of convective dynamics and characteris- tics during the initiation of the MJO. A large body of literature exists describing MJO characteristics, especially large-scale dynamics (Lau and Waliser 2005; Zhang 2005). Briefly, a composite view of MJO phases indicates that inactive (i.e., suppressed or dry) phases are characterized by easterly winds and synoptic subsidence; and as an MJO event develops, moistening of the lower atmosphere in conjunction with surface westerlies occurs. The troposphere remains anomalously moist throughout with cool low-level anom- alies during peak convective (MJO) activity (wet) phases. Drying occurs during the decay of the MJO, along with the reestablishment of surface easterlies. Deep convec- tion, climatologically initiating over the equatorial Indian Ocean region, often organizes into clusters of mesoscale convective systems (MCSs). The deep convective enve- lope propagates across the Maritime Continent and into the western Pacific warm pool. The Tropical Ocean and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE; Webster and Lukas 1992) was conducted in the western Pacific and observed three MJO passages. Details regarding the MJO (e.g., Lin and Johnson 1996) and mesoscale (e.g., Rickenbach and Rutledge 1998) structure were reported, resulting in a better under- standing of the MJO in this region. However, using satellite and sounding data, Kiladis et al. (2005) sug- gested that MJO structure varied with longitude. De- spite this, the Indian Ocean Basin has remained largely unobserved by weather radar and in situ instrumentation as in TOGA COARE. To address the limited observational data of the life cycle of an MJO in the climatological initiation region, the Dynamics of the MJO (DYNAMO; Yoneyama et al. 2013) field experiment was undertaken from October 2011 to March 2012 (Fig. 1). A large amount of data not typically available was obtained using in situ and remote sensing techniques. Convection in this region has largely been studied via satellite observations, as well as a brief ship-based scanning weather radar project (Yoneyama et al. 2008), a precursor to the DYNAMO project. While these above studies have provided much needed in- formation regarding the composite view of convection during various MJO phases, a greater understanding of the evolution of mesoscale characteristics during active and inactive MJO phases is required to properly repre- sent smaller-scale variability statistically or explicitly in numerical weather models. Each corner of the quadrilateral in Fig. 1 indicates the location of a stationary ground- or ship-based weather radar, allowing for precipitation and cloud population statistics within about 100 km of each radar site. While this design resulted in extensive data at four unique points, the center of the quadrilateral lacked detailed radar observations. In addition, only the northwest corner (Gan Island) was able to accommodate two Doppler ra- dars in close enough proximity to attain robust kinematic properties of precipitation systems. To alleviate this gap, the suite of instruments on board the WP-3D aircraft (hereafter P-3) operated by the National Oceanic and Atmospheric Administration (NOAA) were deployed during a portion of the intensive observing period (IOP; 1 October 2011-15 January 2012) of the DYNAMO project (Yoneyama et al. 2013), with the primary ob- jectives to provide information regarding tropical convection and air-sea interactions. Measurements of environmental state variables (e.g., temperature and relative humidity) and 3D storm structure (via Doppler weather radar) were used in this study. The mobile as- pect of this platform allowed sampling of convective systems during daylight hours between the fixed-point observations recorded on island- and ship-based plat- forms depicted in Fig. 1. Tropical MCSs have been studied extensively (e.g., Zipser 1977; Liu 2011), using both surface-based (e.g., Houze 1977; Rickenbach and Rutledge 1998) and air- craft radar observations (e.g., Jorgensen et al. 1997; Kingsmill and Houze 1999). This study uses a common MCS definition of contiguous precipitating convective clouds with a minimum length scale of at least 100 km. There is a great deal of literature describing the mor- phology and characteristics of MCSs, which account for a large amount of precipitation in the tropics and in- teract with the larger environment. Various modes of structural organization exist (e.g., Houze et al. 1990)- from highly organized systems that exhibit linearly aligned convective cell elements, often with an associ- ated stratiform shield, to more amorphous MCSs that have clustered convective elements embedded within the larger stratiform cloud area. The distinct combination of organization and convective-stratiform precipitation cloud proportions provide a means for vertical mo- mentum transport and heating. The three-dimensional (3D) kinematic and precipitation structure and convective environment of MCSs sampled during the DYNAMO experiment is described here. Expanding our under- standing of convective dynamic and thermodynamic structure in this region is important to improve modeled MJO characteristics and forecast. Section 2 provides details about the data and meth- odology used in this study. An overview of the synoptic environment is given in section 3 to provide context for flight modules. Section 4 discusses characteristics of the sampled convective systems and compares these char- acteristics to previous work. A summary and discussion of results is provided in section 5. 2. Data and methodology a. Airborne Doppler radar The P-3 (N43) was deployed from a base at Diego Garcia Island (DGO in Fig. 1), embarking on 12 flights from 11 November to 13 December 2011 (Table 1). The primary mission of the P-3 was to collect data on tropical convection and air-sea interactions and provide obser- vations in the unsampled region between island and ship fixed locations. All missions were during daylight hours because low-level traverses (;50 m AGL) could not be conducted at night. The primary observational data were obtained by the tail-mounted, vertically scanning X-band Doppler radar (Jorgensen et al. 1983), which provided a 3D representation of storm clouds within ;40 km of the aircraft. In addition, the P-3 is also equipped with a horizontally scanning C-band lower fuselage (LF) radar, which mapped radar reflectivity out to approximately 400 km range from the aircraft. The LF radar was used during flights to identify convective systems (i.e., targets) of interest and in this study as a tool to visualize the broader convective activity. The LF radar provided only two-dimensional (2D) data, and does not lend to rigorous analysis because of coarse resolution and susceptibility to sea clutter. Characteris- tics for both radar systems are listed in Table 2. The tail Doppler radar has a dual-plate antenna pro- viding alternating scans forward and aft [fore/aft scan- ning technique (FAST)] at a 208 angle from perpendicular to the aircraft longitudinal axis (Jorgensen et al. 1996). During a relatively straight flight path, the FAST tech- nique results in the tail radar sweeping consecutive full 3D volumes. With the P-3 nominal ground speed of 120 m s21, coincident measurements result from the al- ternating scans approximately every 1.4 km, with a ;408 angle between beams (Fig. 2). The system employs a staggered pulse repetition frequency (PRF) approach to extend the unambiguous radial (Nyquist) velocity to ;51 m s21, eliminating velocity ''folding'' issues in this study. The dual-PRF operates in batch-mode (sending out pulse stream pairs), using 3200 and 2400 Hz. The data were quality controlled (QC) using a com- bination of automated and manual techniques within the interactive SOLO data editor (Oye et al. 1995) de- veloped by the National Center for Atmospheric Re- search. The QC algorithms used in this study made use of the zero (reflectivity; dBZ), first (Doppler velocity), and second [spectral width (SW)] moments of the re- turned signal. Information provided by the aircraft inertial navigation and global positioning systems (i.e., ground-relative speed, altitude, and pitch, roll, and drift angles) allowed for pointing angle corrections, as well as the removal of aircraft motion from the radial velocity measurements. Tail radar scan geometry resulted in beam intersection with aircraft motion (Fig. 2). For this dataset, topography was not an issue and the SOLO editor allows the automated removal of the surface echo (due to the vertically scanning geometry) via geo- metrical calculations based on the antenna beamwidth. Threshold values for the aforementioned variables were tuned for the automated algorithm to remove noise and nonmeteorological echo, while retaining the maximum amount of meteorological information. These scripts removed the majority of artifacts in the data including: ''freckling'' (individual gates that deviate significantly from the surrounding mean), ''speckling'' (isolated gates with no surrounding information), and second-trip echo (return from targets, generally sea clutter in this case, beyond the unambiguous range that manifest as elongated spikes along a small number of radials). The remaining nonmeteorological return was conse- quently eliminated through manual editing. Greater than 10 000 individual radar volumes underwent these procedures. Once QC and a wind synthesis (described in the following section) were performed, the data were interpolated from native radar coordinates to a Cartesian grid with horizontal and vertical spacing of 1.5 and 0.5 km, respectively. Maximum reflectivity of gates was retained horizontally and interpolated vertically. b. Wind synthesis A pseudo-dual-Doppler approach (Jorgensen et al. 1996) was employed on the edited data to construct 3D wind fields. Terminal fall speeds of precipitation were removed from radial velocity estimates using empirical equations relating radar reflectivity and terminal fall speed. Different relationships were used for rain below 4 km (Joss and Waldvogel 1970) and snow above 4.5 km (Atlas et al. 1973). Between 4 and 4.5 km, a weighted average of the rain and snow relationships was com- puted. These heights agree well with climatological tropical freezing level heights, and with dropsonde measurements performed throughout the P-3 observa- tions (section 2c). Though no attenuation correction algorithm was employed, an attempt was made to com- pensate for some X-band attenuation in heavy precip- itation by choosing the maximum reflectivity associated with each grid point in cases where more than one beam intersected a collocated point. A comparison was made to a limited number of coincident observations acquired by the S-band National Center for Atmospheric Re- search SpolKa radar (not shown). Maximum recorded reflectivity values were nearly identical near the surface and vertical profiles of minimum, mean, and maximum reflectivity were within ;3-4 dB throughout the column. Therefore, it was decided that there was minimal, if any, evidence of attenuation in the P-3 data. Horizontal winds (u, y) were computed from radial velocities using an overdetermined, two-equation solu- tion. The two-equation system is a function of the zonal (u), meridional (y), and vertical (w) wind components. A two-pass Leise filter (Leise 1981) was applied to hori- zontal winds to reduce noise resulting from features 3-4 times the horizontal grid spacing (6-7.5 km). Once so- lutions for u and y were found, vertical velocity was estimated through upward integration of the continuity equation, with a boundary condition of w 5 0 assumed at the surface. Vertical column mass balance was achieved by applying the O'Brien (1970) correction to the di- vergence profile through setting w 5 0 at echo top. It was found that two iterations were sufficient for solution convergence (less than 10% deviation between estimates). Given the maximum unambiguous range of the radar was ;40 km, the maximum time between fore and aft scan coincident measurements was less than 4 min. It was assumed that the observed systems were stationary during this time for Doppler analysis. This is a common assumption in nearly all dual-Doppler analyses, though it should be noted as a possible limitation when in- terpreting results. Organized convective systems are largely unaffected, as storm-scale features evolve slowly on a 5-min time scale. However, individual convective cells (,1-min time scale) within an organized system may suffer from such an assumption. Though the large- scale signal indicated propagation of the convective envelope, analysis of LF radar image time series revealed no coherent propagation vector of individual systems; therefore, no system advection component was applied to the MCSs in this study. The limited temporal reso- lution of the LF [2 revolutions per minute (rpm)] may also result in slight cell motions going unnoticed. Do- main sizes of the gridded analyses depended upon the size of the convective systems, ranging from 75-150 km along each horizontal axis. c. Flight modules The scientific goals of the P-3 aircraft (the study of tropical convection and air-sea interactions) necessi- tated the design of numerous sampling strategies (e.g., convective storms, boundary layer, and mesoscale fluxes, etc.). As this study is focused solely on tropical convection system analysis, only data obtained using the radar convective element (RCE) modules (Fig. 3) are presented. Distances shown in Fig. 3 are approximations and varied depending upon the actual size of the con- vective system observed. The strongest convective sys- tems were identified using real-time LF radar imagery and targeted for sampling. Identification of the direction of propagation was attempted, though often difficult during the DYNAMO project as the convective lines sampled were exclusively organized parallel to the low- level shear vector and exhibited little motion. Once the ''front'' of the system was defined, the P-3 flew parallel to the convective feature at ;915 m (3000 ft). A turn was executed to transit to the rear of the system, and the aircraft ascended to ;3 km (10 000 ft). Next the P-3 would transect the convective ''line,'' releasing drop- sondes every 2-3 min. This provided detailed data of the convective systems along with observations of the thermodynamic structure of the convective environ- ment, particularly the cold pool. During the 12 DYNAMO flights, a total of 9 RCE modules were executed. The RCE modules were per- formed at approximately the same time of day because of flight requirements of having to see the surface for flight segments below ;150 km. This was beneficial for comparison and statistical analysis of systems occurring on different days and within varying phases of the MJO. However, this sampling strategy inhibited any analysis of diurnal cycle. Because the convective systems were targets of opportunity, geographic location varied ex- tensively. Table 1 summarizes the RCE modules (in boldface) during DYNAMO. 3. Large regional-scale overview and RCE modules In this study, the large regional-scale is defined ap- proximately as the observational domain (Fig. 1) 6108 of longitude or latitude and aligns well with latitudinal boundaries used to study the MJO in literature. Gottschalck et al. (2013, hereafter G13) provide an overview of global atmospheric patterns during the DYNAMO project, as well as large regional-scale atmospheric and oceanic patterns for this region. The time period pre- sented in this paper occurs in their DP1 time period (17 September-8 December 2011). In terms of monthly means, G13 noted very little departure from a 30-yr climatology was observed for winds and moisture during November-December 2011 for the DYNAMO region. The Wheeler and Hendon (2004) MJO index, as well as an MJO-filtered OLR anomaly index computed for the DYNAMO region, indicated a robust MJO in November, peaking on 26 November in the study region. At the beginning of the P-3 operational period, widespread convection was suppressed in the observational domain and was defined by scattered, localized convection. The troposphere exhibited easterly winds and was relatively dry when compared to a 30-yr base period (G13). Near 17 November, gradual moistening began in the lower troposphere and a westerly wind anomaly developed as a coherent deep convective signal began to appear as part of the MJO event. A deep column of moisture (up to 400 hPa) was present at the peak of the MJO. Con- vection associated with the MJO began to diminish in terms of coverage and precipitation amount within 2-3 days following the MJO peak. Tropospheric moisture decreased as an inactive phase was reestablished, be- coming relatively dry for the remainder of the P-3 op- erational time period. Kelvin wave (KW) activity was strong during this study, including an occurrence in the DYNAMO domain concomitant with the MJO (G13). Though westward-moving equatorial Rossby wave (ER) activity was generally weak, it should be noted that an ER was present during the peak MJO period as well. A time-longitude diagram of Tropical Rainfall Mea- suring Mission gridded 3B42 precipitation data (Huffman et al. 2001) showed the existence of propagating pre- cipitation signals that stand out from the relatively ubiquitous background signal (Fig. 4). The precipitation signal associated with the previously discussed MJO was apparent in the observed domain (longitudinal limits denoted by vertical black lines) centered on 24 November. Time and longitude locations of RCEs are identified (red squares) to provide spatial and temporal context for each module. Precipitation data along the latitudinal direction were averaged at each longitudinal point in Fig. 4 from 108Sto58N; latitudinal locations of RCE flights can be found in Table 1. While the P-3 attempted to intercept the strongest MCSs, it should be noted that missions were planned using forecasted precipitation and refined based upon infrared satellite imagery preceding takeoff. Once the flight mission was in progress, individual MCS targets (i.e., convective lines) were decided upon by the aircraft mission scientists using the LF radar to detect the most vigorous convective systems in the area. Postproject analysis of infrared satellite imagery (not presented here) suggested that the MCSs chosen for the RCE modules were among the strongest and the sample of convective systems presented in this study is represen- tative of the vigorous convective systems in the ob- served domain. Nevertheless, the rapidity with which DYNAMO MCSs evolved often meant the systems were in their dissipative stages by the time the RCE module was completed. Thus, the sample of MCSs in this study should be considered in the mature to dissi- pating stages. Figure 5 shows a planar overview of the nine RCE modules. The horizontal depiction of composite radar reflectivity is overlaid by the P-3 flight path, with the starting point of the RCE indicated by a filled circle. Common tick mark spacing was used to differentiate the size of each system sampled. Spatial coverage increased through 24 November, and then began to decrease for MCSs for the remainder of the P-3 mission. No quanti- tative size was calculated because of the mobile nature of the platform. 4. Results a. Overall MCS structure The precipitating systems sampled could generally be described as having little to no distinguishable system motion vector, weak linear organization, and moderate to high reflectivity values in the range 45-58 dBZ (in- dicative of either large precipitation size particles, a large number of precipitation-sized particles, or a com- bination of both). Soundings (Fig. 6) near the time of RCE modules on 24 November and 8 December (which offer distinct MJO phase differences, discussed in sec- tion 4b) were chosen to exemplify typical environmental characteristics during this study. Differences in thermal structure existed between the two soundings; however, vertical wind structure (important for organization) in- dicated that weak magnitude wind vectors were largely unidirectional below the 800-hPa level, with a distinct shift between 500 and 700 hPa for both soundings. Inlaid hodographs (Fig. 6) indicated that the orientation of the convective features of the MCSs was shear parallel to low-level wind shear (950-750 hPa). Weak shear values over this layer for 24 November (1 m s21) and 8 December (2 m s21) were consistent with the Alexander-Young criterion (,5ms21) for shear-parallel systems (Alexander and Young 1992). Similar characteristics have been observed for slow-moving, loosely organized convec- tion in oceanic environments (Barnes and Sieckman 1984; Lemone et al. 1998). Rickenbach and Rutledge (1998) divided convection in the western Pacific into linear and nonlinear MCS and sub-MCSs using ship-based radar observations, and noted that linear MCSs dominated precipitation char- acteristics during the 4-month observational period. Dur- ing observations in this study, convective cells at times appeared clustered in a linear orientation; however, the characteristic line motion associated with those linear MCSs (system motion perpendicular to the orientation of the convective line) was not present. Very little cell or system motion was observed. In the life cycle of MCSs, many convective cells may exist. As these convective cells grow older and decay, they transition to stratiform morphology and increase the coverage area of the pre- cipitating system. Horizontal areal coverage varied be- tween RCE modules, with a clear tendency of increased size to the peak phase of the late November MJO event and declining coverage afterward (Fig. 5). Vertical characteristics from each RCE module are shown in Fig. 7. Echo top height (ETH), defined as the maximum height of the 0-dBZ echo, was found for each gridded column. Obvious differences existed in number (Fig. 7a) and percentage (Fig. 7b) occurrence frequency and will be discussed in more detail in the following sections. Contoured frequency-by-altitude (CFAD) di- agrams (Yuter and Houze 1995) of radar reflectivity (Fig. 7c) and vertical velocity (Fig. 7d) were constructed to explore the microphysical and dynamic structure of convective systems sampled during the RCE modules. At least 10% of possible points were required at each vertical level when constructing the CFADs, which lead to the flat tops of the distributions. This was not viewed as detrimental to the analysis, however, and acted to decrease skew toward a handful of intense convective cells. No attempt was made to separate the statistics into convective and stratiform portions. While airborne ra- dar data provides fine system detail, the application of a traditional convective-stratiform partitioning algo- rithm is not ideal because horizontal reflectivity fields (of the associated RCE modules) are a composite with large temporal steps. Additionally, the stratiform and convective archetypes were not always clear in this da- taset and are currently under investigation. A greater diagonalization of reflectivity CFADs (de- creasing reflectivity with increasing height) is often as- sociated with a population of mature convective cells (Zeng et al. 2001). The similarity throughout the RCE modules was another indication that the sampled sys- tems were comparable in life cycle as well. In general, Fig. 7 indicated that the MJO event (22, 24, and 30 November panels) included more robust convective storms in comparison to non-MJO periods, as indicated by higher echo tops and reflectivity distributions aloft, median vertical reflectivity profiles offset to higher values, and deeper updrafts. These results will be expanded upon in the following sections through the comparison of subsets of RCE modules. b. MJO active and inactive observations Two representative cases were chosen to analyze differences between convective systems occurring dur- ing active (24 November) and inactive (8 December) MJO phases. Figure 7 showed that similar distributions of echo intensity were obtained for both RCE modules on their respective days. Kinematic (Fig. 7d) and ther- modynamic patterns (not shown) were comparable within each active/inactive period, therefore, the second RCE module on 24 November was chosen because of similar data collection time to the inactive cases. The first RCE module on 8 December was selected as it exhibited convective characteristics closer to the active case. Environmental soundings were very close to those shown in Fig. 6. The logic behind this was that differ- ences would correspond to the most conservative esti- mates of active and inactive phase differences. When data for both RCEs on each day were combined, there were no changes in the interpretation of results. Not only did the areal coverage increase during the MJO event (Fig. 5f), but each metric in Fig. 7 indicated that convective systems reached greater heights during the active MJO period. At altitudes with observations for both cases, the number of points (Fig. 7a) was up to 5 times greater during the active phase (the total number of points was 4 times greater, with NActive 5 12 184 and NInactive 5 3140). This result was in agreement with re- sults from Mapes and Houze (1993) and Chen et al. (1996) and schematics of convective cloud populations (Morita et al. 2006; Benedict and Randall 2007) that suggested more widespread deep convection during the active phase. The larger population of convective cells that occur during the active phase directly leads to a larger stratiform area (through convective decay to stratiform). This is evident in the reflectivity CFADs (Fig. 7c), where a brightband signature (enhanced re- flectivity near the melting level) is obvious during the active case, while not evident in the inactive case. The bright band is associated with the stratiform region of a convective system where the terminal velocities of ice crystals may overcome the relatively modest vertical motions and begin a downward descent and melt during transition through the freezing level. Below the bright band, reflectivity remained nearly constant toward the surface during the active phase. However, in the inactive phase there is a small decrease in reflectivity near the lowest levels (,1.5 km) that could be an indication of an evaporative process. A drier lower troposphere has been associated with the inactive phase and could explain this behavior. The active phase ex- hibited a higher median vertical reflectivity profile over the depth of observations, often associated with more vigorous convective systems. In addition, the distribu- tion of reflectivity values is broader at low levels during the inactive phase. This might be explained by vertical velocity CFADs (Fig. 7d). During the inactive phase, a mean updraft was present up to ; 8 km, with a greater probability of updrafts throughout. This is not surprising given the less organized and more scattered nature of the deep convection, consisting of individual convective elements and little stratiform. The greater number of organized convective systems that occurred during the active phase resulted in a more symmetric distribution of updraft and downdraft probabilities, in large part due to the mesoscale descent below the melting level that is characteristic of stratiform precipitation. Further characterization of the differences between the active and inactive phases was explored through analysis of the 3D wind field observations of the P-3 tail radar. Figure 8a displays the horizontal reflectivity field at 2-km height overlaid by the horizontal wind solutions of the dual-Doppler analysis of the tail radar. No system motion was discernable, though the quasi-linear convective features nearly align perpendicular to the 2-km system wind vector. A single cross section was chosen as the most representative of inherent kinematic and radar reflectivity characteristics following thorough dissec- tion of the system at various points. A cross section of the convective feature near the aircraft track (Fig. 8b) showed representative strong, deep updrafts beginning at ;4 km and reaching above 12 km near the convective cell (nominally ;60 km along track). These updrafts lofted hydrometeors well above the melting level, feeding ice crystals to the spreading anvil cloud. No mesoscale descent or ascent (i.e., rear inflow jet) was found, with perturbations in vertical flow corresponding to convective cell locations. There was a general weak descent below 5 km during this period. The convective thermodynamic environment was sampled using dropsondes (along the red line in Fig. 8a), which allowed the characterization of the lower- tropospheric thermodynamic structure. Figure 9a in- dicated relatively homogenous temperature stratification, with no apparent (or very weak) cold pool at the surface (,18C change). The humidity structure (Fig. 9b) indi- cates a moist environment, with two small dry anomalies near 800 hPa. The authors speculate that since these dry anomalies occurred between mature and decaying convective cells, the convective environment moisture had been depleted and had not recovered fully. In agreement with findings from the dual-Doppler anal- ysis, vertical wind measurements indicated general subsidence (Fig. 9c), consistent with the large strati- form area during the active phase. Upward motion near the 5- and 80-km distances correspond to locations of convective elements (see Fig. 8a) in close proximity. Figures 10 and 11 show the same analyses for the in- active case. Convective systems during the inactive phase were smaller (in terms of horizontal reflectivity area) than during the active phase with a weaker hori- zontal wind field (Fig. 10a). A cross section (Fig. 10b) through the most vigorous convective element exhibited maximum ETH to only ;9 km, with the majority ,6km (for both stratiform and convective clouds). Reflectivity values were comparable, though updrafts were weaker (and, therefore, lower vertical extent) than during the active phase. Broad descent was not observed because of the lack of stratiform precipitation clouds, which is also evident in the vertical motions recorded by drop- sondes (Fig. 11c). No cold pools were evident in the vertical temperature profiles (Fig. 11a) and relative humidity (Fig. 11b) was lower in a bulk sense, with greater stratification observed-unlike the deep mois- ture columns seen during the active phase. A shallow dry layer was observed near 950 hPa, though whether this acted to suppress convective activity is unclear. c. MJO onset, active, and decay observations A key component of the DYNAMO mission was to characterize convection in the climatological MJO ini- tiation region. While the active and inactive phases exhibited clear differences in convective characteristics, it was also of interest to investigate the evolution of the sampled precipitating cloud population characteristics during an MJO event. As discussed in section 3, G13 established a peak in the MJO signature on 26 November. A number of missions were flown surrounding this time period. Using indices presented in G13 and in- formation regarding the monitoring of the MJO and tropical waves maintained by Cooperative Institute for Climate and Satellites (http://monitor.cicsnc.org/ mjo/archive/), it was determined that 22, 24, and 30 November represented ''onset,'' ''active,'' and ''decay'' phases of the late November MJO event, respectively. While two RCE modules were executed on both 22 and 24 November, only a single RCE was collected on 30 November. Therefore, mission times were used to select case comparisons, with the second RCE modules for both 22 and 24 November used for this study. Figures 5c-g indicated extensive stratiform pre- cipitation coverage during the entire MJO period. Or- ganization was as discussed in section 4b, with similarly aligned quasi-linear elements that exhibited little system motion. A similar number of points were collected for the onset (10367), peak (12184), and decay (14 371) cases. Frequency of ETH (Figs. 7b) occurred with dis- tinct distributions for each case. A bimodal distribution was observed during the onset phase, with the primary mode at ;12 km and a secondary, weaker signal at ;7km. The peak phase featured a broad vertical distribution, while the decay phase displayed a strong upper-level peak near 14 km. Reflectivity CFADs (Fig. 7c) indicated that the strongest precipitation occurred during the peak phase, where higher probabilities of high reflectivity values (.30 dBZ) were present below the freezing level. In addition, the median, mean, 10th, and 90th percentile vertical profiles were displaced to higher reflectivity values during the peak case. Mean and contoured ver- tical velocity CFAD distributions (Fig. 7d) revealed downward motion below 4 km during the onset (mean negative value and CFAD distribution skewed nega- tively), with upward motion above this height. The peak and decay phases displayed upward motion on average throughout the vertical column. The CFAD distribution was more symmetric during the peak, while skewed positive above 6 km during the decay phase. This was indicative of widespread convection with equivalent convective and stratiform precipitation modes; and the presence of a deep convective precipitation mode, with less low- to midlevel stratiform precipitation during the decay phase. Taken as a whole, measurements during the onset indicated a transition from moderate to deep convective storms, resulting in increased stratiform precipitation. A cross-sectional view of the sampled MCSs (Fig. 12) supports this view and indicated deep updrafts from 2 to 12 km in height, with a large area of weak downdrafts at low levels. A relatively stronger cold pool (,38C) was observed near the 40-km mark of the dropsonde track (likely associated with the dying convective element at 50 km), with increasing relative humidity from 950 to 750 hPa (Figs. 13a,b). Overall downward vertical motion was observed (Fig. 13c), consistent with the dual- Doppler analysis. Reflectivity values for this case were among the largest observed by the P-3 during DYNAMO, though the possibility of a fortuitous measurement of an exceptionally strong storm must be acknowledged. However, it is believed that this was unlikely and was in fact representative of the transitioning nature into more widespread and less vertically extended convec- tive systems. After the transition to a more widespread convective signal (peak phase), greater variability in convective life cycle was present, acting to broaden the ETH distribu- tion. The narrowing of CFAD reflectivity distributions below the melting level and the establishment of a modal value near ;30 dBZ indicated strong and per- sistent widespread precipitation near the surface. A typical cross section was discussed in section 4b, indi- cative of a large stratiform precipitation contribution and widespread convection. As the MJO event decayed, the modal value subtly shifted to a lower reflectivity value (;25 dBZ), with slightly less diagonalization apparent (Fig. 7c). A cross-sectional view during this phase (Fig. 14) showed continued convective activity with a broader echo above 10 km, indicating spreading anvil cloud aloft. Updrafts were observed up to near 13 km, with closely coupled downdrafts adjacent. The occurrence probability of stron- ger updrafts was offset to higher altitudes in the decay phase (Fig. 7d). These deep updrafts acted to loft hy- drometeors to high levels and increase ice production, resulting in the shift of the reflectivity CFAD toward higher reflectivity aloft. Cold pools were weak to non- existent (Fig. 15a), and the convective thermodynamic environment displayed high moisture (Fig. 15b), with dry intrusions into low levels and weakening mesoscale ascent (Fig. 15c) from the peak of the MJO event. d. Comparison to previous experiments The DYNAMO flight pattern was designed to compare MCS observations to those during TOGA COARE, where three dual-Doppler radar instrumented aircraft, includingbothNOAAP-3aircraft (N42and N43)and the National Center for Atmospheric Research (NCAR) Electra operated for a longer time period (59 days) than in DYNAMO and observed 25 cloud systems (Kingsmill and Houze 1999). A great deal of information regarding mesoscale characteristics during MJO events was pro- vided by the TOGA COARE project. However, TOGA COARE was located in the western Pacific and, there- fore, did not observe the MJO initiation region. In addi- tion, only results from airborne radar measurements from both TOGA COARE and DYNAMO will be discussed in this section. The properties reported in this study generally align with tropical, maritime convection where convective systems attain large horizontal coverage, but are gen- erally less vigorous (e.g., vertical radar reflectivity, up- draft strength, etc.) and display a prominent warm rain precipitation mechanism (precipitation growth pro- cesses primarily below the melting level) than their midlatitude and continental counterparts. Houze et al. (2000) reported on differences observed in convective systems as a function of environmental conditions (west- erly onset versus deep westerly wind regions). Similar characteristic environmental differences between con- vective system cases in this study were discussed in sections 4b,c. There were regional characteristics evi- dent throughout the dataset, regardless of MJO phase. An example was the general lack of strong near-surface cold pools and highly linearly oriented (squall-line archetype with convective lines oriented perpendicular to the low-level shear) convective systems (Jorgensen et al. 1997). The precipitating systems observed by the P-3 during DYNAMO were dominated by convective cell life cycle (order of 60 min), with little indication of a propagation direction and longer life cycles associated with more organized MCS structure (e.g., leading line- trailing stratiform squall line). Jorgensen et al. (1997) studied the strongest arche- typal TOGA COARE squall line and discovered simi- larities to previous observed and simulated results of squall lines in general, such as the presence of midlevel rotating vortex on the northern flank and upshear-tilted convection along the leading line. Their results also in- dicated that boundary layer recovery was highly coupled to strong cold pools generated and strengthened by the convective systems and that momentum transport parameterizations must take into account system- produced vorticity as well as ambient conditions. Kingsmill and Houze (1999) synthesized results from all TOGA COARE airborne observations, confirming findings in Jorgensen et al. (1997), and finding coupling between the sloped stratiform inflow and convec- tive downdrafts for nearly all large convective systems, leading to a more complex view of MCS-environmental feedbacks that went beyond the Moncrieff (1992) layer model of convection. Owing to the lack of strong vertical wind shear during DYNAMO observations, (because of both environ- mental vertical wind profiles and the lack of a system propagation vector), convective cell tilting was limited. In addition, sloping stratiform inflow was not evident (Figs. 8, 10, 12, and 14) as in TOGA COARE squall lines, and therefore was not apparently coupled to convective downdrafts. This may have led to weaker downdrafts via reduced precipitation loading, and therefore decreased generation of (or weaker) cold pools. It is possible that the lack of strong cold pools during DYNAMO contributed to the lack of generation and maintenance of linear convective systems observed, also affecting boundary layer recovery times. These re- sults suggested that there were dynamical differences between the DYNAMO cases presented here and TOGA COARE MCSs, leading to different momentum transport characteristics. The less shear perpendicular linear orientation of DYNAMO MCSs could lead to a decreased countergradient nature of line-normal mo- mentum transport. Given the dynamical differences suggested by these results, it was of interest to compare vertical profiles of reflectivity and vertical velocity measured by the P-3 aircraft. As might be expected the MJO inactive case, which represented more isolated maritime convection, resulted in the weakest reflectivity profile (Fig. 16a). The continental Bow Echo and Mesoscale Convective Vor- tex Experiment (BAMEX; Davis et al. 2004) case was included to provide context in comparison to vigorous linear MCS systems that occur over land but will not be discussed. The active phase case from DYNAMO ex- hibited a similar reflectivity profile to the extensively studied 22 February 1993 TOGA COARE squall-line case, with greater reflectivity values aloft. The descending stratiform flow observed in TOGA COARE acted to transport hydrometeors from upper levels downward. Since radar reflectivity is proportional to both particle size and number, the decreased population aloft would effectively lower reflectivity values in the TOGA COARE profile. However, vertical velocities in TOGA COARE were relatively larger from near the surface to 15 km. Stronger upward velocities could, in theory, transport larger particles above the melting level. This does not appear to be the case given the reflectivity profiles. Analysis of vertical profiles of drop size distri- butions would be required to address this more fully, but are beyond the scope of this paper. It should be noted that additional ice crystals above the melting level dur- ing the DYNAMO active case could result in the descent of larger particles through the melting level, indicating increased importance of ice microphysics during the MJO active phase and leading to more efficient coalescence processes at lower-levels. 5. Summary and conclusions Characteristics of MCSs were compared over a por- tion of the IOP during the DYNAMO project using airborne Doppler weather radar on board the NOAA P-3 instrumented aircraft. Nine convection-specific missions (RCEs) were flown during both the active and inactive phases in the Indian Ocean climatological MJO initia- tion region. Systems were compared statistically using frequency distributions of ETH, reflectivity, and vertical velocity. Analysis of system structures was accom- plished using 3D MCS reflectivity and wind fields and representative cross sections. In general the archetype included convective systems that exhibited weak orga- nization (e.g., weak linearity), were aligned parallel to low-level vertical wind shear vector, and had no dis- cernable motion vector. Similar to previous findings, convective systems went from isolated to more widespread at the peak of the MJO event, and back again to isolated convection fol- lowing the MJO active phase. Changes in ETH fre- quency distributions corresponded with MJO phase, broadening with the increased convective activity at the MJO peak. Representative MJO active and inactive cases illustrated that both the larger population and greater vertical extent of convective elements during the active phase lead to a substantial difference in the stratiform proportion of precipitating systems. Verti- cal velocity distributions showed stronger relative up- drafts during the inactive phase, but were confined to lower levels. This difference indicated that ice micro- physics might play a greater role during the active MJO phase. Variability in system characteristics were also ob- served during the onset, peak, and decay portion of the MJO event, demonstrating a transition from deep con- vection at the onset of the MJO to more widespread convection during the peak and a decrease in convective activity led to reduced stratiform precipitation during the decay phase. A distinct shift in ETH distributions was observed with a prominent peak near 12 km pre- ceding the MJO peak, at which time the distribution broadened and exhibited no prominent peak. As the MJO decayed, a pronounced peak reemerged at ;14 km, with an accompanying decrease in ETH occurrence fre- quency below ;5km. Comparison with TOGA COARE suggested distinc- tions between convection associated with the MJO in the DYNAMO region and the western Pacific. In a mean sense, the less organized DYNAMO MCSs exhibited less tilted convective portions with relatively weaker up- drafts. However, the updrafts in DYNAMO extended to greater heights and lacked the descending stratiform flow that coupled the region above the melting level with convective downdrafts. This may suggest that ice mi- crophysicsmayplayamoreprominent role in precipitation and system dynamic processes in DYNAMO than dur- ing TOGA COARE. In addition, weaker cold pools were observed during DYNAMO, which likely contributed to less linearly oriented convection and could also lead to a modification of MCS maintenance mechanisms. During the course of the entire DYNAMO project, there were three separate MJO events observed. How- ever, NOAA P-3 aircraft data were only available for a single event. Therefore, an inherent limitation of the current study is that the results presented here are characteristic of a single MJO event and may not be representative of other MJO events. Further study of the ground- and ship-based radars deployed during DYNAMO will be needed to ascertain differences in convective populations over a longer time period and during unique MJO events. Simulations will be impor- tant to quantify the effect on MCS kinematics and structure due to the differences found in this study. In addition, precipitation probe data on board the P-3 may provide insight into the microphysical differences during the various phases of the MJO in the DYNAMO region. Acknowledgments. This research was undertaken as a National Research Council postdoctoral research as- sociate. Funding was provided by the NOAA Climate Program Office (Grant NA11OAR4310077). Special thanks are accorded to the NOAA Aircraft Operations Center, and especially the flight crew of the P-3 aircraft for a successful execution of project objectives. Also, Qing Wang and the NCAR EOL team for providing quality-controlled dropsonde data. The authors thank Shuyi Chen, Angela Rowe, and Elizabeth Thompson for many interesting and useful conversations, along with presentations from many members of the DYNAMO community. This manuscript was improved by the thorough and constructive comments by two anonymous reviewers. REFERENCES Alexander, G. D., and G. S. Young, 1992: The relationship between EMEX mesoscale precipitation feature properties and their environmental characteristics. Mon. Wea. Rev., 120, 554-564, doi:10.1175/1520-0493(1992)120,0554:TRBEMP.2.0.CO;2. Atlas, D., R. C. Srivastava, and R. S. Sekhon, 1973: Doppler radar characteristics of precipitation at vertical incidence. Rev. Geo- phys., 11, 1-35, doi:10.1029/RG011i001p00001. Barnes, G. M., and K. Sieckman, 1984: The environment of fast- and slow-moving tropical mesoscale convective cloud lines. Mon. Wea. Rev., 112, 1782-1794, doi:10.1175/ 1520-0493(1984)112,1782:TEOFAS.2.0.CO;2. Benedict, J. J., and D. A. Randall, 2007: Observed characteristics of the MJO relative to maximum rainfall. J. Atmos. Sci., 64, 2332-2354, doi:10.1175/JAS3968.1. -, and -, 2009: Structure of the Madden-Julian oscillation in the superparameterized CAM. J. Atmos. Sci., 66, 3277-3296, doi:10.1175/2009JAS3030.1. Chen, S. S., R. A. Houze, and B. E. Mapes, 1996: Multiscale vari- ability of deep convection in realation to large-scale circulation in TOGA COARE. J. Atmos.Sci., 53, 1380-1409,doi:10.1175/ 1520-0469(1996)053,1380:MVODCI.2.0.CO;2. Davis, C., and Coauthors, 2004: The Bow Echo and MCV Exper- iment: Observations and opportunities. Bull. Amer. Meteor. Soc., 85, 1075-1093, doi:10.1175/BAMS-85-8-1075. Gottschalck, J., P. E. Roundy, C. J. Schreck, A. Vintzileos, and C. Zhang, 2013: Large-scale atmospheric and oceanic condi- tions during the 2011-12 DYNAMO field campaign. Mon. Wea. Rev., 141, 4173-4196, doi:10.1175/MWR-D-13-00022.1. Houze, R. A., 1977: Structure and dynamics of a tropical squall- line system. Mon. Wea. Rev., 105, 1540-1567, doi:10.1175/ 1520-0493(1977)105,1540:SADOAT.2.0.CO;2. -, B. F. Smull, and P. Dodge, 1990: Mesoscale organization of springtime rainstorms in Oklahoma. Mon. Wea. Rev., 118, 613- 654, doi:10.1175/1520-0493(1990)118,0613:MOOSRI.2.0.CO;2. -, S. S. Chen, D. E. Kingsmill, Y. Serra, and S. E. Yuter, 2000: Convection over the Pacific warm pool in relation to the at- mospheric Kelvin-Rossby wave. J. Atmos. Sci., 57, 3058-3089, doi:10.1175/1520-0469(2000)057,3058:COTPWP.2.0.CO;2. Huffman, G. J., R. F. Adler, M. M. Morrissey, D. T. Bolvin, S. Curtis, R. Joyce, B. McGavock, and J. Susskind, 2001: Global precipitation at one-degree daily resolution from multi- satellite observations. J. Hydrometeor., 2, 36-50, doi:10.1175/ 1525-7541(2001)002,0036:GPAODD.2.0.CO;2. Jorgensen, D. P., P. H. Hildebrand, and C. L. Frush, 1983: Feasi- bility test of an airborne pulse-Doppler meteorological radar. J. Climate Appl. Meteor., 22, 744-757, doi:10.1175/ 1520-0450(1983)022,0744:FTOAAP.2.0.CO;2. -, T. Matejka, and J. D. DuGranrut, 1996: Multi-beam tech- niques for deriving wind fields from airborne Doppler radars. Meteor. Atmos. Phys., 59, 83-104, doi:10.1007/BF01032002. -, M. A. Lemone, and S. B. Trier, 1997: Structure and evolu- tion of the 22 February 1993 TOGA COARE squall line: Aircraft observations of precipitation, circulation, and sur- face energy fluxes. J. Atmos. Sci., 54, 1961-1985, doi:10.1175/ 1520-0469(1997)054,1961:SAEOTF.2.0.CO;2 Joss, J., and A. Waldvogel, 1970: Raindrop size distribution and Doppler velocities. Preprints, 14th Conf. on Radar Meteorol- ogy, Tucson, AZ, Amer. Meteor. Soc., 153-156. Kiladis, G. N., K. H. Straub, and P. T. Haertel, 2005: Zonal and vertical structure of the Madden-Julian oscillation. J. Atmos. Sci., 62, 2790-2809, doi:10.1175/JAS3520.1. Kingsmill, D. E., and R. A. Houze Jr., 1999: Kinematic charac- teristics of air flowing into and out of precipitating convec- tion over the west Pacific warm pool: An airborne Doppler radar survey. Quart. J. Roy. Meteor. Soc., 125, 1165-1207, doi:10.1002/qj.1999.49712555605. Lau, W. K. M., and D. E. Waliser, 2005: Intraseasonal Vari- ability in the Atmosphere-Ocean Climate System. Springer, 477 pp. Leise, J. A., 1981: A multidimensional scale-telescoped filter and data extension package. NOAA Tech. Memo. ERL WPL-82, 18 pp. [NTIS PB82-164104.] Lemone, M. A., E. J. Zipser, and S. B. Trier, 1998: The role of environmental shear and thermodynamic conditions in de- termining the structure and evolution of mesoscale convective systems during TOGA COARE. J. Atmos. Sci., 55, 3493-3518, doi:10.1175/1520-0469(1998)055,3493:TROESA.2.0.CO;2. Lin, J.-L., and Coauthors, 2006: Tropical intraseasonal variability in 14 IPCC AR4 climate models. Part I: Convective signals. J. Climate, 19, 2665-2690, doi:10.1175/JCLI3735.1. Lin, X., and R. H. Johnson, 1996: Heating, moistening, and rainfall over the western Pacific warm pool during TOGA COARE. J. Atmos. Sci., 53, 3367-3383, doi:10.1175/ 1520-0469(1996)053,3367:HMAROT.2.0.CO;2. Liu, C., 2011: Rainfall contributions from precipitation systems with different sizes, convective intensities, and durations over the tropics and subtropics. J. Hydrometeor., 12, 394-412, doi:10.1175/2010JHM1320.1. Madden, R. A., and P. R. Julian, 1971: Detection of a 40-50 day oscillation in the zonal wind in the tropical Pacific. J. Atmos. Sci., 28, 702-708, doi:10.1175/1520-0469(1971)028,0702: DOADOI.2.0.CO;2. -, and -, 1972: Description of global-scale circulation cells in the tropics with a 40-50 day period. J. Atmos. Sci., 29, 1109-1123, doi:10.1175/1520-0469(1972)029,1109:DOGSCC.2.0.CO;2. Mapes, B. E., and R. A. Houze, 1993: Cloud clusters and super- clusters over the oceanic warm pool. Mon. Wea. Rev., 121, 1398- 1416, doi:10.1175/1520-0493(1993)121,1398:CCASOT.2.0.CO;2. Moncrieff, M. W., 1992: Organized convective systems: Archetypal dynamical models, mass and momentum flux theory, and pa- rametrization. Quart. J. Roy. Meteor. Soc., 118, 819-850, doi:10.1002/qj.49711850703. Morita, J., Y. N. Takayabu, S. Shige, and Y. Kodama, 2006: Analysis of rainfall characteristics of the Madden-Julian os- cillation using TRMM satellite data. Dyn. Atmos. Oceans, 42, 107-126, doi:10.1016/j.dynatmoce.2006.02.002. O'Brien, J. J., 1970: Alternative solutions to the classical vertical velocity problem. J. Appl. Meteor., 9, 197-203, doi:10.1175/ 1520-0450(1970)009,0197:ASTTCV.2.0.CO;2. Oye, R., C. Mueller, and S. Smith, 1995: Software for radar trans- lation, visualization, editing, and interpolation. Preprints, 27th Conf. on Radar Meteorology, Vail, CO, Amer. Meteor. Soc., 359-361. Rickenbach, T. M., and S. A. Rutledge,1998: Convection in TOGA COARE: Horizontal scale, morphology, and rainfall pro- duction. J. Atmos. Sci., 55, 2715-2729. Webster, P. J., and R. Lukas, 1992: TOGA COARE: The coupled ocean-atmosphere response experiment. Bull. Amer. Meteor. Soc., 73, 1377-1416, doi:10.1175/1520-0477(1992)073,1377: TCTCOR.2.0.CO;2. Wheeler, M. C., and H. H. Hendon, 2004: An all-season real-time multivariate MJO index: Development of an index for moni- toring and prediction. Mon. Wea. Rev., 132, 1917-1932, doi:10.1175/1520-0493(2004)132,1917:AARMMI.2.0.CO;2. Yoneyama, K., andCoauthors, 2008:Mismo field experiment in the equatorial Indian Ocean. Bull. Amer. Meteor. Soc., 89, 1889- 1903, doi:10.1175/2008BAMS2519.1. -, C. Zhang, and C. N. Long, 2013: Tracking pulses of the Madden-Julian oscillation. Bull.Amer. Meteor. Soc., 94, 1871- 1891, doi:10.1175/BAMS-D-12-00157.1. Yuter, S. E., and R. A. Houze, 1995: Three-dimensional kinematic and microphysical evolution of Florida cumulonimbus. Part II: Frequency distributions of vertical velocity, reflectivity, and differential reflectivity. Mon. Wea. Rev., 123, 1941-1963, doi:10.1175/1520-0493(1995)123,1941:TDKAME.2.0.CO;2. Zeng, Z., S. E. Yuter, R. A. Houze, and D. E. Kingsmill, 2001: Microphysics of the rapid development of heavy convective precipitation. Mon. Wea. Rev., 129, 1882-1904, doi:10.1175/ 1520-0493(2001)129,1882:MOTRDO.2.0.CO;2. Zhang, C., 2005: Madden-Julian oscillation. Rev. Geophys., 43, RG2003, doi:10.1029/2004RG000158. Zipser, E. J., 1977: Mesoscale and convective-scale downdrafts as distinct components of squall-line structure. Mon. Wea. Rev., 105, 1568-1589, doi:10.1175/1520-0493(1977)105,1568: MACDAD.2.0.CO;2. NICK GUY AND DAVID P. JORGENSEN NOAA/National Severe Storms Laboratory, Norman, Oklahoma (Manuscript received 7 August 2013, in final form 8 November 2013) Corresponding author address: Nick Guy, NOAA/NSSL/WRDD, 120 David L. Boren Blvd., Norman, OK 73072. E-mail: [email protected] (c) 2014 American Meteorological Society |