1. Introduction
A dominant component of intraseasonal tropical variability 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 phenomena (e.g., El Niño–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 characteristics 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 anomalies during peak convective (MJO) activity (wet) phases. Drying occurs during the decay of the MJO, along with the reestablishment of surface easterlies. Deep convection, climatologically initiating over the equatorial Indian Ocean region, often organizes into clusters of mesoscale convective systems (MCSs). The deep convective envelope 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 understanding of the MJO in this region. However, using satellite and sounding data, Kiladis et al. (2005) suggested that MJO structure varied with longitude. Despite 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 information 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 represent smaller-scale variability statistically or explicitly in numerical weather models.
Map showing the primary DYNAMO project quadrilateral observational domain. Dashed lines connect ship-based [R/V Revelle (REV) and R/V Mirai (MAR)] and island-based [Diego Garcia (DGO) and Addu Atoll (SPOL)] stationary sites. The NOAA P-3 aircraft operated largely within the indicated domain, acting as a gap-filling sampling platform. The star on the inset global map indicates the approximate position of the quadrilateral drawn here.
Citation: Monthly Weather Review 142, 4; 10.1175/MWR-D-13-00252.1
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 radars 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 objectives 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 aspect of this platform allowed sampling of convective systems during daylight hours between the fixed-point observations recorded on island- and ship-based platforms 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 aircraft 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 morphology and characteristics of MCSs, which account for a large amount of precipitation in the tropics and interact 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 associated 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 momentum 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 understanding 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 methodology 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 characteristics 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 observations 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. Characteristics for both radar systems are listed in Table 2.
NOAA P-3 flights during the DYNAMO project. Boldface rows indicate days in which radar convective element (RCE) modules were flown. Date, time, and approximate location of the middle of flight pattern are provided for RCE performed during the DYNAMO field experiment. All dates occur during 2011. Local time is UTC + 5 h.
NOAA WP-3D radar characteristics.
The tail Doppler radar has a dual-plate antenna providing alternating scans forward and aft [fore/aft scanning technique (FAST)] at a 20° angle from perpendicular to the aircraft longitudinal axis (Jorgensen et al. 1996). During a relatively straight flight path, the FAST technique results in the tail radar sweeping consecutive full 3D volumes. With the P-3 nominal ground speed of 120 m s−1, coincident measurements result from the alternating scans approximately every 1.4 km, with a ~40° 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 s−1, eliminating velocity “folding” issues in this study. The dual-PRF operates in batch-mode (sending out pulse stream pairs), using 3200 and 2400 Hz.
Scanning geometry of the X-band tail Doppler radar on board the NOAA P-3. The FAST scanning technique employs alternating fore–aft scanning, with each beam directed ±20° from a plane perpendicular to the aircraft longitudinal axis. Aircraft motion results in intersecting radar beams, with a horizontal data spacing of approximately 1.2–1.4 km.
Citation: Monthly Weather Review 142, 4; 10.1175/MWR-D-13-00252.1
The data were quality controlled (QC) using a combination of automated and manual techniques within the interactive SOLO data editor (Oye et al. 1995) developed by the National Center for Atmospheric Research. 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 returned 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 geometrical 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 consequently 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 computed. These heights agree well with climatological tropical freezing level heights, and with dropsonde measurements performed throughout the P-3 observations (section 2c). Though no attenuation correction algorithm was employed, an attempt was made to compensate for some X-band attenuation in heavy precipitation 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 Research 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, υ) were computed from radial velocities using an overdetermined, two-equation solution. The two-equation system is a function of the zonal (u), meridional (υ), and vertical (w) wind components. A two-pass Leise filter (Leise 1981) was applied to horizontal winds to reduce noise resulting from features 3–4 times the horizontal grid spacing (6–7.5 km). Once solutions for u and υ were found, vertical velocity was estimated through upward integration of the continuity equation, with a boundary condition of w = 0 assumed at the surface. Vertical column mass balance was achieved by applying the O’Brien (1970) correction to the divergence profile through setting w = 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 interpreting 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 resolution of the LF [2 revolutions per minute (rpm)] may also result in slight cell motions going unnoticed. Domain 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) necessitated 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 convective system observed. The strongest convective systems 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 dropsondes every 2–3 min. This provided detailed data of the convective systems along with observations of the thermodynamic structure of the convective environment, particularly the cold pool.
A diagram of the flight pattern employed to sample convective systems during the DYNAMO field project, termed a radar convective element (RCE) module. The module began by paralleling the front convective feature, followed by a turn to transit to the rear of the system. The front was defined by system motion; however, this was somewhat subjective in this field project. The final portion of the RCE consisted of a transit orthogonally through the convective feature, releasing dropsondes often to characterize the convective environment. Also shown is the flux module that sometimes directly followed the RCE pattern. Leg lengths are approximate, dependent upon the size of the convective feature.
Citation: Monthly Weather Review 142, 4; 10.1175/MWR-D-13-00252.1
During the 12 DYNAMO flights, a total of 9 RCE modules were executed. The RCE modules were performed 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 extensively. 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 approximately as the observational domain (Fig. 1) ±10° 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 presented 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. Convection 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, becoming relatively dry for the remainder of the P-3 operational 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 Measuring Mission gridded 3B42 precipitation data (Huffman et al. 2001) showed the existence of propagating precipitation 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 10°S to 5°N; latitudinal locations of RCE flights can be found in Table 1.
Time–latitude diagram of TRMM 3B42 precipitation (mm h−1) averaged between 10°S and 5°N for the month coinciding with flight dates of the NOAA P-3 aircraft during the DYNAMO project. A minimum threshold of 0.7 mm h−1 is used for visualization. The vertical dashed, black lines correspond to the eastern and western boundaries of the DYNAMO quadrilateral observational domain. The red boxes indicate the position in time and space of RCE modules. The eastward-propagating precipitation maximum within the DYNAMO domain from 22 to 25 Nov is an MJO event.
Citation: Monthly Weather Review 142, 4; 10.1175/MWR-D-13-00252.1
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 representative of the vigorous convective systems in the observed 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 dissipating 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 quantitative size was calculated because of the mobile nature of the platform.
A constant altitude plan position indicator (CAPPI) of composite radar reflectivity (color contours) at 2 km for each of the nine RCE flight modules executed during the DYNAMO project. Panels are arranged in temporal sequence: (a) 11 Nov; (b) 16 Nov; (c),(d) 22 Nov; (e),(f) 24 Nov; (g) 30 Nov; and (h),(i) 8 Dec. Dates are found at the top left of the plot and duration of RCE module (UTC time) is indicated on the top right. The flight track (black line) is overlaid, with a filled circle indicating the starting point for the RCE. Interruption of flight track lines indicates missing data. Latitudinal (longitudinal) tick mark spacing of 0.2° (0.5°) is consistent throughout the panels. By convention, equivalent Cartesian horizontal grids were created sized for each RCE.
Citation: Monthly Weather Review 142, 4; 10.1175/MWR-D-13-00252.1
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 (indicative of either large precipitation size particles, a large number of precipitation-sized particles, or a combination 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 section 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) indicated 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 s−1) and 8 December (2 m s−1) were consistent with the Alexander–Young criterion (<5 m s−1) for shear-parallel systems (Alexander and Young 1992). Similar characteristics have been observed for slow-moving, loosely organized convection in oceanic environments (Barnes and Sieckman 1984; Lemone et al. 1998).
Radiosonde profiles for (a) 24 Nov and (b) 8 Dec launched at the R/V Revelle and Gan Island, respectively. Thermodynamic profiles for each environment differ; however, the wind profiles for each day show that the vertical wind vector at midlevels (see inlaid hodograph) indicated that convection was aligned shear parallel for both days. See Fig. 5 for horizontal reflectivity maps.
Citation: Monthly Weather Review 142, 4; 10.1175/MWR-D-13-00252.1
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 characteristics during the 4-month observational period. During 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 precipitating system. Horizontal areal coverage varied between 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) diagrams (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 radar data provides fine system detail, the application of a traditional convective-stratiform partitioning algorithm 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 dataset and are currently under investigation.
A comparison of statistics of observed convective systems during each RCE module, with time increasing moving from left to right. Date and RCE module information is shown above each column; refer to Table 2 for more information regarding RCE module time and geographic location. The frequency in terms of the (a) number of points and (b) percentage indicated difference in vertical structure throughout the observed time period. Percentages were calculated by the number of points at each height divided by the total number of sampled points. CFADs of (c) reflectivity and (d) vertical velocity supported the deepening of convection during the MJO event. Color contours indicate the probability frequency at each vertical level of the observed values. The short dashed lines at each extreme of reflectivity distributions in (c) represent the 10th and 90th percentiles, while the long dashed line indicates the median vertical profile. Thick solid lines in the contoured plots indicate the mean vertical profiles. The thin solid line in (d) is the zero line divider of positive (upward) and negative (downward) vertical velocity.
Citation: Monthly Weather Review 142, 4; 10.1175/MWR-D-13-00252.1
A greater diagonalization of reflectivity CFADs (decreasing reflectivity with increasing height) is often associated with a population of mature convective cells (Zeng et al. 2001). The similarity throughout the RCE modules was another indication that the sampled systems 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 during 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 thermodynamic 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 differences would correspond to the most conservative estimates 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 = 12 184 and NInactive = 3140). This result was in agreement with results 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 reflectivity 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 exhibited a higher median vertical reflectivity profile over the depth of observations, often associated with more vigorous convective systems. In addition, the distribution 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 dissection 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.
(a) Horizontal reflectivity map at 2-km altitude collected by the tail radar during the second RCE module on 24 Nov 2011. Overlaid vector arrows indicated the horizontal wind solution from the quasi-dual-Doppler analysis (with reference vector at the top right) and the solid black line shows the aircraft flight path. The dropsonde release path is displayed as a solid red line. The red numbers at the beginning and end of the dropsonde release indicate the distance traveled along the path. (b) A cross section uses the same reflectivity contours and wind vectors indicating a direction parallel to the cross section and vertical wind solution. The cross section is plotted as a function of distance, with the “A” and “B” along the abscissa corresponding to positions indicated in (a) and connected by a red and white line.
Citation: Monthly Weather Review 142, 4; 10.1175/MWR-D-13-00252.1
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 indicated relatively homogenous temperature stratification, with no apparent (or very weak) cold pool at the surface (<1°C change). The humidity structure (Fig. 9b) indicates 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 analysis, vertical wind measurements indicated general subsidence (Fig. 9c), consistent with the large stratiform 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.
Dropsonde measurements from the NOAA P-3 aircraft of (a) temperature, (b) relative humidity, and (c) vertical wind during the second RCE module on 24 Nov 2011. The observations are plotted as a function of distance along the track indicated by heavy red line in Fig. 8. Vertical dashed lines represent the halfway point in descent (according to time) of individual dropsondes.
Citation: Monthly Weather Review 142, 4; 10.1175/MWR-D-13-00252.1
Figures 10 and 11 show the same analyses for the inactive case. Convective systems during the inactive phase were smaller (in terms of horizontal reflectivity area) than during the active phase with a weaker horizontal 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 <6 km (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 dropsondes (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 moisture 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.
As in Fig. 8, but for the first RCE module on 8 Dec 2011.
Citation: Monthly Weather Review 142, 4; 10.1175/MWR-D-13-00252.1
As in Fig. 9, but for the first RCE module on 8 Dec 2011 and with reference to Fig. 10.
Citation: Monthly Weather Review 142, 4; 10.1175/MWR-D-13-00252.1
c. MJO onset, active, and decay observations
A key component of the DYNAMO mission was to characterize convection in the climatological MJO initiation 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 information 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 precipitation coverage during the entire MJO period. Organization 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 (10 367), peak (12 184), and decay (14 371) cases. Frequency of ETH (Figs. 7b) occurred with distinct 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 ~7 km. 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 vertical velocity CFAD distributions (Fig. 7d) revealed downward motion below 4 km during the onset (mean negative value and CFAD distribution skewed negatively), 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 (<3°C) 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 convective systems.
As in Fig. 8, but for the second RCE module on 22 Nov 2011.
Citation: Monthly Weather Review 142, 4; 10.1175/MWR-D-13-00252.1
As in Fig. 9, but for the first RCE module on 22 Nov 2011 and with reference to Fig. 12.
Citation: Monthly Weather Review 142, 4; 10.1175/MWR-D-13-00252.1
After the transition to a more widespread convective signal (peak phase), greater variability in convective life cycle was present, acting to broaden the ETH distribution. The narrowing of CFAD reflectivity distributions below the melting level and the establishment of a modal value near ~30 dBZ indicated strong and persistent widespread precipitation near the surface. A typical cross section was discussed in section 4b, indicative 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 stronger updrafts was offset to higher altitudes in the decay phase (Fig. 7d). These deep updrafts acted to loft hydrometeors to high levels and increase ice production, resulting in the shift of the reflectivity CFAD toward higher reflectivity aloft. Cold pools were weak to nonexistent (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.
As in Fig. 8, but for the first (only) RCE module on 30 Nov 2011.
Citation: Monthly Weather Review 142, 4; 10.1175/MWR-D-13-00252.1
As in Fig. 9, but for the first RCE module on 30 Nov 2011 and with reference to Fig. 14.
Citation: Monthly Weather Review 142, 4; 10.1175/MWR-D-13-00252.1
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, including both NOAA P-3 aircraft (N42 and 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 provided by the TOGA COARE project. However, TOGA COARE was located in the western Pacific and, therefore, did not observe the MJO initiation region. In addition, 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 generally less vigorous (e.g., vertical radar reflectivity, updraft strength, etc.) and display a prominent warm rain precipitation mechanism (precipitation growth processes 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 (westerly onset versus deep westerly wind regions). Similar characteristic environmental differences between convective system cases in this study were discussed in sections 4b,c. There were regional characteristics evident 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 archetypal TOGA COARE squall line and discovered similarities 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 indicated 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 convective 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 environmental 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 results 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 momentum 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 Vortex 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 exhibited 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 distributions 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 during 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.
Mean vertical profiles of (a) reflectivity and (b) vertical velocity derived from NOAA P-3 measurements. Active (red; 24 Nov 2011 RCE 2) and inactive (black; 8 Dec 2011 RCE 1) DYNAMO profiles are compared to a typical TOGA COARE (green; 22 Feb 1993) tropical squall line and BAMEX (blue; 10 Jun 2003) continental U.S. bow echo profiles.
Citation: Monthly Weather Review 142, 4; 10.1175/MWR-D-13-00252.1
5. Summary and conclusions
Characteristics of MCSs were compared over a portion 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 initiation region. Systems were compared statistically using frequency distributions of ETH, reflectivity, and vertical velocity. Analysis of system structures was accomplished using 3D MCS reflectivity and wind fields and representative cross sections. In general the archetype included convective systems that exhibited weak organization (e.g., weak linearity), were aligned parallel to low-level vertical wind shear vector, and had no discernable 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 following the MJO active phase. Changes in ETH frequency 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. Vertical velocity distributions showed stronger relative updrafts during the inactive phase, but were confined to lower levels. This difference indicated that ice microphysics might play a greater role during the active MJO phase.
Variability in system characteristics were also observed during the onset, peak, and decay portion of the MJO event, demonstrating a transition from deep convection 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 preceding 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 frequency below ~5 km.
Comparison with TOGA COARE suggested distinctions 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 updrafts. 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 microphysics may play a more prominent role in precipitation and system dynamic processes in DYNAMO than during 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. However, 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 important 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 associate. 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.
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