1. Motivation and goals
Deep convective systems play a significant role in a number of critical components of the climate system through their large contribution to the hydrological cycle, feedback on the large-scale circulation, and their radiative effects and importance in regulating climate sensitivity. Aerosol–cloud interactions (ACI) remain one of the most uncertain components in our estimates of total global anthropogenic radiative forcing (IPCC 2021). In deep convection, estimates of the aerosol indirect effect on the top-of-atmosphere radiative forcing through changes in the properties of clouds disagree in magnitude and even sign (e.g., Khairoutdinov and Yang 2013; Fan et al. 2013; Peng et al. 2016; Yan et al. 2014; Koren et al. 2010; Fan et al. 2012). In addition, ACI may alter deep convection precipitation accumulations (Teller and Levin 2006; Wang 2005; Tao et al. 2012), precipitation onset and rate distributions (van den Heever et al. 2006; Lin et al. 2018), updraft intensity and vertical development (Rosenfeld et al. 2008; Fan et al. 2018; Marinescu et al. 2021), and storm electrification (e.g., Williams et al. 2002; Ren et al. 2018, 2019).
Some of the uncertainty in estimates of ACI effects on deep convection stems from the fact that aerosol affects both warm- and cold-phase microphysical processes (Rosenfeld et al. 2008; Sheffield et al. 2015; Fan et al. 2018). However, high-resolution spatiotemporal observations for both the concentrations and physicochemical properties of cloud condensation nuclei (CCN) are often only available from localized field campaigns. There are even fewer observations of ice nucleating particles (INPs) and a still incomplete understanding of ice formation processes (Khain and Pinsky 2018; Kanji et al. 2017) and their role in ACI.
Complicating matters even further, studies have shown that deep convection and the viability of potential ACI effects are modulated by the background meteorological environment conditions, including humidity, wind shear, instability, and storm organization (e.g., Khain 2009; Fan et al. 2009). Moreover, the correlation between CCN and these other environmental factors like CAPE and the level of neutral buoyancy make it especially difficult to separate the ACI radiative response from the meteorology (Varble 2018).
On top of the meteorological considerations, many previous studies of ACI do not realistically account for the full horizontal and vertical variations of aerosols in the storm environment (Lebo 2014), especially in regions where significant mesoscale boundaries exist, such as the sea breeze in the Houston, Texas, region. The continued conflicting results of ACI in deep convection in both observational and modeling studies highlight the need for careful analysis and better observations to advance our understanding of ACI and isolate their effects from other meteorological environmental effects.
To address this, the U.S. Department of Energy (DOE)-funded Tracking Aerosol Convection interactions Experiment (TRACER; Jensen et al. 2019) focused on collecting high spatial and temporal resolution observations of the properties of convection, as well as the thermodynamic and aerosol environment in which convection occurs. The Houston, Texas, region was chosen for TRACER because of its diversity of aerosol conditions and consistent isolated convection initiated by the sea breeze (Fridlind et al. 2019), as well as its long history as the basis for air quality studies (e.g., Daum et al. 2004; Parrish et al. 2009; Atkinson et al. 2010; Wright et al. 2010) and both observational and model studies on ACI (e.g., Orville et al. 2001; Jin et al. 2005; Fan et al. 2008; Carrio et al. 2010; Hu et al. 2019; Fan et al. 2020; Zhang et al. 2021 among many others). A full suite of atmospheric state, cloud, aerosol, and precipitation measurements were collected from October 2021 to September 2022 at two fixed sites: the first Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF1) located at La Porte, Texas, near Galveston Bay and an ancillary site (ANC) that collected measurements from June to September 2022 in a more rural area outside of the Houston metropolitan area, with the second generation C-band scanning ARM precipitation radar (CSAPR2) in between for radar coverage of both sites. An intensive observation period (IOP) occurred from June to September 2022 where the CSAPR2 operated in an automated cell-tracking mode (Lamer et al. 2023) and radiosondes were launched with increased frequency on days designated by the forecast and science team for enhanced operations. Days with a strong sea breeze in an environment conducive to isolated convection were considered ideal for enhanced operations.
Summertime deep convection in the Houston region typically occurs in onshore flow regimes west of the semipermanent Bermuda high with relatively large instability and limited vertical wind shear. Foci for convection initiation are provided by both the inland-propagating sea-breeze front from the Gulf of Mexico (GOM) and/or the westward propagating bay-breeze front associated with Galveston Bay (Fig. 1). Once initial convection has developed, outflow often reinforces both the sea- and bay-breeze fronts or produces new outflow boundaries capable of triggering subsequent convection. Typically, there are several mesoscale air masses in the Houston region on a convective day: maritime GOM air south of the sea-breeze front, maritime Galveston Bay air southeast of the bay-breeze front, continental air north of the sea- and bay-breeze fronts, and air modified by recent convective outflow. Each air mass is likely to have significantly different thermodynamic and aerosol vertical profiles which may be ingested by proximate convection such that horizontal adaptability in measurements is critical to have any hope of disentangling aerosol effects from meteorology.
GOES-16 visible satellite image overlaid with KHGX WSR-88D reflectivity in the Houston region showing the estimated position of the sea- and bay-breeze front (dashed line), DOE ARM AMF1, ANC, and CSAPR2 sites and the TAMU deployment locations (blue stars) typical of our (a) early afternoon deployment in a maritime air mass and (b) late afternoon deployment in a continental air mass. Red line indicates 150-km range ring from KHGX. (c) Map of region inside white box in (b) showing TAMU maritime (light blue star) and continental (red stars) deployment sites indicated in Table 2 as well as DOE AMF1, ANC, CSAPR2 (purple stars), and KHGX and UH coastal center deployment locations (dark blue stars).
Citation: Bulletin of the American Meteorological Society 105, 9; 10.1175/BAMS-D-23-0218.1
Full understanding of ACI requires collocated meteorological and aerosol profiling at multiple sites spread across different air masses where convection is initiated. The overarching goal of the Texas A&M University (TAMU) TRACER field campaign was to provide meteorological and aerosol profiles of air masses unsampled by the fixed ARM sites in the context of the convection initiated by the inland propagating sea breeze. To achieve this goal, we deployed a suite of mobile measurements in conjunction with DOE ARM TRACER facilities from June to September 2022 to measure the thermodynamic, kinematic, and aerosol populations in different air masses across the sea- and bay-breeze fronts on days of sea-breeze-initiated isolated convection. This combination of fully mobile aerosol measurements and thermodynamic and kinematic observations provides a unique set of observations that captures the near-storm environments to better represent the inflow air mass that is actually influencing deep convection. This paper provides an overview of the TAMU TRACER deployment strategy, measurements, preliminary case studies, and some planned analysis and possible science opportunities for ACI-related studies and beyond.
2. TAMU TRACER field campaign
a. Instrumentation and measurements.
Throughout the TAMU TRACER field campaign, iMet-4/4c radiosondes were used to obtain profiles of pressure, temperature, relative humidity (RH), wind speed, and wind direction at a temporal resolution of 1 s. For more information about sensor details, iMet software, and uncertainties, interested readers can visit the website (https://www.intermetsystems.com/products/imet-4-radiosonde/).
For the duration of each deployment, conventional meteorological surface observations (pressure, temperature, humidity, wind speed, and direction) were collected using a portable Met One AIO 2 Sonic Weather Sensor (SWS; https://metone.com/products/aio-2-sonic-weather-sensor/). The self-contained sensor was deployed on a 2-m tripod over an open grassy surface at each site with an internal compass for automatic direction finding. Three-minute averages of each variable were archived.
TRACER marked the first deployment of the TAMU Rapid Onsite Atmospheric Measurement Van (ROAM-V, shown in Fig. 2), a fully mobile and customizable laboratory. Five rechargeable lithium-ion batteries (Big Battery Rhino 276AH LiFePO4) allow for continuous and untethered sampling with ROAM-V for up to 8 h without the risk of self-contamination from engine or generator exhaust. Additionally, an isokinetic inlet enables in-transit sampling at reduced speeds if needed. During TRACER, ROAM-V was outfitted with a suite of aerosol instruments that focused on measuring cloud-forming properties (Table 1). In situ measurements included aerosol concentration (unsized and sized) and CCN concentration. While a condensation particle counter (CPC) sampled unsized concentrations, sized concentrations were measured by a scanning mobility particle sizer (SMPS) and a portable optical particle spectrometer (POPS) with a combined size range of 7.23–3370 nm. For CCN concentrations, a CCN counter scanned through six supersaturations (0.2%, 0.4%, 0.6%, 0.8%, 1.0%, and 1.2%) at 5-min intervals. Ambient aerosol was also collected through impaction for offline ice nucleation and single particle analyses. The Davis Rotating Uniform size-cut Monitor (DRUM) was used for impaction and has a series of four impactors (>3, 3–1.2, 1.2–0.34, and 0.34–0.15 μm). To minimize contamination, aerosol was collected onto precombusted aluminum foil substrates and, after each deployment, stored at −80°C until ice nucleation analysis at TAMU (Alsante et al. 2024). In addition to the INP concentration measurements provided by the DRUM deployed on the ROAM-V, INP concentrations were measured at AMF1 and the ANC through deployment of two additional DRUM samplers and offline analysis in the Brooks laboratory at the TAMU campus. Instrumentation comparable to the other ROAM-V instrumentation was operated by the DOE at AMF1.
(left) ROAM-V and (right) instrument payload during TRACER.
Citation: Bulletin of the American Meteorological Society 105, 9; 10.1175/BAMS-D-23-0218.1
Instrument payload during TAMU TRACER.
The ROAM-V instrument suite also included a 532-nm mini micro pulse lidar (miniMPL) to measure the vertical profile of backscatter and depolarization by aerosols and cloud particles. Using the ROAM-V aerosol, CCN, and INP and the radiosonde data as inputs, the miniMPL observations can be used to produce vertical profiles of aerosol, CCN, and INP concentration (Ghan and Collins 2004; Ghan et al. 2006; Marinou et al. 2019; Lenhardt et al. 2023). First, operating on the assumption that the measured aerosol population and its cloud-forming properties are representatives of those aerosols aloft, we can use the ROAM-V aerosol concentration and size distribution measurements are used to convert lidar backscatter into an aerosol concentration profile. Next, the ROAM-V CCN measurements are used to prescribe the subsaturated hygroscopicity and subsequent growth of the aerosol population at ambient RHs provided by the radiosonde data to generate a humidity-corrected aerosol profile. In addition, the ROAM-V CCN measurements are used to estimate the concentration of aerosols which would activate at supersaturations of 0.2%–1.2%. The ROAM-V ice nucleation measurements provide the fraction of the aerosol population that can act as INP as a function of temperature. These data are combined with the aerosol profiles to produce vertical profiles of INP.
b. Primary deployment strategy.
The guiding mission for our mobile deployment strategy was to sample vertical profiles of meteorological variables and aerosol concentrations simultaneously with the ARM fixed-site measurements, but within a different air mass (typically defined by the position of the sea-breeze front). For a typical observing day, this involved two separate ∼3-h deployments.
The first deployment was generally in late morning through early afternoon on the GOM coast in Galveston, Texas, to sample the air mass on the maritime side of the developing sea-breeze front (hereafter maritime air mass). At this time, the AMF1 and ANC sites were typically on the inland side of the sea-breeze front (hereafter continental air mass) or often the AMF1 site was in a maritime air mass representative of Galveston Bay, but not necessarily the GOM (Fig. 1a).
Later in the day, generally mid-to-late afternoon, the sea-breeze front and/or bay-breeze front, often augmented by convective outflow boundaries, would push inland beyond the AMF1 and ANC sites, placing them both in a maritime or convective outflow air mass. To fulfill our mission, the TAMU team would redeploy at a site on the inland side of the new boundary position, to sample a continental air mass (Fig. 1b). Our late afternoon inland site selection varied depending on the inland propagation speed of the sea-breeze front/outflow boundaries and locations of active convection (see Fig. 1c), with the goal of sampling the undisturbed late-day continental air mass for 2–3 h.
c. Secondary deployment strategies.
In practice, conditions occasionally necessitated a shift to secondary mission goals. These included longer (∼6 h) single-site continental airmass heterogeneity measurements at an inland site northwest (NW) of Houston if early morning convection disturbed the maritime air mass or if another team was collecting measurements near the coast. For prolonged, single-site continental deployments, a site was typically chosen such that it would be within a different air mass from the AMF1 or ANC site for most of the deployment, or that we would sample both the inflow and outflow of nearby convection during the deployment. Another secondary mission goal for the late afternoon deployment was targeting airmass recovery after a boundary passage in cases where convection ahead of the sea-breeze front was more widespread than expected and no undisturbed air mass was within range of the CSAPR2.
TAMU TRACER also included radiosonde-only and aerosol-only missions. The radiosonde-only missions generally targeted the primary and secondary goals listed above (Table 2). ROAM-V deployed without the radiosonde team to the University of Houston Coastal Center for long-term collection of background aerosol conditions and to the AMF1 site for instrument calibration and comparison missions (Table 3).
List of deployment dates and measurements categorized by sampled air mass, the time of the radiosonde launch(es) (R), the location of each deployment in parentheses after the radiosonde launch time (corresponding to abbreviations in Fig. 1c), and the collection period of CPC aerosol and lidar sampling (A), for each air mass. All times are given in UTC. Boldface rows represent the dates following the primary deployment strategy of early afternoon maritime airmass sampling and late afternoon continental airmass sampling. On days of secondary strategy, the notes column indicates the reasoning.
ROAM-V aerosol-only deployment date, site (corresponding to abbreviations in Fig. 1c), and collection period.
d. Deployment procedure.
A typical deployment of the mobile radiosonde team and ROAM-V generally proceeded as follows: the mobile radiosonde team deployed two radiosonde ground stations (an iMet 3050a system and an iMet 3150 system) for redundancy and the SWS for conventional meteorological surface observations for the deployment duration. The ROAM-V would park upwind to sample air undisturbed by exhaust from other nearby vehicles, as shown in Fig. 3.
TAMU ROAM-V and mobile radiosonde teams on a deployment, graduate students operating instruments in ROAM-V, undergraduates launching radiosondes, and a subset of the faculty, research staff, and graduate and undergraduate student participants in TAMU TRACER.
Citation: Bulletin of the American Meteorological Society 105, 9; 10.1175/BAMS-D-23-0218.1
The mobile radiosonde team timed launch to coincide with one of the ARM-enhanced IOP radiosonde launch times (1800, 1930, 2100, or 2230 UTC). In practice, this timing was typically achieved at the Galveston maritime site, but radiosondes at the inland (usually continental) sites were often launched ad hoc (but within an hour of ARM launches) to avoid active convection or boundary passage (e.g., Fig. 5). Radiosonde launches were generally terminated at 100 hPa (after about 1 h), at which point data were archived and sounding diagrams were shared in real-time with other TRACER teams. During the radiosonde setup, launch, and ascent, the ROAM-V continuously collected surface aerosol and lidar profiling measurements to provide requisite data for collocated, simultaneous CCN and INP profiles within the air mass. Once the radiosonde data collection was complete and the ROAM-V had collected at least two full hours of aerosol observations, the team would transit to the second deployment location or return to TAMU. During longer single-site deployments, multiple radiosondes were launched with continuous surface meteorology and aerosol sampling for the entire deployment.
e. Deployment decisions and site selection.
The decision of when and where to deploy was made jointly by the rotating pair of forecasting and deployment leaders (faculty members or research staff) with the goal of targeting days where a clearly defined sea-breeze front was expected to initiate relatively isolated convection. If ARM declared the next day as an enhanced sounding day for their facilities, the TAMU deployment and forecast teams would meet to determine if the scenario met our primary or secondary deployment goals. If so, the meeting transitioned to logistics and operations to plan the next day’s schedule and preliminary site selections.
Candidate deployment sites were selected in advance to identify locations that were publicly accessible, had a large open parking lot with relatively little traffic, and did not have obvious point sources of aerosols immediately upwind. Most deployment sites were at public parks or schools. Throughout the project, we deployed to one maritime site and seven different continental sites (Fig. 1c, Table 2) because afternoon convective evolution differed considerably from day to day. In conjunction with the nowcasting support team on TAMU’s campus, a continental site was often determined during the mobile team’s inland transit. For primary missions, we targeted a location within the range of the CSAPR2 radar but far enough removed from active convection, outflow boundaries, and the sea-breeze front so that radiosonde(s) could be launched in an unmodified continental air mass.
f. Student high-impact learning experience.
TAMU TRACER represented a tremendous high-impact learning experience for students and would not have been possible without their involvement. In total, 16 graduate students and 19 undergraduate students, many from underrepresented groups in science, participated in TAMU TRACER through field deployments, forecasting/nowcasting, and operational support (Fig. 3). Each field deployment involved a rotating crew of 1–2 faculty/research staff, 2–3 graduate students, and 2–3 undergraduate students. In the field, students were responsible for deploying and maintaining the aerosol equipment and SWS, as well as launching radiosondes under the guidance of the faculty/research staff deployment leader. Observing days typically began around 0730 LT with return as late as 2130 LT to the TAMU campus in College Station, Texas (∼90 miles northwest of Houston), often requiring exhausting 12–15-h days in over 100°F heat and humid conditions.
Students were also assigned rotations as the daily forecaster/nowcaster and on-campus deployment support staff. Under the guidance of the forecast leader, the daily student forecaster prepared customized short-term and extended-range forecasts of sea-breeze front location and convection likelihood, with recommendations for potential future deployment days. Another student provided remote nowcasting support for the deployment team, providing updates on sea-breeze front location and active convection/outflow, and making calls to local airports/Federal Aviation Administration centers for balloon launch clearance. Many of our students also participated in preparing briefing slides or gave parts of forecast briefings for the TRACER-wide daily forecast discussion.
Student participation was solicited and supported through a unique mix of paid positions, research credits, and volunteerism. Prior to the campaign, we offered a 1-credit directed studies course in spring 2022, where prospective undergraduate student participants were trained on the aerosol and radiosonde equipment, aerosol–cloud interactions, sea-breeze and convection forecasting, and our standard operating procedures. DOE ASR funds partially supported three graduate students and six part-time undergraduate students. Undergraduate employment and travel were also subsidized through TAMU College of Arts and Sciences (formerly Geosciences) High-Impact Learning Experience funds. Other undergraduates were incentivized to participate through a points-based system, where different TRACER-related activities described above accrued points toward undergraduate research credits, resulting in 1–4 research credits per student. Alternatively, many graduate students and some undergraduates participated entirely on a volunteer basis for experience.
3. Example deployment and data
The section below highlights an example of the TAMU TRACER dataset compared to AMF1 measurements for one of our primary missions targeting maritime and continental airmass heterogeneity across the sea-breeze front. On the morning of 8 August 2022, the synoptic environment was conducive to the development of a sea breeze in southeast Texas. A ridge pattern at the 500-hPa level led to midtropospheric convergence, resulting in high surface pressure over the southern CONUS. The southeasterly onshore flow associated with this high pressure system facilitated the advection of low-level moisture from the GOM over the TRACER domain, providing sufficient instability for deep convection initiation. The presence of weak synoptic-scale onshore winds, combined with the absence of shortwave disturbances (i.e., weak large-scale ascent), created ideal conditions for the development of a sea-breeze circulation. As the land–sea temperature gradient gradually strengthened throughout the afternoon, the sea breeze propagated inland.
The first TAMU radiosonde launch at 1724 UTC sampled the maritime air mass, as the sea-breeze front had already propagated ∼50 km inland from the coast (Fig. 1a). Based on the visible satellite imagery in Fig. 1a, the AMF1 radiosonde likely sampled a mixture of the GOM and Galveston Bay maritime air mass, while the sea breeze was still south of ANC where the continental air mass was sampled. The simultaneous sampling of the background environment from the three different sites revealed fine-scale spatial heterogeneity in the mesoscale environments of deep convection. In the first sounding (Fig. 4a), even though the TAMU and AMF1 sites were under the influence of a maritime air mass, the mixed-layer CAPE (MLCAPE) at AMF1 was much larger (2130 J kg−1) compared to the TAMU site (1781 J kg−1). This difference in instability can be primarily attributed to relatively large values of near-surface dewpoint temperature and a steeper lapse rate within the 850–500-hPa layer at the AMF1 site. These values were typical of early afternoon deployments, falling close to the median MLCAPE values of 1780 J kg−1 at the TAMU site and 2118 J kg−1 at AMF1 for the entire TAMU TRACER campaign. The ANC site (not shown) had a much deeper well-mixed layer (surface to 800 hPa), with little potential instability above the 700-hPa level, resulting in the least MLCAPE (1346 J kg−1), which was lower than the typical TAMU TRACER campaign median MLCAPE value (1817 J kg−1) at ANC in the early afternoon.
(a) 1800 UTC TAMU and AMF1 Skew T–logP comparison (launch time shown in panel); (b) CPC aerosol concentration and SWS temperature, dewpoint, and winds; (c) miniMPL backscatter; (d) TAMU and AMF1 SMPS aerosol size distributions; (e) TAMU and AMF1 CCN activated fraction; (f) INP freezing temperatures; (g) TAMU and AMF1 retrieved profile of aerosol and CCN concentration; and (h) retrieved TAMU INP concentration profile for early afternoon maritime deployment at Seawolf Park in Galveston, on 8 Aug 2022. Shading on (g) and (h) represent the uncertainty range due to the lidar inversion process and hygroscopic growth corrections. TAMU maritime is represented in blue with AMF1 maritime represented in magenta.
Citation: Bulletin of the American Meteorological Society 105, 9; 10.1175/BAMS-D-23-0218.1
The time series of ROAM-V aerosol concentrations (Fig. 4b) shows relatively large background aerosol concentrations for a maritime air mass, near 2000 cm−3 with intermittent spikes, which we attribute to ship exhaust from the nearby Houston Ship Channel. Surprisingly, the relatively “clean” maritime background air mass had unexpectedly large aerosol concentrations throughout the TRACER campaign. The fine-scale heterogeneity observed in the mesoscale thermodynamic environment shows an even greater contrast in aerosols. The bay-breeze maritime air mass at the AMF1 site, with nearby industry and refineries, showed notably larger aerosol concentrations shifted toward smaller sizes than those sampled in the sea-breeze maritime air mass (Fig. 4d). Both sites showed relatively small observed CCN activated fractions at greater supersaturations compared to laboratory activation fractions for 50-nm particles composed of ammonium sulfate (Fig. 4e, shown here for a supersaturation of 1%), a representative continental background aerosol. Overall, the case shown here is representative of typical aerosol measured during the early afternoon deployments, which had an average background concentration of 2500 cm−3 and an activation fraction of 0.4 at 1% supersaturation, while the AMF1 site observed higher concentrations and lower activation fractions. These site-to-site differences are likely due to differences in the size distributions and possibly in aerosol composition.
The TAMU miniMPL lidar collected a vertical profile of backscatter and depolarization by aerosols and cloud particles (Fig. 4c). Surface aerosol, CCN, and INP measurements and sounding profiles are used as inputs to a vertical profile retrieval that uses these lidar backscatter measurements. Micropulse lidar and radiosonde data are used to calculate the aerosol backscatter coefficient profile, which was adjusted for aerosol hygroscopic growth. This corrected profile was then used to linearly scale surface measurements of aerosol, CCN, and INP concentrations. The preliminary retrieval of aerosol, CCN, and INP concentration profiles are shown in Figs. 4g and 4h. A full description of these retrievals, their assumptions, and uncertainties will be described in another manuscript in preparation. These retrieved vertical profiles demonstrate the significant airmass heterogeneity between the sea- and bay-breeze air masses, with considerably lower aerosol and CCN concentrations over a shallower layer in the sea-breeze air mass at the TAMU site. They also highlight the significant differences between surface aerosol, CCN, and INP concentrations and those near cloud base. The LCL is just above 1 km, so at both sites, aerosol and CCN concentrations near cloud base are less than half of surface concentrations and INP concentrations near cloud base are 3–4 times smaller than the surface. This suggests that previous observational ACI studies only using surface-based aerosol concentrations may have significantly overestimated aerosols. These lidar-derived profile products represent a significant advance in our understanding of the vertical profiles of CCN and INP and can be used as input for real-case numerical simulations rather than some assumed profile based solely on surface aerosol number concentrations.
For the second, inland deployment on 8 August 2022, the TAMU team launched the radiosonde from Hempstead, Texas, at 2131 UTC. The sounding was launched earlier than the scheduled ARM site launch at 2200 UTC due to an approaching outflow boundary, which eventually arrived at Hempstead around 2208 UTC (Fig. 5b). This enabled the sampling of a continental air mass at Hempstead (TAMU site), while radiosondes from both ARM sites sampled a maritime air mass at 2200 UTC. As a result, the TAMU observations provide the only measurements of the undisturbed continental air mass for cells initiating along and ahead of the sea-breeze front at this time.
(a) 2200 UTC TAMU and AMF1 SkewT–logP comparison (launch time shown in panel); (b) CPC aerosol concentration and SWS temperature, dewpoint, and winds; (c) miniMPL backscatter; (d) TAMU and AMF1 SMPS aerosol size distributions; (e) TAMU and AMF1 CCN activated fraction; (f) INP freezing temperatures; (g) TAMU and AMF1 retrieved profile of aerosol and CCN concentration; and (h) retrieved TAMU INP concentration profile for afternoon continental deployment at City Park in Hempstead, on 8 Aug 2022. Shading on (g) and (h) represent the uncertainty range on the retrieved profiles due to the lidar inversion process and hygroscopic growth corrections. TAMU is shown in orange to represent the continental airmass sampling in the late afternoon with AMF1 maritime sampling still represented in magenta.
Citation: Bulletin of the American Meteorological Society 105, 9; 10.1175/BAMS-D-23-0218.1
Considerable mesoscale heterogeneity in CAPE persisted during the second (late afternoon) deployment (Fig. 5a). The continental air mass at the inland TAMU site exhibited a deep and well-mixed planetary boundary layer (PBL), albeit with a lower RH compared to the ARM sites (TAMU = 44%, AMF1/ANC > 60%). The well-mixed and moist PBL at the ANC site (not shown) significantly contributed to the MLCAPE value of 1719 J kg−1, which was the largest among the three sites. The reduced MLCAPE at the other two sites (TAMU = 1192 J kg−1 and AMF1 = 1438 J kg−1) was due to the low water vapor mixing ratio within the lowest 150-hPa layer, as well as smaller lapse rates throughout the midtroposphere to upper troposphere. These MLCAPE values for the three sites fall very close to the median-observed MLCAPE (1170 J kg−1 at TAMU, 1415 J kg−1 at AMF1, and 1628 J kg−1 at ANC) for all TAMU TRACER late afternoon deployments.
As expected, the time series of ROAM-V continental aerosols (Fig. 5b) showed higher concentrations than the background concentrations for the maritime air mass. There is also evidence of an enhancement in aerosols as an outflow boundary (evident in the SWS temperature and humidity measurements) overtakes the site just after 2205 UTC. Again, the mesoscale heterogeneity in aerosols and CCN accompanying the different air masses is showcased in the AMF1 and TAMU size distributions (Fig. 5d), activated fractions (Fig. 5e), and retrieved profiles (Figs. 5g,h). The AMF1 site, which was overtaken by the bay breeze and sea breeze and was also likely under the influence of earlier convection outflow boundaries, showed much lower concentrations, smaller sizes, and lower activated fractions compared to TAMU’s observations of the continental air mass likely influencing many of the cells shown in Fig. 1b. The case shown here is a representative of the TAMU late afternoon deployments with higher average concentrations, around 6000 cm−3, and greater average CCN activation fractions, near 0.5, at 1% supersaturation when compared to the average maritime air mass. The retrieved vertical profiles also show important structural differences in the aerosol and CCN profiles, with the TAMU continental aerosol measurements showing a deep layer of increased aerosol and CCN concentrations extending nearly 2-km deeper than the AMF1 profiles. They again show significant differences in aerosols, CCN, and INP concentrations between the surface and cloud base that may be important for determining the impacts of ACI.
4. Planned analysis and science opportunities
The example cases shown here highlight some of the unique measurements collected by the TAMU TRACER team: collocated mobile meteorology and aerosol sampling, CCN and INP cloud-forming properties, and retrievals of vertical profiles of CCN and INP concentrations in environments serving as the inflow region for convection. They also demonstrate the large spatial and temporal heterogeneity in the meteorological and aerosol environments across the Houston, Texas, region during the TRACER field campaign and the complementary dataset to the DOE-fixed ARM site measurements collected by TAMU. From this case and others sampled during TRACER, it is clear that a single, fixed site cannot account for the heterogeneity of conditions experienced by convection in this region and that the environmental differences in the air mass serving as the inflow region for convection must be accounted for to have any hope of using observations to understand and disentangle the effects of aerosols and meteorology on deep convection.
Ultimately, we hope to use the TAMU measurements to quantify the ability of the complex aerosol populations in the Houston area to form CCN and INP (Thompson et al. 2023) and compare with ARM observations, use these observations to better constrain vertical CCN and INP profiles (Chen et al. 2024), and understand how meteorology and aerosol populations relate to observed changes in convection characteristics (Sharma et al. 2024). We also plan to use the measured meteorological environment and retrieved CCN and INP profiles as input for idealized numerical simulations to help disentangle meteorological effects from aerosol effects on deep convection updraft and precipitation characteristics. We envision a number of research questions that could be addressed by the TAMU TRACER dataset including the following:
What is the horizontal, vertical, and temporal variability of temperature, moisture, winds, and aerosols (specifically potential CCN and INP) in the Houston region, particularly relative to sea/bay-breeze fronts and outflow boundaries?
How do the cloud-forming properties of CCN and INP vary with the different mesoscale air masses observed during TRACER? How does cloud processing impact CCN and INP properties measured in convective outflow?
How do updraft and precipitation characteristics vary with aerosols and meteorological environments across the sea/bay-breeze fronts?
Do vertical distributions of CCN and INPs vary within the inflow layer of convection in different air masses in the Houston region? If so, might aerosol–cloud interactions influence deep convective updraft and precipitation characteristics? Do ACI results differ when assuming surface versus cloud base aerosol concentrations?
Does entrainment of aerosols above the storm inflow layer influence the thermodynamic properties, aerosol concentrations, and microphysical properties of deep convective updrafts?
What are the separate influences of meteorological conditions and aerosols in determining updraft characteristics and precipitation processes in deep convection?
In addition to the aforementioned questions on airmass heterogeneity across the sea-breeze front and its influence on the properties of convection, the time series data in the examples shown here also highlight additional science opportunities for understanding the evolution of boundary layer thermodynamics and aerosol populations. During TAMU TRACER, we sampled the passage of the sea-breeze front, numerous outflow boundaries, anvil shading influences, and airmass recovery from prior convection. Thus, our data may be useful to future investigators in answering a host of science questions beyond those posed above. All TAMU TRACER data are freely available at the DOE ARM Data Discovery.
Acknowledgments.
This project is funded by Department of Energy Atmospheric System Research (ASR) program Grant DE-SC0021047 and supported by ARM field campaigns AFC07023 and AFC07055. Some undergraduate participants were also supported by Texas A&M University College of Arts and Sciences (formerly Geosciences) High-Impact Learning Experience grant. Special thanks to Dr. Don Conlee and TAMU students C. Hood, P. Langford, S. Lewis, C. Perez, B. Tomerlin, J. Treviño, B. Musall, M. Mancilla, K. Nunez, T. Borgstedte, K. Griese, T. Peña, S. Alegrias, L. Mata-Rodriguez, R. Lane, B. Kropp, S. Gardner, J. Ribail, J. Hale, S. Butler, K. Lange, J. Lewis, A. Sebok, D. Leathe, S. Jorgensen, B. Smith, J. Spotts, and D. Topping for assisting with TAMU TRACER and broader DOE TRACER forecasting, nowcasting, deployments, and instrumentation. We also appreciate I.T. Holleman Elementary School and Buc-ee’s #18 in Waller, Texas, for allowing use of their facilities for several multihour deployments.
Data availability statement.
TAMU TRACER data are available for download from the ARM Data Center through Data Discovery at https://doi.org/10.5439/1968819 (radiosonde), https://doi.org/10.5439/1972461 (MPL), https://doi.org/10.5439/1971998 (CPC), https://doi.org/10.5439/1972181 (SMPS), and https://doi.org/10.5439/1972179 (CCN counter). ARM AMF1 data are available to download from the ARM Data Center through Data Discovery at https://doi.org/10.5439/1595321 (radiosonde), https://doi.org/10.5439/1320657 (MPL), https://doi.org/10.5439/1228061 (CPC), https://doi.org/10.5439/1476898 (SMPS), https://doi.org/10.5439/1323892, and https://doi.org/10.5439/1323896 (CCN counter). KHGX level-II data can be downloaded from the National Centers for Environmental Information (NCEI) NEXRAD data inventory [NOAA National Weather Service (NWS) Radar Operations Center 1991] at https://doi.org/10.7289/V5W9574V.
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