Angela K. Rowe

Prior studies have linked increased environmental moisture to larger tropical oceanic mesoscale convective systems (MCSs) and higher rainfall rates, with conditional dependence on vertical wind shear and mixed results across studies. A challenge in comparing these observations across studies and regions is the use of different datasets (i.e., satellite, reanalysis, and models), with limited in situ observations over tropical oceans, and differing definitions of MCSs, moisture, and wind shear. To address data sparsity in the East Atlantic, NASA’s Convective Processes Experiment-Cabo Verde (CPEX-CV) conducted multiple Research flights (RFs) in 2022 using modern remote sensing and dropsonde instrumentation to sample a variety of oceanic MCSs and their environments. This study uses high-resolution CPEX-CV airborne observations to examine the interaction between near-storm moisture, vertical shear, and oceanic MCS characteristics in the East Atlantic, and evaluates the sensitivity of these relationships to dataset. Using an MCS tracker with geostationary satellite data as a storm-relative framework, we compared moisture-shear-convection relationships between remote sensors, dropsondes, and reanalysis for RFs 7 and 11. Most datasets showed a long-lived MCS growing in a moister mid-level and lower deep-layer shear environment than a short-lived, less intense storm. However, moisture-convection relationships were less clear when using remote sensor data, owing to sampling biases that affected conclusions about the temporal evolution of both cases, as well as challenges in reanalysis representing observed convection. These findings suggest that using different datasets can yield different conclusions about MCS-environment relationships, with implications for tropical regions with limited data availability.

Deep tropical oceanic convection is a key component of the tropical atmosphere, with environmental moisture and vertical wind shear influencing its structure and intensity. However, attempts to generalize convection‐environment relationships across the broad‐scale tropics have produced inconsistent results, partly owing to limits of reanalysis, modeling, and satellite remote sensing, along with suggested regional variability that altogether behoove regionally targeted field campaigns. The NASA 2022 Convective Processes Experiment—Cabo Verde (CPEX‐CV) airborne field campaign collected rare, coincident, high‐resolution convective structure and near‐storm environmental measurements suitable to investigate convection‐environment relationships in the tropical East Atlantic. Analysis of collocated CPEX‐CV radar, LiDAR, and dropsonde observations, particularly in convective inflow regions, linked multi‐core convection to greater median deep layer wind shear and free‐tropospheric moisture, but lesser planetary boundary layer wind shear than single‐core convection among large near‐storm environmental variabilities that contributed to statistically insignificant differences. Regional comparisons with analogous data sets from two prior NASA CPEX campaigns in the tropical West Atlantic and the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP ² Ex) in the tropical Northwest Pacific revealed similar statistically insignificant links to near‐storm moisture but differing wind shear results, highlighting regional variability in convection‐environment relationships. The interregional analysis also revealed free‐tropospheric moisture to be less of a determining factor on convective type in strong‐sheared environments, and vice versa. CPEX‐CV convective intensity relationships with near‐storm moisture and wind shear were not definitive, likely owing to broader scale environmental influences that warrants future research using model simulations informed by field campaign data.

Deep tropical oceanic convection is a key component of the tropical atmosphere, with environmental moisture and vertical wind shear influencing its structure and intensity. However, attempts to generalize convection-environment relationships across the broad-scale tropics have produced inconsistent results, partly owing to limits of reanalysis, modeling, and satellite remote sensing, along with suggested regional variability that altogether behoove regionally targeted field campaigns. The NASA 2022 Convective Processes Experiment—Cabo Verde (CPEX-CV) airborne field campaign collected rare, coincident, high-resolution convective structure and near-storm environmental measurements suitable to investigate convection-environment relationships in the tropical East Atlantic. Analysis of collocated CPEX-CV radar, lidar, and dropsonde observations, particularly in convective inflow regions, linked multi-core convection to greater median deep layer wind shear and free-tropospheric moisture, but lesser planetary boundary layer wind shear than single-core convection amongst large near-storm environmental variabilities that contributed to statistically insignificant differences. Regional comparisons with analogous datasets from two prior NASA CPEX campaigns in the tropical West Atlantic and the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP ² Ex) in the tropical Northwest Pacific revealed similar statistically insignificant links to near-storm moisture but differing wind shear results, highlighting regional variability in convection-environment relationships. The interregional analysis also revealed free-tropospheric moisture to be less of a determining factor on convective type in strong-sheared environments, and vice versa. CPEX-CV convective intensity relationships with near-storm moisture and wind shear were not definitive, likely owing to broader scale environmental influences that warrants future research using model simulations informed by field campaign data.

Extreme rainfall is fundamentally driven by microphysical processes aloft, which can be strongly influenced by complex terrain. The 2022 Prediction of Rainfall Extremes Campaign in the Pacific (PRECIP 2022) provided a unique opportunity to study these relationships through the deployment of the NSF NCAR S‐band dual‐polarization radar (S‐Pol) in Taiwan, a region characterized by steep topography and frequent extreme precipitation. This study examines a Mei‐Yu front case characterized by widespread, long‐duration rainfall with embedded deep convective cells occurring both upstream and over Taiwan's topography. Our objective is to link microphysical processes to the varying terrain in context of rainfall during this high‐impact event. Microphysical characteristics are inferred from vertical gradients of dual‐polarization radar variables and modeled drop size distribution (DSD) moments, supported by ground‐based disdrometer observations that resolve both the drizzle and precipitation modes. A normalized double‐moment generalized gamma DSD model is applied to S‐Pol to obtain DSD moments that are linked to dominant microphysical processes aloft including radar‐inferred graupel presence. Results show that collision coalescence is the most frequent warm‐rain process in convection, contributing to large drop production and increased rainfall rates. Additionally, graupel presence is associated with precipitation enhancement, with the magnitude of graupel‐related amplification increasing with terrain height. This study highlights the benefit of modeling both the drizzle and precipitation modes of the DSD using dual‐polarization radars to connect microphysical processes aloft to complex terrain.

Extreme rainfall is fundamentally driven by microphysical processes aloft, which can be strongly influenced by complex terrain. The 2022 Prediction of Rainfall Extremes Campaign in the Pacific (PRECIP 2022) provided a unique opportunity to study these relationships through the deployment of the NSF NCAR S-band dual-polarization radar (S-Pol) in Taiwan, a region characterized by steep topography and frequent extreme precipitation. This study examines a Mei-Yu front case characterized by widespread, long-duration rainfall with embedded deep convective cells occurring both upstream and over Taiwan’s topography. Our objective is to link microphysical processes to the varying terrain in context of rainfall during this high-impact event. Microphysical characteristics are inferred from vertical gradients of dual-polarization radar variables and modeled drop size distribution (DSD) moments, supported by ground-based disdrometer observations that resolve both the drizzle and precipitation modes. A normalized double-moment generalized gamma DSD model is applied to S-Pol to obtain DSD moments that are linked to dominant microphysical processes aloft including radar-inferred graupel presence. Results show that collision coalescence is the most frequent warm rain process in convection, contributing to large drop production and increased rainfall rates. Additionally, graupel presence is associated with precipitation enhancement, with the magnitude of graupel-related amplification increasing with terrain height. This study highlights the benefit of modeling both the drizzle and precipitation modes of the DSD using dual-polarization radars to connect microphysical processes aloft to complex terrain.

This study uses a convection‐permitting model simulation to describe the environmental conditions under which convective upscale growth occurs in central Argentina, particularly examining environmental parameters when deep convection initially forms that could differentiate the rate of initial upscale growth. Simulated mesoscale convective systems (MCSs) are separated into slow and rapid growth by the rate of spatial growth from convection initiation until reaching the MCS scale. A low‐level jet (LLJ) is found more frequently near the deep convection that experiences rapid growth to an MCS, but its presence alone is not predictive of rapid growth. Using spatially‐averaged parameters, we find that rapid growth to MCSs also occurs in environments that are significantly more thermodynamically favorable with greater low‐level moisture and instability. Fewer significant differences are found in the kinematic environment with only the 0–2 km vertical wind shear magnitude being significantly larger for rapid growth MCSs compared to slow growth MCSs, potentially related to LLJs often peaking near this height. When focusing only on MCSs with the slowest and fastest growth rates, elevated‐layer shear is significantly smaller for very rapid growth MCSs, suggesting elevated‐layer shear may help discriminate between the upper and lower bounds of growth rate. Finally, when upscale growth occurs near the Sierras de Córdoba (SDC) with a LLJ present, rapid growth is also supported by favorable wind shear orientation. However, this does not hold for upscale growth occurring away from the SDC, highlighting the importance of interpreting shear direction relative to the orientation of features initiating deep convection.

Deep tropical oceanic convection (TOC) is a prevailing component of the tropical atmosphere. Given its frequent occurrence, understanding environmental controls on collective spatial organization of TOC has implications for TOC impacts on global and regional weather and climate. Isolating the influence of known environmental factors, such as vertical wind shear and moisture, require idealized modeling grounded in reality. Informed by high-resolution near-storm environmental observations from the NASA Convective Processes Experiment (CPEX) airborne field campaign series in the tropical North Atlantic, Cloud Model 1 idealized simulations of TOC were executed to investigate how local wind shear and moisture separately influence collective TOC spatial organization. Using sensitivity simulations, each with a different combination of three unique deep layer wind shear and lower free tropospheric moisture profiles, deep layer shear was found to consistently promote collective TOC spatial organization. Notably, convective spatial organization was more dependent on deep layer shear in environments with moderate lower free tropospheric moisture (e.g., 60-76% relative humidity), wherein convection self-aggregated perpendicular to the shear vector. When lower free tropospheric moisture was high (e.g., 90% relative humidity), it was the dominant control of TOC spatial organization over deep layer shear. Extending impacts to the vertical, stronger deep layer shear and a drier lower free troposphere were both found to promote more bottom-heavy convection. Deep layer shear was also consistently linked to less intense convection, likely through updraft deflection from convective tilting that also increased convective system areas, further highlighting the three-dimensional influence of shear on TOC.

Mesoscale convective systems (MCSs) associated with African easterly waves (AEWs) that propagate and intensify over the tropical East Atlantic may serve as precursors for tropical cyclones. Previous studies utilizing satellite‐ and reanalysis‐based data emphasized that deep convective growth over tropical oceans favors moister environments, particularly near the AEW trough. Unknowns remain in the relationship between near‐storm environmental parameters and convective lifecycle over the tropical East Atlantic. To address these knowledge gaps, NASA Convective Processes Experiment—Cabo Verde (CPEX‐CV), based out of Sal Island in September 2022, deployed an airborne precipitation radar, a Doppler wind lidar, a microwave sounding radiometer, and dropsondes in this region. This study assessed the relationship between moisture and deep convection growth and sustainability using a combination of this unique airborne data set and satellite‐derived products. More specifically, layer‐averaged relative humidity was analyzed for a growing deep convection system sampled with multiple passes during Research Flight 7. These aircraft observations, supplemented with a geostationary satellite‐based MCS tracker and reanalysis data, showed mid‐tropospheric moistening facilitating continued growth and maintenance of the convective system during and after the flight in association with an AEW. In comparison, Research Flight 11 sampled a convective system in a drier environment closer to the West African coastline that dissipated after the flight, underscoring the importance of mid‐tropospheric moisture for sustaining convective growth.

Dual-polarization radar is a valuable tool for quantifying rainfall, including in remote and mountainous regions, but subject to partial beam blockage and ground clutter. Recent studies have shown that the utilization of specific attenuation by a radar for rain-rate estimations R(A) can overcome partial beam blockage impacts by relying on radial profiles of differential phase shifts. This study applies this R(A) algorithm to the National Science Foundation (NSF) National Center for Atmospheric Research (NCAR) dual-polarization S-band (S-Pol) radar deployment in northwest Taiwan for the NSF-funded 2022 Prediction of Rainfall Extremes Campaign in the Pacific (PRECIP) dataset to provide reliable rain estimates, including over the mountains. While operating for nearly 3 months, S-Pol measured multiple heavy rainfall events including isolated convective cells and widespread stratiform precipitation, thus providing an ideal dataset for evaluating R(A) performance sensitivities to local terrain, clutter, ray segmentation, and rain type. The R(A) performance improved over the more commonly used NSF NCAR hybrid rain algorithm when applying to an extreme PRECIP event after several modifications to the R(A) algorithm. Over the entire campaign, R(A) overestimated low-intensity rainfall and was challenged in overall performance owing to remaining clutter. A new algorithm R(Synth), developed to merge R(A) into the hybrid algorithm when it was most optimal, led to improved performance in lower intensity rainfall when compared to R(A) alone. Significance Statement: Heavy rainfall is impactful globally, but difficult to accurately measure, especially in remote mountainous regions. Radar is useful for estimating rainfall, but encounters challenges in steep terrain owing to partial or total beam blockage. This study examines the advantages and disadvantages of applying a rain estimation technique based on radar attenuation, or loss of a signal by precipitation, to a 3-month radar deployment in mountainous Taiwan. This technique performed best in extreme rainfall scenarios, but not as well in lighter rainfall. Nearby terrain amplifies errors compared to other rain estimation methods, regardless of intensity. A unique aspect of this study is the development of a new rain-rate estimation technique, combining multiple retrievals to take advantage of their individual strengths.

Mesoscale bands develop within winter cyclones as concentrated regions of locally enhanced radar reflectivity, often corresponding to intensified precipitation rates lasting several hours. Surface precipitation characteristics are governed by the microphysical properties of the ice-phase particles aloft, yet their unique microphysical evolutionary pathways and ambient environmental dependencies in banded regions remain poorly understood, in part due to a paucity of observations within clouds. Addressing this need, the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms measured properties of winter cyclones from airborne in situ and remote sensing platforms. Observations collected within a banded region of a decaying-stage northeast United States cyclone revealed a microphysical pathway characterized by precipitation fallout from a weak generating cell layer through an ∼ 2 km deep subsaturated downdraft region. Sublimation was a dominant evolutionary process, resulting in a > 70 % reduction in the initial characteristic ice water content (IWC). This vertical evolution was reproduced by a one-dimensional (1D) particle-based model simulation constrained by observations, conveying accuracy in the process representation. Four sensitivity simulations assessed evolutionary dependencies based on observationally informed perturbations of the ambient relative humidity, RH, and vertical air motion, w. Perturbations of ∼ 2 % RH significantly varied the resultant characteristic IWC loss, by as much as 29 %, whereas comparable perturbations of w had negligible effects. Intrinsic particle evolution during sublimation demonstrated a notable imprint on vertical profiles of radar reflectivity, but the Doppler velocity was more strongly governed by the ambient w profile. These findings contextualize radar-based discrimination of sublimation from other ice-phase processes, including riming and aggregation.