Breakout Summary Report

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This year, our discussion centered around three key aspects of deep convective clouds:

1. The role of entrainment, detrainment, and dilution.

2. Environmental controls on convective organization.

3. The characteristics of updrafts.

These topics were selected based on abstract submissions, as they emerged as the most prominent themes. To provide a comprehensive perspective, we invited three speakers who addressed these topics from both observational and modeling standpoints. This broader approach encouraged the community to consider how ARM observations can be integrated with modeling efforts to advance our understanding of deep convective cloud processes. The discussion resonated strongly with the audience, who remained engaged throughout.

1. The Role of Entrainment, detrainment, and dilution

Entrainment, detrainment, and dilution remain long-standing and critical topics within the working group, as they play a key role in deep convective cloud initiation and evolution. Enoch Jo presented The Effect of Updraft Entrainment on Convective Cell Deepening in LASSO-CACTI Simulations. Their study employed multinomial logistic regression with four predictors to assess the factors influencing the transition from shallow to deep convection. The most significant predictor was found to be relative humidity at 600 hPa, followed by lower-cloud CAPE and updraft width. Fractional entrainment had the smallest impact overall.

This raised an important question: Should entrainment and updraft width be treated separately as predictors, given their strong correlation? Additional concerns were raised about potential biases in models—specifically, whether updrafts and entrainment are skewed toward certain conditions or regimes to favor the initiation of the convection.

A key challenge is the lack of direct entrainment measurements, compounded by varying definitions and retrieval methodologies. This highlights the need to evaluate modeled relationships against ARM observations and to explore novel techniques for deriving causal relationships between environmental factors and convective cloud processes.

2. Environmental Controls on Convective Organization

This topic is particularly timely, as ARM has conducted multiple field campaigns collecting extensive data on both isolated and organized convection in diverse environmental conditions. Kathleen Schiro presented A Multi-Platform Observational Approach to Studying Controls on the Organization and Upscale Growth of Mesoscale Deep Convection.

Her talk addressed a central question: Are mesoscale convective systems (MCSs) associated with higher column water vapor (CWV) and buoyancy compared to isolated deep convection (IDC)? Using ARM data from sites such as the Amazon, Manus, and Darwin, her team examined pre-convective environmental conditions and cross-referenced them with datasets like AIRS and ERA5 for robustness. They found that enhanced lower-tropospheric moisture precedes MCS development by several hours, a pattern consistent across datasets. Moreover, lower-tropospheric moisture levels are systematically higher ahead of MCSs than IDCs.

This study exemplifies the value of linking ARM data with other observational sources and reinforces the role of ARM in environmental sampling. The audience emphasized the need for more such observations and broader spatial coverage of environmental sampling, highlighting its importance for future research.

3. Updraft Velocity Retrievals

The retrieval of updraft velocity remains a high-priority need for the community, both to improve our understanding of convective dynamics and to provide constraints for model simulations. Mariko Oue presented Updraft Velocity Retrieved from TRACER Using Fast Scanning Radar, highlighting new datasets that allow for the analysis of rapid convective core evolution.

This dataset provides an opportunity to characterize updraft core structures—distinguishing between thermal and plume-like formations from an observational perspective. However, key questions emerged regarding how this dataset can be evaluated, how it compares with alternative retrieval methods (e.g., multi-Doppler retrievals and radar wind profilers), and its broader implications for model evaluation.

The discussion also touched on the practical aspects of data collection, including optimal scanning strategies for field campaigns, post-processing considerations, and the need for collaborative efforts to refine best practices for sampling updrafts. This session underscored the ongoing need for coordinated efforts between observationalists and modelers to maximize the utility of updraft velocity datasets.

This year’s discussion underscored key challenges and new insights in deep convective cloud research, with strong audience engagement reflecting a shared commitment to advancing observational and modeling methodologies and use these advances to improve process-level understanding of deep convection. Specific key findings include:

1. ARM observations and LASSO simulations play a crucial role in various aspects of deep convective cloud research, supporting both scientific discoveries and model improvements.

2. Further efforts are needed in updraft velocity retrievals, entrainment estimation, and environmental sampling to enable cross-comparisons and strengthen scientific discoveries.

3. Advancements in instrumentation, deployment strategies, and statistical methods are essential for addressing persistent challenges and uncovering new insights.

Moving forward, continued focus on observational strategies and model evaluation will be vital to tackling these open questions.

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Historically, our efforts have focused on convective dynamics and entrainment. This year, we have broadened the scope to include convective organization. In the future, we are planning on also incorporating microphysics and radiation to engage a wider audience and enhance the impact of ARM data. Additionally, we aim to highlight emerging technologies in both machine learning and instrumentation, paving the way for new and exciting discoveries.

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