Breakout Summary Report

The goal of this panel discussion session is to facilitate two-way discussion between the ARM translators and data analysts, the ASR science team, and other ARM data users. The session will begin with a representative from the ARM translators and data analysts providing short updates on current major activities and their plans for developing new and data products that they expect will become available to the scientific community. After these updates, representatives from the aerosol measurement science group (AMSG), cloud processes measurement science group (CPMSG), and the User Executive Committee will share perspectives on data needs from their respective groups. The translators and analysts are particularly interested in hearing from the science community regarding new data product needs and limitations or challenges encountered in using ARM data. Additional topics that the translators are interested in hearing feedback on include: tools and open source code developments for enabling access to and analysis of ARM data, strategies for addressing uncertainty in ARM data products, and open access to the code used to generate data products. The majority of the time will be dedicated to discussion.

This session is aimed at ensuring that the development of ARM data products is aligned with ASR and ARM data user scientific needs.

Most of the discussion revolved around community needs. It was readily apparent that different research communities have very different needs. In some cases, the data needs from one community were entirely the opposite of the feedback from another research community.

Much of the common discussion revolved around difficulty users are having in finding the data they need on the ARM website. Users report that they are overwhelmed by the number of datasets and VAPs that they are presented with by Data Discovery. This is most challenging for non-expert users, who aren’t aware of the subtle differences between data levels and VAPS. The community would like the best datasets be more readily identified on Data Discovery. To this end, they would like to have some reasoning made public pertaining to why certain datasets are preferred over others. It was clear that many users are not familiar with the “preferred dataset” radial button and even fewer are aware that explanatory text is available if they click on the datasets. Users were supportive of the idea of bundled datasets so that they don’t need to pick the “best” datastream themselves. They also were supportive of the idea of having ‘cheat sheets’ curated by mentors for a particular science subject area (i.e., “aerosol cheat sheet”) that would provide the best datastream for a particular scientific variable.

Feedback from the survey conducted by the UEC subcommittee on model outreach highlights the need for high-quality, long-term, and continuous measurements of key variables related to aerosols and clouds. Specifically, variables such as NDROP, INP, vertical profiling of aerosols and clouds, gas-phase aerosol precursors, and ACI-related parameters are identified as priorities. There is also a strong demand for clear specification of data quality and uncertainty. It is recommended that ARM continues to enhance the alignment of future campaigns with modeling needs by involving modelers early in the planning stages of field campaigns. Additionally, funding joint projects could strengthen connections between observationalists and modelers. The use of OSSEs could provide valuable guidance for shaping future ARM field campaigns. One significant current challenge identified by the survey is the integration frameworks for model and data.

Feedback from the AMSG highlighted the need for measurements of volatile organic compound (VOC), particularly during IOPs, expansion of black carbon aerosol measurements, and continued support for coarse mode aerosol. The AMSG recommended focusing ice nucleation measurements on campaigns/regimes where mixed phase clouds are prevalent to increase use of INP data. The AMSG also expressed a need for vertical distributions of aerosol properties including size distributions from lidar retrievals and CCN number concentrations at cloud base. The AMSG also emphasized the need for continuing HTDMA measurements because they provide information about size dependent chemical composition and recommended revising the scanned diameters to smaller sizes. Finally, the AMSG supported the idea of networks of low-cost sensors to improve measurement spatial coverage as is being done at the BNF and SGP sites. 

The CPMSG provided a set of recommendations focusing on both mature and urgent areas with actionable steps to advance retrieval methods and data products. Emphasis was placed on improving the calibration of measurements to ensure significant progress, intercomparisons of retrieval methods, and the adoption of well-established techniques like the O’Connor method for drizzle retrievals. Regular reassessment of data products, suggested every five years, was advised to maintain their reliability. The use of machine learning for surface precipitation and the development of retrievals for blowing snow, potentially supported by new lidar systems with depolarization capabilities, were highlighted. For ice-containing clouds, physically-based retrievals were recommended, along with the application of Bayesian inference techniques to better quantify product uncertainties. Retrieval bundles should explicitly incorporate uncertainty estimates, while hackathons and focused small-group collaborations were suggested to enhance two-way communication and problem-solving. Additional recommendations included the calibration of vertical air motion measurements at regular intervals, refinement of hydrometeor identification algorithms, and comprehensive error propagation assessments. The integration of SOM regimes and LASSO bundles for case selections, along with improved handling of disdrometer discrepancies, were also encouraged to achieve more consistent and robust retrievals. Finally, clear communication with data users, consideration of instrument uncertainties, and awareness of retrieval assumptions were stressed as essential for delivering actionable and reliable products.

• The main challenge users expressed was finding the data they need on data discovery.

• Users would like to see more text describing why certain datasets are better than others.

• Different User communities have very different, sometimes contradictory needs.

• The AMSG predominantly identified their need for additional measurements of VOCs, black carbon, vertically resolved aerosol and continued support for low cost sensors.

• The UEC modeling committee emphasized continued high quality measurements over a longer time period at the super sites and suggested focusing on NDROP, INP, vertical profiling of aerosols and clouds, gas-phase aerosol precursors, and ACI-related parameters.

• UEC modeling community also suggested involving modelers in field campaign planning at an early stage.

• The CPMSG emphasized the need for improving retrievals and calibrations of lidar and radar products and intercomparison of these retrievals. Particular needs included retrieval of drizzle, surface precipitation, blowing snow, vertical velocity, and hydrometeor identification.

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There was a request that VAP code be made available to the research community. The translators will discuss whether this is practical and the ramification of making VAP code open.