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1. 3MileBeach: A Tracer with Teeth

   https://doi.org/10.1145/3472883.3486986  

   Zhang, Jun; Ferydouni, Robert; Montana, Aldrin; Bittman, Daniel; Alvaro, Peter (November 2021, Proceedings of the ACM Symposium on Cloud Computing)

   We present 3MileBeach, a tracing and fault injection platform designed for microservice-based architectures. 3Mile-Beach interposes on the message serialization libraries that are ubiquitous in this environment, avoiding the application code instrumentation that tracing and fault injection infrastructures typically require. 3MileBeach provides message-level distributed tracing at less than 50% of the overhead of the state-of-the-art tracing frameworks, and fault injection that allows higher precision experiments than existing solutions. We measure the overhead of 3MileBeach as a tracer and its efficacy as a fault injector. We qualitatively measure its promise as a platform for tuning and debugging by sharing concrete use cases in the context of bottleneck identification, performance tuning, and bug finding. Finally, we use 3MileBeach to perform a novel type of fault injection - Temporal Fault Injection (TFI), which more precisely controls individual inter-service message flow with temporal prerequisites, and makes it possible to catch an entirely new class of fault tolerance bugs. 

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2. TIPT: The Tracer Injection Planning Tool

   https://doi.org/10.1016/j.envsoft.2022.105504  

   González-Pinzón, Ricardo; Dorley, Jancoba; Singley, Joel; Singha, Kamini; Gooseff, Michael; Covino, Tim (October 2022, Environmental Modelling & Software)
3. A multi-tracer model approach to estimate reef water residence times: A multi-tracer residence time model

   https://doi.org/10.4319/lom.2012.10.1078  

   Venti, A.; Kadko, D.; Andersson, A. J.; Langdon, C.; Bates, N. R. (December 2012, Limnology and Oceanography: Methods)
4. CSAPR2 cell-tracking data collected during TRACER

   https://doi.org/10.5439/1969992  

   Oue, Mariko; Puigdoménech-Treserras, Bernat; Luke, Edward; Kollias, Pavlos (January 2023, Atmospheric Radiation Measurement (ARM) Archive, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US); ARM Data Center, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States))

   One of the challenges of analyzing convective cell properties is quick evolution of the individual convective cells.  While the operational radar data provide great a data set to analyze the evolution of radar observables of convective precipitation clouds statistically, previous studies also suggested that, because of the quick evolution of cell life cycle, conventional radar volume scan strategies taking ~5-7 minutes might not capture the detailed evolution. The TRACER campaign deployed CSAPR2, which performed frequent update of RHI and sector PPI scans to track convective cells every < 2 minutes guided by a new cell-tracking framework, Multisensor Agile Adaptive Sampling (MAAS; Kollias et al. 2020). This allows for capturing fast-evolving radar observables. The submitted data files are CSAPR2 data in CfRadial format collected during the TRACER field campaign from June to September 2020. The data files include processed radar variables including: noise-masked reflectivity and differential reflectivity corrected for rain attenuation and systematic biases, noise-masked dealiased radial velocity, specific differential phase, locations of target cells (latitude, longitude, radar range), and radar-echo classification.   

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5. Evaluating Stratospheric Tropical Width Using Tracer Concentrations

   https://doi.org/10.1029/2020JD033081  

   Shah, Kasturi S.; Solomon, Susan; Thompson, David W. J.; Kinnison, Douglas E. (October 2020, Journal of Geophysical Research: Atmospheres)

   Abstract Quantifying the width of the tropics has important implications for understanding climate variability and the atmospheric response to anthropogenic forcing. Considerable effort has been placed on quantifying the width of the tropics at tropospheric levels, but substantially less effort has been placed on quantifying the width at stratospheric levels. Here we probe tropical width in the stratosphere using chemical tracers, which are accessible by direct measurement. Two new tracer‐based width metrics are developed, denoted here as the “1σ method” and the gradient weighted latitude (GWL) method. We evaluate widths from three tracers, CH₄, N₂O, and SF₆. We demonstrate that unlike previously proposed stratospheric width methods using tracers, these metrics perform consistently throughout the depth of the stratosphere, at all times of year and on coarse temporal data. The GWL tracer‐based widths correlate well with the turnaround latitude and the critical level, where wave dissipation occurs, in the upper and midstratosphere during certain months of the year. In the lower stratosphere, the deseasonalized tracer‐based widths near the tropical tropopause correlate with the deseasonalized tropopause‐height based metrics. We also find that tracer‐tracer width correlations are strongest at pressure levels where their chemical lifetimes are similar. These metrics represent another useful way to estimate stratospheric tropical width and explore any changes under anthropogenic forcing. 

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