Communicating weather-related hazards to the public can be a challenge for meteorologists, particularly given the nature of confidence levels in forecasting science. Despite these challenges, communicating high-impact weather remains extremely important because it has implications for the safety, health, and resilience of impacted communities. Because the dynamics of this issue are complex, solutions to weather hazard communication benefit from interdisciplinary solutions and multiple types of expertise. Our work demonstrates how rhetoric, a foundational communication discipline, can be applied to improving weather forecast communication. Applying a rhetorical framework allows the identification of communication strategies that not only invite public involvement but encourage users to act as conduits for weather information distribution. As a result, trust can be developed between the National Weather Service (NWS) and public audiences. The initial results support the hypothesis that effective public communication from NWS messaging can be improved by incorporating the concept of “commonplaces,” which are the expressions of beliefs, values, and norms that construct community attitudes toward weather or natural hazard forecasts, into visual communication techniques such as NWS Weather Stories.

Recent literature has highlighted how citizen science approaches can engage volunteers, expand scientific literacy, and accomplish targeted research objectives. However, there is limited information on how specific recruitment, retention, and engagement strategies enhance scientific outcomes. To help fill this important information gap, we detail the use of various approaches to engage citizen scientists in the collection of precipitation phase data (rain, snow, or mixed). In our study region, the Sierra Nevada and Central Basin and Range of California and Nevada near Lake Tahoe, a marked amount of annual precipitation falls near freezing. At these air temperatures, weather forecasts, land surface models, and satellites all have difficulty correctly predicting and observing precipitation phase, making visual observations the most accurate approach. From January to May 2020, citizen scientists submitted timestamped, geotagged observations of precipitation phase through the Citizen Science Tahoe mobile phone application. Our recruitment strategy included messaging to winter, weather, and outdoor enthusiasts combined with amplification through regional groups, which resulted in over 199 citizen scientists making 1,003 ground-based observations of rain, snow, and mixed precipitation. We enhanced engagement and retention by targeting specific storms in the region through text message alerts that also allowed for questions, clarifications, and training opportunities. We saw a high retention rate (88%) and a marked increase in the number of observations following alerts. For quality control of the data, we combined various meteorological datasets and compared to the citizen science observations. We found that 96.5% of submitted data passed our quality control protocol, which enabled us to evaluate rain-snow partitioning patterns. Snow was the dominant form of precipitation at air temperatures below and slightly above freezing, with both ecoregions expressing a 50% rain-snow air temperature threshold of 4.2°C, a warmer value than what would be incorporated into most land surface models. Thus, the use of a lower air temperature threshold in these areas would produce inaccuracies in event-based rain-snow proportions. Overall, our high retention rate, data quality, and rain-snow analysis were supported by the recruitment strategy, text message communication, and simplicity of the survey design. We suggest other citizen science projects may follow the approaches detailed herein to achieve their scientific objectives.

No abstract

Sampling the aquatic environment for microplastic concentration is inherently difficult because of variations in microplastic concentration, shape, and density and the potential for contamination. We present an assessment of a method for microplastic sampling that uses a peristaltic pump to pump water through a series of in-line stainless-steel mesh filters. Following filtration, the stainless-steel filters were treated using previously published methods to isolate microplastics, adjusted for the stainless-steel mesh filters. Microplastics were identified using micro-Fourier transform infrared (μFTIR) spectroscopy in transmission mode. This method was tested in the laboratory using standard polyethylene beads and was applied to two sample sites at the Las Vegas Wash in Nevada. The results showed that 70% of the polyethylene beads were recovered after the peristaltic pump and laboratory steps with minimal blank contamination. The advantages of the peristaltic pump sampling method are it (1) supports a range of sample volumes, (2) reduces sample handling, (3) reduces the potential for contamination, (4) provides flexibility in sampling locations, and (5) supports a variety of filter types. Using stainless-steel mesh filters allows for (1) streamlined and direct field-to-laboratory sample processing, (2) μFTIR transmission mode analysis of filter-mounted microplastics, and (3) reduced filter and sample processing costs.