No abstract

Unmanned aerial systems (UAS) can advance understanding of the atmosphere and improve weather prediction, but public perceptions of drone technologies need to be assessed to ensure successful societal integration. Our qualitative study examines public perceptions of UAS technology, and the associated risks and benefits, for such civilian purposes. We examine how people form perceptions, and discuss the implications of these perceptions for UAS design and regulation. Our study finds the public to be favorable toward UAS used for "noble" purposes. Participant views are informed by popular media, personal experiences, comparisons between technologies, and consideration of the trustworthiness of the users, regulators, and technology itself.

The integration of unmanned aircraft systems (UAS) into the weather surveillance network must be guided by the data needs of the principal stakeholders. This work aims to assess data needs/gaps for short-term forecasts (<1-day lead time) issued by the National Weather Service (NWS) and then identify UAS characteristics required to fill these gaps. Results from focus groups and interviews of forecasters in the central United States are presented. Participant verbal responses were coded and then categorized into a set of 25 unique features. Each feature was classified according to four characteristics: 1) environmental properties that need to be measured to represent a given feature, 2) flight type (vertical profile, horizontal transect, and/or survey) 3) flight height required to measure the environmental properties, and 4) relevance of feature to the forecasting of deep convection. Findings indicate the majority of identified features require measurement of typical state variables (temperature, moisture, and wind), but more than a third require visual imagery. Almost all of the features require either survey flight operations or vertical profiles. Additionally, 96% of the features require observations collected below 1000 m. Nearly two-thirds of the features are associated with deep convection. This work represents the first step towards establishing how UAS could be used to fill data gaps that exist for short-term forecasts issued by the NWS. The results stand alone in demonstrating the potential applications of UAS from the perspective of operational forecasters and have also informed ongoing efforts to develop a nationwide survey of forecasters.

Inclusion of unmanned aircraft systems (UAS) into the weather surveillance network has the potential to improve short-term (< 1 day) weather forecasts through direct integration of UAS-collected data into the forecast process and assimilation into numerical weather prediction models. However, one of the primary means by which the value of any new sensing platform can be assessed is through consultation with principal stakeholders. National Weather Service (NWS) forecasters are principal stakeholders responsible for the issuance of short-term forecasts. The purpose of the work presented here is to use results from a survey of 630 NWS forecasters to assess critical data gaps that impact short-term forecast accuracy, and explore the potential role of UAS in filling these gaps.NWS forecasters view winter precipitation, icing, flood, lake-effect/enhanced snow, turbulence, and waves as the phenomena principally impacted by data gaps. Of the ten high-priority weather-related characteristics that need to be observed to fill critical data gaps, seven are either measures of precipitation or related to precipitation-producing phenomena. The three most important UAS capabilities/characteristics required for useful data for weather forecasting are real- or near-real-time data, the ability to integrate UAS data with additional data gathered by other systems, and UASs equipped with cameras to verify forecasts and monitor weather. Of the three operation modes offered for forecasters to consider, targeted surveillance is considered to be the most important compared to fixed site profiling or transects between fixed sites.