NWS Data Needs for Short-term Forecasts and the Role of Unmanned Aircraft in Filling the Gap

Unmanned aircraft systems (UAS) are non-traditional measurement platforms that have the potential to revolutionize the terrestrial meteorological surveillance network.  The assimilation of data collected by UAS into numerical weather prediction models could improve the accuracy of model predicted atmospheric phenomena/processes across multiple scales.  UAS data could also be directly integrated into the data stream available to forecasters.  For terrestrial atmospheric phenomena, it is likely that the greatest impact of these data will be on short-term (< 1 day) forecasts/nowcasts including warning and advisory issuance.  However, assessing the potential value of this new technology for operational short-term forecasts must begin with an evaluation of the data needs of forecasters. 

Supported through the NSF-funded CLOUD-MAP (Collaboration Leading Operational UAS Development for Meteorology and Atmospheric Physics) project, the authors are undertaking a survey of NWS employees, initially via focus groups, to identify their data needs for short-term forecasts.  Forecasters are first asked to identify the challenges of short-term (1 day) forecasts, warm season advisories, and cold season advisories.  They are then asked to consider the new data that would be needed to address these challenges and the dissemination (e.g., fidelity, latency) and visualization requirements of these data.  Finally, they are asked to consider how UAS might be used to meet their data needs.  Results from analysis of these data will be presented at the conference along with ways in which these results inform technology development and regulation that advance the readiness level of this technology.