14A.7 Observation System Simulation Experiment Studies (OSSEs) on the Use of Small Unmanned Aerial Systems (sUAS) for Boundary Layer Sampling

Thursday, 7 June 2018: 3:00 PM
Colorado A (Grand Hyatt Denver)
Andrew D. Moore, Univ. of Oklahoma, Norman, OK; and F. H. Carr, K. A. Brewster, and P. B. Chilson

A long-desired component to the U.S. operational observing systems is the capability to measure vertical profiles of wind, temperature and moisture in the lower troposphere at high spatial and temporal resolution. This study proposes that such profiling could be done by small unmanned aerial systems (sUAS) assuming that autonomous flights at least through the depth of the boundary layer be permitted by aviation authorities. Since we do not yet have FAA permission to test such an observing network at this time, we examine the potential improvement that a sUAS network could have on storm-scale numerical weather prediction using an Observation System Simulation Experiment (OSSE) approach.

We perform the OSSE over the state of Oklahoma where we assume that an sUAS could be launched from each of the 121 Oklahoma Mesonet stations every hour, fly vertically to an assigned height and return to its charging station, providing soundings at a 35 km horizontal resolution. We begin with a case study of convective initiation (CI) as a compromise between a fair weather day and one with extensive convection. The OU ARPS model provides a nature run at high (1 km) resolution, while the control run and OSSE experiments are done with the WRF model at 3 km. To simulate the effect of the dozens of observing systems used by operational centers, the nature run data volume is sampled frequently and inserted into the control run via a 6-hr data assimilation (DA) period. Simulated UAS temperature, moisture and wind profiles, with expected errors, are then added to the DA, followed by 12-hr forecasts. The analyses and forecasts are examined to assess the added value of sUAS data. Various experiments can be run with different UAS sampling frequencies and densities, as well as different maximum heights. Initial results clearly show an improved boundary layer structure and subsequent CI location and timing when simulated sUAS data are added to the control experiment.

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