Abstract
This paper discusses results of the CLOUD-MAP (Collaboration Leading Operational UAS Development for Meteorology and Atmospheric Physics) project dedicated to developing, fielding, and evaluating integrated small unmanned aircraft systems (sUAS) for enhanced atmospheric physics measurements. The project team includes atmospheric scientists, meteorologists, engineers, computer scientists, geographers, and chemists necessary to evaluate the needs and develop the advanced sensing and imaging, robust autonomous navigation, enhanced data communication, and data management capabilities required to use sUAS in atmospheric physics. Annual integrated evaluation of the systems in coordinated field tests are being used to validate sensor performance while integrated into various sUAS platforms. This paper focuses on aspects related to atmospheric sampling of thermodynamic parameters with sUAS, specifically sensor integration and calibration/validation, particularly as it relates to boundary layer profiling. Validation of sensor output is performed by comparing measurements with known values, including instrumented towers, radiosondes, and other validated sUAS platforms. Experiments to determine the impact of sensor location and vehicle operation have been performed, with sensor aspiration a major factor. Measurements are robust provided that instrument packages are properly mounted in locations that provide adequate air flow and proper solar shielding.
Highlights
The availability of high-quality atmospheric measurements over extended spatial and temporal domains provides unquestionable value to meteorological studies
Once data are available from unmanned aircraft systems (UAS) deployments, these data will be assimilated into numerical weather prediction (NWP) models along with all other available weather data to determine the extent of improvement to the model forecasts and the longevity of the impact with a focus on high impact weather events depending on the season and location
As part of our efforts to establish guidance for the system capabilities required to maximize the impact of UAS on modeling efforts, we developed a simple experiment for execution during the summer 2017 CLOUD-MAP field deployment in Oklahoma
Summary
The availability of high-quality atmospheric measurements over extended spatial and temporal domains provides unquestionable value to meteorological studies. Four specific objectives are being addressed in CLOUD-MAP related to program governance, atmospheric measurement and sensing, unmanned systems development and operations, and public policy They are listed as (1) Develop a strong mentoring program and intellectual center of gravity in the area of UAS for weather, and develop joint efforts for future funding; (2) Create and demonstrate UAS capabilities needed to support UAS operating in conditions that may be present in atmospheric sensing , including the sensing, planning, asset management, learning, control and communications technologies; (3) Develop and demonstrate coordinated control and collaboration between autonomous air vehicles; and (4) Conduct UAS-themed outreach in support of NSF’s technology education and workforce development. This paper focuses on aspects related to atmospheric sampling of thermodynamic parameters with sUAS, boundary layer profiling, sensor integration and calibration/validation
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