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Completed TRL 3 (started at 2, targeting 3)
This effort builds on previous efforts to assess the suitability of commercial-off-the-shelf (COTS) lidars designed for the automotive industry and entry-descent-landing (EDL) altimeters for spaceborne landing applications for atmospheric science. The COTS lidar industry is developing at a rapid pace for leading companies that sell compact, low-cost lidars that use various wavelengths (850, 905, 1550 nm), timing techniques, and methods to direct laser beams in different directions. Through previously funded GSFC IRAD efforts, signal denoising and machine learning (ML) techniques have been applied to single wavelength (e.g 1064 nm) data from the Cloud-Aerosol Transport System (CATS) and have shown encouraging results for feature detection at finer resolutions compared to traditional methods, notably during noisy daytime conditions. These denoising and ML methods will be applied to small single wavelength COTS lidars flying on UAVs as part of this effort.
UAV implementation of lidars allows for targeted sampling of aerosol, cloud, and PBL processes that can be readily implemented as an affordable network to improve both spatial and temporal coverage. Unlike satellite and airborne implementations, UAVs enable sustained measurements of the time evolution of aerosol-cloud-PBL interactions, processes poorly represented in current global models.
This concept is highly relevant to the anticipated future NASA PBL Decadal Survey mission (currently a 2017 Decadal Survey Incubator study), as a network of affordable lidars would be a desirable complement to spaceborne sensors in targeted regions (e.g. fires in the US Pacific Northwest).
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