Global Orbital Research with a Diurnal Observing Network (GORDON): Towards realizing the potential of affordable spaceborne lidar (GORDON)

Objectives and benefits Spaceborne backscatter lidar pointing in a single nadir direction has proven extremely useful for providing vertically-resolved profiles of cloud and aerosol structure but is limited in utility and to-date has proven expensive. Extending a single lidar sensor to provide cross-track coverage requires either an expensive scanning telescope or extremely high laser power. An alternate approach, especially well-suited to studies of diurnal evolution of aerosols, clouds, and the Planetary Boundary Layer (PBL), is to launch a series of small, inexpensive lidar sensors that fly in formation providing enhanced spatiotemporal sampling while providing near-real time data products for use in aerosol and air quality forecasts. Pursuing innovative observational strategies such as a distributed constellation of minisats, means the sensors must be affordable and easily replicated but does not necessarily mean they have to be long-lived. In fact, the concept of shorter-lived, low-cost packages that can be routinely launched on low-cost commercial access-to-space opportunities permits a continuous replenishment of constellation-based remote sensing capability. This concept of lower-cost but continuously replaceable on-orbit assets is particularly relevant with today's budget realities and increasingly commercialized approaches to Earth Science measurements. The pathway to smaller, more affordable lidar sensors is, we believe, tied to use of advanced processing algorithms that can more effectively identify signal embedded in noise thereby reducing the power-aperture product without compromising performance. We will push the limits of instrument design by invoking advanced information processing techniques (i.e., machine learning algorithms) to extract information from noisier data and thereby enable needed science measurements with smaller-sized/lower cost sensors. Advanced processing is also commensurate with future need to provide real time data products that can be quickly assimilated into predictive models (for air quality and human health) and for generating real-time data products for decision making (such as hazardous plume detection and monitoring). Outline of proposed work and methodology We propose to demonstrate a novel backscatter lidar that can scale to space to provide a low-cost yet scientifically desirable solution for diurnal profiling of aerosols, clouds, and the PBL. Based on a fiber laser transmitter, and packaged in the smallest possible volume, the goal is to provide a space-scalable solution that shatters the cost barrier common to current lidar design concepts. In addition, to extend the science capability we will combine the lidar with an inexpensive polarized camera. The combined active+passive sensing will permit development of data products that, along with a distributed architecture of such sensors, will provide needed and affordable measurement capability for aerosol, cloud, and PBL studies. Our work will use airborne operation of a prototype sensor package to demonstrate advanced algorithms, applied to the GORDON instrument design, to quantify the attainable improvement in performance (or, alternately, to quantify the corresponding reduction in power-aperture product, a major design driver of cost). An important, and very intentional, aspect of our methodology is to involve students in all aspects of the research. Engaging students in hardware development is the best way to actively encourage a next generation of instrument-oriented researchers and develop a pipeline of instrument capable scientists and engineers. Period of performance The GORDON development effort will span a 36-month schedule for design, fabricate, test, and delivery. Entry and planned exit TRL The GORDON entry TRL is 3 with a planned exit TRL of 6 (instrument has conducted airborne engineering demonstration flights and data analyzed to verify performance predictions and scaling to space).

Increase scientific understanding of natural phenomena using remote sensing.

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