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Marine Atmospheric Boundary Layer Profiles via Satellite-based Remote Sensing Data Fusion


OUSD (R&E) MODERNIZATION PRIORITY: Artificial Intelligence (AI)/Machine Learning (ML);Space


TECHNOLOGY AREA(S): Battlespace Environments;Information Systems


OBJECTIVE: Develop novel software algorithms to characterize vertical thermodynamic profiles in the lowest 2-3 km of the atmosphere, leveraging satellite-based environmental monitoring (SBEM) data that combines information from at least 2 of the following observing methods: optical, infrared, microwave, radio occultation.


DESCRIPTION: While characterization of the marine atmospheric boundary layer (MABL) environment is fundamental for Naval operations (e.g., directed energy, C4ISR, and communication applications), there is a lack of sufficient data in areas of interest to analyze and predict tactical scale environmental conditions. Current satellite data methods to measure MABL thermodynamics have limitations based on physical observing characteristics, such as horizontal resolution, vertical resolution, refractivity, or temporal refresh. With the proliferation of broader environmental data availability and smallsat platforms, there exists the potential to improve vertical profiles of temperature, water vapor, and/or refractivity in the boundary layer by combining data from two or more observed mediums. Innovation is sought to develop the theory, algorithm, and software to demonstrate, verify, and validate such a satellite data fusion technique. This development will result in valuable knowledge and technology advances beyond DoD specific applications for the entire meteorological analysis and forecasting community.


PHASE I: Determine and demonstrate the technical capability to leverage at least two different environmental satellite remote sensing observation types (including, but not exclusive to, optical channels, infrared channels, microwave imagers, microwave sounders, radio occultation, synthetic aperture radar, etc.) to add value to current single source atmospheric profiling techniques. Identify those factors that will contribute to enhanced understanding of the MABL compared to conventional methods using historical meteorological data from available defense, civil, research, international partner, and/or commercial data streams. Develop a final summary report, including literature review and overall conclusions/recommendations, to be presented at the end of this Phase. Develop a Phase II plan.


PHASE II: Expand technical development and validation of a robust prototype system for retrieval of MABL thermodynamics in a variety of maritime environments. Given feeds of meteorological satellite information, the algorithm should produce near-real time estimates of temperature, water vapor, refractivity at a higher spatial resolution than conventional satellite retrievals, on the order of 250 m vertical and 10 km horizontal. This prototype software should be capable of interoperating alongside conventional satellite algorithms in a similar computing environment, including both a stand-alone server for single algorithmic demonstration and high performance computing cluster for parallelization of near-real time satellite feeds. Demonstration during a government meteorological field event will be coordinated to provide additional verification and validation opportunities. Characterization of data quality and uncertainty will also be necessary to support potential for data assimilation into numerical modeling systems. It is anticipated that the prototype software will be expanded, or in a position to be expanded, to other satellite platforms and/or sensing methods at the conclusion of Phase II efforts, such demonstration/research sensors being demonstrated in near-realtime by NASA. Delivery of a prototype software package and final verification report is expected at the end of this Phase.


PHASE III DUAL USE APPLICATIONS: This development will result in valuable knowledge and technology advances for the entire meteorological analysis and forecasting community. Naval applications will immediately benefit from a significant increase in environmental data and prediction availability/quality where the Navy operates. Other civil and commercial applications will benefit from enhanced data streams for broad blue-water maritime applications, improved predictability in numerical weather prediction, and increased cross-over between civil and commercial satellite remote sensing activities. Specifically, environmental characterization and prediction efforts by NOAA will be improved by augmenting meteorological analysis and data assimilation with new observations. Commercial meteorological entities will be able to add value with targeted local enhancement to atmospheric characterization and forecasting by leveraging such data and techniques. This effort has the potential to fill a data gap in all aspects of meteorological analysis as well as provide a proof of concept for additional data fusion opportunities.




  1. Healy, S.B. and Eyre, J.R. “Retrieving temperature, water vapour and surface pressure information from refractive-index profiles derived by radio occultation: A simulation study.” Quarterly Journal of the Royal Meteorological Society, Vol. 126, Issue 566, pp. 1661-1683.
  2. Blackwell, W.J.; Leslie, R. Vincent; Pieper, Michael L. and Samra, Jenna E. "All-weather hyperspectral atmospheric sounding." Lincoln Laboratory Journal, Vol. 18, No. 2, 2010, pp. 28-46.
  3. Lindsey, Daniel T.; Grasso, Louie; Dostalek, John F. and Kerkmann. Jochen. "Use of the GOES-R Split-Window Difference to Diagnose Deepening Low-Level Water Vapor." Journal of Applied Meteorology and Climatology 53, 8, 2014.
  4. Sun, B.; Reale, A.; Tilley, F.H.; Pettey, M.E.; Nalli, N.R. and Barnet, C.D. "Assessment of NUCAPS S-NPP CrIS/ATMS Sounding Products Using Reference and Conventional Radiosonde Observations." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 6, June 2017, pp. 2499-2509. doi: 10.1109/JSTARS.2017.2670504.


KEYWORDS: Meteorology; Boundary Layer; Sounding; Profile; Satellite; Remote Sensing; Algorithm; Temperature; Water Vapor; Refractivity

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