OUSD (R&E) CRITICAL TECHNOLOGY AREA(S): Advanced Computing and Software;Space Technology;Sustainment OBJECTIVE: Demonstrate novel capabilities to retrieve ocean surface vector winds (OSVW) and related supporting information within environmental regimes including, but not limited to, precipitation (especially in rain rates above 2 mm/hr to and in exceedance of 50 mm/hr), coastal zones, and regions with sea ice - at a horizontal resolution less than 9 km and error less than 9% - from disaggregated space based environmental monitoring (SBEM) platforms. DESCRIPTION: Satellite remote sensing of earth's atmosphere has provided incalculable benefit to meteorological understanding and forecasting systems. As traditional large SBEM systems are becoming deprecated in favor of smaller, proliferated observing platforms, there is a growing gap to represent key air-sea interaction state variables. In particular, OSVW represents a critical environmental quantity that modulates both atmospheric and oceanic predictability. Previous work (see References) has shown the ability to derive OSVW from a variety of sensor types and algorithmic capabilities - such as via active scatterometry, passive polarimetry, and synthetic aperture radar (SAR). However, the trend for satellite system capabilities over the past decade has generally degraded OSVW retrievals due to spatial and spectral measurement compromises emphasizing other missions. This has particularly affected accuracy of OSVW in high interest areas, such as coastal zones, tropical cyclones, and around sea ice. This SBIR topic aims to leverage cutting edge developments in Small- and Cube-Sat design, sensor capabilities, and algorithmic development that permit improved performance and lower Size, Weight, and Power (SWaP) compared to legacy observing systems. In particular, the focus of this effort is architecting and prototyping end-to-end software/algorithmic methodologies to improve the retrieval of OSVW and related quantities (such as ocean surface stress, wave and current information, etc.) under a broad variety of weather regimes and surface conditions, ultimately to demonstrating a new capability to observe atmospheric environmental variables. PHASE I: Outline and determine the end-to-end feasibility of building and operating a small form factor space-based OSVW platform and the novel science needed to better use observed information to derive OSVW data. Detail all essential components of the remote sensor architecture as well as the infrastructure needed to collect, transmit, and process observations. Delineate the parts of the software that would be on board, versus processed after downlink from a ground station. Scope out and provide preliminary testing of an appropriate modeling and simulation (M&S) framework, including a numerical weather prediction model, surface impacts, and line element atmospheric transmittance modeling. 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: Produce and demonstrate a prototype software process, including the full capability to derive OSVW and related variables - potentially with a relevant sensor payload and its testing on a representative observing platform (e.g., aircraft, low earth orbit). Include a plan for a specific test validation opportunity (such as an existing planned field campaign or other data collect event) to harden development and testing timeline, as well as providing the ability to refine error and uncertainty as needed. Algorithmic development should include the framework and test cases for calibration and validation activities from raw remote sensing observations, intermediate calibrated variables, through environmental retrieval quantities. Co-location with other sources of validation, such as buoys, in-situ profilers, and/or ship or aircraft based remote sensing, will be required. Deliver a prototype software suite and a final validation report of sensor performance in a field event compared to M&S testing at the end of this Phase. PHASE III DUAL USE APPLICATIONS: Conduct maturation efforts into a satellite analysis system: the algorithmic processing should be well aligned with the end-to-end platform integration, mission operations, communication infrastructure, and data processing chain. Commercialization efforts should be able to support/include a data service that supports meteorological data analysis, forecasting operations, and characterization for data assimilation into numerical weather prediction. With the expansion of governmental commercial data buys (for example, by NOAA, NASA, and DoD), it is expected this project will fill critical need in the global observing system of atmospheric properties. Downstream product development for various specialized environmental applications (such as tropical cyclone intensity analysis, marine boundary layers, and ocean modeling) are also anticipated. Other civil and commercial applications, including cargo shipping and leisure cruises, will benefit from enhanced data streams and meteorological services provided from this unique observing capability. REFERENCES: 1. Yang, Xiaofeng et al. "Comparison of ocean-surface winds retrieved from QuikSCAT scatterometer and Radarsat-1 SAR in offshore waters of the US west coast." IEEE Geoscience and Remote Sensing Letters 8.1, 2010, pp. 163-167. https://ieeexplore.ieee.org/document/5530352 2. Stoffelen, Ad et al. "Ocean surface vector wind observations." Remote sensing of the Asian Seas, 2019, pp. 429-447. https://link.springer.com/chapter/10.1007/978-3-319-94067-0_24 3. Migliaccio, Maurizio; Huang, Lanqing and Buono, Andrea. "SAR speckle dependence on ocean surface wind field." IEEE Transactions on Geoscience and Remote Sensing 57.8, 2019, pp. 5447-5455. https://ieeexplore.ieee.org/document/8666150 4. Du, Yan et al. "Ocean surface current multiscale observation mission (OSCOM): Simultaneous measurement of ocean surface current, vector wind, and temperature." Progress in Oceanography 193, 102531, 2021,. https://www.sciencedirect.com/science/article/abs/pii/S0079661121000215 5. Vogelzang, Jur, and Stoffelen, Ad. "On the Accuracy and Consistency of Quintuple Collocation Analysis of In Situ, Scatterometer, and NWP Winds." Remote Sensing 14.18, 4552, 2022. https://www.mdpi.com/2072-4292/14/18/4552 6. Hauser, Dani le et al. "Satellite Remote Sensing of Surface Winds, Waves, and Currents: Where are we now?" Surveys in Geophysics 44.5, 2023, pp. 1357-1446. https://link.springer.com/content/pdf/10.1007/s10712-023-09771-2.pdf 7. Gao, Yuan; Wang, Yunhua and Wang, Weili. "A New Approach for Ocean Surface Wind Speed Retrieval Using Sentinel-1 Dual-Polarized Imagery." Remote Sensing 15.17, 4267, 2023. https://www.mdpi.com/2072-4292/15/17/4267 8. Asiyabi, Reza Mohammadi et al. "Synthetic aperture radar (SAR) for ocean: A review." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, 2023, pp. 9106-9138. doi: 10.1109/JSTARS.2023.3310363 https://ieeexplore.ieee.org/document/10234538 KEYWORDS: Ocean surface vector winds; osvw; scatterometry; geophysical model function; space-based environmental modeling; SBEM; cubesat; microwave; radar
