3D Coastal Ocean Foundational Model Using AI, SCHISM and MLEOF Models.view on SAM.gov

***THE NATIONAL OCEANIC AND ATMOSPHERIC ADMINISTRATION'S (NOAA) ACQUISITION & GRANTS OFFICE, EASTERN ACQUISITION DIVISION-NORFOLK, NATIONAL OCEAN SERVICE (NOS) OFFICE OF COAST SURVEY (OCS), INTENDS TO NEGOTIATE AND AWARD A PURCHASE ORDER, ON A SOLE SOURCE BASIS, UNDER AUTHORITY OF RFO FAR 6.103-1, WITH VIRGINIA INSTITUTE OF MARINE SCIENCE (VIMS) TO DEVELOP AN AI-BASED PREDICTIVE MODEL OF OCEAN TEMPERATURE, SALINITY, AND CURRENTS USING SCHISM AND MLEOF MODELS. NO SET ASIDE IS TO BE USED FOR THIS SOLE SOURCE REQUIREMENT. THE ASSOCIATED NAICS CODE IS 541715. ***THE SOLE SOURCE DETERMINATION IS BASED ON NOAA'S REQUIREMENT THAT VIRGINIA INSTITUTE OF MARINE SCIENCE (VIMS) IS THE OWNER AND DEVELOPER OF THE SCHISM MODEL WHICH WILL BE USED TO GENERATE THE PHYSICS- BASED SIMULATIONS UPON WHICH THE AI TOOLS WILL BE APPLIED. VIMS ALSO DEVELOPED THE SPECIFIC 3D COMPONENT OF THE SURGE AND TIDE OPERATIONAL FORECAST SYSTEM FOR THE ATLANTIC OCEAN (STOFS-3D-ATLANTIC), WHICH IS THE SCHISM-BASED MOD APPLICATION TO BE USED IN THIS PROJECT. VIMS CREATED THE PHYSICS-GROUNDED MACHINE-LEARNING EMPIRICAL ORTHOGONAL FUNCTION (MLEOF) AI TOOL REQUIRED FOR THIS PREDICTIVE MODELING CONTRACT. VIMS DOES NOT HAVE ANY AUTHORIZED PARTNERS WHO CAN PROVIDE THESE TECHNOLOGIES. THE SERVICES PROVIDED WILL BE THE APPLICATION OF AI TECHNIQUES TO LEARN FROM OCEAN MODEL SIMULATIONS IN ORDER TO DEVELOP AN AI-BASED PREDICTIVE MODEL OF OCEAN TEMPERATURE, SALINITY, AND CURRENTS. THE MODEL SIMULATIONS TO BE USED FOR THIS WILL BE FROM AN APPLICATION OF THE SCHISM (SEMI-IMPLICIT CROSS-SCALE HYDROSCIENCE INTEGRATED SYSTEM MODEL) MODEL DEVELOPED BY THE VIRGINIA INSTITUTE OF MARINE SCIENCE (VIMS). THE AI TECHNOLOGY THAT WILL BE USED TO LEARN FROM THE SCHISM MODEL RESULTS WILL INCLUDE A MACHINE-LEARNING EMPIRICAL ORTHOGONAL FUNCTION (MLEOF) AND A GENERATIVE FORECASTING TRANSFORMER (GFT). VIMS HAS DEVELOPED EXPERTISE WITH THESE TECHNIQUES THAT WILL ALLOW THEIR APPLICATION TO ITS SCHISM-BASED MODELING RESULTS. THE RESULTING AI-BASED MODEL WILL THEREFORE PROVIDE A READILY-DEPLOYABLE TOOL FOR PREDICTION OF TEMPERATURE, SALINITY, AND CURRENTS. THIS OPPORTUNITY WILL ENABLE NOS TO MAKE MAJOR ADVANCEMENTS IN COASTAL OCEAN MODELING AND PREDICTION THROUGH AI. FAILING TO SECURE THESE SERVICES THROUGH VIMS WOULD SEVERELY IMPEDE THE NOS'S ABILITY TO MEET MISSION-CRITICAL OBJECTIVES FOR COASTAL OCEAN MODELING AND PREDICTION. FURTHERMORE, IT WOULD CAUSE THE AGENCY TO MISS A PIVOTAL OPPORTUNITY FOR TRANSFORMATIVE PROGRESS IN ITS OPERATIONAL CAPABILITIES. MARKET RESEARCH FOR ADDITIONAL SOURCES FOUND NO OTHER QUALIFIED ENTITIES BECAUSE THE PROJECT REQUIRES A UNIQUE INTEGRATION OF PHYSICS-BASED MODELING AND SPECIFIC AI EXPERTISE HELD EXCLUSIVELY BY THE VIRGINIA INSTITUTE OF MARINE SCIENCE (VIMS). PREVIOUS RESEARCH FOR THE SURGE AND TIDE OPERATIONAL FORECAST SYSTEM WAS PERFORMED ON SELECTION OF BOTH THE PHYSICS-BASED MODELS. SCHISM WAS SELECTED FROM A RANGE OF OPEN SOURCE COMMUNITY OCEAN MODELS, DUE TO ITS ABILITY T…