GLERL’s Dr. Eric Anderson has recently been awarded funding from the Research Transition Acceleration Program (RTAP), placing two of GLERL’s FVCOM modeling projects on the fast track to transition from research to operations (R2O). R2O is the pathway by which fundamental research is developed into a useful tool or product and implemented into an automated or operational environment accessible for use by the public. RTAP, a highly competitive grants program, prioritizes projects based on their ability to advance NOAA’s mission and benefit society with the ultimate goal of accelerating the transition of promising NOAA research to operations and applications.
Anderson focuses primarily on hydrodynamics, using computer modeling to study how forcing conditions, such as meteorological (weather) events, affect the motion and energy of a body of water. His research on the physical nature of the Great Lakes in response to natural forces is improving our ability to make predictions on currents, temperature, water levels, waves, harmful algal blooms (HABs), and ice characteristics. The RTAP awards will provide Anderson and his collaborative team of researchers the resources needed to advance the following two projects: “Implementation of a 3D HAB forecast model for Lake Erie using FVCOM” and “Implementation of the FVCOM-Ice model for the Great Lakes Operational Forecasting System (GLOFS).” Project outcomes will support services such as safe drinking water, recreation, and navigation.
Notably, both forecast models are built upon the Finite Volume Community Ocean Model (FVCOM), an open-source community model that uses an unstructured grid (triangular shapes of adaptable size) to represent the Great Lakes and connecting channels (such as the coastline illustrated above) with increased grid resolution and model accuracy. FVCOM solves the three-dimensional (3-D), integral form of the equations of motion. This modeling approach also provides for an established framework for coupled modules (interconnection between the biological and physical components in the ecosystem, such as biological processes, currents, sediment, ice, etc.). The seminal research paper explaining the structure and function of the FVCOM is provided in the Oceanography journal article, “An Unstructured Grid, Finite Volume Coastal Ocean Model FVCOM System” (Chen, et al., 2006) with further background on the FVCOM and its research application available on GLERL’s webpage, Great Lakes Coastal Forecasting: Next Generation.
The first of the RTAP awards listed above will enable Anderson with a group of NOAA partners to accelerate the implementation of a 3-D harmful algal bloom (HAB) forecast model by at least two years— providing decision makers with unprecedented real-time information on HAB extent, vertical distribution, and concentration. The experimental version of the model, known as the “HAB Tracker,” was first developed by GLERL in 2014 and has since been improved in collaboration with the National Ocean Service (NOS) National Centers for Coastal Ocean Science (NCCOS) as a tool that combines remote sensing and modeling to produce daily 5-day forecasts of bloom transport and concentration. The HAB Tracker is based on the 3-D FVCOM Lagrangian particle model, a sub-component of the FVCOM hydrodynamic model system currently being transitioned to operations. This transition will occur on NOAA’s high performance computing system for the NOAA production suite by NOS’ Center for Operational Oceanographic Products and Services (CO-OPS) as part of the next-generation Lake Erie Operational Forecasting System (LEOFS).
The second RTAP grant awarded to GLERL will facilitate incorporation of an ice model (FVCOM-Ice) in the Great Lakes Operational Forecasting System (GLOFS) by directly coupling it with the hydrodynamic FVCOM model. RTAP funding will provide the personnel and infrastructure needed to support the development, validation, and implementation of the FVCOM coupled hydrodynamic-ice model and accelerate transition as part of the GLOFS upgrade. This transition to operations will provide the first-ever ice forecasts of extent/concentration, thickness, and velocity for the Great Lakes. The process will occur first for the Lake Michigan-Huron Operational Forecast System (LMHOFS) and then add to the existing Lake Erie Operational Forecast System (LEOFS). The coupled hydrodynamics-ice modeling systems for Lakes Michigan, Huron, and Erie will provide users with operational 120-hour forecast guidance of ice conditions, water temperature, currents, and water levels, updated four times per day during the winter as well as spring months.
Anderson recognizes the value of these RTAP awards by providing “the resources and personnel we need across Line Offices to validate and transition these models into operations, and avoid the so-called ‘valley of death’ between fundamental research and operational applications.”