Integrated Physical and Ecological Modeling and Forecasting

Program Leader: Philip Chu


High waves in Lake Michigan along the Chicago shoreline.
GLERL’s Integrated Physical and Ecological Modeling and Forecasting (IPEMF) branch develops, evaluates, and applies models for use in testing scientific hypotheses and predicting the effects of natural and human-generated changes on the Great Lakes environment. The approach to IPEMF research provides information used to forecast environmental conditions at different points in time and geographic location, and to increase knowledge of the interactions between the components of the complex physical and ecological systems in the Great Lakes basin (see schematic below). The recipients of IPEMF’s research and development products, services, and information include federal, public, private, and academic organizations who apply the research outcomes to make better operational decisions supporting various societal and economic sectors.

The IPEMF research program advances the following NOAA objectives:

The IPEMF branch focuses on advancing the development of an integrated environmental modeling system for the Great Lakes. The branch also works to accelerate the transition of research to operations and applications as advised in NOAA’s Annual Guidance Memorandum.

IPEMF conducts innovative research and develops numerical models to predict the physical, chemical, biological, and ecological response in the Great Lakes due to weather, climate, and human-induced changes. The forecast models and quantitative tools developed by IPEMF researchers allow scientists, coastal resource managers, policy makers, and the public to make informed decisions for optimal management of the Great Lakes and to maintain a healthy, sustainable, resilient ecosystem.

IPEMF has a long history of conducting innovative research, transitioning models from research to operations, and collaborating with academia, organizational partners, and private industry. IPEMF’s primary goal is to develop and implement an integrated environmental modeling system that can provide accurate forecasts of physical, ecological, biological and chemical parameters at various time and space scales. The integrated system suite consists of climate, meteorology, lake circulation hydrodynamics, watershed hydrology, waves, ice, and ecological models. Since the ecosystem and hydrological cycles of the Great Lakes are interconnected, an important way to improve forecast capability is to understand the relationships and interactions between each component and then to develop a coupled environmental system model.

Internally, IPEMF scientists work closely with OSAT, EcoDyn, and IS branches. Environmental observations measured and collected by OSAT and EcoDyn are used to initialize, validate, verify, and improve hydrodynamic, ecological, water quality, and ice model predictions. The IS branch works with IPEMF to ensure accessibility of the modeling outcomes. IPEMF also collaborates with CIGLR, external agencies, organizational partners, and universities. The forms of collaboration include joint research projects, leveraging resources, application transition, and product dissemination.

The long-term focus of IPEMF is to further advance a fully coupled integrated modeling forecasting system, and to further enhance internal and external collaboration. Future work will advance our capabilities in model coupling, skill assessment, performance accuracy testing, and uncertainty analysis of models. Outputs of models will be made available to constituents through a variety of means, both directly from GLERL, other NOAA partners and line offices, and in coordination with partners such as the Great Lakes Observing System (GLOS).

IPEMF Guiding Principles:

The GLERL-developed Huron to Erie Connecting Waterways Forecasting System (HECWFS) predicts real-time water levels and currents to simulate where and how quickly potential contaminant spills could travel.

Short-Term Coastal Dynamics Modeling

Coastal dynamics research is focused on addressing water quality problems (chemical pollution and bacterial contamination) as well as physical threats to public safety (storms, oil spills, waves, rip currents) on a localized and lake-wide basis. The length of time for these problems ranges from hours to days. Our research includes the development and use of hydrologic (water cycle), hydrodynamic (circulation of water), and ice models in the prediction of runoff, nutrient or bacteria loads, currents, water temperature, storm surge, waves, and ice cover. As a result, these predictions enable us to forecast events, such as beach closures, hazardous material spill paths, and movement of harmful algal blooms, among others.

MODIS image of maximum ice cover on Great Lakes, 92.5%

Seasonal Atmosphere-Lake-Ice-Ecosystem Modeling

Modeling of the atmosphere, lakes, seasonal changes in ice cover, and the ecosystem dynamics of the lakes adds to our understanding of how the Great Lakes basin changes over the course of months and years. Results from our researchers’ work on these models address problems involving water resource management, human health and ecology. Our main challenges involve improving seasonal forecasts of Great Lakes water levels and ice cover and linking physical conditions (air and water temperature, wind, ice cover) to ecological responses.

Regional Climate Projections: Impact Assessment and Historical Trends Analysis

Our research on regional climate projections is based on atmospheric and coupled hydrodynamics-ice-ecosystem models. Results are used to predict the physical and ecological conditions of the Great Lakes over the course of yearly seasonal changes to decades. Our research tools are designed to examine the effects of climate on regional air temperature, precipitation, water levels, lake temperature and thermal structure, ice cover, and ecological changes and trends.

Featured Research

Great Lakes Coastal Forecasting System (GLCFS)

Making the transition from research to operations
NOAA’s Great Lakes Coastal Forecasting System (GLCFS) is a set of hydrodynamic computer models that predict lake circulation and other physical processes (e.g. circulation, thermal structure, waves, ice dynamics) of the lakes and connecting channels in a real-time nowcast and forecast mode. These research models provide us with timely information on currents, water temperatures, short-term water level fluctuations (e.g. seiche, storm surge), ice, and waves for up to 120 hours into the future. Predictions of these lake conditions assist planners and managers in addressing several critical issues in the Great Lakes such as navigation, search and rescue,contaminant spill response, harmful algal blooms, beach management, and recreational use. The GLCFS also functions to provide NOAA’s National Weather Service (NWS) marine forecasters with information that improves the accuracy and efficiency of Great Lakes marine forecasts and warnings. The current 3rd generation of the GLCFS is run in near real-time at NOAA’s Great Lakes Environmental Research Laboratory (GLERL), and operationally at NOAA’s National Ocean Service (NOS) under the name Great Lakes Operational Forecast System (GLOFS).

Additional Information:
NOAA Great Lakes Coastal Forecasting System (Fact sheet)

Great Lakes Ice Cover Observations

Understanding the major effect of ice on the Great Lakes is crucial because it impacts a range of societal benefits provided by the lakes, from hydropower generation to commercial shipping to the fishing industry. The amount of ice cover varies from year to year, as well as how long it remains on the lakes. GLERL scientists are observing long-term changes in ice cover as a result of global warming. Studying, monitoring, and predicting ice coverage on the Great Lakes plays an important role in determining climate patterns, lake water levels, water movement patterns, water temperature structure, and spring plankton blooms.

Additional Information:
Great Lakes Ice Cover (Fact sheet)

Great Lakes Ice, Arctic Ice, and Climate Studies: Research, Modeling, and Prediction

Knowledge of the lake (sea) ice dynamics, thermodynamics, and regional climate in the Great Lakes (Arctic) are possibly associated with global atmospheric teleconnection patterns. Ice cover is important not only to navigation and rescue efforts, but also to prediction of precipitation, lake water level variability, and environmental preconditioning for phytoplankton and zooplankton blooms. Building such knowledge requires an update of observation data, continued improvement of existing coupled ice-ocean-ecosystem models (e.g. CIOM), development of new models (e.g. FVCOMice and regression models), and sub-scale models for important ice-ocean dynamics and thermodynamics. These models will be validated against observations and then transferred to operational facilities for prediction and projection in the Great Lakes and Arctic.

Additional Information:
Quarterly Climate Impacts and Outlook for the Great Lakes Region (Fact sheet)
The Climate Observer - A publication of the Midwestern Regional Climate Center (External website)

Great Lakes Water Level Observations

Great Lakes water levels constitute one of the longest high quality hydrometeorological data sets in North America with reference gage records beginning about 1860 with sporadic records back to the early 1800s. These levels are collected and archived by NOAA’s National Ocean Service.

Additional Information:
Water Levels in the Great Lakes (Fact sheet)
Water Budgets of the Great Lakes (Infographic)
Record-setting Water Levels Rise in the Great Lakes (Infographic)

Great Lakes Water Level Dashboard

Effectively communicating the Great Lakes water level story is an important part of NOAA’s mission to understand and predict changes in climate, weather, oceans, and coasts. This interactive tool greatly enhances our ability to educate a diverse audience about the normal variability in Great Lakes water levels. Other versions of the dashboard make additional hydro-climate data sets available, allowing users to observe the relationships between weather, climate, and water levels. The dashboard portal page referenced above allows access to additional versions of this tool.