The two-year COMPASS-GLM pilot study aims to enhance predictive understanding of freshwater coastal The Coastal Observations, Mechanisms, and Predictions Across Systems and Scales–Great Lakes Modeling (COMPASS-GLM) project is focused on developing a fully coupled regional earth system model centered around the Portage River basin in northern Ohio.

The COMPASS-GLM pilot study aims to enhance predictive understanding of freshwater coastal systems, especially how they respond to climate warming, Land Use Land Cover Change (LULCC), and other perturbations at watershed-to-regional scales, and how these changes interact with and impact human systems. This includes, for example, local climate and weather feedbacks due to atmosphere lake interactions, lake breeze effects modulating urban heat island associated heat stresses, and climate mitigation strategies for farming.

Figure 1: This figure shows the three components of the project, as circles, with connections between the tasks indicated with arrows.

We are focusing on three tasks during our pilot study (see Figure 1): Regional Coupled Modeling, High-resolution 3D Regional Land Modeling, and Agricultural Dynamics. These tasks are tightly coupled, and together focus on answering these overarching long-term science questions:

  1. How do coastal systems respond to natural and anthropogenic influences?
  2. What multiscale mechanisms govern the structure, function, and dynamics of coastal systems at different spatial and temporal scales?
  3. Which processes are the most important to resolve to understand coastal systems in the context of climate change?
  4. What are the most effective ways to incorporate critical small scale processes in global earth system models that cannot resolve these processes?
  5. How do we best generalize new process knowledge and predictive skill gained at a small number of sites or regions across the observed diversity of coastal systems?

In the Great Lakes region, previous studies have already identified a number of processes, occurring at a wide range of scales from city to continental, that impact both human and natural systems. Figure 2 illustrates some of these important processes in the Great Lakes region.

Figure 2: A schematic of key processes in the Great Lakes Region (from Sharma et al. 2018). The lakes influence, and are influenced by, many different processes that affect regional ecosystems and human activities.

Expected outcomes of the pilot study include:

  • A flexible, integrated, and well-tested WRF+FVCOM modeling system that has multiple land surface, dimensionality, and resolution options will be developed. Model output from multiple scenarios and configurations, at a scales ranging from watershed to the entire Great Lakes region, will be archived and shared with the broader scientific community and can be leveraged by other agencies and groups to inform regional decision-making.
  • Improved understanding of coupled processes and interactions that occur at sub-regional scales will be used to develop multiple peer-reviewed publications and to inform development of E3SM and other modeling systems. Improved methodologies for representing high-resolution watershed and lake processes within E3SM at regionally refined scales will be incorporated into the E3SM framework.
  • An assessment of changing farming practice impacts on the regional ecosystem, climate change impacts on farming communities, and the effectiveness of various climate mitigation strategies will be performed to identify the most impactful regional climate signals and the most effective response strategies.

Task: Regional modeling

Figure 3: The Regional Coupled Modeling domain for the atmosphere and lakes (left), and diagram depicting the component coupling (right).

The first task is focused on coupled, integrated atmosphere–land–lake regional modeling in the Great Lakes Region (Figure 3). We will use standard community models typically used for regional coastal studies: the Weather Research and Forecasting (WRF) Model for the atmosphere, the WRF-Hydro Model for land, and the Finite Volume Community Ocean Model (FVCOM) for the lakes.

Key scientific questions to be addressed are:

  • How will lake water balance be affected by precipitation and runoff?
  • How will changes in physical lake processes drive changes to Great Lakes properties and consequently influence regional climate?
  • How will summer storms and winter lake-effect snowstorms be influenced by regional warming, surface moisture flux, and other factors?
  • What is the importance of resolving clouds, lake circulation, thermal structure, and ice coverage for accurately simulating atmosphere-lake interactions?
  • What are the relative contributions of internal variability, parameters, and parameterizations to uncertainties in our coupled model?

We will also use this modeling system to understand how lake-breezes will alter urban heat stress, convective storms, and flooding around Chicago. We will use a refined, nested WRF grid (~0.25-1km grid spacing), coupled with the FVCOM lake model to investigate how the urban heat island affects convective storms and rainfall in the Chicago area. Key scientific questions to be addressed are:

  1. How do interactions among lake breezes and urban thermodynamic and dynamic processes affect heat stress, mesoscale and locally driven convective systems, and corresponding flooding risk in coastal urban areas?
  2. How will regional LULCC (including urbanization) and climate warming influence summer heat stress events, storm patterns, and flooding in the Great Lakes Region?

Expected outcomes of the Regional Coupled Modeling task during the pilot phase include:

  • A flexible, integrated, and well-tested WRF+FVCOM modeling system that has multiple land surface, dimensionality, and resolution options will be developed.
  • Model output from multiple scenarios and configurations will be archived and shared with the broader scientific community and can be leveraged by other agencies and groups to inform regional decision-making.
  • Improved understanding of coupled processes and interactions will be used to develop multiple peer-reviewed publications and to inform development of E3SM and other modeling systems.

Task: High-resolution watershed modeling

Figure 4: The Portage River watershed in northern Ohio, including a map showing the complexity of agricultural drainage ditches (left) and an ATS simulation of ponded depth (right).

The second task will focus on high-resolution, 3D regional land surface modeling. Early work has focused on the Portage River basin (Figure 4), with the goal of understanding and representing the role of agricultural water management practices in watershed simulations. An important enhancement to The Advanced Terrestrial Simulator (ATS) was the inclusion of tile drains and drainage ditches. Ongoing work is coupling ATS with the E3SM Land Model (ELM) in order for ELM to include surface and subsurface lateral flow, which play a primary role in controlling water and nutrient exports in these flat, agriculture-dominated systems. 

The key scientific questions to be addressed are:

  1. At what scales must watershed features, including water management infrastructure, topography, and soil properties, be represented in order to accurately capture river discharge from agriculturally dominated systems?
  2. How are nutrient exports from agricultural watersheds controlled by hydrologic variability, including flashy storms, overland flow, managed flows, and surface water-groundwater interactions?
  3. What is the integrated export of nutrients across the entire river basin?
  4. How will changing land cover, agricultural practices, and climate change affect the future export of nutrients to the downstream lake?

Expected outcomes of the pilot study within this task include:

  • Coupled ELM/ATS code that will allow ELM to resolve surface and subsurface properties at unprecedented scales.
  • State-of-the-art high-resolution capability for modeling agricultural watersheds based on ELM/ATS.
  • Improved understanding of the relative importance of nutrient removal mechanisms in the Portage River watershed and how those mechanisms will be affected by an intensified hydrological cycle.
  • A demonstrated multifidelity approach that makes mechanistically detailed simulations of nutrient transport and transformation tractable at river-basin scales.

Task: Modeling climate-agriculture interactions

This task focuses on understanding and modeling local-scale interactions between hydroclimatic conditions and agricultural processes in the Portage River watershed. To do so, we are developing a new agent-based modeling (ABM) framework that allows us to capture agricultural adaptation decisions in response to climate stressors and socio-environmental influences. Our modeling capabilities build on extensive analysis of empirical data, including the use of satellite data and machine learning for identifying and analyzing key adaptation drivers.

The ABM will be combined with an enhanced Soil & Water Assessment Tool (SWAT) model as part of a broader exploratory modeling framework to characterize the uncertainties present in the system and in the modeling outcomes. The exploratory modeling analysis will rely on large-ensemble Monte Carlo modeling to combine and propagate uncertainties present in future hydroclimatic conditions, human adaptation behavior, and modeling assumptions, including coupling relationships.  

The key scientific questions to be addressed are:

  1. What have been the main drivers of adaptation in land use and agricultural practices historically and how might they change in the future?
  2. How do agricultural management practices interact with natural processes (regional climate, watershed transport, etc.) to shape impacts?
  3. How does the presence of uncertainty in both the human and natural systems shape our understanding of these impacts?

The expected outcomes of the pilot study for this task are:

  • Better understanding of agricultural adaptation processes and their impacts in a representative Great Lakes watershed. 
  • Empirically-based modeling capabilities to capture interactions between human and natural system processes.
  • Prototype of a generalizable and transferable agricultural ABM that enables the application of exploratory modeling workflows.

COMPASS is a multi-institutional effort funded by the Earth and Environmental System Science Division of the U.S. Department of Energy’s Office of Science. Participating institutions include: Pacific Northwest National Laboratory, Los Alamos National Laboratory, Lawrence Berkeley National Laboratory, Argonne National Laboratory, Oak Ridge National Laboratory, Baylor University, University of Toledo, Michigan Technological University, and Heidelberg University.