Studying: Modeling

Modeling and its importance

Information about sea ice processes can come from field camps or aircraft and satellites, but data from these sources are limited. Sensors cannot account for all characteristics of sea ice, and the record of sea ice data has a relatively short history. Satellite observations date back only to the mid-1970s; other observations, such as ship records, may go back as far as the late 19th century, but they are sparse. Moreover, these data cannot predict the future of sea ice extent.

To fill in the gaps in sea-ice knowledge, scientists use models to simulate sea ice processes. A model is a mathematical representation of a real-world physical process. These models allow scientists to reconstruct historical patterns of sea ice and predict future changes.

Sea ice modeling

Sea ice models provide valuable information on how sea ice evolves and how it will be affected by changing climate. Scientists use models for long-term climate studies, short-term operational forecasts (within the next 10 days or so), and for seasonal forecasts (such as the upcoming summer minimum).

When used to predict future conditions, sea ice models fall into three general categories. Heuristic models can be characterized as educated guesses. Statistical models predict events based on past trends and variability, for instance predicting the upcoming sea ice minimum extent based on past extents. Dynamical models simulate conditions in the ocean, atmosphere, and sea ice with mathematical equations.

The evolution of sea ice is influenced by the ocean below and the atmosphere above. These influences are represented in models as boundary conditions, or forcings, because they force the sea ice to change based on influences from the ocean and atmosphere. For example, air temperatures above freezing cause the sea ice to melt, whereas air temperatures below freezing cause the sea ice to grow.

Sea ice models are often combined with ocean or atmospheric models. These are called coupled models, because rather than specifying the ocean or atmosphere as forcings, the sea ice, ocean, or atmosphere interact with each other and all the components evolve together. Coupled models can include sea ice and ocean, sea ice and atmosphere, or all three.

How sea ice models work

Numerical models represent sea ice in cells. A cell is the smallest discrete area that can be described by the model. An analogy is an image captured by a digital camera where the image is comprised of individual pixels. Each pixel can be only one color. In a model, each cell generally has an average value for each property, such as ice thickness, though can be a distribution of that value across the cell. A certain percentage of the cell might have an ice thickness of 1 meter, and another percentage of the cell might have a thickness of 2 meters.

Models can have both horizonal and vertical resolution, especially when modeling the atmosphere and ocean and differences occur at different altitudes and depths.

Each cell has a finite area, for example, 10 square kilometers (3.9 square miles). The entire group of cells is referred to as a domain. As the number of grid cells increases in a model domain, so does the spatial resolution. Having a large number of grid cells describes sea ice conditions on smaller scales—tens of kilometers, versus hundreds—but the cost of storing and computing the model increases.

Last updated: 3 April 2020