William H. Lipscomb

The Community Earth System Model: A Framework for Collaborative Research

The Community Earth System Model (CESM) is a flexible and extensible community tool used to investigate a diverse set of Earth system interactions across multiple time and space scales. This global coupled model significantly extends its predecessor, the Community Climate System Model, by incorporating new Earth system simulation capabilities. These comprise the ability to simulate biogeochemical cycles, including those of carbon and nitrogen, a variety of atmospheric chemistry options, the Greenland Ice Sheet, and an atmosphere that extends to the lower thermosphere. These and other new model capabilities are enabling investigations into a wide range of pressing scientific questions, providing new foresight into possible future climates and increasing our collective knowledge about the behavior and interactions of the Earth system. Simulations with numerous configurations of the CESM have been provided to phase 5 of the Coupled Model Intercomparison Project (CMIP5) and are being analyzed by the broad com...

An energy‐conserving thermodynamic model of sea ice

We introduce an energy-conserving sea ice model for climate study that accounts for the effect of internal brine-pocket melting on surface ablation. Sea ice models that parameterize latent heat storage in brine pockets often fail to reduce the energy required for surface ablation in proportion to the internal melting that has already occurred. These models do not conserve energy during the summer melt season. Compared with our energy-conserving model, a nonconserving model underestimates top-surface ablation of multiyear ice by 12–22% and overestimates the equilibrium ice thickness by 50–124 cm. In addition, a nonconserving model is less sensitive to perturbative forcing than our energy-conserving model is: The equilibrium thickness changes 22–44% less owing to surface albedo perturbations and 13–31% less owing to downward longwave radiation perturbations. The smaller differences are associated with a model that has a time-independent, vertically varying salinity profile, and the larger differences are associated with a model that assumes the ice is isosaline with a salinity of 3.2‰. Simulations with a vertically varying salinity profile have low salinity at the top surface compared to isosaline cases, which leads to reduced heat conduction, less internal brine-pocket melting, and more surface ablation.

Influence of the Sea Ice Thickness Distribution on Polar Climate in CCSM3

Abstract The sea ice simulation of the Community Climate System Model version 3 (CCSM3) T42-gx1 and T85-gx1 control simulations is presented and the influence of the parameterized sea ice thickness distribution (ITD) on polar climate conditions is examined. This includes an analysis of the change in mean climate conditions and simulated sea ice feedbacks when an ITD is included. It is found that including a representation of the subgrid-scale ITD results in larger ice growth rates and thicker sea ice. These larger growth rates represent a higher heat loss from the ocean ice column to the atmosphere, resulting in warmer surface conditions. Ocean circulation, most notably in the Southern Hemisphere, is also modified by the ITD because of the influence of enhanced high-latitude ice formation on the ocean buoyancy flux and resulting deep water formation. Changes in atmospheric circulation also result, again most notably in the Southern Hemisphere. There are indications that the ITD also modifies simulated sea...

Ridging, strength, and stability in high-resolution sea ice models

[1] In multicategory sea ice models the compressive strength of the ice pack is often assumed to be a function of the potential energy of pressure ridges. This assumption, combined with other standard features of ridging schemes, allows the ice strength to change dramatically on short timescales. In high-resolution (∼10 km) sea ice models with a typical time step (∼1 hour), abrupt strength changes can lead to large internal stress gradients that destabilize the flow. The unstable flow is characterized by large oscillations in ice concentration, thickness, strength, velocity, and strain rates. Straightforward, physically motivated changes in the ridging scheme can reduce the likelihood of abrupt strength changes and improve stability. In simple test problems with flow toward and around topography, stability is significantly enhanced by eliminating the threshold fraction G* in the ridging participation function. Use of an exponential participation function increases the maximum stable time step at 10-km resolution from less than 30 min to about 2 hours. Modifying the redistribution function to build thinner ridges modestly improves stability and also gives better agreement between modeled and observed thickness distributions. Allowing the ice strength to increase linearly with the mean ice thickness improves stability but probably underestimates the maximum stresses.

Adaptive mesh, finite volume modeling of marine ice sheets

Continental scale marine ice sheets such as the present day West Antarctic Ice Sheet are strongly affected by highly localized features, presenting a challenge to numerical models. Perhaps the best known phenomenon of this kind is the migration of the grounding line - the division between ice in contact with bedrock and floating ice shelves - which needs to be treated at sub-kilometer resolution. We implement a block-structured finite volume method with adaptive mesh refinement (AMR) for three dimensional ice sheets, which allows us to discretize a narrow region around the grounding line at high resolution and the remainder of the ice sheet at low resolution. We demonstrate AMR simulations that are in agreement with uniform mesh simulations, but are computationally far cheaper, appropriately and efficiently evolving the mesh as the grounding line moves over significant distances. As an example application, we model rapid deglaciation of Pine Island Glacier in West Antarctica caused by melting beneath its ice shelf.

Remapping the thickness distribution in sea ice models

In sea ice models with multiple thickness categories the ice thickness distribution evolves in time. The evolution of the thickness distribution as ice grows and melts is analogous to one-dimensional fluid transport and can be treated by similar numerical methods. One such method, remapping, is applied here. Thickness categories are represented as Lagrangian grid cells whose boundaries are projected forward in time. The thickness distribution is approximated as a linear or quadratic polynomial in each displaced category, and ice area and volume are transferred between categories so as to restore the original boundaries. In simple test problems and in a single-column model with forcing typical of the central Arctic, remapping performs significantly better than methods previously used in sea ice models. It is less diffusive than a scheme that fixes the ice thickness in each category and behaves better numerically than a scheme that represents the thickness distribution as a set of delta functions. Also, remapping converges faster (i.e., with fewer thickness categories) than the alternative schemes. With five to seven categories the errors due to finite resolution of the thickness distribution are much smaller than the errors due to other sources. Linear remapping performs as well as the more complex quadratic version and is recommended for climate modeling. Its computational cost is minimal compared to other sea ice model components.

Late-Twentieth-Century Simulation of Arctic Sea Ice and Ocean Properties in the CCSM4

AbstractTo establish how well the new Community Climate System Model, version 4 (CCSM4) simulates the properties of the Arctic sea ice and ocean, results from six CCSM4 twentieth-century ensemble simulations are compared here with the available data. It is found that the CCSM4 simulations capture most of the important climatological features of the Arctic sea ice and ocean state well, among them the sea ice thickness distribution, fraction of multiyear sea ice, and sea ice edge. The strongest bias exists in the simulated spring-to-fall sea ice motion field, the location of the Beaufort Gyre, and the temperature of the deep Arctic Ocean (below 250 m), which are caused by deficiencies in the simulation of the Arctic sea level pressure field and the lack of deep-water formation on the Arctic shelves. The observed decrease in the sea ice extent and the multiyear ice cover is well captured by the CCSM4. It is important to note, however, that the temporal evolution of the simulated Arctic sea ice cover over the...

Modeling Sea Ice Transport Using Incremental Remapping

Sea ice models contain transport equations for the area, volume, and energy of ice and snow in various thickness categories. These equations typically are solved with first-order-accurate upwind schemes, which are very diffusive; with second-order-accurate centered schemes, which are highly oscillatory; or with more sophisticated second-order schemes that are computationally costly if many quantities must be transported [e.g., multidimensional positive-definite advection transport algorithm (MPDATA)]. Here an incremental remapping scheme, originally designed for horizontal transport in ocean models, is adapted for sea ice transport. This scheme has several desirable features: it preserves the monotonicity of both conserved quantities and tracers; it is second-order accurate except where the accuracy is reduced locally to preserve monotonicity; and it efficiently solves the large number of equations in sea ice models with multiple thickness categories and tracers. Remapping outperforms the first-order upwind scheme and basic MPDATA scheme in several simple test problems. In realistic model runs, remapping is less diffusive than the upwind scheme and about twice as fast as MPDATA.

Insights into spatial sensitivities of ice mass response to environmental change from the SeaRISE ice sheet modeling project I: Antarctica

Sophie Nowicki, Robert A. Bindschadler, Ayako Abe-Ouchi, Andy Aschwanden, Ed Bueler, Hyeungu Choi, Jim Fastook, Glen Granzow, Ralf Greve, Gail Gutowski, Ute Herzfeld, Charles Jackson, Jesse Johnson, Constantine Khroulev, Eric Larour, Anders Levermann, William H. Lipscomb, Maria A. Martin, Mathieu Morlighem, Byron R. Parizek, David Pollard, Stephen F. Price, Diandong Ren, Eric Rignot, Fuyuki Saito, Tatsuru Sato, Hakime Seddik, Helene Seroussi, Kunio Takahashi, Ryan Walker, and Wei Li Wang

Evaluation of the sea ice simulation in a new coupled atmosphere‐ocean climate model (HadGEM1)

A rapid increase in the variety, quality, and quantity of observations in polar regions is leading to a significant improvement in the understanding of sea ice dynamic and thermodynamic processes and their representation in global climate models. We assess the simulation of sea ice in the new Hadley Centre Global Environmental Model (HadGEM1) against the latest available observations. The HadGEM1 sea ice component uses elastic-viscous-plastic dynamics, multiple ice thickness categories, and zero-layer thermodynamics. The model evaluation is focused on the mean state of the key variables of ice concentration, thickness, velocity, and albedo. The model shows good agreement with observational data sets. The variability of the ice forced by the North Atlantic Oscillation is also found to agree with observations.