Coupled Prediction of the Polar Regions

Lead: Adam Herrington, NCAR
What processes control atmospheric predictability in the Arctic?
Can realistic predictions of the Greenland Ice Sheet and its mass balance evolution be made?
Streamlines of wind over the Greenland ice sheet from a 1/8˚ refined mesh, the CESM2-Greenland Ice sheet grid. Visualization from Matt Rehme (CISL) and Adam Herrington (CGD) Streamlines of wind over the Greenland ice sheet from a 1/8˚ refined mesh, the CESM2-Greenland Ice sheet grid. Visualization from Matt Rehme (CISL) and Adam Herrington (CGD)

One area where weather and climate questions overlap is in atmospheric predictability in polar regions, especially the Arctic. Accurate prediction of the Arctic atmosphere is being seen as increasingly important in light of expanding maritime activity, continuity of the livelihoods of indigenous communities, and climate change regional effects. .

Arctic research problems exemplify the need for integrated system tools with their encompassing interactions of the atmosphere and aerosols, the land surface, biogeochemistry, the cryosphere (ice sheets and sea ice), and the ocean. The Arctic setting may have a higher level of atmospheric predictability on sub-seasonal to seasonal (S2S) and longer timescales due to the persistence of ice and ocean conditions, with their atmospheric forcing. An important line of inquiry here concerns the surface mass budget of the Greenland ice sheet, and understanding the processes that control its evolution will be critical for understandings of sea level response.

Resolving the fine scales that strongly influence Arctic predictability motivates the use of refined mesh models that can deliver high resolution (e.g., 5–10-km grids) where needed. In the SIMA application, the high-resolution atmospheric model would be coupled to oceanic and sea ice modeling components as an Earth system model. The system’s inclusion of data assimilation would enhance its S2S predictive capabilities.

SIMA Polar setup for the Greenland application showing the atmospheric modeling configuration having the refined-mesh Spectral Element (SE) dynamical core, data assimilation, CAM physics, and MUSICA aerosols. The atmospheric model would be coupled to ocean, sea ice, and land ice models (not shown) SIMA Polar setup for the Greenland application showing the atmospheric modeling configuration having the refined-mesh Spectral Element (SE) dynamical core, data assimilation, CAM physics, and MUSICA aerosols. The atmospheric model would be coupled to ocean, sea ice, and land ice models (not shown)

Configurations

  • 25-km refined-mesh CAM-SE
    • Arctic region with Greenland Ice sheet representation
    • Antarctic region
Precipitation field from a refined mesh Arctic simulation showing higher resolution precipitation structures inside of the polar refinement square (think black line)

Figure: Precipitation field from a refined mesh Arctic simulation showing higher resolution precipitation structures inside of the polar refinement square (think black line)