First Application of Artificial Neural Networks to Estimate 21st Century Greenland Ice Sheet Surface Melt.

Future Greenland ice sheet (GrIS) melt projections are limited by the lack of explicit melt calculations within most global climate models and the high computational cost of dynamical downscaling with regional climate models (RCMs). Here, we train artificial neural networks (ANNs) to obtain relationships between quantities consistently available from global climate model simulations and annually integrated GrIS surface melt. To this end, we train the ANNs with model output from the Community Earth System Model 2.

Influence of Arctic sea-ice loss on the Greenland ice sheet climate.

Unlabelled: The Arctic is the region on Earth that is warming the fastest. At the same time, Arctic sea ice is reducing while the Greenland ice sheet (GrIS) is losing mass at an accelerated pace. Here, we study the seasonal impact of reduced Arctic sea ice on GrIS surface mass balance (SMB), using the Community Earth System Model version 2.

Description and Demonstration of the Coupled Community Earth System Model v2 - Community Ice Sheet Model v2 (CESM2-CISM2).

Earth system/ice-sheet coupling is an area of recent, major Earth System Model (ESM) development. This work occurs at the intersection of glaciology and climate science and is motivated by a need for robust projections of sea-level rise. The Community Ice Sheet Model version 2 (CISM2) is the newest component model of the Community Earth System Model version 2 (CESM2).

Global Warming Threshold and Mechanisms for Accelerated Greenland Ice Sheet Surface Mass Loss.

The Community Earth System Model version 2.1 (CESM2.1) is used to investigate the evolution of the Greenland ice sheet (GrIS) surface mass balance (SMB) under an idealized CO forcing scenario of 1% increase until stabilization at 4× pre-industrial at model year 140.

An Efficient Ice Sheet/Earth System Model Spin-up Procedure for CESM2-CISM2: Description, Evaluation, and Broader Applicability.

Spinning up a highly complex, coupled Earth system model (ESM) is a time consuming and computationally demanding exercise. For models with interactive ice sheet components, this becomes a major challenge, as ice sheets are sensitive to bidirectional feedback processes and equilibrate over glacial timescales of up to many millennia. This work describes and demonstrates a computationally tractable, iterative procedure for spinning up a contemporary, highly complex ESM that includes an interactive ice sheet component.