Collaborative Research: Research Advancing Arctic Climate Projection Capability at Seasonal to Decadal Scales
The overarching motivation for this project is to capitalize on the PIs recent expertise in building and using a new high resolution fully coupled arctic model (RASM) to: (i) facilitate construction of multi- model Arctic test-bed tool, (ii) contribute to the advancement of a new sea ice model within the framework of the LANL Model for Prediction across Scales (MPAS-CICE) by offering innovative model evaluation methods for the task, and (iii) aid development of the next generation of global Earth System models by the Department of Energy. We propose to investigate and better understand model sensitivities and to quantify model uncertainties in simulating variability and predicting seasonal to decadal change in Arctic climate by exploring this variable multi-parameter space. This project aims to initially use a regional model (RASM) and a global model (CESM) to evaluate their skill in representing past and present climate variability against observationally derived metrics. Within the confines of our work with RASM and CESM, we will: (i) quantify the added value of using regional models for downscaling arctic simulations from global models, (ii) address the impacts of high resolution, improved process representations and coupling between model components on predictions at seasonal to decadal time scales, (iii) identify the most important processes essential for inclusion in future high resolution GC/ESMs, e.g. ACME, using CESM as a test bed, and (iv) better quantify the relationship between skill and uncertainty in the Arctic Region for high fidelity models. This work will be conducted in parallel with ACME development at Los Alamos National Laboratory (LANL) and other DOE laboratories. Beneficial RASM modeling techniques, metrics and analysis methods stemming from our work as well as our expertise gained in this project will be shared as part of ongoing collaboration with LANL to aid development of the Department of Energy (DOE) Accelerated Climate Modeling for Energy (ACME) to improve simulation for the polar regions.