DASIM: Data Assimilation for a new generation of Sea Ice Models

DASIM II follows the 1-year pilot project DASIM I and will explore the mathematical issues for assimilating data in modern sea-ice models

Objectives

DASIM I and II ultimate, mid/long-term objective, is the application of advanced ensemble data assimilation methods to the new generation of state-of-the-art Lagrangian sea-ice models in a quasi-operational setting. 

DASIM I has employed one postdoctoral scientist: Matthias Rabatel.

DASIM II will employ one PhD student.

Project Summary

DASIM comes as the natural fusion between the recent achievements in Lagrangian Data Assimilation (LaDA) and sea-ice modelling. Most existing models treat the sea-ice as a visco-plastic and are unable to describe important features such as cracks, leads, and ridges. Only recently has sea-ice motion been described with Lagrangian dynamics. As for other fields in geosciences in the recent past, merging the data provided by new observing suppliers with advanced models is expected to significantly improve the sea-ice predicting capabilities. DASIM is an interdisciplinary project between geoscientists and mathematicians whose main objective is to contribute to the birth of novel DA and uncertainty quantification methods for Lagrangian sea-ice models.

The simultaneous presence of a Lagrangian model and observational suppliers make the problem unique and completely new. Basic research is required to develop the appropriate mathematical framework and to explore novel DA strategies to this class of problems. The fundamental driving idea in DASIM is the existence of a subspace of the system dynamics, and a subset of the observations, in which is embedded the largest informational content for the signal to be retrieved. Despite the intractable large size of the full problem, by monitoring and exploiting this subspace one can hope to achieve a satisfactory track of the unknown signal while reducing the computational load. DASIM’s ultimate, mid/long-term objective, is the application of advanced LaDA methods to the new generation of state-of-the-art Lagrangian sea-ice models in a quasi- operational setting, setting up the basis for new sea-ice forecasting systems at the forefront in its domain. The necessary mathematical investigation envisaged in DASIM will put light on the feasibility of such a purpose and open the path toward its accomplishment. DASIM’s last deliverable will be the preparation of a scope document reporting pros and cons of a fully Lagrangian platform for sea-ice prediction that may serve as the basis for a larger proposal for an applied-oriented research initiative.

DASIM is a partnership between NERSC and RENCI-UNC. The project brings together leading scientists in mathematics, dynamical systems, DA, climate science and sea-ice modeling. NERSC is a world class Norwegian institute of climate science, leader in the research and application of DA to oceanography and sea-ice. RENCI is a multidisciplinary institute that brings the latest cyber tools and technologies to bear on pressing problems such as the genetic causes of cancer or the impacts of climate change. RENCI research teams involve faculty members at universities across North Carolina and the U.S. and that are positioned to bring major research projects to North Carolina. DASIM relies also on external collaborators in France and India, all with years of leading roles in applying mathematics to climate science, particularly involving DA. DASIM will not only provide valuable outputs to the sea-ice modelling and DA communities, but also contribute to the awareness and endorsement of new DA methodologies within the wider scientific arena. 

 
Project Details
Acronym: 
DASIM
Funding Agency: 
Office of Naval Research
NERSC Principal Investigator: 
Alberto Carrassi
Coordinating Institute: 
Nansen Environmental and Remote Sensing Center
Project Status: 
Completed