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HIOMAS

High Resolution Ice-Ocean Modeling and Assimilation System

Established

2017

Summary

This ADAC project developed an accurate, High-resolution Ice-Ocean Modeling and Assimilation System (HIOMAS) to simulate and predict sea ice and currents in the Arctic Ocean. The system was calibrated and validated using a range of available sea ice and ocean observations and then used for (near) real-time hindcast and daily-to-seasonal forecast of Arctic Ocean currents, sea ice, and change. The research pays particular attention to the prediction of spatial distribution of ice motion and thickness, the fraction of thick-ridged or multi-year ice, and to the retreat and advance of ice edge. These are the sea ice factors, which are most relevant to Arctic operators. The prediction data allows the U.S. Coast Guard to more safely and reliably conduct search and rescue missions and is also useful for assisting other stakeholders in the planning and management of economic activities and for other modeling efforts, such as oil spill and wave modeling. HIOMAS is currently operational and the project team is working to refine the model in response to new research directions and emerging stakeholder needs.

HIOMAS
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Abstract

This ADAC project is completing an accurate High-resolution Ice-Ocean Modeling and Assimilation System (HIOMAS) to simulate and predict sea ice and currents in the Arctic Ocean. This system is calibrated and validated using a range of available sea ice and ocean observations. Once validated, the system is used for near real-time hindcasting and daily to seasonal forecasting of the Arctic Ocean currents, sea ice, and other environmental changes. The research pays particular attention to: (1) the prediction of spatial distribution of ice motion and thickness, (2) the fraction of thick-ridged or multi-year ice, and (3) the retreat and advance of ice edges. These are the sea ice factors that are most relevant to Arctic operators.

Accurate high-resolution prediction of ocean currents and sea ice conditions will enhance the Coast Guard’s ability to prepare for and respond to oil spills in the Arctic Ocean. The prediction data will aim to improve Coast Guard safety and consistency when conducting search and rescue missions. The prediction data may also be useful for assisting other stakeholders in planning and management of economic activities. In addition, the data may be useful for other modeling efforts, such as oil spill and wave modeling. An inherent strength of HIOMAS is the ability to generate high precision models of sea ice thickness, the movement of ice, and ocean currents across the Arctic Ocean. When focused on a particular region of concern, HIOMAS is able to achieve even greater data precision. Through prior ADAC investigation, pan-Arctic resolution has reached the limits of the existing computing ability.

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Gallery

Researchers

Portrait of 		Rob
			 		Bochenek
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AIS-PAC

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HIOMAS

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Arctic Geofencing

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ICECON

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AIFC

Rob Bochenek

Support Team



rob@axiomdatascience.com

Portrait of 		Jinlun
			 		Zhang
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HIOMAS

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ARCTICE

Dr. Jinlun Zhang



zhang@apl.washington.edu