The Bering Sea Regional Data Assimilation System: From Climate Variability to Short Term Hindcasting
Abstract
In the last decades, 4d variational (4dVar) data assimilation (DA) has become the most acknowledged tool for advanced hindcasting and forecasting of the ocean circulation. Starting from DA systems constrained by simple dynamics (e.g., [1,16]), the 4dVar approach [9] has gradually evolved into advanced DA systems based on state-of-the-art ocean models (MIT, ROMS) and is now routinely applied toward reconstructing the circulation in the Arctic, Pacific, or World Ocean (e.g., [5,15]). These state-of-the-art DA systems involve the assimilation of a variety of observations from satellites, surface and Argo drifters and climatological observations from oceanographic databases. Assimilation of these publicly accessible, near real-time observations is natural since the major goal of the global DA systems is to provide hindcasting of the global circulation and/or analysis of observed climate changes on a global scale. Meanwhile, due to the low flexibility of the global DA systems in assimilating regional data on smaller scales, the regional DA systems have been under extensive development within the last decade (e.g. [6, 8]).
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2018
- Accession Number
- AD1057977
Entities
People
- Gleb G. Panteleev
- Max I. Yaremchuk
- Oceana Francis
- Vladimir Luchin
Organizations
- Russian Academy of Sciences
- United States Naval Research Laboratory
- University of Hawaiʻi System