Book contents
- Sea Ice Analysis and Forecasting
- Sea Ice Analysis and Forecasting
- Copyright page
- Dedication
- Contents
- Contributors
- Preface
- Acknowledgements
- Abbreviations
- 1 Introduction
- 2 Sea Ice Physics and Modelling
- 3 Sea Ice Observations
- 4 Sea Ice Data Assimilation
- 5 Automated Sea Ice Prediction Systems
- 6 System Evaluation
- 7 Current Ice Services and Their Expected Evolution
- Index
- References
4 - Sea Ice Data Assimilation
Published online by Cambridge University Press: 12 October 2017
Book contents
- Sea Ice Analysis and Forecasting
- Sea Ice Analysis and Forecasting
- Copyright page
- Dedication
- Contents
- Contributors
- Preface
- Acknowledgements
- Abbreviations
- 1 Introduction
- 2 Sea Ice Physics and Modelling
- 3 Sea Ice Observations
- 4 Sea Ice Data Assimilation
- 5 Automated Sea Ice Prediction Systems
- 6 System Evaluation
- 7 Current Ice Services and Their Expected Evolution
- Index
- References
Summary
Data assimilation is a critical component of any automated prediction system used to forecast the weather, ocean or sea ice with lead times from hours to weeks. In the context of sea ice prediction, it enables the vast amount of information from all available in situ and remote sensing sea ice observations and forecasts from large-scale sea ice models to be optimally combined. Several existing sea ice prediction systems use data assimilation techniques for this purpose. The merging of the information from observations and model forecasts results in more accurate and useful estimates of the sea ice conditions than could otherwise be obtained using either the observations or model forecasts in isolation. The goal of this chapter is to provide an overview of data assimilation with an emphasis on the particular challenges posed by its application to operational sea ice prediction.
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- Chapter
- Information
- Sea Ice Analysis and ForecastingTowards an Increased Reliance on Automated Prediction Systems, pp. 51 - 108Publisher: Cambridge University PressPrint publication year: 2017
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