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    On using numerical sea-ice prediction and indigenous observations to improve operational sea-ice forecasts during spring in the Bering Sea

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    Author
    Deemer, Gregory Joseph
    Chair
    Bhatt, Uma
    Eicken, Hajo
    Committee
    Hutchings, Jennifer
    Danielson, Seth
    Metadata
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    URI
    http://hdl.handle.net/11122/4917
    Abstract
    Impacts of a rapidly changing climate are amplified in the Arctic. The most notorious change has come in the form of record-breaking summertime sea-ice retreat. Larger areas of open water and a prolonged ice-free season create opportunity for some industries, but bring new challenges to indigenous populations that rely on sea-ice cover for subsistence. Observed and projected increases in Arctic maritime activities require accurate sea-ice forecasts on the weather timescale, which are currently lacking. Motivated by emerging needs, this study explores how new modeling developments and local-scale observations can contribute to improving sea-ice forecasts. The Arctic Cap Nowcast/Forecast System, a research sea-ice forecast model developed by the U.S. Navy, is evaluated for forecast skill. Forecasts of ice concentration, thickness, and drift speed produced by the model from April through June 2011 in the Bering Sea have been investigated to determine how the model performs relative to persistence and climatology. Results show that model forecasts can outperform forecasts based on climatology or persistence. However, predictive skill is less consistent during powerful, synoptic-scale events and near the Bering Slope. Forecast case studies in Western Alaska are presented. Community-based observations from recognized indigenous sea-ice experts have been analyzed to gauge the prospect of using local observations in the operational sea-ice monitoring and prediction process. Local observations are discussed in the context of cross-validating model guidance, data sources used in operational ice monitoring, and public sea-ice information products issued by the U.S. National Weather Service. Instrumentation for observing sea-ice and weather at the local scale was supplied to key observers. The instrumentation shows utility in the field and may help translate the context of indigenous observations and provide ground-truth data for use by forecasters.
    Description
    Thesis (M.S.) University of Alaska Fairbanks, 2015
    Table of Contents
    Chapter 1. Introduction and Background -- 1.1 The Need for Sea-Ice Forecasts -- 1.2 Operational Sea: Ice Forecasting: A United States Perspective -- 1.3 The Bering Sea as an Operational Forecasting Springboard -- 1.4 Sea Ice Characteristics in the Bering Sea -- 1.5 Thesis Overview and Goals -- Chapter 2. Sea-Ice Forecast Model and Analysis Methods -- 2.1 The Arctic Cap Nowcast Forecast System -- 2.1.1 Background Leading to Forecast Model Selection -- 2.1.2 Model Configuration -- 2.1.3 Data Assimilated in Near Real-Time -- 2.1.4 Computational Process of the ACNFS -- 2.2 ACNFS Forecast Evaluation with a Skill Score Metric -- 2.3 Regional Forecast Verification of Sea-Ice Variables -- 2.3.1 Regional Forecast Skill in the Spatial Domain -- 2.3.2 Regional Forecast Skill in the Time Domain -- 2.4 Climatological Reference Datasets -- 2.4.1 Sea-Ice Concentration Climatology -- 2.4.2 Sea-Ice Thickness Climatology -- 2.4.3 Sea-Ice Drift Speed Climatology -- Chapter 3. Results of ACNFS Forecast Verification in the Bering Sea -- 3.1 The 2011 Sea-Ice Retreat Season -- 3.2 Spatial Verification Results Using Climatology as a Reference Forecast -- 3.2.1 Sea-Ice Concentration Forecasts Relative to Climatology -- 3.2.2 Sea-Ice Thickness Forecasts Relative to Climatology -- 3.2.3 Sea-Ice Drift Speed Forecasts Relative to Climatology -- 3.3 Spatial Verification Results with Persistence as a Reference Forecast -- 3.3.1 Sea-Ice Concentration Forecasts Relative to Persistence -- 3.3.2 Sea-Ice Thickness Forecasts Relative to Persistence -- 3.3.3 Sea-Ice Drift Speed Forecasts Relative to Persistence -- 3.4 Trends in Skillful Forecast Fraction Over Forecast Lead Time -- 3.5 Time Series Verification Results -- 3.5.1 Persistence as the Reference Forecast -- 3.5.2 Climatology as the Reference Forecast -- 3.6 Discussion of Time Series Verification -- 3.6.1 Skill Relative to Persistence -- 3.6.2 Skill Relative to Climatology -- 3.7 Closing Comments -- Chapter 4. Incorporating Indigenous Observations in Operational Sea-Ice Information Products: Case Studies from Western Alaska -- 4.1 Introduction -- 4.2 Methods -- 4.2.1 Community Observations Database -- 4.2.2 Extracting Information from Community Reports -- 4.2.3 The Setting of Gambell, AK and Case Study Selection -- 4.2.4 The Setting of Wales, AK and Case Study Selection -- 4.3 Case Study Results -- 4.3.1 Gambell, Alaska 07 May 2011 -- 4.3.2 Wales, Alaska 17 June 2013 -- 4.4 Discussion -- 4.4.1 Gambell Case Study -- 4.4.2 Wales Case Study -- 4.5 Conclusions -- Chapter 5. Conclusions -- 5.1 Summary -- 5.2 Conclusions from Regional Evaluation of the ACNFS -- 5.3 Conclusions from Community-Scale Observation Case Studies -- Appendix -- References.
    Date
    2015-05
    Type
    Thesis
    Collections
    Atmospheric Sciences

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