Seasonal predictability of sea ice and boreal fire in Alaska

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Author
Borries-Strigle, Cecilia
Chair
Bhatt, Uma S.
Committee
Bieniek, Peter
McMonigal, Kay
Polyakov, Igor
Keyword
Wildfire forecasting
Sea ice
Bering Sea
Ocean heat
Metadata
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URI
http://hdl.handle.net/11122/16244
Abstract
Attribution studies have shown that warming Arctic temperatures have led to a substantial loss of sea ice and an increase in large wildfire seasons. With wildfire and sea ice decline impacting everyday life by disrupting transportation or damaging infrastructure, for example, a clear need for skillful forecasts at seasonal timescales has emerged. This dissertation addresses critical challenges in seasonal prediction for wildfire and sea ice in Alaska. The first study evaluates outlooks of Buildup Index derived from three seasonal forecasts to assess their skill in predicting fire conditions. Forecast skill is greatest during the wind (April 1-June 10) and drought (July 21-August 9) fire subseasons and in the Western Boreal subregion of Alaska. Combining the forecasts into a multimodel ensemble substantially improves skill. Next, the same seasonal forecasts undergo a comprehensive evaluation of temperature and precipitation in Alaska. While forecasts exhibit similar biases in average precipitation, biases in average temperature vary among the models. However, wrong forecasts for all models tend to forecast temperature anomalies that are too warm. Case studies of good and bad forecast years suggest that forecast skill is influenced by the strength of teleconnection indices relevant to Alaska climate. The final study quantifies impacts of anomalous ocean heat content (OHC) in the Bering Sea and ocean heat transport through the Bering Strait on September Arctic sea ice concentrations (SIC). The addition of one-time OHC anomalies in the Bering Sea results in enhanced SIC decreases along the shallow continental shelves near Alaska but increases on the order of ~10% in the Central Arctic. Increasing SIC is modeled by suppressed upward heat flux and atmospheric forcing. This research was conducted in collaboration with community partners, and their sustained engagement ensured that the resulting tools and insights were scientifically robust and directly relevant to operational decision making.
Description
Dissertation (Ph.D.) University of Alaska Fairbanks, 2025
Table of Contents
Chapter 1: General introduction -- 1.1 Motivation -- 1.2 A very brief history of seasonal forecasting -- 1.3 Chapter overviews -- 1.3.1 On using dynamical seasonal forecasts to develop management-driven wildland fire outlooks in Alaska -- 1.3.2 Evaluation of summer temperature and precipitation in Alaska from dynamical seasonal forecasts -- 1.3.3 Impacts of anomalous Bering Strait heat transport on regional Arctic sea ice -- 1.4 Summary -- 1.5 References. Chapter 2: On using dynamical seasonal forecasts to develop management-driven wildland fire outlooks in Alaska -- 2.1 Abstract -- 2.2 Practical implications -- 2.3 Introduction -- 2.4 Materials -- 2.4.1 Canadian fire weather index system -- 2.4.2 Observational domain and station data -- 2.4.3 Seasonal forecast data -- 2.5 Methods -- 2.6 Results -- 2.6.1 Model comparisons with station observations -- 2.6.1.1 Temperature biases -- 2.6.1.2 Precipitation biases -- 2.6.2 Model metrics -- 2.6.2.1 Root mean square error (RMSE) -- 2.6.2.2 Interquartile range (IQR) -- 2.6.3 Seasonal forecast skill -- 2.6.3.1 Area under the ROC curve (AUROC) -- 2.6.3.2 Heidke skill score (HSS) -- 2.6.4 Annual forecast skill -- 2.6.4.1 Regional patterns -- 2.6.4.2 Large fire years -- 2.6.4.3 ANSO years -- 2.7 Discussions -- 2.7.1 Summary of forecast skill across metrics -- 2.7.2 Spring predictability barrier and subseasonal skill -- 2.7.3 Performance in large fire years and ENSO conditions -- 2.7.4 Comparison with previous studies and forecat adjustments -- 2.7.5 Limitations of forecasting in Alaska and high latitudes -- 2.7.6 Toward a comprehensive seasonal outlook framework -- 2.8 Conclusions -- 2.9 References. Chapter 3: Evaluation of summer temperature and precipitation in Alaska from dynamical seasonal forecasts -- 3.1 Abstract -- 3.2 Introduction -- 3.3 Data and methods -- 3.3.1 Observational data -- 3.3.2 Seasonal forecast and reanalysis data -- 3.3.3 Mean biases -- 3.3.4 Temperature and precipitation distributions -- 3.3.5 Anomaly correlations -- 4.4.6 Teleconnection indices and self-organizing maps -- 3.4 Results -- 3.4.1 Mean biases -- 3.4.2 Evaluation of temperature and precipitation distributions -- 3.4.3 Correlations of forecast anomalies with ERA5 -- 3.4.4 Case studies -- 3.4.4.1 2004 case study -- 3.4.4.2 2010 case study -- 3.5 Discussion -- 3.5.1 Model biases -- 3.5.2 Case studies -- 3.6 Conclusions -- 3.7 References. Chapter 4: Impacts of anomalous Bering Strait heat transport on regional Arctic sea ice -- 4.1 Abstract -- 4.2 Introduction -- 4.3 Data and methods -- 4.3.1 Model description -- 4.3.2 LENS2 data -- 4.3.3 LENS2 evaluation -- 4.3.4 Bering Sea ocean heat content experiments -- 4.4 Results -- 4.4.1 LENS2 evaluation -- 4.4.2 +2x July OHC experiment results -- 4.4.2.1 Arctic ocean heat content -- 4.4.2.2 Arctic sea ice concentration -- 4.4.2.3 Regional results -- 4.4.2.3.2 East Siberian Sea -- 4.4.2.3.3 Chukchia Sea -- 4.4.2.3.4 Beaufort Sea and Northern Canadian Coast -- 4.4.2.3.5 Central Arctic -- 4.4.3 Role of stratification on sea ice response -- 4.5 Discussion -- 4.5.1 Arctic shelf sea ice response to Bering OHC -- 4.5.2 Central Arctic sea ice response to Bering OHC -- 4.5.3 Potential role of tropical variability -- 4.6 Conclusions -- 4.7 References. Chapter 5: General conclusions -- 5.1 Summary -- 5.2 Conclusions for chapter 2 -- 5.3 Conclusions for chapter 3 -- 5.4 Conclusions for chapter 4 -- 5.5 Key conclusions and future work.
Date
2025-08
Type
Dissertation
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