Advanced Sea Ice Modeling for Short-Term Forecasting for Alaska’s Coasts

Details

• Journal Title:
  Weather and Forecasting
• Personal Author:
  Fujisaki-Manome, Ayumi ; Hu, Haoguo ; Wang, Jia ; Westerink, Joannes J. ; Wirasaet, Damrongsak ; Ling, Guoming ; Choi, Mindo ; Moghimi, Saeed ; Myers, Edward ; Abdolali, Ali ; Dawson, Clint ; Janzen, Carol
• NOAA Program & Office:
  NOS (National Ocean Service) ; NWS (National Weather Service) ; OAR (Oceanic and Atmospheric Research) ; CIGLR (Cooperative Institute for Great Lakes Research) ; EMC (Environmental Modelling Center) ; GLERL (Great Lakes Environmental Research Laboratory) ; NCEP (National Centers for Environmental Prediction) ; OCS (Office of Coast Survey)
• Description:
  In Alaska’s coastal environment, accurate information of sea ice conditions is desired by operational forecasters, emergency managers, and responders. Complicated interactions among atmosphere, waves, ocean circulation, and sea ice collectively impact the ice conditions, intensity of storm surges, and flooding, making accurate predictions challenging. A collaborative work to build the Alaska Coastal Ocean Forecast System established an integrated storm surge, wave, and sea ice model system for the coasts of Alaska, where the verified model components are linked using the Earth System Modeling Framework and the National Unified Operational Prediction Capability. We present the verification of the sea ice model component based on the Los Alamos Sea Ice Model, version 6. The regional, high-resolution (3 km) configuration of the model was forced by operational atmospheric and ocean model outputs. Extensive numerical experiments were conducted from December 2018 to August 2020 to verify the model’s capability to represent detailed nearshore and offshore sea ice behavior, including landfast ice, ice thickness, and evolution of air–ice drag coefficient. Comparisons of the hindcast simulations with the observations of ice extent presented the model’s comparable performance with the Global Ocean Forecast System 3.1 (GOFS3.1). The model’s skill in reproducing landfast ice area significantly outperformed GOFS3.1. Comparison of the modeled sea ice freeboard with the Ice, Cloud, and Land Elevation Satellite-2 product showed a mean bias of −4.6 cm. Daily 5-day forecast simulations for October 2020–August 2021 presented the model’s promising performance for future implementation in the coupled model system.
• Source:
  Weather and Forecasting, 39(5), 793-806
• DOI:
  https://doi.org/10.1175/WAF-D-23-0178.1
• ISSN:
  0882-8156 ; 1520-0434
• Format:
  PDF
• Publisher:
  American Meteorological Society
• Document Type:
  Journal Article
• Funding:
  Grant no. NA22OAR4320150 ; Grant no. NA18NOS0120164
• Rights Information:
  Other
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha-512:a1326fe43cced16a68ae4e879062e305465938862a669cae5a989bb5696c3119204fd92e335e255b5e1e740c94afc566538d9bdf45cae546d6bd98f8e1277e89
• Download URL:
  https://repository.library.noaa.gov/view/noaa/65960/noaa_65960_DS1.pdf
• File Type:
  [PDF - 31.77 MB ]