Impact of Assimilating Satellite and Glider Observations on Hurricane Isaias (2020) Forecast Using Marine JEDI

Ling Liu, Avichal Mehra, Daryl Kleist, Guillaume Vernieres, Travis Sluka, Kriti Bhargava, Patrick Stegmann, Hyun Sook Kim, Shastri Paturi, Jiangtao Xu, Ilya Rivin

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Realistic ocean initial conditions are essential for coupled hurricane forecasts. This study focuses on the impact of assimilating high-resolution ocean observations for initialization of the Modular Ocean Model (MOM6) in a coupled configuration with the Hurricane Analysis and Forecast System (HAFS). Based on the Joint Effort for Data Assimilation Integration (JEDI) framework, numerical experiments were performed for the Hurricane Isaias (2020) case, a category-1 hurricane, with use of underwater glider datasets and satellite observations. Assimilation of ocean glider data together with satellite observations provides opportunity to further advance understanding of ocean conditions and air–sea interactions in coupled model initialization and hurricane forecast systems. This comprehensive data assimilation approach has led to a more accurate prediction of the salinity-induced barrier layer thickness that suppresses vertical mixing and sea surface temperature cooling during the storm. Increased barrier layer thickness enhances ocean enthalpy flux into the lower atmosphere and potentially increases tropical cyclone intensity. Assimilation of satellite observations demonstrates improvement in Hurricane Isaias’s intensity forecast. Assimilating glider observations with broad spatial and temporal coverage along Isaias’s track in addition to satellite observations further increase Isaias’s intensity forecast. Overall, this case study demonstrates the importance of assimilating comprehensive marine observations to a more robust ocean and hurricane forecast under a unified JEDI–HAFS hurricane forecast system. SIGNIFICANCE STATEMENT: This is the first comprehensive study of marine observations’ impact on hurricane forecast using marine JEDI. This study found that assimilating satellite observations increases upper-ocean stratification during the prestorm period of Isaias. Assimilating preprocessed observations from six gliders increases salinity-induced upper ocean barrier layer thickness, which reduces sea surface temperature cooling and increases enthalpy flux during the storm. This mechanism eventually enhances hurricane intensity forecast. Overall, this study demonstrates a positive impact of assimilating comprehensive marine observations to a successful ocean and hurricane forecast under a unified JEDI–HAFS hurricane forecast system.

Original languageEnglish
Pages (from-to)1807-1826
Number of pages20
JournalWeather and Forecasting
Volume38
Issue number9
DOIs
StatePublished - Sep 1 2023

Keywords

  • Atmosphere-ocean interaction
  • Data assimilation
  • Forecast verification/skill
  • Model initialization
  • Oceanic mixed layer
  • Tropical cyclones

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