Toward the development of a multi-scale ensemble-based data assimilation system to improve tropical cyclone analysis and prediction

Abstract

Funds are provided to perform research on scale-dependent localization (SDL) for multi-scale data assimilation for tropical cyclones (TCs). The PI will collaborate with NRL colleagues who are currently developing the LETKF for the Navy Global Environmental Model (NAVGEM). In collaboration with NRL, the PI plans to implement the SDL approach in the context of LETKF and conduct experiments with a statistical TC model. The following questions will be addressed: (1) What would be the best way to implement local multi-scale ETKF (LMETKF)? (2) Will SDL provide a better estimate of the TC and its environment compared to a fixed localization? (3) How would the impact be dependent on the observation network? (4) What is the impact of allowing cross-scale correlation on the accuracy of the analysis? The findings from the proposed work will help guide the future development of the multi-scale ensemble data assimilation for future Navy prediction systems.

Document Details

Document Type
DoD Grant Award
Publication Date
Jul 26, 2018
Source ID
N000141812666

Entities

People

  • Xuguang Wang

Organizations

  • Office of Naval Research
  • United States Navy
  • University of Oklahoma

Tags

Fields of Study

  • Environmental science

Readers

  • Artificial Intelligence
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers