Understanding the response of tropical cyclone structure to the assimilation of synthetic wind profiles

Lisa R. Bucci, Sharanya J. Majumdar, Robert Atlas, G. David Emmitt, Steve Greco

Research output: Contribution to journalArticlepeer-review

Abstract

This study examines how varying wind profile coverages in the tropical cyclone (TC) core, near environment, and broader synoptic environment affects the structure and evolution of a simulated Atlantic Ocean hurricane through data assimilation. Three sets of observing system simulation experiments are examined in this paper. The first experiment establishes a benchmark for the case study specific to the forecast system used by assimilating idealized profiles throughout the parent domain. The second presents how TC analyses and forecasts respond to varying the coverage of swaths produced by polar-orbiting satellites of idealized wind profiles. The final experiment assesses the role of TC inner-core observations by systematically removing them radially from the center. All observations are simulated from a high-resolution regional nature run of a hurricane and the tropical atmosphere, assimilating with an ensemble square root Kalman filter and using the Hurricane Weather and Research Forecast regional model. Results compare observation impact with the analyses, domainwide and TC-centric error statistics, and TC structural differences among the experiments. The study concludes that the most accurate TC representation is a result of the assimilation of collocated and uniform thermodynamic and kinematics observations. Intensity forecasts are improved with increased inner-core wind observations, even if the observations are only available once daily. Domainwide root-mean-square errors are significantly reduced when the TC is observed during a period of structural change, such as rapid intensification. The experiments suggest the importance of wind observations and the role of inner-core surveillance when analyzing and forecasting realistic TC structure.

Original languageEnglish (US)
Pages (from-to)2031-2047
Number of pages17
JournalMonthly Weather Review
Volume149
Issue number6
DOIs
StatePublished - Jun 2021

Keywords

  • Data assimilation
  • Kalman filters
  • Lidars/Lidar observations
  • Mesoscale models
  • Tropical cyclones

ASJC Scopus subject areas

  • Atmospheric Science

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