Details:

Alternative Title:
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.
Journal Title:
Monthly Weather Review
Personal Author:
Bucci, Lisa R. ; Majumdar, Sharanya J. ; Atlas, Robert ; Emmitt, G. David ; Greco, Steve
Bucci, Lisa R. ; Majumdar, Sharanya J. ; Atlas, Robert ; Emmitt, G. David ; Greco, Steve Less -
NOAA Program & Office:
OAR (Oceanic and Atmospheric Research) ; AOML (Atlantic Oceanographic and Meteorological Laboratory)
OAR (Oceanic and Atmospheric Research) ; AOML (Atlantic Oceanographic and Meteorological Laboratory) Less -
Description:
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.
Keywords:
[+]
Cyclones Data Assimilation Kalman Filters Lidar Mesoscale Models Quantitative Observing System Assessment Program (QOSAP)
Source:
Monthly Weather Review, 149(6), 2031-2047
DOI:
https://doi.org/10.1175/MWR-D-20-0153.1
Document Type:
Journal Article
Rights Information:
Other
Compliance:
Submitted
Main Document Checksum:
[+]
urn:sha256:b412ba8a13fa16cacd78f06a11a460212b49e8fa3e56bc631dcb5c6294d74fed
Download URL:
https://repository.library.noaa.gov/view/noaa/30012/noaa_30012_DS1.pdf
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