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Recent advancements for tropical cyclone data assimilation

In this review, data assimilation (DA) techniques used for tropical cyclones (TCs) are briefly overviewed. The strength and weakness of variational methods, ensemble methods, hybrid methods, and particle filter methods are also discussed. Several global numerical weather prediction models and their...

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Published in:Annals of the New York Academy of Sciences 2022-11, Vol.1517 (1), p.25-43
Main Authors: Christophersen, Hui, Sippel, Jason, Aksoy, Altug, Baker, Nancy L.
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Language:English
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description In this review, data assimilation (DA) techniques used for tropical cyclones (TCs) are briefly overviewed. The strength and weakness of variational methods, ensemble methods, hybrid methods, and particle filter methods are also discussed. Several global numerical weather prediction models and their corresponding DA systems frequently used for TC forecasting and verification are described first. The DA research and development efforts in the operational regional model from the National Centers for Environmental Prediction's Hurricane Weather Research and Forecasting are then discussed in greater detail. Focused remarks on TC observations from reconnaissance, ground‐based radar, enhanced satellite‐derived atmospheric motion vectors and all‐sky satellite radiances and their impacts on TC analyses and forecasts are addressed. Recent TC DA advancements and challenges on better use of observations and more advanced DA methods for TC application are also briefly reviewed. Here we review the contemporary data assimilation (DA) techniques used for tropical cyclones (TCs). We also review several global operational models frequently used for TC verification, with an emphasis on efforts to improve TC analyses and forecasts. We discuss in detail the DA research and development efforts for the operational model Hurricane Research and Forecasting. We also review specialized TC observations, such as high‐resolution reconnaissance observations from crewed or uncrewed aircraft systems, coastal ground‐based radars, etc. We conclude by highlighting the advancements and challenges for TC DA.
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subjects Atmospheric models
Cyclones
data assimilation
Data collection
Global weather
Ground-based observation
Hurricanes
Numerical prediction
Numerical weather forecasting
numerical weather prediction
Prediction models
R&D
Regional development
Research & development
tropical cyclone
Tropical cyclones
Variational methods
Weather forecasting
title Recent advancements for tropical cyclone data assimilation
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