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Abstract The radius of maximum wind (Rmax) in a tropical cyclone governs the footprint of hazards, including damaging wind, surge, and rainfall. However,Rmaxis an inconstant quantity that is difficult to observe directly and is poorly resolved in reanalyses and climate models. In contrast, outer wind radii are much less sensitive to such issues. Here we present a simple empirical model for predictingRmaxfrom the radius of 34-kt (1 kt ≈ 0.51 m s−1) wind (R17.5 ms). The model only requires as input quantities that are routinely estimated operationally: maximum wind speed,R17.5 ms, and latitude. The form of the empirical model takes advantage of our physical understanding of tropical cyclone radial structure and is trained on the Extended Best Track database from the North Atlantic 2004–20. Results are similar for the TC-OBS database. The physics reduces the relationship between the two radii to a dependence on two physical parameters, while the observational data enables an optimal estimate of the quantitative dependence on those parameters. The model performs substantially better than existing operational methods for estimatingRmax. The model reproduces the observed statistical increase inRmaxwith latitude and demonstrates that this increase is driven by the increase inR17.5 mswith latitude. Overall, the model offers a simple and fast first-order prediction ofRmaxthat can be used operationally and in risk models. Significance StatementIf we can better predict the area of strong winds in a tropical cyclone, we can better prepare for its potential impacts. This work develops a simple model to predict the radius where the strongest winds in a tropical cyclone are located. The model is simple and fast and more accurate than existing models, and it also helps us to understand what causes this radius to vary in time, from storm to storm, and at different latitudes. It can be used in both operational forecasting and models of tropical cyclone hazard risk.
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Reexamining the Estimation of Tropical Cyclone Radius of Maximum Wind from Outer Size with an Extensive Synthetic Aperture Radar Dataset
Abstract The radius of maximum windRmax, an important parameter in tropical cyclone (TC) ocean surface wind structure, is currently resolved by only a few sensors so that, in most cases, it is estimated subjectively or via crude statistical models. Recently, a semiempirical model relying on an outer wind radius, intensity, and latitude was fit to best-track data. In this study we revise this semiempirical model and discuss its physical basis. While intensity and latitude are taken from best-track data,Rmaxobservations from high-resolution (3 km) spaceborne synthetic aperture radar (SAR) and wind radii from an intercalibrated dataset of medium-resolution radiometers and scatterometers are considered to revise the model coefficients. The new version of the model is then applied to the period 2010–20 and yieldsRmaxreanalyses and trends that are more accurate than best-track data. SAR measurements corroborate that fundamental conservation principles constrain the radial wind structure on average, endorsing the physical basis of the model. Observations highlight that departures from the average conservation situation are mainly explained by wind profile shape variations, confirming the model’s physical basis, which further shows that radial inflow, boundary layer depth, and drag coefficient also play roles. Physical understanding will benefit from improved observations of the near-core region from accumulated SAR observations and future missions. In the meantime, the revised model offers an efficient tool to provide guidance onRmaxwhen a radiometer or scatterometer observation is available, for either operations or reanalysis purposes.
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- Award ID(s):
- 1945113
- PAR ID:
- 10521565
- Publisher / Repository:
- American Meteorological Society
- Date Published:
- Journal Name:
- Monthly Weather Review
- Volume:
- 151
- Issue:
- 12
- ISSN:
- 0027-0644
- Page Range / eLocation ID:
- 3169 to 3189
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1175/MWR-D-23-0119.1
