Improved Tropical-Cyclone Flight-Level Wind Estimates Using Routine Infrared Satellite Reconnaissance

Knaff, John A.; Longmore, Scott P.; DeMaria, Robert T.; Molenar, Debra A.

doi:10.1175/jamc-d-14-0112.1

Cited by 53 publications

(42 citation statements)

References 41 publications

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“…The variational data‐fitting methodology of the analysis follows that described in Knaff et al () where flight‐level (700 hPa) wind vectors and SFMR wind speeds (corrected to flight level) are analyzed on a polar grid with radial resolution of 2 km and azimuthal resolutions of 10°. The enhancements of wind speeds to flight level and the reductions of the final analysis to a 10‐m marine exposure follow recommendations in Franklin et al ().…”

Section: Data Setmentioning

confidence: 99%

Copolarized and Cross‐Polarized SAR Measurements for High‐Resolution Description of Major Hurricane Wind Structures: Application to Irma Category 5 Hurricane

et al. 2019

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C‐band high‐resolution radar (synthetic aperture radar [SAR]) is the only spaceborne instrument able to probe at very high resolution and over all ocean basins the sea surface under extreme weather conditions. When coanalyzed with Stepped Frequency Microwave Radiometer wind estimates, the radar backscatter signals acquired in major hurricanes from Sentinel‐1 and Radarsat‐2 SAR reveal high sensitivity in the cross‐polarized channel for wind speeds up to 75 m/s. The combination of the two copolarized and cross‐polarized channels can then be used to derive high‐resolution surface wind estimates. The retrieval methods and impacts of intense rainfall are discussed in the context of a Hurricane Irma (2017) case study. On 7 September 2017, Sentinel‐1 measurements intercepted Hurricane Irma when it was at category 5 intensity. When compared to Stepped Frequency Microwave Radiometer, SAR‐derived wind speeds yield bias and root‐mean‐square of about 1.5 and 5.0 m/s, respectively. The retrieved wind structure parameters for the outer core are found to be in agreement with the Best‐Track and combined satellite‐ and aircraft‐based analyses. SAR measurements uniquely describe the inner core and provide independent measurements of the maximum wind speed and the radius of maximum wind. Near the radius of maximum wind a 65‐m/s increase in wind speed in less than 10 km is detected, corresponding to an instantaneous absolute vorticity of order 210 times the Coriolis parameter. Using a parametric Holland model and the environmental surface pressure (1,011 hPa), SAR‐derived wind speeds correspond to a central surface pressure of 918 hPa (921 hPa from the Best‐Track) in Irma's eye.

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Section: Data Setmentioning

confidence: 99%

Copolarized and Cross‐Polarized SAR Measurements for High‐Resolution Description of Major Hurricane Wind Structures: Application to Irma Category 5 Hurricane

et al. 2019

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“…In general, TCs are considered to be intense when they have a small inner-core and/or large outer-core size and weak when they have a large inner-core and/or small outer-core size [Wu et al, 2015;Knaff et al, 2016]. The radius of maximum wind (RMW) and the radius of gale-force wind (R17) are widely used size parameters; the former describes the radius of the near-center extreme wind (inner-core region), and the latter describes the extent of TC outer circulation (outer-core region).…”

Section: Introductionmentioning

confidence: 99%

Tropical cyclone fullness: A new concept for interpreting storm intensity

Guo

Tan

2017

Geophysical Research Letters

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Intensity and size are two crucial factors in determining the destructiveness of a tropical cyclone (TC), but little is known about the relationship between them because of a lack of observations. TC fullness, a new concept, is proposed to quantitatively measure the storm wind structure, which is defined as the ratio of the extent of the outer‐core wind skirt to the outer‐core size of the TC. TC intensity is more strongly correlated with fullness than with other measures comprising just a single size parameter. A scale is introduced to classify TCs into four categories based on TC fullness (FS1 to FS4). Regardless of the specific inner‐core and outer‐core size, the FS4 fullness structure is necessary for an intense TC's development, while category FS1 and FS2 TCs are generally weak. Most major TCs achieve FS4 fullness structure earlier and more frequently than nonmajor TCs. Rapidly increasing fullness favors the intensification of TC.

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“…Cloud-top brightness temperatures have long been correlated with surface wind structure of tropical cyclones [7,8,10,19,43]. More recently, several new techniques have been developed to estimate TC intensity from satellite measured brightness temperature in the northwestern pacific basin [3,16,20,25].…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, it is necessary to "thin" the initial pool of the potential predictors. Note that for the aim of training an objective method of TC intensity estimation without knowing any information of the TC in advance, any variables that represent TC itself are not included, they had been testified as significant in estimating TC wind structure though [7,8,19,35].…”

Section: Multiple Linear Regression Model Developmentmentioning

confidence: 99%

“…Because it is difficult to obtain direct in-situ measurements of TC intensity [2], satellite remote sensing, especially geostationary meteorological satellite (GMS) remote sensing, has been heavily relied upon in related studies and operational forecasts. On the one hand, GMS has higher temporal and spatial resolution compared to polar satellite microwave remote sensing [3][4][5] and air reconnaissance [6][7][8]. On the other hand, GMS could cover the vast tropical ocean continually, and thereby provide valuable datasets concerning the genesis, track, intensity and other well-concerned information about TCs throughout their life cycles.…”

Section: Introductionmentioning

confidence: 99%

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A Multiple Linear Regression Model for Tropical Cyclone Intensity Estimation from Satellite Infrared Images

Zhao

Sun

et al. 2016

Atmosphere

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An objectively trained model for tropical cyclone intensity estimation from routine satellite infrared images over the Northwestern Pacific Ocean is presented in this paper. The intensity is correlated to some critical signals extracted from the satellite infrared images, by training the 325 tropical cyclone cases from 1996 to 2007 typhoon seasons. To begin with, deviation angles and radial profiles of infrared images are calculated to extract as much potential predicators for intensity as possible. These predicators are examined strictly and included into (or excluded from) the initial predicator pool for regression manually. Then, the "thinned" potential predicators are regressed to the intensity by performing a stepwise regression procedure, according to their accumulated variance contribution rates to the model. Finally, the regressed model is verified using 52 cases from 2008 to 2009 typhoon seasons. The R 2 and Root Mean Square Error are 0.77 and 12.01 knot in the independent validation tests, respectively. Analysis results demonstrate that this model performs well for strong typhoons, but produces relatively large errors for weak tropical cyclones.

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Improved Tropical-Cyclone Flight-Level Wind Estimates Using Routine Infrared Satellite Reconnaissance

Cited by 53 publications

References 41 publications

Copolarized and Cross‐Polarized SAR Measurements for High‐Resolution Description of Major Hurricane Wind Structures: Application to Irma Category 5 Hurricane

Copolarized and Cross‐Polarized SAR Measurements for High‐Resolution Description of Major Hurricane Wind Structures: Application to Irma Category 5 Hurricane

Tropical cyclone fullness: A new concept for interpreting storm intensity

A Multiple Linear Regression Model for Tropical Cyclone Intensity Estimation from Satellite Infrared Images

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