Estimating tropical cyclone surface winds: Current status, emerging technologies, historical evolution, and a look to the future

Knaff, John A.; Sampson, Charles R.; Kucas, Matthew E.; Slocum, Christopher J.; Brennan, Michael J.; Meißner, Thomas; Ricciardulli, Lucrezia; Mouche, Alexis; Reul, Nicolás; Morris, Mary; Chirokova, Galina; Caroff, Philippe

doi:10.1016/j.tcrr.2021.09.002

Cited by 53 publications

(32 citation statements)

References 137 publications

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“…The data set contains structural information such as the RMW and the radial extent of wind speeds of 34, 50, and 64 kt in 4 quadrants. Although TC surface wind analyses have improved, uncertainty remains since the frequency of satellite observations is still insufficient, and the estimated wind speed is strongly affected by thick convective clouds and heavy precipitation of TCs (Demuth et al., 2004, 2006; Knaff et al., 2021). The data set for 2000–2018 was used because of the availability of IR BT data and the quality of the extended best‐track data set (Q. Wu & Ruan, 2021).…”

Section: Methodsmentioning

confidence: 99%

Relationship Between Size and Intensity in North Atlantic Tropical Cyclones With Steady Radii of Maximum Wind

Ruan

2022

Geophysical Research Letters

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Tropical cyclone (TC) intensity, which usually means the minimum pressure at sea level or the maximum sustained wind speed at 10 m, is directly related to the potential destructiveness of the TC (Emanuel, 2005), and has received much attention. Tropical cyclone size, meaning the extent of TC impact, is as important as the TC intensity (Irish et al., 2008;Zhai & Jiang, 2014). Tropical cyclones with similar intensities may vary greatly in size (Chavas & Emanuel, 2010;Knaff et al., 2014;Merrill, 1984), particularly the size of the outer region. The integrated kinetic energy (Powell & Reinhold, 2007), which takes both the maximum sustained wind and wind field into account, continues to grow after the TC reaches peak intensity (Musgrave et al., 2012;Wang & Toumi, 2018). Although many studies of TC size and intensity have been performed in the past few decades

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Section: Methodsmentioning

confidence: 99%

Relationship Between Size and Intensity in North Atlantic Tropical Cyclones With Steady Radii of Maximum Wind

Ruan

2022

Geophysical Research Letters

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“…We also assessed the storm-centric gridded CYGNSS dataset [26], currently available for most intense storms in the North Atlantic and Eastern Pacific over 2018-2020. Organizing the CYGNSS data in a storm-centric framework helps facilitate storm analyses of features often used for forecasting, including estimates of the storm size and intensity at 6-hourly intervals and storm evolution [25,53]. While promising, the storm-centric V1.0 dataset has some limitations at this time.…”

Section: Discussionmentioning

confidence: 99%

“…Because of the lower frequency, SMAP wind observations at lower winds (below 10 m/s) are noisier when compared to AMSR2 and WindSat and have not been used in our assessment. All these datasets have been extensively validated at all wind speed regimes, including in hurricanes [21][22][23]25,42]. The radiometers' data are available as L3 gridded datasets on a 0.25 • Earth grid, with daily files including ascending and descending passes (www.remss.…”

Section: Radiometer Wind Productsmentioning

confidence: 99%

“…These 6-hourly storm "snapshots" are composed by aggregating CYGNSS V3.0 YSLF observations within a ±6-h time window. These aggregations help to facilitate the determination of the storm radii critical for forecasting [25,53] as they minimize the presence of gaps between tracks. Figure 13 qualitatively illustrates the storm-centric wind fields for Hurricane Florence for the 6-hourly samples with at least 1000 valid 0.1 • grid points.…”

Section: L3 Cygnss Storm-centric Windsmentioning

confidence: 99%

“…The CYGNSS spatial sampling configuration, with multiple thin tracks with spatial/temporal gaps in between, makes it hard for the users to easily extract a snapshot of information about a storm at a specific time. Additionally, some forecast systems assimilate easy-to-track storm parameters, such as the storm intensity and radii of gale/storm/hurricane-force winds, rather than trackwise wind retrievals [24,25]. These storm parameters can be more easily determined from gridded storm-centric maps.…”

Section: Introductionmentioning

confidence: 99%

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Assessment of CYGNSS Wind Speed Retrievals in Tropical Cyclones

et al. 2021

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The NASA CYGNSS satellite constellation measures ocean surface winds using the existing network of the Global Navigation Satellite System (GNSS) and was designed for measurements in tropical cyclones (TCs). Here, we focus on using a consistent methodology to validate multiple CYGNSS wind data records currently available to the public, some focusing on low to moderate wind speeds, others for high winds, a storm-centric product for TC analyses, and a wind dataset from NOAA that applies a track-wise bias correction. Our goal is to document their differences and provide guidance to users. The assessment of CYGNSS winds (2017–2020) is performed here at global scales and for all wind regimes, with particular focus on TCs, using measurements from radiometers that are specifically developed for high winds: SMAP, WindSat, and AMSR2 TC-winds. The CYGNSS high-wind products display significant biases in TCs and very large uncertainties. Similar biases and large uncertainties were found with the storm-centric wind product. On the other hand, the NOAA winds show promising skill in TCs, approaching a level suitable for tropical meteorology studies. At the global level, the NOAA winds are overall unbiased at wind regimes from 0–30 m/s and were selected for a test assimilation into a global wind analysis, CCMP, also presented here.

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Diurnal variations of tropical cyclone outer region size growth

Hong

2023

Atmospheric Science Letters

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Various aspects of tropical cyclones (TCs) fluctuate with the diurnal cycle. TC size is critical to the extent of its damage, but diurnal variations in the growth of the outer region size have largely remained unexplored. This paper examines the diurnal variations in the growth of the radius of gale‐force winds (34 kt; R34) by analyzing best‐track data from 2001 to 2019 for both North Atlantic TCs and global TCs outside of the North Atlantic region. Statistically significant diurnal variations was found for R34 growth, with the maximum 6‐h growth rate occurring at 2100–0300 local solar time (LST) for North Atlantic TCs, and at 0300–0900 LST for global TCs excluding the North Atlantic which experienced rapid intensification (≥30 knots within 24 h). The higher R34 6‐h growth rates during the night were linked to a larger extent of very deep convective clouds with infrared brightness temperatures <208 K during this time.

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Estimating tropical cyclone surface winds: Current status, emerging technologies, historical evolution, and a look to the future

Cited by 53 publications

References 137 publications

Relationship Between Size and Intensity in North Atlantic Tropical Cyclones With Steady Radii of Maximum Wind

Relationship Between Size and Intensity in North Atlantic Tropical Cyclones With Steady Radii of Maximum Wind

Assessment of CYGNSS Wind Speed Retrievals in Tropical Cyclones

Diurnal variations of tropical cyclone outer region size growth

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