GPS Dropwindsonde Wind Profiles in Hurricanes and Their Operational Implications

Franklin, James L.; Black, Mark M.; Valde, Krystal

doi:10.1175/1520-0434(2003)018<0032:gdwpih>2.0.co;2

Cited by 341 publications

(274 citation statements)

References 14 publications

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“…Otherwise, most intensity observations are based on the Dvorak (1984) technique. Franklin et al (2003) note the uncertainties associated with estimating intensity from aircraft flight level or dropsonde measurements. Brown and Franklin (2004) report an 11-kt rms error for Dvorak estimates when compared with more reliable aircraft-based estimates.…”

Section: A Best-track Datamentioning

confidence: 99%

Passive-Microwave-Enhanced Statistical Hurricane Intensity Prediction Scheme

Jones

Cecil

DeMaria

2006

Weather and Forecasting

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The formulation and testing of an enhanced Statistical Hurricane Intensity Prediction Scheme (SHIPS) using new predictors derived from passive microwave imagery is presented. Passive microwave imagery is acquired for tropical cyclones in the Atlantic and eastern North Pacific basins between 1995 and 2003. Predictors relating to the inner-core (within 100 km of center) precipitation and convective characteristics of tropical cyclones are derived. These predictors are combined with the climatological and environmental predictors used by SHIPS in a simple linear regression model with change in tropical cyclone intensity as the predictand. Separate linear regression models are produced for forecast intervals of 12, 24, 36, 48, 60, and 72 h from the time of a microwave sensor overpass. Analysis of the resulting models indicates that microwave predictors, which provide an intensification signal to the model when above-average precipitation and convective signatures are present, have comparable importance to vertical wind shear and SSTrelated predictors. The addition of the microwave predictors produces a 2%-8% improvement in performance for the Atlantic and eastern North Pacific tropical cyclone intensity forecasts out to 72 h when compared with an environmental-only model trained from the same sample. Improvement is also observed when compared against the current version of SHIPS. The improvement in both basins is greatest for substantially intensifying or weakening tropical cyclones. Improvement statistics are based on calculating the forecast error for each tropical cyclone while it is held out of the training sample to approximate the use of independent data.

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Section: A Best-track Datamentioning

confidence: 99%

Passive-Microwave-Enhanced Statistical Hurricane Intensity Prediction Scheme

Jones

Cecil

DeMaria

2006

Weather and Forecasting

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“…The wind quickly slows down as it approaches the sea surface (Franklin et al, 2003). Using such data, it is possible to make a comparison between the vertical wind profiles of the western north Pacific Tropical Storm Aere and the Atlantic hurricanes.…”

Section: Dropsonde Observation Of a Tropical Cyclonementioning

confidence: 99%

“…5, 6 and 7, located approximately near the eyewall of the TC, can be used for this purpose. With reference to the statistics for the Atlantic hurricanes provided by Franklin et al (2003), the low-level winds from the three dropsondes representing the eyewall are normalised at 700hPa (an altitude of about 3100m). The results are shown in Figure 5.…”

Section: Dropsonde Observation Of a Tropical Cyclonementioning

confidence: 99%

The first complete dropsonde observation of a tropical cyclone over the South China Sea by the Hong Kong Observatory

Chan

Zhang

et al. 2018

Weather

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For the first time, Hong Kong Observatory conducted a full scale dropsonde observation of the circulation of a tropical cyclone, namely, Tropical Storm Aere, on 7 October 2016, over the northern part of the South China Sea. This paper documents the observations and their use in the prediction of the track and strength of the tropical cyclone in a numerical weather prediction model. In addition to the model analysis fields, the dropsonde observations are found to provide further information about the structure of Aere. The quality of the dropsonde data was found to be satisfactory in comparison with the radiosonde data nearby. The dropsonde data were found to have a positive impact on the prediction of the track of the tropical cyclone, improving track location accuracy by about 13%. The prediction of the strength of Aere was found to have a higher dependence on the assimilation of the wind field than the assimilation of the humidity field.

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“…Doyle et al (2017) summarize the TCI flights and datasets. From the quality controlled dropsonde wind profiles, a layer-average wind speed is computed over the lowest 150 m of the profile (WL150), or the lowest 500 m (MBL, for mean boundary layer) if low level data are unavailable (Franklin et al 2003). This averaging removes some of the effect of gustiness in the dropsonde wind profile.…”

Section: Comparison With Dropsondesmentioning

confidence: 99%

“…2. Otherwise it is estimated as 80% of the MBL value, following Franklin et al (2003). Comparisons were made using any dropsonde that supported such a surface wind estimate, with its lowest reported location within the +/−60° swath from HIRAD.…”

Section: Comparison With Dropsondesmentioning

confidence: 99%

Assimilating Global Wave Model Predictions and Deep-Water Wave Observations in Nearshore Swell Predictions

Cecil

Biswas

2017

Journal of Atmospheric and Oceanic Technology

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Surface wind speed retrievals have been generated and evaluated using Hurricane Imaging Radiometer (HIRAD) measurements from flights over Hurricane Joaquin, Hurricane Patricia, Hurricane Marty, and the remnants of Tropical Storm Erika, all in 2015. Procedures are described here for producing maps of brightness temperature, which are subsequently used for retrievals of surface wind speed and rain rate across a ~50 km wide swath for each flight leg. An iterative retrieval approach has been developed to take advantage of HIRAD’s measurement characteristics. Validation of the wind speed retrievals has been conducted, using 636 dropsondes released from the same WB-57 high altitude aircraft carrying HIRAD during the Tropical Cyclone Intensity (TCI) experiment. The HIRAD wind speed retrievals exhibit very small bias relative to the dropsondes, for winds tropical storm strength (17.5 m s−1) or greater. HIRAD has reduced sensitivity to winds weaker than tropical storm strength, and a small positive bias (~2 m s−1) there. Two flights with predominantly weak winds according to the dropsondes have abnormally large errors from HIRAD, and large positive biases. From the other flights, root mean square differences between HIRAD and the dropsonde winds are 4.1 m s−1 (33%) for winds below tropical storm strength, 5.6 m s−1 (25%) for tropical storm strength winds, and 6.3 m s−1 (16%) for hurricane strength winds. Mean absolute differences for those categories are 3.2 m s−1 (25%), 4.3 m s−1 (19%), and 4.8 m s−1 (12%), with bias near zero for tropical storm and hurricane strength winds.

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GPS Dropwindsonde Wind Profiles in Hurricanes and Their Operational Implications

Cited by 341 publications

References 14 publications

Passive-Microwave-Enhanced Statistical Hurricane Intensity Prediction Scheme

Passive-Microwave-Enhanced Statistical Hurricane Intensity Prediction Scheme

The first complete dropsonde observation of a tropical cyclone over the South China Sea by the Hong Kong Observatory

Assimilating Global Wave Model Predictions and Deep-Water Wave Observations in Nearshore Swell Predictions

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