Estimation of Tropical Cyclone's Intensity Using TRMM/TMI Brightness Temperature Data

Hoshino, Shunsuke; Nakazawa, Tetsuo

doi:10.2151/jmsj.85.437

Cited by 29 publications

(24 citation statements)

References 12 publications

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“…The rain rate was found to be a function of the current TC intensity, and not the subsequent 24-h intensity change. The correlation of rain rates with TC intensity has also been emphasized by Cecil and Zipser (1999) and Hoshino and Nakazawa (2007). As such, in both basins the weakening composite had the largest rain rates, followed by the RI composite, while the intensifying and neutral composites had similar rain rates.…”

Section: K Rain Ratementioning

confidence: 80%

Quantifying Environmental Control on Tropical Cyclone Intensity Change

Hendricks¹,

Peng²,

et al. 2010

Monthly Weather Review

215

169

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Composite analysis is used to examine environmental and climatology and persistence characteristics of tropical cyclones (TCs) undergoing different intensity changes in the western North Pacific (WPAC) and North Atlantic (ATL) ocean basins. Using the cumulative distribution functions of 24-h intensity changes from the 2003-08 best-track data, four intensity change bins are defined: rapidly intensifying (RI), intensifying, neutral, and weakening. The Navy Operational Global Atmospheric Prediction System daily 0000 and 1200 UTC global analysis and Tropical Rainfall Measuring Mission Microwave Imager data are then used as proxies for the real atmosphere, and composites of various environmental fields believed relevant to TC intensity change are made in the vicinity of the TCs. These composites give the average characteristics near the TC, prior to undergoing a given intensity change episode.For the environmental variables, statistically significant differences are examined between RI storms and the other groups. While some environmental differences were found between RI and weakening/neutral TCs in both basins, an interesting result from this study is that the environment of RI TCs and intensifying TCs is quite similar. This indicates that the rate of intensification is only weakly dependent on the environmental conditions, on average, provided the environment is favorable. Notable exceptions were that in the WPAC, RI events occurred in environments with significantly larger conditional instability than intensifying events. In the ATL, RI events occurred in environments with weaker deep-layer shear than intensifying events. An important finding of this work is that SSTs are similar between intensifying and rapidly intensifying TCs, indicating that the rate of intensification is not critically dependent on SST.The TCs in both basins were more intense prior to undergoing an RI episode than an intensifying or neutral episode. In the WPAC, the three groups had similar translational speeds and headings, and average initial position. In the ATL, RI storms were located farther south than intensifying and neutral storms, and had a larger translational speed and a more westward component to the heading.

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Section: K Rain Ratementioning

confidence: 80%

Quantifying Environmental Control on Tropical Cyclone Intensity Change

Hendricks¹,

Peng²,

et al. 2010

Monthly Weather Review

215

169

View full text Add to dashboard Cite

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“…Cecil and Zipser [38] find that the inner core average 85-GHz polarization corrected temperature (PCT) is correlated with the intensity. Hoshino and Nakazawa [39] find that the minimum 10-GHz horizontally polarized brightness temperature within 0.5° distance of the center has the highest correlation with intensity. They also find that the averaged 10-GHz horizontally polarized brightness temperature within 1° of the center is correlated with intensity.…”

Section: Satellite Remote Sensing Of Intensitymentioning

confidence: 95%

Remote Sensing and Modeling of Cyclone Monica near Peak Intensity

Durden

2010

Atmosphere

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Cyclone Monica was an intense Southern Hemisphere tropical cyclone of 2006.Although no in situ measurements of Monica's inner core were made, microwave, infrared, and visible satellite instruments observed Monica before and during peak intensity through landfall on Australia's northern coast. The author analyzes remote sensing measurements in detail to investigate Monica's intensity. While Dvorak analysis of its imagery argues that it was of extreme intensity, infrared and microwave soundings indicate a somewhat lower intensity, especially as it neared landfall. The author also describes several numerical model runs that were made to investigate the maximum possible intensity for the observed environmental conditions; these simulations also suggest a lower intensity than estimates from Dvorak analysis alone. Based on the evidence from the various measurements and modeling, the estimated range for the minimum sea level pressure at peak intensity is 900 to 920 hPa. The estimated range for the one-minute averaged maximum wind speed at peak intensity is 72 to 82 m/s. These maxima were likely reached about 24 hours prior to landfall, with some weakening occurring afterward.

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“…Many well-calibrated ocean emissivity models have been developed for passive microwave radiometers (Stogryn 1967;Wilheit 1979;Wentz et al 1986;Wentz and Meissner 2000) and applied to a number of passive satellite sensors, including the TRMM Microwave Imager (TMI), the Special Sensor Microwave Imager (SSM/I), Special Sensor Microwave Imager/Sounder (SSMIS), and the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) sensor on board the Aqua satellite. A method for estimating the TC intensity utilizing TMI data, based on a multiple regression technique, has also been developed (Hoshino and Nakazawa 2007). In addition, Saitoh and Shibata (2010) described a method for estimating the W S using horizontal T B at 6.925-and 10.65-GHz channels of AMSR-E on board the Aqua satellite.…”

Section: Introductionmentioning

confidence: 99%

A Unique Satellite-Based Sea Surface Wind Speed Algorithm and Its Application in Tropical Cyclone Intensity Analysis

Hong

Seo

Kwon

2016

Journal of Atmospheric and Oceanic Technology

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This study proposes a sea surface wind speed retrieval algorithm (the Hong wind speed algorithm) for use in rainy and rain-free conditions. It uses a combination of satellite-observed microwave brightness temperatures, sea surface temperatures, and horizontally polarized surface reflectivities from the fast Radiative Transfer for TOVS (RTTOV), and surface and atmospheric profiles from the European Centre for MediumRange Weather Forecasts (ECMWF). Regression relationships between satellite-observed brightness temperature and satellite-simulated brightness temperatures, satellite-simulated brightness temperatures, rough surface reflectivities, and between sea surface roughness and sea surface wind speed are derived from the Advanced Microwave Scanning Radiometer 2 (AMSR-2). Validation results of sea surface wind speed between the proposed algorithm and the Tropical Atmosphere Ocean (TAO) data show that the estimated bias and RMSE for AMSR-2 6.925-and 10.65-GHz bands are 0.09 and 1.13 m s 21 , and 20.52 and 1.21 m s 21 , respectively. Typhoon intensities such as the current intensity (CI) number, maximum wind speed, and minimum pressure level based on the proposed technique (the Hong technique) are compared with best-track data from the Japan Meteorological Agency (JMA), the Joint Typhoon Warning Center (JTWC), and the Cooperative Institute for Mesoscale Meteorological Studies (CIMSS) for 13 typhoons that occurred in the northeastern Pacific Ocean throughout 2012. Although the results show good agreement for low-and medium-range typhoon intensities, the discrepancy increases with typhoon intensity. Consequently, this study provides a useful retrieval algorithm for estimating sea surface wind speed, even during rainy conditions, and for analyzing characteristics of tropical cyclones.

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Estimation of Tropical Cyclone's Intensity Using TRMM/TMI Brightness Temperature Data

Cited by 29 publications

References 12 publications

Quantifying Environmental Control on Tropical Cyclone Intensity Change

Quantifying Environmental Control on Tropical Cyclone Intensity Change

Remote Sensing and Modeling of Cyclone Monica near Peak Intensity

A Unique Satellite-Based Sea Surface Wind Speed Algorithm and Its Application in Tropical Cyclone Intensity Analysis

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