Evaluating Environmental Impacts on Tropical Cyclone Rapid Intensification Predictability Utilizing Statistical Models

Kaplan, John; Rozoff, Christopher M.; DeMaria, Mark; Sampson, Charles R.; Kossin, James P.; Velden, Christopher S.; Cione, Joseph J.; Dunion, Jason; Knaff, John A.; Zhang, Jun A.; Dostalek, John F.; Hawkins, Jeffrey D.; Lee, Thomas F.; Solbrig, Jeremy E.

doi:10.1175/waf-d-15-0032.1

Cited by 172 publications

(187 citation statements)

References 45 publications

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“…Despite recent advances (e.g., Kaplan et al 2015), the accurate forecasting of TC intensity change stands as one of the foremost challenges in meteorology (Doyle et al 2017). The concept described in this paper is intended to address this deficiency by undertaking continuous, high-spatiotemporal observation of GWs generated by TCs, and also convective severe storms, throughout their life cycles.…”

Section: Storm Observation Requirementsmentioning

confidence: 99%

“…The National Hurricane Center (NHC) has maintained an operational TC-RI forecast capability since the early 2000s, and improved versions are currently undergoing trials at the NHC's Joint Hurricane Testbed. However, notwithstanding recent progress in the ability to predict RI (Kaplan et al 2015), this remains a difficult forecast problem (DeMaria et al 2014;Emanuel 2017;Rogers et al 2017) that is hindered by a lack of knowledge concerning the processes occurring below the central dense overcast region of the storm (Willoughby et al 1982;Rappaport et al 2009). …”

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confidence: 99%

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GHOST: A Satellite Mission Concept for Persistent Monitoring of Stratospheric Gravity Waves Induced by Severe Storms

Tratt

Hackwell

Valant-Spaight

et al. 2018

Bulletin of the American Meteorological Society

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Section: Storm Observation Requirementsmentioning

confidence: 99%

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confidence: 99%

GHOST: A Satellite Mission Concept for Persistent Monitoring of Stratospheric Gravity Waves Induced by Severe Storms

Tratt

Hackwell

Valant-Spaight

et al. 2018

Bulletin of the American Meteorological Society

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“…Within the community of scientists working on tropical cyclones, efforts have been directed toward improving dedicated tropical cyclone models (e.g., Gopalakrishnan et al 2011), real-time in situ and remote sensing observations of storms (e.g., Ruf et al 2016), assimilation of those observations into models (Zhang and Weng 2015;Weng and Zhang 2016;Zhang et al 2016), and statistical forecast models, which are still competitive with deterministic models (Kaplan et al 2015). Numerical modeling of tropical cyclones is especially challenging owing to the very high resolution required to resolve the critical eyewall region (Rotunno et al 2009), to the complex physics of boundary layers and air-sea interaction at high winds speeds (Nolan et al 2009;Green and Zhang 2014;Andreas et al 2015;Green and Zhang 2015), and to the importance of correctly modeling the response of the upper ocean to the storms (Moon et al 2007;Yablonsky and Ginis 2009).…”

Section: Introductionmentioning

confidence: 99%

On the Predictability and Error Sources of Tropical Cyclone Intensity Forecasts

Emanuel

Zhang

2016

Journal of the Atmospheric Sciences

122

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The skill of tropical cyclone intensity forecasts has improved slowly since such forecasts became routine, even though track forecast skill has increased markedly over the same period. In deciding whether or how best to improve intensity forecasts, it is useful to estimate fundamental predictability limits as well as sources of intensity error. Toward that end, the authors estimate rates of error growth in a ''perfect model'' framework in which the same model is used to explore the sensitivities of tropical cyclone intensity to perturbations in the initial storm intensity and large-scale environment. These are compared to estimates made in previous studies and to intensity error growth in real-time forecasts made using the same model, in which model error also plays an important role. The authors find that error growth over approximately the first few days in the perfect model framework is dominated by errors in initial intensity, after which errors in forecasting the track and large-scale kinematic environment become more pronounced. Errors owing solely to misgauging initial intensity are particularly large for storms about to undergo rapid intensification and are systematically larger when initial intensity is underestimated compared to overestimating initial intensity by the same amount. There remains an appreciable gap between actual and realistically achievable forecast skill, which this study suggests can best be closed by improved models, better observations, and superior data assimilation techniques.

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“…Statistical and dynamical models provide intensity forecasts of comparable accuracy. However, statistical models are still superior for anticipating rapid intensity changes (Kaplan et al ). Parameters derived from infrared imagery from geostationary satellites, and PMW data from LEO satellites, are important components of statistical RI models (Rozoff et al ).…”

Section: Science Objectivesmentioning

confidence: 99%

An overview of the TROPICS NASA Earth Venture Mission

Blackwell

Braun

Bennartz

et al. 2018

Quart J Royal Meteoro Soc

108

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The Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission was selected by NASA as part of the Earth Venture-Instrument (EVI-3) program. The overarching goal for TROP-ICS is to provide nearly all-weather observations of 3D temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. TROPICS will provide rapid-refresh microwave measurements (median refresh rate better than 60 min for the baseline mission) which can be used to observe the thermodynamics of the troposphere and precipitation structure for storm systems at the mesoscale and synoptic scale over the entire storm life cycle. TROPICS comprises six CubeSats in three low-Earth orbital planes. Each CubeSat will host a high-performance radiometer to provide temperature profiles using seven channels near the 118.75 GHz oxygen absorption line, water vapour profiles using three channels near the 183 GHz water vapour absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher-resolution water vapour channels), and a single channel near 205 GHz which is more sensitive to precipitation-sized ice particles. This observing system offers an unprecedented combination of horizontal and temporal resolution to measure environmental and inner-core conditions for tropical cyclones on a nearly global scale and is a major leap forward in the temporal resolution of several key parameters needed for assimilation into advanced data assimilation systems capable of utilizing rapid-update radiance or retrieval data. Launch readiness is currently projected for late 2019.

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Evaluating Environmental Impacts on Tropical Cyclone Rapid Intensification Predictability Utilizing Statistical Models

Abstract: 2015: Evaluating environmental impacts on tropical cyclone rapid intensification AMERICAN METEOROLOGICAL SOCIETY predictability utilizing statistical models. Wea. Forecasting.

Cited by 172 publications

References 45 publications

GHOST: A Satellite Mission Concept for Persistent Monitoring of Stratospheric Gravity Waves Induced by Severe Storms

GHOST: A Satellite Mission Concept for Persistent Monitoring of Stratospheric Gravity Waves Induced by Severe Storms

On the Predictability and Error Sources of Tropical Cyclone Intensity Forecasts

An overview of the TROPICS NASA Earth Venture Mission

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