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Eric A. Hendricks
,
Russell L. Elsberry
,
Christopher S. Velden
,
Adam C. Jorgensen
,
Mary S. Jordan
, and
Robert L. Creasey

Abstract

The objective in this study is to demonstrate how two unique datasets from the Tropical Cyclone Intensity (TCI-15) field experiment can be used to diagnose the environmental and internal factors contributing to the interruption of the rapid decay of Hurricane Joaquin (2015) and then a subsequent 30-h period of constant intensity. A special CIMSS vertical wind shear (VWS) dataset reprocessed at 15-min intervals provides a more precise documentation of the large (~15 m s−1) VWS throughout most of the rapid decay period, and then the timing of a rapid decrease in VWS to moderate (~8 m s−1) values prior to, and following, the rapid decay period. During this period, the VWS was moderate because Joaquin was between large VWSs to the north and near-zero VWSs to the south, which is considered to be a key factor in how Joaquin was able to be sustained at hurricane intensity even though it was moving poleward over colder water. A unique dataset of High Definition Sounding System (HDSS) dropwindsondes deployed from the NASA WB-57 during the TCI-15 field experiment is utilized to calculate zero-wind centers during Joaquin center overpasses that reveal for the first time the vortex tilt structure through the entire troposphere. The HDSS datasets are also utilized to calculate the inertial stability profiles and the inner-core potential temperature anomalies in the vertical. Deeper lower-tropospheric layers of near-zero vortex tilt are correlated with stronger storm intensities, and upper-tropospheric layers with large vortex tilts due to large VWSs are correlated with weaker storm intensities.

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Nannan Qin
and
Da-Lin Zhang

Abstract

Hurricane Patricia (2015) broke records in both peak intensity and rapid intensification (RI) rate over the eastern Pacific basin. All of the then-operational models predicted less than half of its extraordinary intensity and RI rate, leaving a challenge for numerical modeling studies. In this study, a successful 42-h simulation of Patricia is obtained using a quintuply nested-grid version of the Weather Research and Forecast (WRF) Model with the finest grid size of 333 m. Results show that the WRF Model, initialized with the Global Forecast System Final Analysis data only, could reproduce the track, peak intensity, and many inner-core features, as verified against various observations. In particular, its simulated maximum surface wind of 92 m s−1 is close to the observed 95 m s−1, capturing the unprecedented RI rate of 54 m s−1 (24 h)−1. In addition, the model reproduces an intense warm-cored eye, a small-sized eyewall with a radius of maximum wind of less than 10 km, and the distribution of narrow spiral rainbands. A series of sensitivity simulations is performed to help understand which model configurations are essential to reproducing the extraordinary intensity of the storm. Results reveal that Patricia’s extraordinary development and its many inner-core structures could be reasonably well simulated if ultrahigh horizontal resolution, appropriate model physics, and realistic initial vortex intensity are incorporated. It is concluded that the large-scale conditions (e.g., warm sea surface temperature, weak vertical wind shear, and the moist intertropical convergence zone) and convective organization play important roles in determining the predictability of Patricia’s extraordinary RI and peak intensity.

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Quanjia Zhong
,
Jianping Li
,
Lifeng Zhang
,
Ruiqiang Ding
, and
Baosheng Li

Abstract

The predictability limits of tropical cyclone (TC) intensity over the western North Pacific (WNP) are investigated using TC best track data. The results show that the predictability limit of the TC minimum central pressure (MCP) is ~102 h, comparable to that of the TC maximum sustained wind (MSW). The spatial distribution of the predictability limit of the TC MCP over the WNP is similar to that of the TC MSW, and both gradually decrease from the eastern WNP (EWNP) to the South China Sea (SCS). The predictability limits of the TC MCP and MSW are relatively high over the southeastern WNP where the modified accumulated cyclone energy (MACE) is relatively large, whereas they are relatively low over the SCS where the MACE is relatively small. The spatial patterns of the TC lifetime and the lifetime maximum intensity (LMI) are similar to that of the TC MACE. Strong and long-lived TCs, which have relatively long predictability, mainly form in the southwestern WNP. In contrast, weak and short-lived TCs, which have relatively short predictability, mainly form in the SCS. In addition to the dependence of the predictability limit on genesis location, the predictability limits of TC intensity also evolve in the TC life cycle. The predictability limit of the TC MCP (MSW) gradually decreases from 102 (108) h at genesis time (00 h) to 54 (84) h 4 days after TC genesis.

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William A. Komaromi
and
James D. Doyle

Abstract

The interaction between a tropical cyclone (TC) and an upper-level trough is simulated in an idealized framework using Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) for Tropical Cyclones (COAMPS-TC) on a β plane. We explore the effect of the trough on the environment, structure, and intensity of the TC. In a simulation that does not have a trough, environmental inertial stability is dominated by Coriolis, and outflow remains preferentially directed equatorward throughout the simulation. In the presence of a trough, negative storm-relative tangential wind in the base of the trough reduces the inertial stability such that the outflow shifts from equatorward to poleward. This interaction results in a ~24-h period of enhanced upper-level divergence coincident with intensification of the TC. Sensitivity tests reveal that if the TC is too far from the trough, favorable interaction does not occur. If the TC is too close to the trough, the storm weakens because of enhanced vertical wind shear. Only when the relative distance between the TC and the trough is 0.2–0.3 times the wavelength of the trough in x and 0.8–1.2 times the amplitude of the trough in y does favorable interaction and TC intensification occur. However, stochastic effects make it difficult to isolate the intensity change associated directly with the trough interaction. Outflow is found to be predominantly ageostrophic at small radii and deflects to the right (in the Northern Hemisphere) since it is unbalanced. The outflow becomes predominantly geostrophic at larger radii but not before a rightward deflection has already occurred. This finding sheds light on why the outflow accelerates toward but generally never reaches the region of lowest inertial stability.

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T. Ghosh
and
T. N. Krishnamurti

Abstract

Forecasting tropical storm intensities is a very challenging issue. In recent years, dynamical models have improved considerably. However, for intensity forecasts more improvement is necessary. Dynamical models have different kinds of biases. Considering a multimodel consensus could eliminate some of the biases resulting in improved intensity forecasts as compared to the individual models. Apart from the ensemble mean, the construction of multimodel consensuses has always contributed to somewhat improved forecasts. The Florida State University (FSU) multimodel superensemble is one that, over the years, has systematically provided improved forecasts for hurricanes, numerical weather prediction, and seasonal climate forecasts. The present study considers an artificial neural network (ANN), based on biological principles, for the construction of a multimodel ensemble. ANN has been used for constructing multimodel consensus forecasts for tropical cyclone intensities. This study uses the generalized regression neural network (GRNN) method for the construction of consensus intensity forecasts for the Atlantic basin. Hurricane seasons 2012–16 are considered. Results show that with only five input models improved guidance for tropical storm intensities may be obtained. The consensus using GRNN mostly outperforms all the models included in the study and the ensemble mean. Forecast errors at the longer forecast leads are considerably less for this multimodel superensemble based on the generalized regression neural network. The skill and correlations of different models along with the developed consensus are provided in our analysis. Results suggest that this consensus forecast may be used for operational guidance and for planning and emergency evacuation management. Possibilities for future improvements of the consensus based on new advances in statistical algorithms are also indicated.

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Shixuan Zhang
,
Zhaoxia Pu
, and
Christopher Velden

Abstract

The impacts of enhanced satellite-derived atmospheric motion vectors (AMVs) on the numerical prediction of intensity changes during Hurricanes Gonzalo (2014) and Joaquin (2015) are examined. Enhanced AMVs benefit from special data-processing strategies and are examined for impact on model forecasts via assimilation experiments by employing the National Centers for Environmental Prediction (NCEP) operational Hurricane Weather Research and Forecasting (HWRF) Model using a Gridpoint Statistical Interpolation analysis system (GSI)-based ensemble–variational hybrid system. Two different data assimilation (DA) configurations, one with and one without the use of vortex initialization (VI), are compared. It is found that the assimilation of enhanced AMVs can improve the HWRF track and intensity forecasts of Gonzalo and Joaquin during their intensity change phases. The degree of data impact depends on the DA configuration used. Overall, assimilation of enhanced AMVs in the innermost domain (e.g., storm inner-core region and its immediate vicinity) outperforms other DA configurations, both with and without VI, as it results in better track and intensity forecasts. Compared to the experiment with VI, assimilation of enhanced AMVs without VI reveals more notable data impact on the forecasts of Hurricane Gonzalo, as the VI before DA alters the first guess and reduces the actual number of AMV observations assimilated into the DA system. Even with VI, assimilation of enhanced AMVs in the inner-core region can at least partially mitigate the negative effect of VI on the intensity forecast of Hurricane Gonzalo and alleviate the unrealistic vortex weakening in the simulation by removing unrealistic outflow structure and unfavorable thermodynamic conditions, thus leading to improved intensity forecasts.

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Robert G. Nystrom
,
Fuqing Zhang
,
Erin B. Munsell
,
Scott A. Braun
,
Jason A. Sippel
,
Yonghui Weng
, and
Kerry Emanuel

Abstract

Real-time ensemble forecasts from the Pennsylvania State University (PSU) WRF EnKF system (APSU) for Hurricane Joaquin (2015) are examined in this study. The ensemble forecasts, from early in Joaquin’s life cycle, displayed large track spread, with nearly half of the ensemble members tracking Joaquin toward the U.S. East Coast and the other half tracking Joaquin out to sea. The ensemble forecasts also displayed large intensity spread, with many of the members developing into major hurricanes and other ensemble members not intensifying at all.

Initial condition differences from the regions greater than (less than) 300 km were isolated by effectively removing initial condition differences in desired regions through relaxing each ensemble member to GFS (APSU) initial conditions. The regions of initial condition errors contributing to the track spread were examined, and the dominant source of track errors arose from the region greater than 300 km from the tropical cyclone center. Further examination of the track divergence revealed that the region between 600 and 900 km from the initial position of Joaquin was found to be the largest source of initial condition errors that contributed to this divergence. Small differences in the low-level steering flow, originating from perturbations between 600 and 900 km from the initial position, appear to have resulted in the bifurcation of the forecast tracks of Joaquin. The initial condition errors north of the initial position of Joaquin were also shown to contribute most significantly to the track divergence. The region inside of 300 km, specifically, the initial intensity of Joaquin, was the dominant source of initial condition errors contributing to the intensity spread.

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Patrick Duran
and
John Molinari

Abstract

Dropsondes with horizontal spacing as small as 4 km were released from the stratosphere in rapidly intensifying Hurricane Patricia (2015) during the Office of Naval Research Tropical Cyclone Intensity experiment. These observations provide cross sections of unprecedented resolution through the inner core of a hurricane. On 21 October, Patricia exhibited a strong tropopause inversion layer (TIL) across its entire circulation, with a maximum magnitude of 5.1 K (100 m)−1. This inversion weakened between 21 and 22 October as potential temperature θ increased by up to 16 K just below the tropopause and decreased by up to 14 K in the lower stratosphere. Between 22 and 23 October, the TIL over the eye weakened further, allowing the tropopause to rise by 1 km. Meanwhile over Patricia’s secondary eyewall, the TIL restrengthened and bulged upward by about 700 m into what was previously the lower stratosphere. These observations support many aspects of recent modeling studies, including eyewall penetration into the stratosphere during rapid intensification (RI), the existence of a narrow inflow layer near the tropopause, and the role of subsidence from the stratosphere in developing an upper-level warm core. Three mechanisms of inner-core tropopause variability are hypothesized: destabilization of the TIL through turbulent mixing, weakening of the TIL over the eye through upper-tropospheric subsidence warming, and increasing tropopause height forced by overshooting updrafts in the eyewall. None of these processes are seen as the direct cause of RI, but rather part of the RI process that includes strong increases in boundary layer moist entropy.

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James D. Doyle
,
Jonathan R. Moskaitis
,
Joel W. Feldmeier
,
Ronald J. Ferek
,
Mark Beaubien
,
Michael M. Bell
,
Daniel L. Cecil
,
Robert L. Creasey
,
Patrick Duran
,
Russell L. Elsberry
,
William A. Komaromi
,
John Molinari
,
David R. Ryglicki
,
Daniel P. Stern
,
Christopher S. Velden
,
Xuguang Wang
,
Todd Allen
,
Bradford S. Barrett
,
Peter G. Black
,
Jason P. Dunion
,
Kerry A. Emanuel
,
Patrick A. Harr
,
Lee Harrison
,
Eric A. Hendricks
,
Derrick Herndon
,
William Q. Jeffries
,
Sharanya J. Majumdar
,
James A. Moore
,
Zhaoxia Pu
,
Robert F. Rogers
,
Elizabeth R. Sanabia
,
Gregory J. Tripoli
, and
Da-Lin Zhang

Abstract

Tropical cyclone (TC) outflow and its relationship to TC intensity change and structure were investigated in the Office of Naval Research Tropical Cyclone Intensity (TCI) field program during 2015 using dropsondes deployed from the innovative new High-Definition Sounding System (HDSS) and remotely sensed observations from the Hurricane Imaging Radiometer (HIRAD), both on board the NASA WB-57 that flew in the lower stratosphere. Three noteworthy hurricanes were intensively observed with unprecedented horizontal resolution: Joaquin in the Atlantic and Marty and Patricia in the eastern North Pacific. Nearly 800 dropsondes were deployed from the WB-57 flight level of ∼60,000 ft (∼18 km), recording atmospheric conditions from the lower stratosphere to the surface, while HIRAD measured the surface winds in a 50-km-wide swath with a horizontal resolution of 2 km. Dropsonde transects with 4–10-km spacing through the inner cores of Hurricanes Patricia, Joaquin, and Marty depict the large horizontal and vertical gradients in winds and thermodynamic properties. An innovative technique utilizing GPS positions of the HDSS reveals the vortex tilt in detail not possible before. In four TCI flights over Joaquin, systematic measurements of a major hurricane’s outflow layer were made at high spatial resolution for the first time. Dropsondes deployed at 4-km intervals as the WB-57 flew over the center of Hurricane Patricia reveal in unprecedented detail the inner-core structure and upper-tropospheric outflow associated with this historic hurricane. Analyses and numerical modeling studies are in progress to understand and predict the complex factors that influenced Joaquin’s and Patricia’s unusual intensity changes.

Open access
Daniel J. Cecil
and
Sayak K. Biswas

Abstract

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 of 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). Two flights with predominantly weak winds according to the dropsondes have abnormally large errors from HIRAD and large positive biases. From the other flights, the 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. The mean absolute differences for those three categories are 3.2 m s−1 (25%), 4.3 m s−1 (19%), and 4.8 m s−1 (12%), respectively, with a bias near zero for winds of tropical storm and hurricane strength.

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