Axisymmetric Potential Vorticity Evolution of Hurricane Patricia (2015)

Abstract Operational numerical models failed to predict the record-setting rapid intensification and rapid overwater weakening of Hurricane Patricia (2015) in the eastern North Pacific basin, resulting in large intensity forecast errors. In an effort to better understand the mesoscale processes contributing to Patricia’s rapid intensity changes, we analyze high-resolution aircraft observations collected on 22–23 October. Spline-based variational analyses are created from observations collected via in situ measurements, Doppler radar, and full-tropospheric dropsonde profiles as part of the Office of Naval Research Tropical Cyclone Intensity (TCI) experiment and the National Oceanic and Atmospheric Administration Intensity Forecasting Experiment (IFEX). We present the first full-tropospheric calculation of the dry, axisymmetric Ertel’s potential vorticity (PV) in a tropical cyclone without relying on balance assumptions. Detailed analyses reveal the formation of a “hollow tower” PV structure as Patricia rapidly approached its maximum intensity, and a subsequent breakdown of this structure during Patricia’s rapid overwater weakening phase. Transforming the axisymmetric PV analyses from radius–height to potential radius–isentropic coordinates reveals that Patricia’s rapid intensification was closely related to the distribution of diabatic heating and eddy mixing. During Patricia’s rapid overwater weakening phase, eddy mixing processes are hypothesized to be the primary factor rearranging the PV distribution near the eye–eyewall region, diluting the PV previously confined to the hollow tower while approximately conserving the absolute circulation.

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Understanding Biases in Tropical Cyclone Intensity Forecast Error

Weather and Forecasting ◽

10.1175/waf-d-17-0106.1 ◽

2018 ◽

Vol 33 (1) ◽

pp. 129-138 ◽

Cited By ~ 5

Author(s):

Wei Na ◽

John L. McBride ◽

Xing-Hai Zhang ◽

Yi-Hong Duan

Keyword(s):

Tropical Cyclone ◽

Forecast Error ◽

Correlation Coefficients ◽

Rate Of Change ◽

Intensity Change ◽

Forecast Errors ◽

Second Derivative ◽

Rapid Intensification ◽

Time Curve ◽

Large Intensity

Abstract The characteristics of 24-h official forecast errors (OFEs) of tropical cyclone (TC) intensity are analyzed over the North Atlantic, east Pacific, and western North Pacific. The OFE is demonstrated to be strongly anticorrelated with TC intensity change with correlation coefficients of −0.77, −0.77, and −0.68 for the three basins, respectively. The 24-h intensity change in the official forecast closely follows a Gaussian distribution with a standard deviation only ⅔ of that in nature, suggesting the current official forecasts estimate fewer cases of large intensity change. The intensifying systems tend to produce negative errors (underforecast), while weakening systems have consistent positive errors (overforecast). This asymmetrical bias is larger for extreme intensity change, including rapid intensification (RI) and rapid weakening (RW). To understand this behavior, the errors are analyzed in a simple objective model, the trend-persistence model (TPM). The TPM exhibits the same error-intensity change correlation. In the TPM, the error can be understood as it is exactly inversely proportional to the finite difference form of the concavity or second derivative of the intensity–time curve. The occurrence of large negative (positive) errors indicates the intensity–time curve is concave upward (downward) in nature during the TC’s rapid intensification (weakening) process. Thus, the fundamental feature of the OFE distribution is related to the shape of the intensity–time curve, governed by TC dynamics. All forecast systems have difficulty forecasting an accelerating rate of change, or a large second derivative of the intensity–time curve. TPM may also be useful as a baseline in evaluating the skill of official forecasts. According to this baseline, official forecasts are more skillful in RW than in RI.

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Potential vorticity dynamics of life cycles of blocked weather regimes in the Euro-Atlantic region: A diagnostic framework

10.5194/egusphere-egu21-12847 ◽

2021 ◽

Author(s):

Seraphine Hauser ◽

Christian M. Grams ◽

Michael Riemer ◽

Peter Knippertz ◽

Franziska Teubler

Keyword(s):

Potential Vorticity ◽

Large Scale ◽

Climate Models ◽

Numerical Models ◽

Weather Prediction ◽

Life Cycles ◽

Forecast Errors ◽

Atlantic Region ◽

Weather Regimes ◽

Medium Range

<p>Quasi-stationary, persistent, and recurrent states of the large-scale extratropical circulation, so-called weather regimes, characterize the atmospheric variability on sub-seasonal timescales of several days to a few weeks. Weather regimes featuring a blocking anticyclone are of particular interest due to their long lifetime and potential for high-impact weather. However, state-of-the-art numerical weather prediction and climate models struggle to correctly represent blocking life cycles, which results in large forecast errors at the medium-range to sub-seasonal timescale. Despite progress in recent years, we are still lacking a process-based conceptual understanding of blocked regime dynamics, which hinders a better representation of blocks in numerical models. In particular the relative contributions of dry and moist processes in the onset and maintenance of a block remain unclear.</p><p>Here we aim to revisit the dynamics of blocking in the Euro-Atlantic region. To this end we investigate the life cycles of blocked weather regimes from a potential vorticity (PV) perspective in ERA5 reanalysis data (from 1979 to present) from the European Centre for Medium-Range Weather Forecasts. We develop a diagnostic PV framework that allows the tracking of negative PV anomalies associated with blocked weather regimes. Complemented by piecewise PV-tendencies - separated into advective and diabatic PV tendencies - we are able to disentangle different physical processes affecting the amplitude evolution of negative PV anomalies associated with blocked regimes. Most importantly, this approach newly enables us to distinguish between the roles of dry and moist dynamics in the initiation and maintenance of blocked weather regimes in a common framework. A first application demonstrates the functionality of the developed PV framework and corroborates the importance of moist-diabatic processes in the initiation and maintenance of a block in a regime life cycle.&#160;</p>

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Rewriting the Tropical Record Books: The Extraordinary Intensification of Hurricane Patricia (2015)

Bulletin of the American Meteorological Society ◽

10.1175/bams-d-16-0039.1 ◽

2017 ◽

Vol 98 (10) ◽

pp. 2091-2112 ◽

Cited By ~ 39

Author(s):

Robert F. Rogers ◽

Sim Aberson ◽

Michael M. Bell ◽

Daniel J. Cecil ◽

James D. Doyle ◽

...

Keyword(s):

Tropical Cyclone ◽

High Altitude ◽

Doppler Radar ◽

Pressure Sensors ◽

Data Sources ◽

Naval Research ◽

Office Of Naval Research ◽

Intensity Changes ◽

Flight Level ◽

Airborne Doppler Radar

Abstract Hurricane Patricia was a historic tropical cyclone that broke many records, such as intensification rate, peak intensity, and overwater weakening rate, during its brief 4-day lifetime in late October 2015 in the eastern Pacific basin. Patricia confounded all of the intensity forecast guidance owing to its rapid intensity changes. Fortunately, the hurricane-penetrating National Oceanic and Atmospheric Administration WP-3D and U.S. Air Force C-130 aircraft and the National Aeronautics and Space Administration WB-57 high-altitude jet, under support of the Office of Naval Research, conducted missions through and over Patricia prior to and during its extreme intensity changes on all 4 days, while an extensive array of pressure sensors sampled Patricia after landfall. The observations collected from these missions include traditional data sources such as airborne Doppler radar and flight-level instruments as well as new data sources like a high-density array of dropsondes released from high-altitude and wide-swath radiometer. The combination of data from these sources and from satellites provides an excellent opportunity to investigate the physical processes responsible for Patricia’s structure and evolution and offers the potential to improve forecasts of tropical cyclone rapid intensity changes. This paper provides an overview of Patricia as well as the data collected during the aircraft missions.

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Characteristics of Deep Tropical and Subtropical Convection from Nadir-Viewing High-Altitude Airborne Doppler Radar

Journal of the Atmospheric Sciences ◽

10.1175/2009jas3132.1 ◽

2010 ◽

Vol 67 (2) ◽

pp. 285-308 ◽

Cited By ~ 115

Author(s):

Gerald M. Heymsfield ◽

Lin Tian ◽

Andrew J. Heymsfield ◽

Lihua Li ◽

Stephen Guimond

Keyword(s):

Tropical Cyclone ◽

High Altitude ◽

Field Experiments ◽

Doppler Radar ◽

Numerical Models ◽

Deep Convection ◽

Sea Breeze ◽

Lower Altitude ◽

Linear Relationships ◽

Radar Measurements

Abstract This paper presents observations of deep convection characteristics in the tropics and subtropics that have been classified into four categories: tropical cyclone, oceanic, land, and sea breeze. Vertical velocities in the convection were derived from Doppler radar measurements collected during several NASA field experiments from the nadir-viewing high-altitude ER-2 Doppler radar (EDOP). Emphasis is placed on the vertical structure of the convection from the surface to cloud top (sometimes reaching 18-km altitude). This unique look at convection is not possible from other approaches such as ground-based or lower-altitude airborne scanning radars. The vertical motions from the radar measurements are derived using new relationships between radar reflectivity and hydrometeor fall speed. Various convective properties, such as the peak updraft and downdraft velocities and their corresponding altitude, heights of reflectivity levels, and widths of reflectivity cores, are estimated. The most significant findings are the following: 1) strong updrafts that mostly exceed 15 m s−1, with a few exceeding 30 m s−1, are found in all the deep convection cases, whether over land or ocean; 2) peak updrafts were almost always above the 10-km level and, in the case of tropical cyclones, were closer to the 12-km level; and 3) land-based and sea-breeze convection had higher reflectivities and wider convective cores than oceanic and tropical cyclone convection. In addition, the high-resolution EDOP data were used to examine the connection between reflectivity and vertical velocity, for which only weak linear relationships were found. The results are discussed in terms of dynamical and microphysical implications for numerical models and future remote sensors.

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Intensity fluctuations in Hurricane Irma (2017) during a period of rapid intensification

10.5194/wcd-2021-81 ◽

2022 ◽

Author(s):

William Stanley Torgerson ◽

Juliane Schwendike ◽

Andrew Ross ◽

Chris Short

Keyword(s):

Boundary Layer ◽

Tropical Cyclone ◽

Vertical Velocity ◽

Potential Vorticity ◽

Relative Vorticity ◽

Rapid Intensification ◽

Intensity Fluctuations ◽

Strengthening Phases ◽

Hurricane Irma ◽

Vorticity Structure

Abstract. Intensity fluctuations observed during a period of rapid intensification of Hurricane Irma (2017) between 04 September and 06 September were investigated in a detailed modelling study using an ensemble of Met Office Unified Model (MetUM) convection permitting forecasts. These intensity fluctuations consisted of alternating weakening and strengthening phases. During weakening phases the tropical cyclone temporarily paused its intensification. It was found that weakening phases were associated with a change in the potential vorticity structure, with a tendency for it to become more monopolar. Convection during strengthening phases was associated with isolated local regions of high relative vorticity and vertical velocity in the eyewall, while during weakening phases the storm became more azimuthally symmetric with weaker convection spread more evenly. The boundary layer was found to play an important role in the cause of the intensity fluctuations with an increase in the agradient wind within the boundary layer causing a spin--down just above the boundary layer during the weakening phases whereas during the strengthening phases the agradient wind reduces. This study offers new explanations for why these fluctuations occur and what causes them.

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Track Dependence of Tropical Cyclone Intensity Forecast Errors in the COAMPS-TC Model

Weather and Forecasting ◽

10.1175/waf-d-20-0085.1 ◽

2021 ◽

Cited By ~ 1

Author(s):

Chanh Kieu ◽

Cole Evans ◽

Yi Jin ◽

James D. Doyle ◽

Hao Jin ◽

...

Keyword(s):

Tropical Cyclone ◽

Numerical Models ◽

Intensity Variation ◽

Absolute Intensity ◽

Mature Stage ◽

Lead Times ◽

Track Forecast ◽

Forecast Errors ◽

Intensity Forecast ◽

Tc Model

AbstractThis study examines the dependence of tropical cyclone (TC) intensity forecast errors on track forecast errors in the Coupled Ocean/Atmosphere Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC) model. Using real-time forecasts and retrospective experiments during 2015-2018, verification of TC intensity errors conditioned on different 5-day track error thresholds shows that reducing the 5-day track errors by 50-70% can help reduce the absolute intensity errors by 18-20% in the 2018 version of the COAMPS-TC model. Such impacts of track errors on the TC intensity errors are most persistent at 4-5 day lead times in all three major ocean basins, indicating a significant control of global models on the forecast skill of the COAMPS-TC model. It is of interest to find, however, that lowering the 5-day track errors below 80 nm does not reduce TC absolute intensity errors further. Instead, the 4-5 day intensity errors appear to be saturated at around 10-12 kt for cases with small track errors, thus suggesting the existence of some inherent intensity errors in regional models.Additional idealized simulations under a perfect model scenario reveal that the COAMPS-TC model possesses an intrinsic intensity variation at the TC mature stage in the range of 4-5 kt, regardless of the large-scale environment. Such intrinsic intensity variability in the COAMPS-TC model highlights the importance of potential chaotic TC dynamics, rather than model deficiencies, in determining TC intensity errors at 4-5 day lead times. These results indicate a fundamental limit in the improvement of TC intensity forecasts by numerical models that one should consider in future model development and evaluation.

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

Weather and Forecasting ◽

10.1175/waf-d-15-0032.1 ◽

2015 ◽

Vol 30 (5) ◽

pp. 1374-1396 ◽

Cited By ~ 79

Author(s):

John Kaplan ◽

Christopher M. Rozoff ◽

Mark DeMaria ◽

Charles R. Sampson ◽

James P. Kossin ◽

...

Keyword(s):

Tropical Cyclone ◽

Prediction Models ◽

Numerical Models ◽

Lead Times ◽

Rapid Intensification ◽

Linear Discriminant ◽

Predictive Skill ◽

Prediction Scheme ◽

Model Probability ◽

The Individual

Abstract New multi-lead-time versions of three statistical probabilistic tropical cyclone rapid intensification (RI) prediction models are developed for the Atlantic and eastern North Pacific basins. These are the linear-discriminant analysis–based Statistical Hurricane Intensity Prediction Scheme Rapid Intensification Index (SHIPS-RII), logistic regression, and Bayesian statistical RI models. Consensus RI models derived by averaging the three individual RI model probability forecasts are also generated. A verification of the cross-validated forecasts of the above RI models conducted for the 12-, 24-, 36-, and 48-h lead times indicates that these models generally exhibit skill relative to climatological forecasts, with the eastern Pacific models providing somewhat more skill than the Atlantic ones and the consensus versions providing more skill than the individual models. A verification of the deterministic RI model forecasts indicates that the operational intensity guidance exhibits some limited RI predictive skill, with the National Hurricane Center (NHC) official forecasts possessing the most skill within the first 24 h and the numerical models providing somewhat more skill at longer lead times. The Hurricane Weather Research and Forecasting Model (HWRF) generally provides the most skillful RI forecasts of any of the conventional intensity models while the new consensus RI model shows potential for providing increased skill over the existing operational intensity guidance. Finally, newly developed versions of the deterministic rapid intensification aid guidance that employ the new probabilistic consensus RI model forecasts along with the existing operational intensity model consensus produce lower mean errors and biases than the intensity consensus model alone.

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Current Capability of Operational Numerical Models in Predicting Tropical Cyclone Intensity in the Western North Pacific

Weather and Forecasting ◽

10.1175/waf-d-11-00100.1 ◽

2013 ◽

Vol 28 (2) ◽

pp. 353-367 ◽

Cited By ~ 14

Author(s):

Hui Yu ◽

Peiyan Chen ◽

Qingqing Li ◽

Bi Tang

Keyword(s):

Tropical Cyclone ◽

North Pacific ◽

Western North Pacific ◽

Numerical Models ◽

Wind Pressure ◽

Skill Assessment ◽

Intensity Change ◽

Lead Times ◽

Forecast Errors ◽

Trend Forecasting

Abstract Forecasts of tropical cyclone (TC) intensity from six operational models (three global models and three regional models) during 2010 and 2011 are assessed to study the current capability of model guidance in the western North Pacific. The evaluation is performed on both Vmax and Pmin from several aspects, including the relative error, skill assessment, category score, the hitting rate of trend, and so on. It is encouraging to see that the models have had some skills in the prediction of TC intensity, including that two of them are better than a statistical baseline in Vmax at several lead times and three of them show some skill in intensity change. With dissipated cases included, all the models have skills in category and trend forecasting at lead times longer than 24 h or so. The model forecast errors are found to be significantly correlated with initial error and the observed initial intensity. A statistical calibration scheme for model forecasting is proposed based on such an attribute, which is more effective for Pmin than Vmax. The statistically calibrated model forecasts are important in setting up a skillful multimodel consensus, for either the mean or the statistically weighted mean. The Vmax forecasts converted from the calibrated Pmin consensus based on a statistical wind–pressure relationship show significant skill over the baseline and a skillful scheme is also proposed to deal with the delay of the model forecasts in operation.

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Development and Nondevelopment of Binary Mesoscale Vortices into Tropical Cyclones in Idealized Numerical Experiments

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-15-0028.1 ◽

2016 ◽

Vol 73 (3) ◽

pp. 1223-1254 ◽

Cited By ~ 5

Author(s):

David A. Schecter

Keyword(s):

Tropical Cyclone ◽

Tropical Cyclones ◽

Potential Vorticity ◽

Numerical Experiments ◽

Separation Distance ◽

Rapid Intensification ◽

Tropical Cyclone Formation ◽

Vortex Separation ◽

Cloud Resolving Model ◽

Insight Into

Abstract The evolution of two symmetric midlevel mesoscale vortices situated above a warm ocean is examined with a basic cloud-resolving model. Idealized numerical experiments provide insight into how the evolution may vary with the initial vortex separation distance D and other parameters that influence the time scale for an isolated vortex to begin rapid intensification. The latter parameters include the ambient middle-tropospheric relative humidity (RH) and the initial midlevel wind speed of each vortex. At relatively low RH, there exists an interval of D where binary midlevel vortex interaction prevents tropical cyclone formation. While tropical cyclones generally develop at high RH, similar values of D can delay the process if the vortices are initially weak. Prevention or inhibition of tropical cyclone formation occurs in association with the outward expulsion of lower-tropospheric potential vorticity anomalies as the two vortices merge in the middle troposphere. It is proposed that the primary mechanism for midlevel merger and low-level potential vorticity expulsion involves the excitation of rotating misalignments in each vortex. An analog model based on this premise provides a good approximation for the range of D in which the merger–expulsion scenario occurs. Relatively strong vortices in high-RH environments promptly develop vigorous convection and begin rapid intensification. Differences between the interaction of such diabatic vortices and their adiabatic counterparts are briefly illustrated. In systems that generate tropical cyclones, the mature vortex properties (size and strength) are found to vary significantly with D.

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A Deterministic Rapid Intensification Aid

Weather and Forecasting ◽

10.1175/waf-d-10-05010.1 ◽

2011 ◽

Vol 26 (4) ◽

pp. 579-585 ◽

Cited By ~ 13

Author(s):

Charles R. Sampson ◽

John Kaplan ◽

John A. Knaff ◽

Mark DeMaria ◽

Chris A. Sisko

Keyword(s):

Real Time ◽

Arithmetic Mean ◽

Forecast Errors ◽

Rapid Intensification ◽

Intensity Forecast ◽

Probability Threshold ◽

Forecast Time ◽

National Hurricane Center ◽

Made In

Abstract Rapid intensification (RI) is difficult to forecast, but some progress has been made in developing probabilistic guidance for predicting these events. One such method is the RI index. The RI index is a probabilistic text product available to National Hurricane Center (NHC) forecasters in real time. The RI index gives the probabilities of three intensification rates [25, 30, and 35 kt (24 h)−1; or 12.9, 15.4, and 18.0 m s−1 (24 h)−1] for the 24-h period commencing at the initial forecast time. In this study the authors attempt to develop a deterministic intensity forecast aid from the RI index and, then, implement it as part of a consensus intensity forecast (arithmetic mean of several deterministic intensity forecasts used in operations) that has been shown to generally have lower mean forecast errors than any of its members. The RI aid is constructed using the highest available RI index intensification rate available for probabilities at or above a given probability (i.e., a probability threshold). Results indicate that the higher the probability threshold is, the better the RI aid performs. The RI aid appears to outperform the consensus aids at about the 50% probability threshold. The RI aid also improves forecast errors of operational consensus aids starting with a probability threshold of 30% and reduces negative biases in the forecasts. The authors suggest a 40% threshold for producing the RI aid initially. The 40% threshold is available for approximately 8% of all verifying forecasts, produces approximately 4% reduction in mean forecast errors for the intensity consensus aids, and corrects the negative biases by approximately 15%–20%. In operations, the threshold could be moved up to maximize gains in skill (reducing availability) or moved down to maximize availability (reducing gains in skill).

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