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

2015 ◽  
Vol 30 (5) ◽  
pp. 1374-1396 ◽  
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.

scholarly journals An Operational Rapid Intensification Prediction Aid for the Western North Pacific

2018 ◽  
Vol 33 (3) ◽  
pp. 799-811 ◽  
Author(s):  
John A. Knaff ◽  
Charles R. Sampson ◽  
Kate D. Musgrave
Keyword(s):  
Logistic Regression ◽  
Discriminant Analysis ◽  
Tropical Cyclone ◽  
North Pacific ◽  
Western North Pacific ◽  
Rapid Intensification ◽  
Linear Discriminant ◽  
Probabilistic Forecasts ◽  
Weighted Probability ◽  
Joint Typhoon Warning Center

Abstract This work describes tropical cyclone rapid intensification forecast aids designed for the western North Pacific tropical cyclone basin and for use at the Joint Typhoon Warning Center. Two statistical methods, linear discriminant analysis and logistic regression, are used to create probabilistic forecasts for seven intensification thresholds including 25-, 30-, 35-, and 40-kt changes in 24 h, 45- and 55-kt in 36 h, and 70-kt in 48 h (1 kt = 0.514 m s−1). These forecast probabilities are further used to create an equally weighted probability consensus that is then used to trigger deterministic forecasts equal to the intensification thresholds once the probability in the consensus reaches 40%. These deterministic forecasts are incorporated into an operational intensity consensus forecast as additional members, resulting in an improved intensity consensus for these important and difficult to predict cases. Development of these methods is based on the 2000–15 typhoon seasons, and independent performance is assessed using the 2016 and 2017 typhoon seasons. In many cases, the probabilities have skill relative to climatology and adding the rapid intensification deterministic aids to the operational intensity consensus significantly reduces the negative forecast biases.

scholarly journals Forecasting Tropical Cyclone Eye Formation and Dissipation in Infrared Imagery

2017 ◽  
Vol 32 (6) ◽  
pp. 2103-2116 ◽  
Author(s):  
John A. Knaff ◽  
Robert T. DeMaria
Keyword(s):  
Tropical Cyclone ◽  
Northern Hemisphere ◽  
North Atlantic ◽  
Model Development ◽  
Heat Content ◽  
Detection Algorithm ◽  
Lead Times ◽  
Probability Forecast ◽  
Linear Discriminant ◽  
Analysis Technique

Abstract The development of an infrared (IR; specifically near 11 μm) eye probability forecast scheme for tropical cyclones is described. The scheme was developed from an eye detection algorithm that used a linear discriminant analysis technique to determine the probability of an eye existing in any given IR image given information about the storm center, motion, and latitude. Logistic regression is used for the model development and predictors were selected from routine information about the current storm (e.g., current intensity), forecast environmental factors (e.g., wind shear, oceanic heat content), and patterns/information (e.g., convective organization, tropical cyclone size) extracted from the current IR image. Forecasts were created for 6-, 12-, 18-, 24-, and 36-h forecast leads. Forecasts were developed using eye existence probabilities from North Atlantic tropical cyclone cases (1996–2014) and a combined North Atlantic and North Pacific (i.e., Northern Hemisphere) sample. The performance of North Atlantic–based forecasts, tested using independent eastern Pacific tropical cyclone cases (1996–2014), shows that the forecasts are skillful versus persistence at 12–36 h, and skillful versus climatology at 6–36 h. Examining the reliability and calibration of those forecasts shows that calibration and reliability of the forecasts is good for 6–18 h, but forecasts become a little overconfident at longer lead times. The forecasts also appear unbiased. The small differences between the Atlantic and Northern Hemisphere formulations are discussed. Finally, and remarkably, there are indications that smaller TCs are more prone to form eye features in all of the TC areas examined.

scholarly journals Objective Estimation of the 24-h Probability of Tropical Cyclone Formation

2009 ◽  
Vol 24 (2) ◽  
pp. 456-471 ◽  
Author(s):  
Andrea B. Schumacher ◽  
Mark DeMaria ◽  
John A. Knaff
Keyword(s):  
Tropical Cyclone ◽  
North Pacific ◽  
Input Parameter ◽  
Probabilistic Prediction ◽  
Linear Discriminant ◽  
Tropical Cyclone Formation ◽  
Formation Probability ◽  
Prediction Scheme ◽  
Skill Scores ◽  
Probabilistic Forecasts

Abstract A new product for estimating the 24-h probability of TC formation in individual 5° × 5° subregions of the North Atlantic, eastern North Pacific, and western North Pacific tropical basins is developed. This product uses environmental and convective parameters computed from best-track tropical cyclone (TC) positions, National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) analysis fields, and water vapor (∼6.7 μm wavelength) imagery from multiple geostationary satellite platforms. The parameters are used in a two-step algorithm applied to the developmental dataset. First, a screening step removes all data points with environmental conditions highly unfavorable to TC formation. Then, a linear discriminant analysis (LDA) is applied to the screened dataset. A probabilistic prediction scheme for TC formation is developed from the results of the LDA. Coefficients computed by the LDA show that the largest contributors to TC formation probability are climatology, 850-hPa circulation, and distance to an existing TC. The product was evaluated by its Brier and relative operating characteristic skill scores and reliability diagrams. These measures show that the algorithm-generated probabilistic forecasts are skillful with respect to climatology, and that there is relatively good agreement between forecast probabilities and observed frequencies. As such, this prediction scheme has been implemented as an operational product called the National Environmental Satellite, Data, and Information Services (NESDIS) Tropical Cyclone Formation Probability (TCFP) product. The TCFP product updates every 6 h and displays plots of TC formation probability and input parameter values on its Web site. At present, the TCFP provides real-time, objective TC formation guidance used by tropical cyclone forecast offices in the Atlantic, eastern Pacific, and western Pacific basins.

scholarly journals Reassessing the Use of Inner-Core Hot Towers to Predict Tropical Cyclone Rapid Intensification*

2015 ◽  
Vol 30 (5) ◽  
pp. 1265-1279 ◽  
Author(s):  
Xiao-Yong Zhuge ◽  
Jie Ming ◽  
Yuan Wang
Keyword(s):  
Tropical Cyclone ◽  
Inner Core ◽  
Prediction Method ◽  
Vertical Shear ◽  
Intensity Change ◽  
False Alarms ◽  
Rapid Intensification ◽  
Central Pacific ◽  
Prediction Scheme ◽  
Skill Scores

Abstract The hot tower (HT) in the inner core plays an important role in tropical cyclone (TC) rapid intensification (RI). With the help of Tropical Rainfall Measurement Mission (TRMM) data and the Statistical Hurricane Intensity Prediction Scheme dataset, the potential of HTs in operational RI prediction is reassessed in this study. The stand-alone HT-based RI prediction scheme showed little skill in the northern Atlantic (NA) and eastern and central Pacific (ECP), but yielded skill scores of >0.3 in the southern Indian Ocean (SI) and western North Pacific (WNP) basins. The inaccurate predictions are due to four scenarios: 1) RI events may have already begun prior to the TRMM overpass. 2) RI events are driven by non-HT factors. 3) The HT has already dissipated or has not occurred at the TRMM overpass time. 4) Large false alarms result from the unfavorable environment. When the HT was used in conjunction with the TC’s previous 12-h intensity change, the potential intensity, the percentage area from 50 to 200 km of cloud-top brightness temperatures lower than −10°C, and the 850–200-hPa vertical shear magnitude with the vortex removed, the predictive skill score in the SI was 0.56. This score was comparable to that of the RI index scheme, which is considered the most advanced RI prediction method. When the HT information was combined with the aforementioned four environmental factors in the NA, ECP, South Pacific, and WNP, the skill scores were 0.23, 0.32, 0.42, and 0.42, respectively.

Impact of CYGNSS-derived winds on tropical cyclone forecasts in a global and regional model

2021 ◽  
Author(s):  
Michael J. Mueller ◽  
Bachir Annane ◽  
S. Mark Leidner ◽  
Lidia Cucurull
Keyword(s):  
Tropical Cyclone ◽  
Regional Model ◽  
Global Model ◽  
Lead Times ◽  
Rapid Intensification ◽  
Lateral Boundary ◽  
Sea Level Pressure ◽  
The Impact ◽  
Vector Wind ◽  
Minimum Sea Level Pressure

AbstractAn observing system experiment (OSE) was conducted to assess the impact of wind products derived from the Cyclone Global Navigation Satellite System (CYGNSS) on tropical cyclone (TC) track, maximum 10-m wind speed (Vmax), and minimum sea level pressure forecasts. The experiment used a global data assimilation and forecast system and the impact of both CYGNSS-derived scalar and vector wind retrievals was investigated. The CYGNSS-derived vector wind products were generated by optimally combining the scalar winds and a gridded a priori vector field. Additional tests investigated the impact of CYGNSS data on a regional model through the impact of lateral boundary and initial conditions from the global model during the developmental phase of Hurricane Michael (2018).In the global model, statistically significant track forecast improvements of 20-40 km were found in the first 60 h. Vmax forecasts showed some significant degradations of ~2 kts at a few lead times, especially in the first 24 h. At most lead times, impacts were not statistically significant. Degradations in Vmax for Hurricane Michael in the global model were largely attributable to a failure of the CYGNSS-derived scalar wind test to produce rapid intensification in the forecast failure of the CYGNSS-derived scalar wind test to produce rapid intensification in the forecast symmetrical compared to the control and CYGNSS-derived vector wind test. The regional model used initial and lateral boundary conditions from the global control and CYGNSS scalar wind tests. The regional forecasts showed large improvements in track, Vmax, and minimum sea level pressure.

Tropical Cyclone Formation Guidance Using Pregenesis Dvorak Climatology. Part I: Operational Forecasting and Predictive Potential

2013 ◽  
Vol 28 (1) ◽  
pp. 100-118 ◽  
Author(s):  
Joshua H. Cossuth ◽  
Richard D. Knabb ◽  
Daniel P. Brown ◽  
Robert E. Hart
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclogenesis ◽  
Lead Times ◽  
Eastern Region ◽  
Regional Variability ◽  
Central Pacific ◽  
The North ◽  
Predictive Skill ◽  
Out Of Sample ◽  
Frequency Maximum

Abstract While there are a variety of modes for tropical cyclone (TC) development, there have been relatively few efforts to systematically catalog both nondeveloping and developing cases. This paper introduces an operationally derived climatology of tropical disturbances that were analyzed using the Dvorak technique at the National Hurricane Center (NHC) and the Central Pacific Hurricane Center from 2001 to 2011. Using these Dvorak intensity estimates, the likelihood of genesis is calculated as a historical baseline for TC prediction. Despite the limited period of record, the climatology of Dvorak analyses of incipient tropical systems has a spatial distribution that compares well with previous climatologies. The North Atlantic basin shows substantial regional variability in Dvorak classification frequency. In contrast, tropical disturbances in the combined eastern and central North Pacific basins (which split at 125°W into an eastern region and a central region) have a single broad frequency maximum and limited meridional extent. When applied to forecasting, several important features are discovered. Dvorak fixes are sometimes unavailable for disturbances that develop into TCs, especially at longer lead times. However, when probabilities of genesis are calculated by a Dvorak current intensity (CI) number, the likelihood stratifies well by basin and intensity. Tropical disturbances that are analyzed as being stronger (a higher Dvorak CI number) achieve genesis more often. Further, all else being equal, genesis rates are highest in the eastern Pacific, followed by the Atlantic. Out-of-sample verification of predictive skill shows comparable results to that of the NHC, with potential to inform forecasts and provide the first disturbance-centric baseline for tropical cyclogenesis potential.

scholarly journals Axisymmetric Potential Vorticity Evolution of Hurricane Patricia (2015)

2019 ◽  
Vol 76 (7) ◽  
pp. 2043-2063 ◽  
Author(s):  
Jonathan Martinez ◽  
Michael M. Bell ◽  
Robert F. Rogers ◽  
James D. Doyle
Keyword(s):  
Tropical Cyclone ◽  
Potential Vorticity ◽  
Doppler Radar ◽  
Numerical Models ◽  
Naval Research ◽  
Forecast Errors ◽  
Rapid Intensification ◽  
Mixing Processes ◽  
Large Intensity ◽  
Isentropic Coordinates

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.

scholarly journals Impact of Storm Size on Prediction of Storm Track and Intensity Using the 2016 Operational GFDL Hurricane Model

2017 ◽  
Vol 32 (4) ◽  
pp. 1491-1508 ◽  
Author(s):  
Morris A. Bender ◽  
Timothy P. Marchok ◽  
Charles R. Sampson ◽  
John A. Knaff ◽  
Matthew J. Morin
Keyword(s):  
Tropical Cyclones ◽  
North Pacific ◽  
Western North Pacific ◽  
Numerical Models ◽  
Storm Track ◽  
Eastern Pacific ◽  
Lead Times ◽  
Rapid Intensification ◽  
Forecast Lead Time ◽  
The Impact

Abstract The impact of storm size on the forecast of tropical cyclone storm track and intensity is investigated using the 2016 version of the operational GFDL hurricane model. Evaluation was made for 1529 forecasts in the Atlantic, eastern Pacific, and western North Pacific basins, during the 2014 and 2015 seasons. The track and intensity errors were computed from forecasts in which the 34-kt (where 1 kt = 0.514 m s−1) wind radii obtained from the operational TC vitals that are used to initialize TCs in the GFDL model were replaced with wind radii estimates derived using an equally weighted average of six objective estimates. It was found that modifying the radius of 34-kt winds had a significant positive impact on the intensity forecasts in the 1–2 day lead times. For example, at 48 h, the intensity error was reduced 10%, 5%, and 4% in the Atlantic, eastern Pacific, and western North Pacific, respectively. The largest improvements in intensity forecasts were for those tropical cyclones undergoing rapid intensification, with a maximum error reduction in the 1–2 day forecast lead time of 14% and 17% in the eastern and western North Pacific, respectively. The large negative intensity biases in the eastern and western North Pacific were also reduced 25% and 75% in the 12–72-h forecast lead times. Although the overall impact on the average track error was neutral, forecasts of recurving storms were improved and tracks of nonrecurving storms degraded. Results also suggest that objective specification of storm size may impact intensity forecasts in other high-resolution numerical models, particularly for tropical cyclones entering a rapid intensification phase.

Gear Hobbing Cutting Process Simulation and Tool Wear Prediction Models

2001 ◽  
Vol 124 (1) ◽  
pp. 42-51 ◽  
Author(s):  
K.-D. Bouzakis ◽  
S. Kombogiannis ◽  
A. Antoniadis ◽  
N. Vidakis
Keyword(s):  
Tool Wear ◽  
High Speed ◽  
Prediction Models ◽  
Numerical Models ◽  
High Speed Steel ◽  
Cutting Process ◽  
Wear Prediction ◽  
Tool Wear Prediction ◽  
Gear Hobbing ◽  
The Individual

Gear hobbing is an efficient method to manufacture high quality and performance toothed wheels, although it is associated with complicated process kinematics, chip formation and tool wear mechanisms. The variant cutting contribution of each hob tooth to the gear gaps formation might lead to an uneven wear distribution on the successive cutting teeth and to an overall poor tool utilization. To study quantitatively the tool wear progress in gear hobbing, experimental-analytical methods have been established. Gear hobbing experiments and sophisticated numerical models are used to simulate the cutting process and to correlate the undeformed chip geometry and other process parameters to the expected tool wear. Herewith the wear development on the individual hob teeth can be predicted and the cutting process optimized, among others, through appropriate tool tangential shifts, in order to obtain a uniform wear distribution on the hob teeth. To determine the constants of the equations used in the tool wear calculations, fly hobbing experiments were conducted. Hereby, it was necessary to modify the fly hobbing kinematics, applying instead of a continuous tangential feed, a continuous axial one. The experimental data with uncoated and coated high speed steel (HSS) tools were evaluated, and correlated to analytical ones, elaborated with the aid of the numerical simulation of gear hobbing. By means of the procedures described in this paper, tool wear prediction as well as the optimization of various magnitudes, as the hob tangential shift parameters can be carried out.

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

2021 ◽  
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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