Tropical Cyclone Rapid Intensification Research Articles

Role of ocean upper layer warm water in the rapid intensification of tropical cyclones: A case study of typhoon Rammasun (1409)

Rammasun intensified rapidly from tropical storm to super typhoon in the northern South China Sea (NSCS) before its landfall on Hainan Island. Analysis of observed data shows that the anomalous ocean upper layer warm water (WW) is important to the rapid intensification of Rammasun. During the period of Rammasun, sea surface temperature (SST) in the NSCS was much warmer than the climatological SST. The anomalous WW supplied more energy to Rammasun, resulting in its rapid intensification. Numerical simulations further confirm that the NSCS WW plays an important role in the rapid intensification of Rammasun. As the WW is removed, the intensification of Rammasun is only 25 hPa, which is 58.1% of that in the original SST-forced run.

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

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.

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

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.

Improvements in the Probabilistic Prediction of Tropical Cyclone Rapid Intensification with Passive Microwave Observations

Abstract The probabilistic prediction of tropical cyclone (TC) rapid intensification (RI) in the Atlantic and eastern Pacific Ocean basins is examined here using a series of logistic regression models trained on environmental and infrared satellite-derived features. The environmental predictors are based on averaged values over a 24-h period following the forecast time. These models are compared against equivalent models enhanced with additional TC predictors created from passive satellite microwave imagery (MI). Leave-one-year-out cross validation on the developmental dataset shows that the inclusion of MI-based predictors yields more skillful RI models for a variety of RI and intensity thresholds. Compared with the baseline forecast skill of the non-MI-based RI models, the relative skill improvements from including MI-based predictors range from 10.6% to 44.9%. Using archived real-time data during the period 2004–13, evaluation of simulated real-time models is also carried out. Unlike in the model development stage, the simulated real-time setting involves using Global Forecast System forecasts for the non-satellite-based predictors instead of “perfect” observational-based predictors in the developmental data. In this case, the MI-based RI models still generate superior skill to the baseline RI models lacking MI-based predictors. The relative improvements gained in adding MI-based predictors are most notable in the Atlantic, where the non-MI versions of the models suffer acutely from the use of imperfect real-time data. In the Atlantic, relative skill improvements provided from the inclusion of MI-based predictors range from 53.5% to 103.0%. The eastern Pacific relative improvements are less impressive but are still uniformly positive.

A Triggering Mechanism for Rapid Intensification of Tropical Cyclones

Triggering processes for the rapidly intensifying phase of a tropical cyclone (TC) were investigated on the basis of numerical experiments using a three-dimensional nonhydrostatic model. The results revealed that the rapid intensification of the simulated TC commenced following the formation of a circular cloud, which occurred about 12 h after the TC became essentially axisymmetric. The circular cloud (eyewall) evolved from a cloudy convective cell that was originally generated near the radius of maximum wind speed (RMW). The development of the convective cell in the eyewall was closely related to the radial location of the strong boundary layer convergence of axisymmetric flow. The radius of maximum convergence (RMC) was small relative to the RMW when the TC vortex was weak, which is consistent with the boundary layer theory for a rotating fluid system on a frictional surface. As the TC intensified, the RMC approached the RMW. An eyewall was very likely to form in the simulated TC when the RMC approached the RMW. Because the RMC is theoretically determined by a Rossby number defined by the maximum tangential velocity, RMW, and Coriolis parameter, a series of numerical experiments was conducted by changing the three parameters. The results were consistent with the hypothesis that intensification occurs earlier for larger Rossby numbers. This finding indicates that initial TC vortices with larger Rossby numbers are more likely to experience rapid intensification and, hence, to evolve into strong hurricanes.

Multidecadal Variability of Tropical Cyclone Rapid Intensification in the Western North Pacific

Abstract This study investigates the variation of tropical cyclone (TC) rapid intensification (RI) in the western North Pacific (WNP) and its relationship with large-scale climate variability. RI events have exhibited strikingly multidecadal variability. During the warm (cold) phase of the Pacific decadal oscillation (PDO), the annual RI number is generally lower (higher) and the average location of RI occurrence tends to shift southeastward (northwestward). The multidecadal variations of RI are associated with the variations of large-scale ocean and atmosphere variables such as sea surface temperature (SST), tropical cyclone heat potential (TCHP), relative humidity (RHUM), and vertical wind shear (VWS). It is shown that their variations on multidecadal time scales depend on the evolution of the PDO phase. The easterly trade wind is strengthened during the cold PDO phase at low levels, which tends to make equatorial warm water spread northward into the main RI region rsulting from meridional ocean advection associated with Ekman transport. Simultaneously, an anticyclonic wind anomaly is formed in the subtropical gyre of the WNP. This therefore may deepen the depth of the 26°C isotherm and directly increase TCHP over the main RI region. These thermodynamic effects associated with the cold PDO phase greatly support RI occurrence. The reverse is true during the warm PDO phase. The results also indicate that the VWS variability in the low wind shear zone along the monsoon trough may not be critical for the multidecadal modulation of RI events.

PDO modulation of ENSO effect on tropical cyclone rapid intensification in the western North Pacific

This study investigates how the Pacific Decadal Oscillation (PDO) modulates the effect of El Nino/Southern Oscillation (ENSO) on tropical cyclone rapid intensification (RI) in the western North Pacific. The analysis shows that the interannual relationship between ENSO and annual RI number in warm PDO phases is strong and statistically significant. In cold PDO phases, however, there is no significant correlation between ENSO and RI on the interannual timescale. The enhancement of the interannual ENSO–RI relationship in warm PDO phases is mainly attributable to the change of the environmental vertical wind shear. The PDO in warm (cold) phases can strengthen (weaken) an El Nino event to increase (reduce) the effects of the warm pool of water over the equatorial Pacific in typhoon season by local diabatic heating. El Nino events are accompanied by the stronger Walker circulation in the equatorial Pacific in the warm PDO phase than in the cold PDO phase. In contrast, the Walker circulation pattern and amplitude associated with La Nina events is less affected by the alternate PDO phase. This tends to make the atmospheric response to ENSO stronger (weaker) in warm (cold) PDO phase, and so is the atmospheric teleconnection of ENSO. Our results indicate that the stratification of ENSO-based statistical RI forecast by the PDO can greatly improve the accuracy of statistical RI predictions.

Are Special Processes at Work in the Rapid Intensification of Tropical Cyclones?

Abstract Probably not. Frequency distributions of intensification and dissipation developed from synthetic open-ocean tropical cyclone data show no evidence of significant departures from exponential distributions, though there is some evidence for a fat tail of dissipation rates. This suggests that no special factors govern high intensification rates and that tropical cyclone intensification and dissipation are controlled by statistically random environmental and internal variability.

Diagnosing Tropical Cyclone Rapid Intensification Using Kernel Methods and Reanalysis Datasets

Abstract Tropical cyclone rapid intensification (RI) continues to be a problem that eludes operational forecasters. Recent work in this area has revealed the value of applying machine learning techniques to classifying storms as RI or non-RI at 24-hours lead time. However, that work showed that differing reanalysis datasets represented the storms in unique ways, offering different discrimination capability and unique predictor sets that are important for RI. The scope of this research is to identify factors important for RI that are consistent among three reanalysis datasets, as these are likely the fields that will provide the greatest discrimination capability. An S-mode rotated principal component analysis was used to formulate unique patterns within RI and non-RI storms, and the resulting RPC scores were used to train a support vector machine classification algorithm that yielded binary RI occurrence output. Base-state meteorological variables (geopotential height, temperature, u and v wind components, vertical velocity, and relative humidity) at single horizontal levels were tested individually as predictors for the SVM. Base-state fields that were consistently good at discriminating RI events from non-RI events among all three reanalysis datasets were deemed most useful for RI classification and will be considered for future forecast applications.

Synoptic-Scale Precursors to Tropical Cyclone Rapid Intensification in the Atlantic Basin

Forecasting rapid intensification (hereafter referred to as RI) of tropical cyclones in the Atlantic Basin is still a challenge due to a limited understanding of the meteorological processes that are necessary for predicting RI. To address this challenge, this study considered large-scale processes as RI indicators within tropical cyclone environments. The large-scale processes were identified by formulating composite map types of RI and non-RI storms using NASA MERRA data from 1979 to 2009. The composite fields were formulated by a blended RPCA and cluster analysis approach, yielding multiple map types of RI’s and non-RI’s. Additionally, statistical differences in the large-scale processes were identified by formulating permutation tests, based on the composite output, revealing variables that were statistically significantly distinct between RI and non-RI storms. These variables were used as input in two prediction schemes: logistic regression and support vector machine classification. Ultimately, the approach identified midlevel vorticity, pressure vertical velocity, 200–850 hPa vertical shear, low-level potential temperature, and specific humidity as the most significant in diagnosing RI, yielding modest skill in identifying RI storms.

The role of ENSO and MJO on rapid intensification of tropical cyclones in the Bay of Bengal during October–December

The influence of El Nino/Southern Oscillation (ENSO) and Madden–Julian Oscillation (MJO) and their combined effect on the rapid intensification (RI) of tropical cyclones (TCs) in the Bay of Bengal (BoB) during the primary cyclone season (October–December) is investigated. An empirical index, called genesis potential index (GPI), is used to quantify the relative importance of four environmental parameters responsible for the modulation of TCs characteristics. The analysis shows that TC frequency and RI of TC’s is higher in La Nina than El Nino regime during the primary TC season in the BoB. The combined effect of enhancement (reduction) in mid-tropospheric humidity (primary factor) and relative vorticity (secondary factor) played a major role in the enhancement (reduction) of the TC activity under La Nina (El Nino) regime. In addition, when the MJO is active over the BoB (phases 3–4; characterized by enhanced convective activity in the BoB) under La Nina regime, environmental conditions were more conducive for enhancement of TC activity and RI of TCs compared to corresponding MJO phase under El Nino regime. Increase in mid-tropospheric humidity and reduction in vertical wind shear were identified as the primary and secondary factors enhancing the likelihood of RI of TCs in the BoB during phases 3–4 of MJO under La Nina regime. Further, the role of accumulated tropical cyclone heat potential (ATCHP) on the RI of TC during primary TC season is also investigated. Our analysis demonstrates that ATCHP is large for TCs which undergo RI compared to TCs not undergoing RI.

Extreme Rapid Intensification of Typhoon Vicente (2012) in the South China Sea

Abstract One of the primary challenges for both tropical cyclone (TC) research and forecasting is the problem of intensity change. Accurately forecasting TC rapid intensification (RI) is particularly important to interests along coastlines and shipping routes, which are vulnerable to storm surge and heavy seas induced by intense tropical cyclones. One particular RI event in the western North Pacific Ocean with important scientific implications is the explosive deepening of Typhoon Vicente (2012). Vicente underwent extreme RI in the northern South China Sea just prior to landfall west of Hong Kong, China, with maximum sustained winds increasing from 50 kt (1 kt = 0.51 m s−1) at 0000 UTC 23 July to 115 kt at 1500 UTC 23 July. This increase of 65 kt in 15 h far exceeds established thresholds for TC RI. Just prior to this RI episode, Vicente exhibited a near-90° poleward track shift. The relationship between the track and intensity change is described, and the authors speculate that the passage of an upper-tropospheric (UT) “inverted” trough was a significant influence. An analysis of real-time numerical model guidance is provided and is discussed from an operational perspective, and high-resolution global model analyses are evaluated. Numerical model forecasts of the UT trough interaction with the TC circulation were determined to be a shortcoming that contributed to the intensity prediction errors for Vicente. This case study discusses the importance of considering UT features in TC intensity forecasting and establishes current modeling capabilities for future research.

Necessary Conditions for Tropical Cyclone Rapid Intensification as Derived from 11 Years of TRMM Data

Abstract Rainfall and convective properties of tropical cyclones (TCs) are statistically quantified for different TC intensity change categories by using Tropical Rainfall Measuring Mission (TRMM) data from December 1997 to December 2008. Four 24-h future intensity change categories are defined: rapidly intensifying (RI), slowly intensifying, neutral, and weakening. It is found that RI storms always have a larger raining area and total volumetric rain in the inner core. The maximum convective intensity in the inner core is not necessarily more intense prior to undergoing an RI episode than a slowly intensifying, neutral, or weakening episode. Instead, a minimum threshold of raining area, total volumetric rain, and convective intensity in the inner core is determined from the RI cases examined in this study. The following necessary conditions for RI are found in the inner core: total raining area > 3000 km2, total volumetric rain > 5000 mm h−1 km2, maximum near-surface radar reflectivity > 40 dBZ, maximum 20-dBZ (40 dBZ) echo height > 8 (4) km, minimum 85-GHz polarization–corrected brightness temperature (PCT) < 235 K, and minimum 10.8-μm brightness temperature < 220 K. To the extent that these thresholds represent all RI cases, they should be of value to forecasters for ruling out RI. This study finds that total lightning activities in the inner core (outer rainband) have a negative (positive) relationship with storm intensification.

On the Rapid Intensification of Hurricane Wilma (2005). Part II: Convective Bursts and the Upper-Level Warm Core

Abstract Previous studies have focused mostly on the roles of environmental factors in the rapid intensification (RI) of tropical cyclones (TCs) because of the lack of high-resolution data in inner-core regions. In this study, the RI of TCs is examined by analyzing the relationship between an upper-level warm core, convective bursts (CBs), sea surface temperature (SST), and surface pressure falls from 72-h cloud-permitting predictions of Hurricane Wilma (2005) with the finest grid size of 1 km. Results show that both the upper-level inertial stability increases and static stability decreases sharply 2–3 h prior to RI, and that the formation of an upper-level warm core, from the subsidence of stratospheric air associated with the detrainment of CBs, coincides with the onset of RI. It is found that the development of CBs precedes RI, but most subsidence warming radiates away by gravity waves and storm-relative flows. In contrast, many fewer CBs occur during RI, but more subsidence warming contributes to the balanced upper-level cyclonic circulation in the warm-core (as intense as 20°C) region. Furthermore, considerable CB activity can still take place in the outer eyewall as the storm weakens during its eyewall replacement. A sensitivity simulation, in which SSTs are reduced by 1°C, shows pronounced reductions in the upper-level warm-core intensity and CB activity. It is concluded that significant CB activity in the inner-core regions is an important ingredient in generating the upper-level warm core that is hydrostatically more efficient for the RI of TCs, given all of the other favorable environmental conditions.

Examining Trends in Satellite-Detected Tropical Overshooting Tops as a Potential Predictor of Tropical Cyclone Rapid Intensification

AbstractA geostationary satellite–derived cloud product that is based on a tropical-overshooting-top (TOT) detection algorithm is described for applications over tropical oceans. TOTs are identified using a modified version of a midlatitude overshooting-top detection algorithm developed for severe-weather applications. The algorithm is applied to identify TOT activity associated with Atlantic Ocean tropical cyclones (TCs). The detected TOTs can serve as a proxy for “hot towers,” which represent intense convection with possible links to TC rapid intensification (RI). The purpose of this study is to describe the adaptation of the midlatitude overshooting-top detection algorithm to the tropics and to provide an initial exploration of possible correlations between TOT trends in developing TCs and subsequent RI. This is followed by a cursory examination of the TOT parameter’s potential as a predictor of RI both on its own and in multiparameter RI forecast schemes. RI forecast skill potential is investigated by examining empirical thresholds of TOT activity and trends within prescribed radii of a large sample of developing North Atlantic TC centers. An independent test on Atlantic TCs in 2006–07 reveals that an empirically based TOT scheme has potential as a predictor for RI occurring in the subsequent 24 h, especially for RI maximum wind thresholds of 25 and 30 kt (24 h)−1 (1 kt ≈ 0.5 m s−1). As expected, the stand-alone TOT-based RI scheme is comparatively less accurate than existing objective multiparameter RI prediction methods. A preliminary experiment that adds TOT-based predictors to an objective logistic regression-based scheme is shown to improve slightly the forecast skill of RI, however.

El Niño‐Southern Oscillation, the Madden‐Julian Oscillation and Atlantic basin tropical cyclone rapid intensification

Both El Niño‐Southern Oscillation (ENSO) and the Madden‐Julian Oscillation (MJO) have previously been documented to impact Atlantic basin tropical cyclone (TC) activity through alterations in large‐scale fields such as vertical wind shear, mid‐level moisture, sea level pressure and sea surface temperature. Atlantic TC activity has been shown to be enhanced when La Niña conditions are present in the tropical Pacific, while activity is reduced when El Niño conditions occur. Atlantic TC activity is enhanced when the convectively active phase of the MJO is over Africa and the western Indian Ocean (Phases 1–2), while TC activity is suppressed when the convectively active phase of the MJO is over the tropical Pacific (Phases 6–7). These relationships are shown to extend to Atlantic basin rapid intensification (RI) events (typically defined as intensification of 30 knots or greater in 24 h), with nearly three times as many RI events in La Niña years when compared with El Niño years. In addition, approximately four times more RI episodes occur when the MJO exceeds one standard deviation in Phases 1–2 than when the MJO exceeds one standard deviation in Phases 6–7. Storms forming in Phases 1–2 are twice as likely to undergo at least one RI episode during their lifetime as storms forming in Phases 6–7. Even stronger relationships are seen when the MJO and ENSO are considered in combination.

Predicting tropical cyclone rapid intensification using the 37 GHz ring pattern identified from passive microwave measurements

A distinctive satellite‐derived precipitative ring pattern around the tropical cyclone (TC) center is found to be related to rapid intensification (RI). The ring pattern appears on the Naval Research Laboratory (NRL) 37 GHz passive microwave composite color product as a cyan color ring. The probability of RI is evaluated for cases with this ring pattern by reviewing images of the NRL product for 84 TCs during 2003–2007 in the Atlantic basin using 6‐hourly National Hurricane Center (NHC) best track data. It is found that when combining the ring criterion with the Statistical Hurricane Prediction Scheme (SHIPS) RI Index (RII), the probability of RI almost doubled, indicating that both the ring and SHIPS RII contain independent information for RI prediction. A subjective technique for predicting RI is proposed using both the 37 GHz ring and the SHIPS RII. Both the probability of detection (POD) and the false alarm ratio (FAR) for the combined ring+SHIPS RII are lower than those for SHIPS RII alone (POD, 24% versus 77%, and FAR, 26% versus 66%) when treating every 6‐hr synoptic time as a separate case. Since the method was initially developed for RI event‐based forecasts, statistics based on 2003–2007 Atlantic RI events, which consist of a contiguous period where any 24‐hour subset shows at least a 30 kt intensity increase, are also generated. The method captures 21 out of these 28 events and produces 2 false alarms, producing a POD of 75% and a FAR of 9%.

New Probabilistic Forecast Models for the Prediction of Tropical Cyclone Rapid Intensification

Abstract The National Hurricane Center currently employs a skillful probabilistic rapid intensification index (RII) based on linear discriminant analysis of the environmental and satellite-derived features from the Statistical Hurricane Intensity Prediction Scheme (SHIPS) dataset. Probabilistic prediction of rapid intensity change in tropical cyclones is revisited here using two additional models: one based on logistic regression and the other on a naïve Bayesian framework. Each model incorporates data from the SHIPS dataset over both the North Atlantic and eastern North Pacific Ocean basins to provide the probability of exceeding the standard rapid intensification thresholds [25, 30, and 35 kt (24 h)−1] for 24 h into the future. The optimal SHIPS and satellite-based predictors of rapid intensification differ slightly between each probabilistic model and ocean basin, but each set of optimal predictors incorporates thermodynamic and dynamic aspects of the tropical cyclone’s environment (such as vertical wind shear) and its structure (such as departure from convective axisymmetry). Cross validation shows that both the logistic regression and Bayesian probabilistic models are skillful relative to climatology. Dependent testing indicates both models exhibit forecast skill that generally exceeds the skill of the present operational SHIPS-RII and a simple average of the probabilities provided by the logistic regression, Bayesian, and SHIPS-RII models provides greater skill than any individual model. For the rapid intensification threshold of 25 kt (24 h)−1, the three-member ensemble mean improves the Brier skill scores of the current operational SHIPS-RII by 33% in the North Atlantic and 52% in the eastern North Pacific.

New probabilistic forecast models for the prediction of tropical cyclone rapid intensification

New probabilistic forecast models for the prediction of tropical cyclone rapid intensification

Relationship of Rapid Intensification of Tropical Cyclones to Dynamical/Thermodynamical Parameters

Many avenues of research are currently being tried for understanding and predicting hurricane intensity forecasts. We have listed several such research avenues being pursued by the research community. This article addresses the use of high-resolution aircraft reconnaissance datasets used for daily data assimilation over three years of hurricane histories that cover rapid intensification cases. We show a number of dynamical and thermodynamical parameters, derived from these datasets, which seem to hold promise for future use in short range statistical forecasts on rapid intensification. These include the vertical differential of heating in the complete potential vorticity equation, the conversion of divergent kinetic energy to rotational kinetic energy, the transformation of shear vorticity to curvature vorticity, and the advection of the earth's and the relative angular momentum into the inner core of hurricanes. We find a rapid growth in the time history of each of these parameters as the rapid intensification occurs. These are demonstrated for a number of recent hurricanes.