Tropical Cyclone Translation Speed Research Articles

Competition between ocean thermal structure and tropical cyclone characteristics modulates ocean environmental responses in the Yellow and Bohai Seas

To study the environmental responses of tropical cyclones (TCs) in continental shelf regions, TCs passing over the Yellow Sea and Bohai Sea (YBS) during 2002–2020 were investigated, with a special focus on how competition between ocean thermal structure and TC characteristics modulates ocean surface changes. The spatial distributions of the climatic mixed layer depth (MLD), accumulated wind forcing power index (WPi), accumulated sea surface temperature (SST) changes and accumulated chlorophyll (Chl-a) changes in the YBS were calculated. The linear regressions indicate that both the TC-induced SST cooling and TC-induced Chl-a increase are correlated with the TC wind speed rather than the translation speed, especially when the TC forcing depth (Zmixing) is greater than the MLD. Otherwise, both the changes in SST and Chl-a are correlated with the TC translation speed when Zmixing is shallower than the MLD. Further study has shown that whether TCs can break the MLD is also a key condition for oceanic responses. In the southern YBS, which has a deep-sea basin and MLD, the TC wind speed is the major factor affecting SST cooling and Chl-a increase, as TCs need more strength to reach the MLD. However, in the northern YBS, which has the shallowest sea basin and MLD, even weak TCs can easily break the MLD and reach the seabed; thus, ocean surface changes are associated mainly with the TC translation speed. The composite results reveal that both the maximum SST cooling center (1.64 °C) and the maximum Chl-a increasing center (0.14 log10(mg/m3)) are located on the right and behind the TC center, respectively. In addition, TC-induced SST cooling and Chl-a increase were initiated two days prior to TC passage and then reached their maximum values after 1 day. It takes approximately 7–8 days for the Chl-a concentration to recover, but it takes a much longer time (>15 days) for the SST to recover.

Environmental ingredients that lead to tornado outbreak and tornado failure: A comparison between two similar recurving tropical cyclones

AbstractRecurving tropical cyclones (TCs) can sometimes produce tornado outbreaks, while some TCs with similar tracks and intensities may produce none of tornado, which makes it challenging to assess tornado risk within recurving TCs. This study investigates two recurving TCs, Typhoon Yagi (2018) and Typhoon In‐Fa (2021), that made landfall in eastern China. Despite the similar recurving tracks and intensities, Yagi produced 11 tornadoes while In‐Fa produced none. Results show that both TCs were characterized by similar large‐scale conditions that were dynamically favourable for tornadoes during the recurvature process. The non‐tornadic In‐Fa even featured a higher shear and helicity environment in its northeast sector than did the tornado‐productive Yagi. The greatest difference between Yagi and In‐Fa is the thermodynamic instability owing to the different lower–middle‐tropospheric lapse rates that are attributable to the differences in air trajectories at low levels. In‐Fa featured marginal instability due to the cooler air at low levels because almost all of the air parcels came from the Pacific Ocean while most air parcels for Yagi came from the warm land. The cooler low‐level air tends to create higher relative humidity in In‐Fa's interior and thus leads to widespread precipitation which in turn also contributes to the low‐level cooling. The different air trajectories are demonstrated related to the TC's translation speed, size and synoptic characteristics days before TC's landfall. Numerical simulations suggest that the upward motions within the widespread precipitation regions of In‐Fa are overall weaker than those of Yagi due to the limited instability in the former. These findings suggest that even though two TCs were characterized by similar tracks, intensities and large‐scale forcings, their different low‐level air pathways may have significant influence on priming the mesoscale environment for supercell or tornado formation.

Total water levels along the South Atlantic Bight during three along-shelf propagating tropical cyclones: relative contributions of storm surge and wave runup

Abstract. Total water levels (TWLs), including the contribution of wind waves, associated with tropical cyclones (TCs) are among the most damaging hazards faced by coastal communities. TC-induced economic losses are expected to increase because of stronger TC intensity, sea level rise, and increased populations along the coasts. TC intensity, translation speed, and distance to the coast affect the magnitude and duration of increased TWLs and wind waves. Under climate change, the proportion of high-intensity TCs is projected to increase globally, whereas the variation pattern of TC translation speed also depends on the ocean basin and latitude. There is an urgent need to improve our understanding of the linkages between TC characteristics and TWL components. In the past few years, hurricanes Matthew (2016), Dorian (2019), and Isaias (2020) propagated over the South Atlantic Bight (SAB) with similar paths but resulted in different coastal impacts. We combined in situ observations and numerical simulations with the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) modeling system to analyze the extreme TWLs under the three TCs. Model verification showed that the TWL components were well reproduced by the present model setup. Our results showed that the peak storm surge and the peak wave runup depended mainly on the TC intensity, the distance to the TC eye, and the TC heading direction. A decrease in TC translation speed primarily led to longer exceedance durations of TWLs, which may result in more severe economic losses. Wave-dependent water level components (i.e., wave setup and wave swash) were found to dominate the peak TWL within the near-TC field. Our results also showed that in specific conditions, the prestorm wave runup associated with the TC-induced swell may lead to TWLs higher than at the peak of the storm. This was the case along the SAB during Hurricane Isaias. Isaias's fast TC translation speed and the fact that its swell was not blocked by any islands were the main factors contributing to these peak TWLs ahead of the storm peak.

Regime Shifts in the Damage Caused by Tropical Cyclones in the Guangdong–Hong Kong–Macao Greater Bay Area of China

Tropical cyclones (TCs) pose a significant threat in terms of wind-induced damage and storm risk to the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) of China. In this research, annual power dissipation index (PDI) and storm surge and wave destructive potential (SDP) index from June to November were used to estimate the damage caused by the TC events in the buffer zone of the GBA. The regime shifts in 1993 and 2013 were identified through the Bayesian changepoint detection in six TC datasets. The TC-induced damage during 1994–2012 (the low-damage period) was weaker than that in 1977–1993 and 2013–2020 (the high-damage periods). The intensity and size of stronger TCs are the dominant factors responsible for the interdecadal changes in the TC damage. This may be explained by the influences of sea surface temperature (SST), surface latent heat flux and mid-level relative humidity. During high-damage periods, TCs can extract more energy from the ocean, leading to increased TC intensity and larger size. Conversely, during low-damage periods, TCs undergo a decrease in energy intake, resulting in reduced TC power and smaller size. The variations in the SST are relative to the Luzon Strait transport. In addition, the reduction in TC translation speed is unfavorable for the development of TCs in low-damage periods. Further research suggested that mid-level steering flow affects the TC movement velocity. The results offer valuable insights into the variations in the TC-induced damage in the GBA.

Predicting Tropical Cyclone‐Induced Sea Surface Temperature Responses Using Machine Learning

AbstractThis study proposes to construct a model using random forest method, an efficient machine learning‐based method, to predict the spatial structure and temporal evolution of the sea surface temperature (SST) cooling induced by northwest Pacific tropical cyclones (TCs), a process of the so‐called wind pump. The predictors in use include 12 predictors related to TC characteristics and pre‐storm ocean conditions. The model is shown to skillfully predict the spatiotemporal evolutions of the cold wake generated by TCs of different intensity groups, and capture the cross‐case variance in the observed SST response. Another model is further built based on the same method to assess the relative importance of the 12 predictors in determining the magnitude of the maximum cooling. Computations of feature scores of those predictors show that TC intensity, translation speed and size, and pre‐storm mixed layer depth and SST dominate, depending on the area where the cooling is considered.

An update on the influence of natural climate variability and anthropogenic climate change on tropical cyclones

A substantial number of studies have been published since the Ninth International Workshop on Tropical Cyclones (IWTC-9) in 2018, improving our understanding of the effect of climate change on tropical cyclones (TCs) and associated hazards and risks. These studies have reinforced the robustness of increases in TC intensity and associated TC hazards and risks due to anthropogenic climate change. New modeling and observational studies suggested the potential influence of anthropogenic climate forcings, including greenhouse gases and aerosols, on global and regional TC activity at the decadal and century time scales. However, there are still substantial uncertainties owing to model uncertainty in simulating historical TC decadal variability in the Atlantic, and the limitations of observed TC records. The projected future change in the global number of TCs has become more uncertain since IWTC-9 due to projected increases in TC frequency by a few climate models. A new paradigm, TC seeds, has been proposed, and there is currently a debate on whether seeds can help explain the physical mechanism behind the projected changes in global TC frequency. New studies also highlighted the importance of large-scale environmental fields on TC activity, such as snow cover and air-sea interactions. Future projections on TC translation speed and medicanes are new additional focus topics in our report. Recommendations and future research are proposed relevant to the remaining scientific questions and assisting policymakers.

Multidecadal Variability of Tropical Cyclone Translation Speed over the Western North Pacific

Abstract Tropical cyclone (TC) translation speed (TCS) over the western North Pacific (WNP) has experienced a long-term decreasing trend. To date, however, little is known about the multidecadal variability of TCS and its possible influence on this trend. This study investigated the multidecadal variability of the WNP TCS and the underlying physical mechanisms. Results show that the WNP TCS presents robust multidecadal variability during the past seven decades, which is dominated by the TCS over the extratropics. Further analysis shows that the Atlantic multidecadal oscillation (AMO) is responsible for the TCS multidecadal variability. AMO positive (negative) phases lead to favorable (unfavorable) large-scale environmental conditions for maintaining TCs over the extratropics, which results in longer (shorter) residence time for TCs having been accelerated by the midlatitude westerlies, thus, leading to higher (lower) TCS. The TCS phase shift strongly offsets its slowdown trend, leading to the inconsistent trends during past decades. This inconsistency may also relate to the influence of extratropical transitioned cyclones without being totally excluded. These cyclones may be inhomogeneously recorded due to the absence of satellite observation before the 1980s. Our results indicate that internal variation such as AMO may dominate TCS low-frequency variations over the past several decades. Previous studies have attributed the inconsistent trends of TCS during different subperiods to data inhomogeneity. This study shows that AMO can modulate the TCS trends in different subperiods with phase shift, thus providing new evidence for the recent controversial TCS slowdown.

Interdecadal Change of Tropical Cyclone Translation Speed during Peak Season in South China Sea: Observed Evidence, Model Results, and Possible Mechanism

Abstract Long-term variations in the translation speed of tropical cyclones (TCs) in the South China Sea (SCS) are examined based on five TC datasets from different institutions. TC translation speed during the TC peak season in the SCS shows an evident rhythm of interdecadal change throughout 1977–2020. This interdecadal change in TC translation speed in the SCS can be well reproduced by a newly developed trajectory model. The model results indicate that the interdecadal change in TC translation speed is primarily due to an interdecadal change in the steering flow in the SCS. Such an interdecadal change in the steering flow is closely related to an east–west shift of the subtropical high in the western North Pacific (WNP) ocean basin, which may be driven by the zonal sea surface temperature (SST) gradient between the north Indian (NI) and WNP ocean basins. A new index of the zonal SST gradient is proposed, which is shown to be effective for indicating the interdecadal change in east–west shift of subtropical high, and thus, the TC translation speed in the SCS. Significance Statement Identification of the prevailing trend of tropical cyclone activities due to climate change has been a challenging subject of scientific studies in recent years. This research focuses on the long-term variability of the tropical cyclone translation speed in the South China Sea. It is demonstrated that there is evidently an interdecadal rhythm for variation of the tropical cyclone translation speed in the South China Sea, and this variation can be well reproduced using a newly developed trajectory model. Based on the simulation results, the possible mechanism for this variation is also elucidated.

Poleward Migration of Spatial Asymmetry in Tropical Cyclone Precipitation over the Western North Pacific

Comprehensive understanding of the spatial characteristics of tropical cyclone (TC) precipitation is essential for effective socioeconomic planning and scientific research. The present study examines the spatial asymmetry in TC precipitation over the western North Pacific (WNP) concerning various factors, including latitudes, sea surface temperature (SST), TC intensity, and translation speed, based on satellite observations. The results reveal a significant poleward migration of TC precipitation asymmetry particularly above 15° N. Furthermore, the asymmetry exhibits considerable sensitivity to changes in TC center latitudes and SSTs, characterized by anticlockwise and northeastward migration, respectively. The poleward migration of TC precipitation spatial asymmetry is primarily due to the poleward decreasing SST, increasing vertical wind shear and increasing TC translation speed. These findings contribute to a comprehensive understanding of TC behavior over the WNP and provide valuable insights for disaster preparedness and mitigation efforts.

Study of Landfalling Typhoon Potential Maximum Gale Forecasting in South China

Based on historical tropical cyclone (TC) tracking data and wind data from observation stations, four comparison experiments were designed that considered TC translation speed similarity and five new ensemble schemes in an improved Dynamical-Statistical-Analog Ensemble Forecast (DSAEF) model for Landfalling Typhoon Gale (LTG), which was tested in terms of forecast capability in South China. The results showed that the improved DSAEF_LTG model with the incorporation of TC translation speed and a new ensemble scheme could improve the forecast threat score (TS) and reduce both the false alarm ratio and the missing ratio in comparison with corresponding values attained before the improvement. The TS of the new ensemble scheme model (DLTG_3) was 0.34 at threshold above Beaufort Scale 7, which was 31% better than that of the unimproved model (DLTG_1). At a threshold above Beaufort Scale 10, the TS of DLTG_3 indicated even greater improvement, reaching 0.25, i.e., 127% higher than that of DLTG_1. The results of the experiments illustrated the marked improvement achievable when using the new ensemble scheme. The reasons for the differences in the DSAEF_LTG model forecasts before and after the introduction of TC translation speed and the new ensemble scheme were analyzed for the cases of Typhoon Haima and Typhoon Hato.

Development of a fully coupled wind stress-wave-ocean coastal model system

ABSTRACT To conserve momentum flux across the air-sea interface, a new wind stress-wave-ocean coupled coastal model system is developed. Via simulating a specific idealized tropical cyclone (TC), this model is firstly applied to study the impacts of three wave effects, including the commonly studied wave-breaking induced acceleration, wave-enhanced bottom friction and the seldom studied wave modified surface stress (WMWS), and the conservation of momentum flux across air-sea interface (MFB) on the predictions of storm surge and inundation. It is then further applied to investigate the role of above four effects in modeling the peak surge and inundation by generalizing the TC forcing with various physical parameters, including the TC intensity, size, translation speed, and bottom slope. The model results reveal that WMWS can contribute considerably to the total surge height and inundation distance in a relatively high-intensity TC and its contribution depends weakly on the varying bottom slopes, TC sizes or translation speeds. By contrast, the MFB can only considerably reduce the maximum storm surge with a small bottom slope, while its reduction on inundation distance is more significant. The present study thus highlights the importance and necessity of incorporating the commonly ignored effects of WMWS and MFB in coastal modeling.

Sea Surface Wind Structure in the Outer Region of Tropical Cyclones Observed by Wave Gliders

AbstractUnderstanding the sea surface wind structure during tropical cyclones (TCs) is the key for study of ocean response and parameterization of air‐sea surface in numerical simulation. However, field observations are scarce. In 2019, three wave gliders were deployed in the South China Sea and the adjacent Western Pacific region, which acquired sea surface wind structure of eight TCs. Analysis of the field data suggests that the wave glider‐observed surface winds are consistent with most analysis/reanalysis data (i.e., ERA5, Cross‐Calibrated Multi‐Platform, and National Centers for Environmental Prediction‐Global Data Assimilation System) and Soil Moisture Active Passive. Both wave glider observations and analysis/reanalysis data indicate that TC wind fields induce an obvious increase in speed toward the sea surface together with a sharp change in direction, showing an asymmetric wind structure which is sensitive to TC translation speed and intensity. Larger mean values of wind speed and inflow angle are located on the right side along TC tracks. The inflow angle shows a highly dynamic dependence on the radial distance from the TC center, the TC intensity, as well as the TC‐relative azimuth. Comparisons between field observations and theoretical models indicate that the most widely used, ideal TC wind profile models can largely represent the observed sea surface wind structure, but generally underestimate the wind speed due to lack of consideration of background wind. Moreover, simple ideal models (e.g., the modified Rankine vortex model) may outperform complex models when accurate information of TCs is limited. Wave glider observations have potential for better understanding of air‐sea exchanges and for improvements of the corresponding parameterization schemes.

The relationship between sea surface temperature anomalies, wind and translation speed and North Atlantic tropical cyclone rainfall over ocean and land

There have been increasing losses from freshwater flooding associated with United States (US) landfalling hurricanes in recent years. This study analyses the relationship between sea surface temperature anomalies (SSTA), wind and translation speed and North Atlantic tropical cyclone precipitation (TCP) for the period 1998-2017. Based on our statistical analysis of observation data, for a 1 °C SST increase in the main development region (MDR), there is a 6% increase (not statistically significant) in the TCP rate (mmhr−1) over the Atlantic, which rises to over 40% over land (US states) and appears linked not only to the Clausius-Clapeyron relationship but also to the increase in tropical cyclone (TC) intensity associated with increasing SSTA. Total annual TCP is significantly correlated with the SST in the MDR. Over the Atlantic there is an increase of 116% and over land there is an increase of 140% in total TCP for a 1 °C rise in SST in the MDR. Again, this is linked to the increase in windspeed and the number of TC tracks which also rises with positive SSTAs in the MDR. Our analysis of landfalling TC tracks for nine US states provides a systematic review and highlights how TCP varies by US state. The highest number of landfalls per year are found in Florida, North Carolina and Texas. The median tropical cyclone translation speed is 20.3kmhr−1, although this falls to 16.5 kmhr−1 over land and there is a latitudinal dependence on translation speed. Overall, we find a different TCP response to rising SST over the ocean and land, with the response over land over four times more than the Clausius-Clapeyron rate. The links between SSTA in the MDR and both TCP rate and annual total TCP provide useful insights for seasonal to decadal US flood prediction from TCs.

Increase in tropical cyclone rain rate with translation speed

In general, tropical cyclone (TC) rainfall accumulation usually decreases with faster TC translation speed but increases with heavier rain rate. However, how the TC rain rate changes with translation speed is unclear. Here we show that, in all TC basins, the average TC rain rate significantly increases with translation speed. On average, the rain rate in a fast-moving TC is 24% higher than in a slow one. This difference increases with TC intensity, with category 3–5 TCs having a 42% increase while tropical depressions exhibit only a 9% increase. The increase in the average TC rain rate with translation speed is mainly caused by the TC net inflow in the lower troposphere, as well as vertical wind shear. These findings have important implications not only for a deeper understanding of rain rate changes in a translating TC but also for short-term forecasts of TC rainfall and disaster preparedness.

Slowdown in Landfalling Tropical Cyclone Motion in South China

AbstractChina is one of the countries suffering the most tropical cyclone (TC) disasters, while changes in translation speed of TCs landfalling in China remain unclear. Here we found that the translation speed of landfalling TCs in south China during the boreal summer has significantly decreased by 0.3 m s−1decade−1 during 1979–2019, which is largely driven by a decadal deceleration in steering flow in the late 1990s. The slowdown in steering flow is found to be a balance of the opposite effects of the negative phase of the Pacific Decadal Oscillation and sea surface temperature (SST) warming in the Indian Ocean since the late 1990s. Given the recent Indian Ocean SST warming has been viewed as a footprint of external forcing, the results suggest that the effects of external forcing and natural variability on TC translation speed can offset each other.

Introducing TC Translation Speed into the Dynamical–Statistical–Analog Ensemble Forecast for Landfalling Typhoon Daily Precipitation Model and Simulating the Daily Precipitation of Supertyphoon Lekima (2019)

Abstract The Dynamical–Statistical–Analog Ensemble Forecast for Landfalling Typhoon Daily Precipitation (DSAEF_LTP_D) model is introduced in this paper. To improve the DSAEF_LTP_D model’s forecasting ability, tropical cyclone (TC) translation speed was introduced. Taking Supertyphoon Lekima (2019), which produced widespread heavy rainfall from 9 to 11 August 2019 as the target TC, two simulation experiments associated with the prediction of daily precipitation were conducted: the first involving the DSAEF_LTP_D model containing only the TC track (the actual trajectory of the TC center), named DSAEF_LTP_D-1; and the second containing both TC track and translation speed, named DSAEF_LTP_D-2. The results show the following: 1) With TC translation speed added into the model, the forecasting performance for heavy rainfall (24-h accumulated precipitation exceeding 50 and 100 mm) on 9 and 10 August improves, being able to successfully capture the center of heavy rainfall, but the forecasting performance is the same as DSAEF_LTP_D-1 on 11 August. 2) Compared with four numerical weather prediction (NWP) models (i.e., ECMWF, GFS, GRAPES, and SMS-WARMS), the TS100 + TS50 (the sum of TS values for predicting 24-h accumulated precipitation of ≥100 and ≥50 mm) of DSAEF_LTP_D-2 is comparable to the best performer of the NWP models (ECMWF) on 9 and 10 August, while the performance of DSAEF_LTP_D model for predicting heavy rainfall on 11 August is poor. 3) The newly added similarity regions make up for the deficiency that the similarity regions are narrower when the TC track is northward, which leads to DSAEF_LTP_D-2 having a better forecasting performance for heavy rainfall on 11 August, with the TS100 + TS50 increasing from 0.3021 to 0.4286, an increase of 41.87%.

Climate trends in tropical cyclone-induced precipitation and wind over Shanghai

The trends in annual precipitation and wind induced by tropical cyclones (TCs) over Shanghai during the last 40 years are estimated. Results indicate that there is a significant increasing trend in the annual total precipitation induced by TCs, which is related to the significant positive trends in daily precipitation and annual torrential rain days. Meanwhile, a significant decreasing trend shows in maximum sustained wind, which seems to be related to the downward trend in the intensity of TCs when affecting Shanghai. The annual frequencies of affected TCs, TC translation speed and distance from Shanghai when affecting Shanghai have no obvious tendency. The different trends in precipitation and wind suggested that a more comprehensive metric for assessing TCs' influence on society is necessary.

Trends of Tropical Cyclone Translation Speed over the Western North Pacific during 1980−2018

Tropical cyclone (TC) translation speed often affects the time of strong wind attacks and precipitation accumulation in the areas that TCs pass through. Therefore, the trend of TC translation speed has important implications for TC-related risks in the current and future climate. In this paper, the trends of TC translation speed over the Western North Pacific (WNP) from 1980 to 2018 are analyzed, and TC lifetime maximum intensity (LMI) is proposed as a factor related to the interdecadal change of translation speed. During the periods with accurate data, 1980–1997 shows a decreasing trend in TC translation speed while an increasing trend was found in 1998–2018. The main lifetime period contributing to a TC translation speed change is before the occurrence of the LMI. The change in the trend is related to both the TC’s characteristics itself and the environmental factors. For the period 1998–2018, an increasing trend of TC intensity has a significant influence on the trend of translation speed. For the environmental factors, a trend of east wind enhancement at and above 500 hPa as the steering flow is found mostly correlated in the active TC region of the WNP with westward translation before reaching LMI, accompanied by a weakening trend of 200–850 hPa vertical wind shear, and an increasing trend of potential intensity.

Comparison of Tropical Cyclone Wind Radius Estimates between the KMA, RSMC Tokyo, and JTWC

This study compared estimates of gale-force wind radii (R30 or R34) and storm-force wind radii (R50) of tropical cyclones (TC) by three agencies—the Korea Meteorological Administration (KMA), the Regional Specialized Meteorological Center (RSMC) Tokyo, and the Joint Typhoon Warning Center (JTWC)—in the western North Pacific during 2015–2018 and investigated the characteristics of these estimates. The results showed that the KMA’s R30 and R50 estimates were smaller (38% and 29%, respectively) than those of the RSMC Tokyo, and larger (11%) for R30 and smaller (12%) for R50 than those of the JTWC. The differences between these agencies seem to be largely determined by whether the agency estimates wind radii based only on a TC’s own winds or on TC winds combined with other mid-latitude synoptic systems to make TC warnings more comprehensive. The former is mainly the practice of the KMA and JTWC, whereas the latter is mainly the practice of the RSMC Tokyo. The factors considered for estimating wind radii also differ between the agencies: the KMA heavily relies on TC intensity—the higher the intensity, the larger the radius—while the RSMC Tokyo and JTWC rely less on TC intensity than the KMA but additionally consider the latitude and storm translation speed in their estimations. In particular, the TC translation speed considered by the RSMC Tokyo and JTWC explains why their estimated wind radii exhibit, on average, greater asymmetries (i.e., greater differences between the longest and shortest radii) than those estimated by the KMA. The findings of agency-dependent characteristics of TC wind radius data help to better determining and understanding the TC impact areas for TC risk reduction and management.

Recent tropical cyclone changes inferred from ocean surface temperature cold wakes

It has been challenging to detect trends of tropical cyclone (TC) properties due to temporal heterogeneities and short duration of the direct observations. TCs impact the ocean surface temperature by creating cold wakes as a “fingerprint”. Here we infer changes of the lifetime maximum intensity (LMI), size and integrated kinetic energy from the cold wakes for the period 1982–2019. We find a globally enhanced local cold wake amplitude 3 days after the LMI of − 0.12 ± 0.04 °C per decade whereas the cold wake size does not show any significant change. Multivariate regression models based on the observed ocean cooling, the TC translation speed and the ocean mixed layer depth are applied to infer LMI and TC size. The inferred annual mean global LMI has increased by 1.0 ± 0.7 m s−1 per decade. This inferred trend is between that found for two directly observed data sets. However, the TC size and the TC destructive potential measured by the integrated kinetic energy, have not altered significantly. This analysis provides new independent and indirect evidence of recent TC LMI increases, but a stable size and integrated kinetic energy.