Power Dissipation Index Research Articles

Distinct Features of Tropical Cyclone Landfall over East Asia during Various Types of El Niño

Abstract Numerous studies focus on the impacts of ENSO diversity on tropical cyclone (TC) activities in the western North Pacific (WNP). In recent years, there is a growing threat of landfalling and northward-moving TCs in East Asia, accompanying an increase in central Pacific (CP) El Niño. Here, we aim to discover variations in landfalling TCs during various types of CP El Niño (CP-I and CP-II El Niño). It is found that significant changes in landfalling and going northward TCs over East Asia north 20°N are modulated by CP-I El Niño. During CP-I El Niño, TCs tend to landfall more often over the mainland of China with longer duration, moving distance, and stronger power dissipation index (PDI) after landfall and increased TC-induced rainfall, due to favorable conditions (beneficial steering flow, weak vertical wind shear, increased specific humidity, increased soil moisture, and temperature), especially significant over the northeastern part. The situation over the mainland of China is reversed during eastern Pacific (EP) El Niño and CP-II El Niño, with a significant decrease in the characteristics with corresponding unfavorable environments. Over the Korean Peninsula and Japan, the frequency of TC landfalls, as well as the duration and the moving distance after landfall, exhibits greater levels during CP-I and CP-II El Niño than during EP El Niño due to favorable steering flow, and thus, TC-induced rainfall enhances correspondingly. Regarding the PDI over the Korean Peninsula and Japan, it remains relatively consistent across all El Niño types. However, a notable increase in the PDI during EP El Niño could be attributed to the higher intensity of TCs prior to landfall.

Decreasing trend in destructive potential of tropical cyclones in the South Indian Ocean since the mid-1990s

Tropical cyclone activity often leads to many adverse impacts and assessing their destructiveness is a crucial scientific concern. Here we investigated changes in the destructiveness of tropical cyclones worldwide using the power dissipation index and found that there is no clear trend in most basins, but a significant decrease in power dissipation index has been detected in the South Indian Ocean basin since 1994, which is almost entirely due to a decrease in both tropical cyclone frequency and duration in this basin. The decrease in tropical cyclone frequency is influenced by increased atmospheric stability. The decrease in tropical cyclone duration can be attributed to the changes in tropical cyclone locations. In addition, the weakened subtropical high is only observed in the South Indian Ocean (i.e., the Mascarene High), which is also associated with the decrease in tropical cyclone destructiveness. These findings have implications for assessing the destructive potential of future tropical cyclones.

Seasonal prediction of tropical cyclones activity in the North Indian Ocean during post‐monsoon months

AbstractThe frequency and power dissipation index (PDI) of tropical cyclones (TCs) in the North Indian Ocean (NIO) has dramatically grown over the last 10 years, according to our analysis utilizing the European Centre for Medium Range Weather Forecasts reanalysis version‐5 (ERA5) dataset and the India Meteorological Department (IMD) best track data over the period 1982–2021. Our findings indicate that the recent increase in the post‐monsoon TC PDI over NIO is caused by a reduction in wind shear and an increase in convective available potential energy over the Bay of Bengal. The importance of improving our understanding and developing more accurate predictions of the TCs activity has increased as TCs become more frequent and intense owing to the effects of global warming. This study therefore develops TC prediction models for frequency and PDI over NIO for various lead times that vary from 2 to 8 months in addition to the trend analysis employing the ERA5 and IMD best track data. The potential predictors used in proposed model are surface temperature (2 m temperature over land and sea surface temperature over oceanic regions), vertical wind shear, winds (zonal, meridional), geopotential height and temperature at different pressure levels during January–August. The developed models are remarkably accurate (skill is ~94%) in forecasting TCs frequency and PDI. The proposed models outperform the best performing models that are already in use for long‐range TC activity prediction. With a lead‐time as long as up to 8 months, this effort is the first to investigate the possibility of forecasting the frequency and PDI of post‐monsoon TC activity over the NIO with good accuracy. Therefore, the developed models show an operational potential for seasonal TC activity forecast over the NIO.

Exploring the Complex Dynamics of Tropical Cyclone Activity in the Southern Indian Ocean: A Multidecade Analysis

This study analyzes tropical cyclones (TCs) in the Southern Indian Ocean from 1970 to 2022, utilizing data from the International Best Track Archive for Climate Stewardship (IBTrACS) and Sea Surface Temperature (SST) data from ERA-5. Trends are assessed with Sen's slope method. Significant TC shifts are evident. Categories 1-2 TCs have substantially reduced in number, duration, and speed, indicating an overall decline in activity. Conversely, more powerful TCs (categories 3-5) have intensified, driven by rising SST. This intensification is associated with alarming increases in the Power Dissipation Index (PDI) and Accumulated Cyclone Energy (ACE), reflecting heightened destructive potential. TCs predominantly occur during DJFM, influenced by elevated SST compared to MJJASO. Climate drivers, including El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Madden-Julian Oscillation (MJO), significantly affect TC characteristics. Elevated TC activity coincides with La Niña, neutral ENSO phases, and positive IOD events. At the same time, MJO influences are nuanced, leading to a slight TC activity decline, potentially due to data limitations in specific MJO phases. This study offers vital climatological insights into evolving TC risks in the Southern Indian Ocean, aiding agencies and decision-makers in understanding TC-related risks in the region.

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.

Prediction of Coral Sea tropical cyclone power and latitude of maximum intensity using climate indices

Tropical cyclone (TC) wind power, often highly destructive, can be quantified using the power dissipation index (PDI) and in this study, the PDIs for Coral Sea TC tracks, as well as the latitude of maximum intensity (LMI) were investigated for correlation with climatological indices. Multiple linear regression with collinearity removed and an overall Pearson correlation of 0.7 or above was used for this. The results for all tracks showed that three indices dominated for PDI: Niño 4 Sea Surface Temperature (SST), the Dipole Mode Index (DMI) and the Madden Julian Oscillation (MJO). Coral Sea TC tracks clustered by maximum windspeed-weighted locations were then examined: For cluster 1 (located more south-east), the additional influence of the Southern Annular Mode (SAM) was apparent, whilst for cluster 2 (located more north-west), the same indices dominated as for the all-tracks model. For LMI, four indices were identified: the Indian Ocean East SST Anomaly (DMI E), the MJO, the Southern Oscillation Index (SOI) and the SAM. Only TCs clustered in the northeast of Australia had a valid model for LMI, with correlation 0.8, using three indices: DMI E, DMI and the SOI. Overall, raised Niño 4 SST combined with a negative DMI and low MJO amplitude were shown to predict large increases in TC power, whilst a combination of increasing DMI E temperature anomaly with a positive SOI moves LMI equator-wards. The models compiled in this study identified the most significant climatic indices and successfully predicted TC power dissipation and LMI.

Spatiotemporal Variability of Tropical Cyclone–Induced Ocean Heat Uptake and Its Effect on Ocean Heat Content

Abstract Tropical cyclones (TCs) can pump heat downward into the ocean through inducing intense vertical mixing. Many efforts have been made to estimate the TC-induced ocean heat uptake (OHU), but spatiotemporal variability of TC-induced OHU remains unclear. This study estimates the TC-induced OHU, which takes into account the heat loss at the air–sea interface during TC passage compared to previous studies and investigates the spatiotemporal variability of TC-induced OHU and its potential impacts on ocean heat content (OHC) during the period 1985–2018. It is found that the spatial distribution of OHU is inhomogeneous, with the largest OHU occurring in the northwest Pacific, and category 3–5 TCs contribute approximately 51% of the total global OHU per year. The annually accumulated TC-induced OHUs in the regional basins exhibit pronounced interannual variability, which is closely related to the TC power dissipation index (PDI). By decomposing PDI into TC intensity, frequency, and duration, we find that the TC characteristics influencing OHU variability vary by basin. Correlation analyses suggest that the interannual variations of OHUs are linked to El Niño–Southern Oscillation (ENSO). In addition, the OHU might have the potential to influence OHC variability, especially in the equatorial eastern Pacific where there are significant positive correlations between the OHU and OHC with lags of 2–6 months. This has an important implication that TC-induced OHU might have potential effects on ENSO evolution.

Divergence of tropical cyclone hazard based on wind-weighted track distributions in the Coral Sea, over 50 years

Tropical cyclones (TCs) with genesis in the Coral Sea present significant hazards to coastal regions in their surroundings. In addition, the erratic nature of TC tracks is not well understood in this region. Therefore, this study grouped Coral Sea TC tracks over the last fifty years based on K-means clustering of the maximum wind-weighted centroids. This was done in order to extract valuable new cyclone power, track curvature and location related information from their historical track records and to predict their behaviour in the light of a changing climate. TC track variance and curvature (sinuosity) were assessed. Three well-defined clusters of TC tracks were identified, and the results showed differing predominant directions of TC movement by cluster. Track sinuosity was shown to increase from east to west. Only one cluster showed a statistically significant trend (decreasing) in TC frequency. The TC power dissipation index (PDI) was used to reveal that two of the clusters have diverging trends for PDI post-2004. Based on the location of cyclone maximum intensity, only one cluster showed a statistically significant trend (towards the equator). All these findings demonstrated a clear variance in between-cluster hazard and show that TC trends discovered for the southwest Pacific are not manifest or consistent across all clusters.

How are Atlantic basin-wide hurricane activity and economic losses related?

The authors investigate the statistical relationships between interannual variations in economic losses from Tropical Cyclones (TCs), basin-wide metrics of TC activity, and indicators of large-scale climate variability in the North Atlantic basin. The results show substantial and statistically significant correlations between the economic losses and some seasonal TC activity metrics, namely the accumulated cyclone energy and power dissipation index. These results suggest that accurate seasonal forecasts of these metrics can be taken as relevant to potential TC losses, even though the metrics in question do not take into account whether storms make landfall, let alone where they do so. The authors suggest that the degree of correlation obtained might be considered a baseline against which to measure some aspects of the performance of catastrophe models.

Future changes of tropical cyclone activity over the west Pacific under the 1.5°C and 2°C limited warming scenarios using a detecting and tracking algorithm

This study evaluates changes to the number, intensity and path of tropical cyclones (TC) in the 21st century under the 1.5°C “never-exceed” (NE), 1.5°C overshoot (OS), and 2.0°C “never-exceed” (NE) limited warming scenarios, compared to the historical experiments of the Community Earth System Model Large Ensemble Project (CESM-LE). The large amount of data generated by the model makes it impossible to manually extract TC activity. A tracking algorithm was developed to detect and track TC activity. The results show that the algorithm has good stability and high accuracy, and it is suitable for grid data with spatial resolutions finer than 2.0° × 2.0°. The analysis shows that changes of sea surface temperature and wind shear are responsible for the increment in the TC mean intensity under warmer scenarios. Under the 1.5°C OS scenario, the annual mean number of TCs and mean TC energy increase the most. The power dissipation index (PDI) of TCs under three scenarios were projected significantly increased. Under the 1.5degNE and 2.0degNE scenarios, more TCs move to the northeast part of China over time. Under the 1.5degOS scenario, more TCs will land in Southeast China in the end of this century. The coastal areas of northern China may gradually become another area of dense TC landing.

Observed tropical cyclone-driven cold wakes in the context of rapid warming of the Arabian Sea

ABSTRACT We present a detailed long-term (1997–2019) analysis of observed cyclone-induced surface cooling (or cold wake) in the Arabian Sea. Here, the analysis is performed for 33 cyclones that drove significant cooling at the sea surface in three different seasons: the pre-monsoon, monsoon and post-monsoon. Our study shows that cyclones can cool the sea surface up to 4.76° C after their passage, depending on the intensity, duration and other factors that contribute to cooling. The monsoon and pre-monsoon cyclones show stronger cooling, but the post-monsoon cyclones exhibit a longer duration (8–10 days) of cooling and slower recovery time (15 days). In general, the pre- and monsoon cyclones exhibit a strong positive correlation with the Latent Heat Flux, whereas the post-monsoon cyclones show a higher correlation with Ekman Pumping Velocity, wind stress and intensity of cyclones. The cold wake composite analysis for the El-Niño, La-Niña and Normal years shows that cyclone-induced cooling is similar in El-Niño and La-Niña years, and the cooling is more dominant during the negative Indian Ocean Dipole (IOD) than that in the positive IOD years. Co-occurrence of positive IOD and La Niña events has led to more intense cyclones in recent decades. The power dissipation index, accumulated cyclone energy and oceanic heat content also show an increasing trend in AS and favour rapid intensification of cyclones. Since the drop in SST normally impedes cyclones from intensification, our study is important and the findings of this study will aid in tropical cyclone predictions. In response to rapid warming of Indian Ocean in recent decades, extreme events such as cyclones are expected to increase in the context of climate change.

Growing Threat of Rapidly-Intensifying Tropical Cyclones in East Asia

This study examines the long-term change in the threat of landfalling tropical cyclones (TCs) in East Asia over the period 1975–2020 with a focus on rapidly intensifying (RI) TCs. The increase in the annual number of RI-TCs over the western North Pacific and the northwestward shift of their genesis location lead to an increasing trend in the annual number of landfalling RI-TCs along the coast of East Asia. The annual power dissipation index (PDI), a measure of the destructive potential of RI-TCs at landfall, also shows a significant increasing trend due to increases in the annual frequency and mean landfall intensity of landfalling RI-TCs. The increase in mean landfall intensity is related to a higher lifetime maximum intensity (LMI) and the LMI location of the landfalling RI-TCs being closer to the coast. The increase in the annual PDI of East Asia is mainly associated with landfalling TCs in the southern (the Philippines, South China, and Vietnam) and northern parts (Japan and the Korean Peninsula) of East Asia due to long-term changes in vertical wind shear and TC heat potential. The former leads to a northwestward shift of favorable environments for TC genesis and intensification, resulting in the northwestward shift in the genesis, RI, and LMI locations of RI-TCs. The latter provides more heat energy from the ocean for TC intensification, increasing its chances to undergo RI.

The Relationship between Environmental Factors and Catch Abundance of Hairtail in the East China Sea Using Empirical Dynamic Modeling

The East China Sea population of hairtail (Trichiurus lepturus, also known as T. japonicus) is a commercially important element of Chinese fisheries. Hairtail has long been widely exploited. Due to overfishing, however, its production declined over the years. One of solutions to this dilemma is to institute reasonable fishery policies. Generally, skillful short-term and long-term prediction of fish catch is a central tool for guiding the development of fishery policy. Accurate predictions require a comprehensive understanding of the relationship between fluctuations in fish catch and variability in both fishing effort and marine environmental conditions. To investigate the combined impact of fishing effort and marine environments on hairtail catch and to develop models to predict hairtail catch, we applied empirical dynamic modeling (EDM) to data on East China Sea fisheries, including hairtail catch, fishing effort, and marine environmental factors. EDM is an equation-free approach that enables the investigation of various complex systems. We constructed all possible multivariate EDM models to investigate the potential mechanisms affecting hairtail catch. Our analysis demonstrates that all key environmental factors (salinity, summer monsoon, sea surface temperature, precipitation, and power dissipation index of tropical cyclones) have an impact on nutrient supply, which we suggest is the central factor influencing hairtail catch. Finally, our comparison of EDM models with parametric models demonstrates that EDM models overwhelmingly outperform parametric models in analysis of these complex interactions.

Understanding the post‐monsoon tropical cyclone variability and trend over the Bay of Bengal during the satellite era

AbstractAn effort is made to investigate the tropical cyclone (TC) variability over the Bay of Bengal in the warming climate scenario during the satellite era (1979–2018). In this study, the authors investigate interannual variations in the overall capacity of the Bay of Bengal (BoB) basin in the post‐monsoon season to produce either intense or moderate TCs. Globally accepted and widely used metrics accumulated cyclone energy (ACE) and power dissipation index (PDI) are used to examine the energy and damage generated by TCs. A statistical change‐point analysis is conducted to detect the shift in the tropical cyclone frequency and ACE during the study period, indicating the year 1999 as a change point. The results show the increasing trend in ACE in the BoB during the post‐monsoon season with a statistical significance of 95%. On the contrary, the overall frequency is almost unchanged but has shown an increasing trend in the last decade of the study period. Additionally, atmospheric and ocean factors influencing the TC intensity are investigated by applying principal component analysis for three categories of TCs, viz. the very severe cyclonic storm, severe cyclonic storm, and cyclonic storm. Implementation of principal component analysis and correlations of maximum sustained wind speed (MSW2; intensity) with relative vorticity, minimum sea‐level pressure (MSLP), sea‐surface temperature (SST), specific rainwater content, and vertical wind shear revealed relative vorticity as the most dominating parameter amongst all governing factors which determine the final intensity of the BoB TCs. On the contrary, SST shows the different nature of the relationship with different TC categories.

Simulated Changes in Tropical Cyclone Size, Accumulated Cyclone Energy and Power Dissipation Index in a Warmer Climate

Detection, attribution and projection of changes in tropical cyclone intensity statistics are made difficult from the potentially decreasing overall storm frequency combined with increases in the peak winds of the most intense storms as the climate warms. Multi-decadal simulations of stabilized climate scenarios from a high-resolution tropical cyclone permitting atmospheric general circulation model are used to examine simulated global changes from warmer temperatures, if any, in estimates of tropical cyclone size, accumulated cyclonic energy and power dissipation index. Changes in these metrics are found to be complicated functions of storm categorization and global averages of them are unlikely to easily reveal the impact of climate change on future tropical cyclone intensity statistics.

Tropical cyclones over the western north Pacific since the mid-nineteenth century

Tropical cyclone (TC) activities over the western North Pacific (WNP) and TC landfall in Japan are investigated by collecting historical TC track data and meteorological observation data starting from the mid-nineteenth century. Historical TC track data and TC best track data are merged over the WNP from 1884 to 2018. The quality of historical TC data is not sufficient to count the TC numbers over the WNP due to the lack of spatial coverage and different TC criteria before the 1950s. We focus on TC landfall in Japan using a combination of TC track data and meteorological data observed at weather stations and lighthouses from 1877 to 2019. A unified TC definition is applied to obtain equivalent quality during the whole analysis period. We identify lower annual TC landfall numbers during the 1970s to the 2000s and find other periods have more TC landfall numbers including the nineteenth century. No trend in TC landfall number is detected. TC intensity is estimated by an annual power dissipation index (APDI). High APDI periods are found to be around 1900, in the 1910s, from the 1930s to 1960s, and after the 1990s. When we focus on the period from 1977 to 2019, a significant increasing trend of ADPI is seen, and significant northeastward shift of TC landfall location is detected. On the other hand, TC landfall location shifts northeastward and then southwestward in about 100-year interval. European and US ships sailed through East and Southeast Asian waters before the weather station network was established in the late nineteenth century. Then, we focus on TC events in July 1853 observed by the US Naval Japan Expedition of Perry’s fleet and August 1863 by a UK Navy ship that participated in two wars in Japan. A TC moved slowly westward over the East China Sea south of the Okinawa Islands from 21 to 25 July 1853. Another TC was detected in the East China Sea on 15–16 August 1863 during the bombardment of Kagoshima in southern Japan. Pressure data are evaluated by comparing the observations made by 10 naval ships in Yokohama, central Japan during 1863–1864. The deviation of each ship pressure data from the 10 ships mean is about 2.7–2.8 hPa.

Precise Prediction of Hurricane Power vs Ocean Temperature

It has long been known that hurricanes, the strongest and most destructive atmospheric events, do not occur below a sea surface temperature near 26 C. The detailed dependence of hurricane power on ocean temperature is of increasing interest and concern in the prospect of continuing global warming. The hurricane power was usefully quantified by Emanuel in 2005 with the definition and tabulations of the power dissipation index, PDI. This is the integral over the relevant sea areas of the cube of the maximum windspeed, representiting the power dissipated over one year. In his important 2005 paper Emanuel found that the PDI for the North Atlantic increased strongly in recent decades and showed in plots a close correlation of PDI with sea surface temperature. A critical temperature Tc, and a linear T-Tc power law dependence, typical of a continuous phase transition, for hurricanes have prcviously (Wolf, 2020) been inferred from plots of the power dissipation index PDI vs sea surface temperature T. This implies that tropical cyclone formation can usefully be regarded as a second order phase transition of the warm ocean-atmosphere system, driven by disequilibrium in atmospheric water content. We here show that the theory of phase transitions allows a precise prediction of the temperature dependence of hurricane power and windspeed on ocean surface temperature. We find that the wind velocity transition of the hurricane is in the same universality class as the Ising Model, the uniaxial antiferromagenet and the vapor- liquid transition of simple fluids, and shares their critical exponent. An implication for the applicability of potential intensity theory is noted.

Increased cyclone destruction potential in the Southern Indian Ocean

The present study examines the role of the Southern Indian Ocean (SIO) warming on the cyclone destruction potential or Power Dissipation Index (PDI) during two contrasting periods of 1980–1998 and 1999–2016. The PDI in the SIO during 1999–2016 is found to have doubled compared to the same during 1980–1998. PDI was computed using the tropical cyclone track data in the SIO region for cyclone category three and above. The increasing trend in PDI during the latter period is primarily due to an increase in the intensity of cyclones and their duration. The increasing PDI is associated with a sea surface temperature warming and an upper ocean heat content increase as well as a significant slowdown in translation speeds. The increase in upper ocean heat content during the recent decades enhances the intensification of cyclones and their duration, which is consistent with the slowdown of cyclones. Analysis of the relevant atmospheric parameters indicates that processes in the atmosphere did not play a major role in the recent decades in increasing cyclone intensity. We show that in the SIO, ocean processes play a major role in the PDI rise during the recent period. Any continued increase in PDI will cause more loss of life and socioeconomic damage to the island countries such as Mozambique, Mauritius, Mascarene Islands and Madagascar, as well as the coastal inhabitants along East Africa.

Tropical Atlantic dust and the zonal circulation

This study examines the factors driving the variability of Saharan dust over the subtropical Atlantic during summer. Monthly tropospheric dust concentrations from satellite-based model assimilation averaged in the area 10–23 N, 30–65 W, are used to create an index over the period 1980–2017. The seasonal cycle peaks in summer and affects tropical cyclones from July to September. Point-to-field regression analysis is performed, and then composites of dusty and clean seasons are analyzed as maps and sections of meteorological fields. The regression reveals significant differences in oceanic trade winds, (detrended) sea surface temperature, and atmospheric convection. Dusty minus clean composites show a zonal overturning circulation with sinking/rising motions over Africa/western Caribbean and lower easterlies/upper westerlies over the subtropical Atlantic. This circulation spreads Saharan dust and warm dry air in the 1–4 km layer westward at ~ 10 m/s over cooler waters, inhibiting convection. Among the factors driving tropospheric dust variability is the Pacific El Nino Southern Oscillation. Composites of dusty and clean hurricane occurrence show a threefold difference in numbers and a tenfold difference in mean power dissipation index. Analysis of a dust event in August 2009 illustrates how wind shear and cool SST conspire to suppress tropical easterly waves. Supplementary work characterizes the dispersion of a dense Saharan dust plume in June 2020.

Tropical Cyclones Downscaled from Simulations of the Last Glacial Maximum

AbstractThe tracks, intensities, and other properties of tropical cyclones downscaled from three models’ simulations of the Last Glacial Maximum (LGM) are analyzed and compared to those of storms downscaled from simulations of the present climate. Globally, the mean maximum intensity of storms generated from each model is lower at LGM, as is the fraction of all storms that reach intensities of category 4 or higher on the Saffir–Simpson hurricane wind scale. The median day of the storm season shifts earlier by an average of one week in all three models in both hemispheres. Two of the three models’ LGM simulations feature a reduction in storm count and global power dissipation index compared to the current climate, but a third shows no significant difference between the two climates. Although each model is forced by the same global changes, differences in the way sea surface temperatures and other large-scale environmental conditions respond in the North Atlantic impart significant differences in the climatology at LGM between models. Our results from the cold LGM provide a novel opportunity to assess how tropical cyclones respond to climate changes.