Tropical Cyclone Changes Research Articles

Tropical Cyclones Intensity Prediction in the Western North Pacific Using Gradient Boosted Regression Tree Model

As an artificial intelligence method, machine learning (ML) has been widely used in prediction models of high-dimensional datasets. This study proposes an ML method, the Gradient Boosted Regression Tree (GBRT), to predict the intensity changes of tropical cyclones (TCs) in the Western North Pacific at 12-, 24-, 36-, 48-, 60-, and 72-h (hr) forecasting lead time and the model is optimized by the Bayesian Optimization algorithm. The model predictands are the TCs intensity changes at different forecasting lead times, obtained from the best track data of the Shanghai Typhoon Institute (STI) and the Joint Typhoon Warning Center (JTWC) from 2000 to 2019. The model predictors are the synoptic variables, climatological and persistent variables derived from the reanalysis data obtained from the National Centers for Environmental Prediction (NCEP), and the sea surface temperature (SST) data obtained from the National Oceanic and Atmospheric Administration (NOAA). The results show that the GBRT model can capture the TCs intensity changes well for the succeeding 12-h, 24-h, 36-h, and 72-h. Compared with the traditional multiple linear regression (MLR) model, the GBRT model has better performance in predicting TCs intensity changes. Compared with the MLR model, R2 of the GBRT model for TCs intensity forecast increases by an average of 8.47% and 4.45% for STI data and JTWC data. MAE (RMSE) drops by 26.24% (25.14%) and 10.51% (4.68%) for the two datasets, respectively. The potential future intensity change (POT), the intensity changes during the previous 12 h (Dvmax), Initial storm maximum wind speed (Vmax), SST, and the Sea-Land ratio are the most significant predictors for the GBRT model in predicting TCs intensity change over the Western North Pacific.

Correlation Between Sea-Level Rise and Aspects of Future Tropical Cyclone Activity in CMIP6 Models.

Future coastal flood hazard at many locations will be impacted by both tropical cyclone (TC) change and relative sea‐level rise (SLR). Despite sea level and TC activity being influenced by common thermodynamic and dynamic climate variables, their future changes are generally considered independently. Here, we investigate correlations between SLR and TC change derived from simulations of 26 Coupled Model Intercomparison Project Phase 6 models. We first explore correlations between SLR and TC activity by inference from two large‐scale factors known to modulate TC activity: potential intensity (PI) and vertical wind shear. Under the high emissions SSP5‐8.5, SLR is strongly correlated with PI change (positively) and vertical wind shear change (negatively) over much of the western North Atlantic and North West Pacific, with global mean surface air temperature (GSAT) modulating the co‐variability. To explore the impact of the joint changes on flood hazard, we conduct climatological–hydrodynamic modeling at five sites along the US East and Gulf Coasts. Positive correlations between SLR and TC change alter flood hazard projections, particularly at Wilmington, Charleston and New Orleans. For example, if positive correlations between SLR and TC changes are ignored in estimating flood hazard at Wilmington, the average projected change to the historical 100 years storm tide event is under‐estimated by 12%. Our results suggest that flood hazard assessments that neglect the joint influence of these factors and that do not reflect the full distribution of GSAT change may not accurately represent future flood hazard.

Mitigation of Significant Data Noise in F17 SSMIS Observations since October 2017

Special Sensor Microwave Imager Sounder (SSMIS) temperature sounding observations have been made available since the launch of the Defense Meteorological Satellite Program (DMSP), F16, on 18 October 2003. These conical-scanning observations of brightness temperature are ideal for investigating long-term structural changes in tropical cyclones throughout the globe. The SSMIS temperature sounding data started to contain significant across-track high-frequency striping noise spikes at a frequency of 0.14 s−1 starting on 20 October 2017 for F17. A Fast Fourier Transform (FFT) was used to remove the noise in channels 1–7 and 24. The across-track striping noise is most significant for the four channels of the lowest peak weighting functions. The data noise is as large as 15 K for channels 1–3, 2.5 K for channel 4, 0.5 K for channels 5–7, and 0.75 K for channel 24. We found some remaining along-track striping noise around 0.5 K in channels 2–4, which is removed by employing a principal component analysis and an ensemble empirical mode decomposition combined method. An advantage for conical-scanning observations of brightness temperature to directly capture typhoon structures is then illustrated. Although buried under the data noise in the original data, the structural features of typhoon Lekima (2019) could clearly be seen after the noise mitigation. Lekima reached a typhoon intensity on 7 August 2019 and its center was characterized by a warm anomaly of more than 7 K around 200 hPa (channel 5) and a cold center of less than −6 K around 945 hPa (channel 2). This study prepares us for using satellite observations to understand the effect of climate change on tropical cyclone intensity and rain-band structures over the past two decades.

Tropical cyclone climatology change greatly exacerbates US extreme rainfall\u2013surge hazard

Tropical cyclones (TCs) are drivers of extreme rainfall and surge, but the current and future TC rainfall–surge joint hazard has not been well quantified. Using a physics-based approach to simulate TC rainfall and storm tides, we show drastic increases in the joint hazard from historical to projected future (SSP5–8.5) conditions. The frequency of joint extreme events (exceeding both hazards’ historical 100-year levels) may increase by 7–36-fold in the southern US and 30–195-fold in the Northeast by 2100. This increase in joint hazard is induced by sea-level rise and TC climatology change; the relative contribution of TC climatology change is higher than that of sea-level rise for 96% of the coast, largely due to rainfall increases. Increasing storm intensity and decreasing translation speed are the main TC change factors that cause higher rainfall and storm tides and up to 25% increase in their dependence.

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.

On occurrence of rapid intensification and rainfall changes in tropical cyclones over the North Indian Ocean

AbstractThe present study examines the climatological characteristics and possible triggers of rapid intensification (RI) of tropical cyclones (TCs) during 1990–2019 over the North Indian Ocean (NIO). RI is defined as an increase in maximum sustained surface wind speed of 30 knots (15.4 m⋅s−1) or more in a 24 hr duration. In the NIO basin, the threshold of 24 hr intensity change represents the 93rd percentile using a 3‐min sustained wind, while, it is 95th percentile in the Atlantic basin, where 1‐min sustained wind is used. A total of 46 TCs (~38% of the total TCs) have exhibited RI at an average rate of 1–2 TCs year−1 over the NIO. A significant increase of RI‐TCs is seen from the year 2000 onwards over the region. The maximum RI‐TCs occurrence is found in the post‐monsoon season. The majority of TCs (~48%) undergo the RI phase within a 12–24 hr time during the depression stage. About ~35% (26%) of the TCs are retained in the RI phase for the duration of at least 24 hr (36 hr). Most of the RI‐TCs move northwestward (38%) and westward (31%) direction 6 hr before the RI onset with slow/normal translation speeds. During the RI phase, ~72% of TCs travels a distance of ~150–450 km. The TC inner‐core region receives heavy rainfall, and a ~ 3 mm⋅hr−1 increment is noticed 12 hr before the RI to the RI onset. Most of the RI‐TCs made landfall over eastern states of India showing the vulnerability of the regions. Composite analysis demonstrated that higher precipitable water (~55 mm), surface flux (500 W⋅m−2), cyclone heat potential (50–60 kJ⋅cm−2) in the moderate shear (6–8 m⋅s−1) environment favours the RI process. This study highlights the significance of RI‐TCs and triggering conditions for the RI onset over the NIO region.

Spatial and Temporal Variation Characteristics of the Intensity of Landfall Tropical Cyclones in China

Based on the tropical cyclone data of the United States Joint Typhoon Center, this paper analyses the characteristics of the temporal and spatial changes of tropical cyclones that landed in China from 1951 to 2015. The conclusions are as follows: (1) The frequency of landings showed a slow upward trend from 1951 to the early 1990s, and showed a slow downward trend from the late 1990s to 2015. In 1988, it changed from a low period to a high period. (2) Tropical cyclones are mainly distributed in the range of 130-140°E, 10-15°N east of the Philippine Islands, and the northeastern part of the South China Sea. The spatial distribution of the first eigenvector of the source frequency EOF is basically the same as the multi-year spatial distribution. From the time coefficient of the first mode, the change trend of the concentrated distribution has undergone a process of strengthening-weakening. From the perspective of the spatial distribution of the second mode, the source frequencies in the Northwest Pacific and the South China Sea have opposite spatial distribution characteristics in the latitude direction. (3) One of the main tracks of landfall tropical cyclones is westward from the tropical Pacific to the Philippine Sea and South China Sea, and the other from the tropical Pacific to the northwest to South Korea and Japan, affecting the area near the coast of East Asia. The spatial distribution of the first eigenvector of the track frequency EOF is basically the same as that of the multi-year spatial distribution, and the spatial distribution of the second mode has a positive-negative opposite spatial distribution characteristic in the meridian direction.

Simulated changes to tropical cyclones across the Paleocene-Eocene Thermal Maximum (PETM) boundary

Tropical cyclones are an important meteorological and climatological process in Earth's climate system. These intense, localized storms mainly form over warm equatorial oceans, and propagate poleward. During their lifetime, tropical cyclones can strengthen leading to intense winds and rainfall events. These storms also carry moist energy that contribute to the poleward transport of atmospheric energy. Presently, concern exists about how the characteristics of tropical cyclones will change in a future warming world. The Paleocene Eocene Thermal Maximum (PETM) was a time in Earth's deep past in which the planet warmed by 5° - 8 °C due to an increase in atmospheric CO2. It is thus of interest to understand how past warming affected tropical cyclone behavior. Here, a high resolution (25 km) atmospheric model is used to study changes in tropical cyclones across the PETM boundary. Orbital variation is also investigated as an additional forcing mechanism at the time of the PETM. The climate simulations indicate that greenhouse forcing leads to a poleward shift in TCs, much like projected future scenarios and in simulations of other warm periods in Earth history. It is also found that the orbital forcing response is very different than the greenhouse cases due to the difference in thermal response, which, in turn, induces a different dynamical response in wind shear. Although the spatial pattern between changes across the PETM and the future differ, there are still many similarities in TC response for these two very different periods in time, indicating the robustness of the TC response to greenhouse warming.

Evaluation of the contribution of tropical cyclone seeds to changes in tropical cyclone frequency due to global warming in high-resolution multi-model ensemble simulations

Previous projections of the frequency of tropical cyclone genesis due to global warming, even in terms of sign of the change, depends on the chosen model simulation. Here, we systematically examine projected changes in tropical cyclones using six global atmospheric models with medium-to-high horizontal resolutions included in the sixth phase of the Coupled Model Intercomparison Project/High-Resolution Model Intercomparison Project. Changes in the frequency of tropical cyclone genesis could be broken down into the contributions from (i) the tropical cyclone seed, a depression having a closed contour of sea level pressure with a warm core and (ii) the survival rate, the ratio of the frequency of tropical cyclone genesis to that of tropical cyclone seeds. The multi-model ensemble mean indicates that tropical cyclone genesis frequencies are significantly decreased during the period 1990–2049, which is attributable to changes in tropical cyclone seeds. Analysis of the individual models shows that although most models project a more or less decreasing trend in tropical cyclone genesis frequencies and seeds, the survival rate also contributes to the result in some models. The present study indicates the usefulness of decomposition into the frequency of the tropical cyclone seeds and the survival rate to understand the cause of uncertainty in projected frequencies of tropical cyclone genesis.

Understanding the characteristics of rapid intensity changes of Tropical Cyclones over North Indian Ocean

North Indian Ocean (NIO), which comprises of Bay of Bengal (BoB) and Arabian Sea (AS) basins, is one of the highly potential regions for Tropical Cyclones (TCs) in the world. Significant improvements have been achieved in the prediction of the movement of TCs, since the last decade. However, the prediction of sudden intensity changes becomes a challenging task for the research and operational meteorologists. Hence, the present study focuses on finding the climatological characteristics of such intensity changes over NIO regions. Rapid Intensification (RI) is defined as the 24-h maximum sustained surface wind speed rate equal to 30 knots (15.4 ms−1). The results suggest that the TCs formed over the NIO basin are both seasonal and basin sensitive. Since 2000, a significant trend is observed in RI TCs over the basin. At least one among three cyclones getting intensified is of RI category. More number of RI cases have been identified in the BoB basin than the AS. The post-monsoon season holds more RI and rapid decay cases, with 63% and 90% contribution. Most of the TCs are attaining RI onset in their initial stage. Further, India is receiving more landfalling RI TCs, followed by Bangladesh and Oman. The east coast of India, Tamil Nadu, and Andhra Pradesh are the most vulnerable states to these RI TCs. The cyclogenesis locations associated with RI cases hold higher moisture, and sea surface temperature as compared to the Non-RI cases.

UNCERTAINTY ASSESSMENT OF FUTURE CHANGE PROJECTION TO TYPHOON PROPERTIES AND MAXIMUM STORM SURGE HEIGHT DEPENDING OF FUTURE SEA SURFACE TEMPERATURE AND GREENHOUSE GAS EMISSION SCENARIOS

In order to evaluate the future storm surge risk at the national scale, it is necessary to evaluate typhoon characteristics for a country-specific in prior to conducting storm surge simulation using them. When projecting future changes of tropical cyclones (TC) by using the atmospheric general circulation model (AGCM), there are several uncertainties due to model resolution, model physics parameterization, given sea surface temperature (SST) under future climate condition, and global warming scenarios. The uncertainties stemming from physics and numerical modeling configuration can be reduced by improving the accuracy of AGCMs, while those from the global warming scenario and future SST condition are unable to be. This study assessed uncertainties in projecting future change to typhoon properties such as tracks, frequency and intensity and extreme storm surge height (SSH) depending of future SST and greenhouse gas emission scenarios.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/Wzp35k4tyhM

Projected Future Changes in Tropical Cyclones Using the CMIP6 HighResMIP Multimodel Ensemble.

Future changes in tropical cyclone properties are an important component of climate change impacts and risk for many tropical and midlatitude countries. In this study we assess the performance of a multimodel ensemble of climate models, at resolutions ranging from 250 to 25 km. We use a common experimental design including both atmosphere‐only and coupled simulations run over the period 1950–2050, with two tracking algorithms applied uniformly across the models. There are overall improvements in tropical cyclone frequency, spatial distribution, and intensity in models at 25 km resolution, with several of them able to represent very intense storms. Projected tropical cyclone activity by 2050 generally declines in the South Indian Ocean, while changes in other ocean basins are more uncertain and sensitive to both tracking algorithm and imposed forcings. Coupled models with smaller biases suggest a slight increase in average TC 10 m wind speeds by 2050.

Effects of climate change on the movement of future landfalling Texas tropical cyclones

The movement of tropical cyclones (TCs), particularly around the time of landfall, can substantially affect the resulting damage. Recently, trends in TC translation speed and the likelihood of stalled TCs such as Harvey have received significant attention, but findings have remained inconclusive. Here, we examine how the June-September steering wind and translation speed of landfalling Texas TCs change in the future under anthropogenic climate change. Using several large-ensemble/multi-model datasets, we find pronounced regional variations in the meridional steering wind response over North America, but―consistently across models―stronger June-September-averaged northward steering winds over Texas. A cluster analysis of daily wind patterns shows more frequent circulation regimes that steer landfalling TCs northward in the future. Downscaling experiments show a 10-percentage-point shift from the slow-moving to the fast-moving end of the translation-speed distribution in the future. Together, these analyses indicate increases in the likelihood of faster-moving landfalling Texas TCs in the late 21st century.

Short-Term Tropical Cyclone Intensity Forecasting from Satellite Imagery Based on the Deviation Angle Variance Technique

Abstract The deviation angle variance (DAV) is a parameter that characterizes the level of organization of a cloud cluster compared with a perfectly axisymmetric tropical cyclone (TC) using satellite infrared (IR) imagery, and can be used to estimate the intensity of the TC. In this study, the DAV technique is further used to analyze the relationship between satellite imagery and TC future intensity over the North Atlantic basin. The results show that the DAV of the TC changes ahead of the TC intensity change, and this can be used to predict short-term TC intensity. The DAV-IR 24-h forecast is close to the National Hurricane Center (NHC) 24-h forecast, and the bias is lower than NHC and other methods during weakening periods. Furthermore, an improved TC intensity forecast is obtained by incorporating all four satellite bands. Using SST and TC latitude as the other two predictors in a linear regression model, the RMSE and MAE of the DAV 24-h forecast are 13.7 and 10.9 kt (1 kt ≈ 0.51 m s−1), respectively, and the skill space of the DAV is about 5.5% relative to the Statistical Hurricane Intensity Forecast model with inland decay (Decay-SHIFOR) during TC weakening periods. Considering the DAV is an independent intensity technique, it could potentially add value as a member of the suite of operational intensity forecast techniques, especially during TC weakening periods.

Influence of eddies and tropical cyclone heat potential on intensity changes of tropical cyclones in the North Indian Ocean

Eddies are known to play a crucial role in the sudden intensification of tropical cyclones. In this study, Sea Level Anomaly (SLA) data from satellite altimetry is utilized to investigate the role of eddies on tropical cyclones intensification in the North Indian Ocean (NIO) basin. SLA data obtained from Archiving Validation and Interpretation of Satellite Data in Oceanography (AVISO), Tropical Cyclone Heat Potential (TCHP) from National Remote Sensing Centre (NRSC) and cyclone intensity data from Indian Meteorological Department (IMD) have been utilized to analyse and understand the impact of TCHP and eddies on 60 tropical cyclones in the NIO spanning the years 2001–2018. Out of these 60 cyclones, 38 were formed in the Bay of Bengal (BoB) and 22 in the Arabian Sea (AS). From the analysis, it is found that nearly 40% cyclones are affected by Warm Core Eddy (WCE) generally intensifying them, 30% are influenced by Cold Core Eddy (CCE) that generally reduce cyclone intensities and the rest 30% are affected by TCHP variations (in the absence of eddies) in the NIO region during the study period. Cyclones which do not follow the established trend of intensifying due to WCEs or increasing TCHP; and diminishing owing to CCEs or TCHP decrease were found to be governed primarily by the Translational Speed of the cyclones. WCE are mostly present during the pre-monsoon season in the NIO (both BoB and AS). This analysis confirms that consideration of the underlying eddies in the cyclone track represented by SLA, TCHP variations, Translational Speed of cyclones and the ocean barrier layer are key factors that must be considered in forecasting cyclone intensity and track.

Interdecadal Change in the Relationship of the Western North Pacific Tropical Cyclogenesis Frequency to Tropical Indian and North Atlantic Ocean SST in Early 1990s

AbstractThe present study investigates reasons of interdecadal changes in the relationship between the western North Pacific (WNP) tropical cyclone (TC) genesis and tropical Indian Ocean (TIO) and tropical North Atlantic Ocean (TNA) sea surface temperature (SST) in early‐1990s. It is found that the above interdecadal changes are related to changes in the coherence of TIO and TNA SST variations with equatorial central‐eastern Pacific Ocean (EPO) SST variations. During 1970s through mid‐1980s, TIO and TNA SSTs tend to vary in phase with EPO SST on both interannual and interdecadal time scales. The combined effects of TIO and EPO SST anomalies induce opposite environment and TC changes in southeastern and northwestern WNP, leading to a weak correlation of basin‐wide WNP TC and TIO SST. Similarly, TNA and EPO SST anomalies induce opposite environment and TC changes in northeastern and southeastern WNP and thus basin‐wide WNP TC‐TNA SST correlation is weak. During late 1990s through early 2000s, TIO and EPO SST variations have a weak coherence due to their opposite relations on interannual and interdecadal time scales. TIO SST anomalies alone induce anomalous circulation over most WNP so that basin‐wide WNP TC‐TIO SST relationship is strong. The interannual and interdecadal SST variations remain coherent in TNA and EPO but with a switch of sign in their relationship in early 1990s. TNA and EPO SST anomalies induce same environment and TC changes in northeastern and southeastern WNP, and thus, basin‐wide WNP TC‐TNA SST relationship is strong. Numerical model experiments validate the importance of coherent regional SST anomalies.

Future Changes of Tropical Cyclones in the Midlatitudes in 4-km-mesh Downscaling Experiments from Large-Ensemble Simulations

Future Changes of Tropical Cyclones in the Midlatitudes in 4-km-mesh Downscaling Experiments from Large-Ensemble Simulations

On the relationship between intensity changes and rainfall distribution in tropical cyclones over the North Indian Ocean

AbstractUsing Tropical Rainfall Measuring Mission rain estimates the relationship between rainfall and intensity changes in tropical cyclones (TCs) over the North Indian Ocean (NIO) based on 71 TCs during 1997–2017 is investigated. The axisymmetric analyses revealed that climatologically the Bay of Bengal (BoB) TCs produce extremely heavy rainfall (~9–10 mm⋅hr−1) and Arabian Sea TCs produce very heavy rainfall (~7–8 mm⋅hr−1) in the storm inner core region (0–100 km). The inner‐core region receives three times higher rainfall than the outer region (100–300 km). The left‐forward sector experiences the maximum rainfall for any TC intensity over the NIO basin. A significant increase (decrease) in the rain rate is seen during normal to rapid intensification (weakening) phase. A notable decrease in rainfall of ~4.3 mm⋅hr−1 is observed for the rapidly weakening TCs. Slow‐moving TCs are generally stronger and produce heavy rainfall (2–4 mm⋅hr−1) up to ~300 km storm radius. As the translation speed increases, rainfall gradually shifts from rear to the forward sector of the TC. The asymmetry (wavenumber‐1) in TC rainfall structures revealed that rainfall maximum is located in the left‐forward sector for almost all intensity stages. The amplitude of wave number‐1 asymmetry in TC rainfall shows cyclonic shift as the TC intensity increases and is particularly prevalent in the BoB region. These analyses would be helpful as a baseline for evaluating the performance of numerical models and to identify the vulnerable areas for TC heavy rainfall.

Tropical Cyclones and Climate Change Assessment: Part I: Detection and Attribution

AbstractAn assessment was made of whether detectable changes in tropical cyclone (TC) activity are identifiable in observations and whether any changes can be attributed to anthropogenic climate change. Overall, historical data suggest detectable TC activity changes in some regions associated with TC track changes, while data quality and quantity issues create greater challenges for analyses based on TC intensity and frequency. A number of specific published conclusions (case studies) about possible detectable anthropogenic influence on TCs were assessed using the conventional approach of preferentially avoiding type I errors (i.e., overstating anthropogenic influence or detection). We conclude there is at least low to medium confidence that the observed poleward migration of the latitude of maximum intensity in the western North Pacific is detectable, or highly unusual compared to expected natural variability. Opinion on the author team was divided on whether any observed TC changes demonstrate discernible anthropogenic influence, or whether any other observed changes represent detectable changes. The issue was then reframed by assessing evidence for detectable anthropogenic influence while seeking to reduce the chance of type II errors (i.e., missing or understating anthropogenic influence or detection). For this purpose, we used a much weaker “balance of evidence” criterion for assessment. This leads to a number of more speculative TC detection and/or attribution statements, which we recognize have substantial potential for being false alarms (i.e., overstating anthropogenic influence or detection) but which may be useful for risk assessment. Several examples of these alternative statements, derived using this approach, are presented in the report.

Tropical cyclone sensitivities to CO2 doubling: roles of atmospheric resolution, synoptic variability and background climate changes

Responses of tropical cyclones (TCs) to CO2 doubling are explored using coupled global climate models (GCMs) with increasingly refined atmospheric/land horizontal grids (~ 200 km, ~ 50 km and ~ 25 km). The three models exhibit similar changes in background climate fields thought to regulate TC activity, such as relative sea surface temperature (SST), potential intensity, and wind shear. However, global TC frequency decreases substantially in the 50 km model, while the 25 km model shows no significant change. The ~ 25 km model also has a substantial and spatially-ubiquitous increase of Category 3–4–5 hurricanes. Idealized perturbation experiments are performed to understand the TC response. Each model’s transient fully-coupled 2 × CO2 TC activity response is largely recovered by “time-slice” experiments using time-invariant SST perturbations added to each model’s own SST climatology. The TC response to SST forcing depends on each model’s background climatological SST biases: removing these biases leads to a global TC intensity increase in the ~ 50 km model, and a global TC frequency increase in the ~ 25 km model, in response to CO2-induced warming patterns and CO2 doubling. Isolated CO2 doubling leads to a significant TC frequency decrease, while isolated uniform SST warming leads to a significant global TC frequency increase; the ~ 25 km model has a greater tendency for frequency increase. Global TC frequency responds to both (1) changes in TC “seeds”, which increase due to warming (more so in the ~ 25 km model) and decrease due to higher CO2 concentrations, and (2) less efficient development of these“seeds” into TCs, largely due to the nonlinear relation between temperature and saturation specific humidity.