Evolution of Tropical Cyclone Properties Across the Development Cycle of the GISS‐E3 Global Climate Model

Climatological characteristics of simulated intense tropical cyclones (TCs) in the western North Pacific were explored with a 20-km-mesh atmospheric general circulation model (AGCM20) and a 5-km-mesh regional atmospheric nonhydrostatic model (ANHM5). From the AGCM20 climate runs, 34 intense TCs with a minimum central pressure (MCP) less than or equal to 900 hPa were sampled. Downscaling experiments were conducted with the ANHM5 for each intense TC simulated by the AGCM20. Only 23 developed into TCs with MCP ≤ 900 hPa. Most of the best-track TCs with an MCP ≤ 900 hPa underwent rapid intensification (RI) and attained maximum intensities south of 25°N. The AGCM20 simulated a similar number of intense TCs as the best-track datasets. However, the intense AGCM20 TCs tended to intensify longer and more gradually; only half of them underwent RI. The prolonged gradual intensification resulted in significant northward shifts of the location of maximum intensity compared with the location derived from two best-track datasets. The inner-core structure of AGCM20 TCs exhibited weak and shallow eyewall updrafts with maxima below an altitude of 6 km, while downscaling experiments revealed that most of the intense ANHM5 TCs underwent RI with deep and intense eyewall updrafts and attained their maximum intensity at lower latitudes. The altitudes of updraft maxima simulated by the AGCM20 descended rapidly during the phase of greatest intensification as midlevel warming markedly developed. The change in major processes responsible for precipitation in AGCM20 TCs before and after maximum intensification suggests close relationships between the large-scale cloud scheme and midlevel warming and prolonged gradual intensification.

Water vapour plays a key role in the Earth's energy balance. Almost 50% of the absorbed solar radiation at the surface is used to cool the surface, through evaporation, and warm the atmosphere, through release of latent heat. Latent heat is the single largest factor in warming the atmosphere and in transporting heat from low to high latitudes. Water vapour is also the dominant greenhouse gas and contributes to a warming of the climate system by some 24°C (Kondratev 1972). However, water vapour is a passive component in the troposphere as it is uniquely determined by temperature and should therefore be seen as a part of the climate feedback system. In this short overview, we will first describe the water on planet Earth and the role of the hydrological cycle: the way water vapour is transported between oceans and continents and the return of water via rivers to the oceans. Generally water vapour is well observed and analysed; however, there are considerable obstacles to observing precipitation, in particular over the oceans. The response of the hydrological cycle to global warming is far reaching. Because different physical processes control the change in water vapour and evaporation/precipitation, this leads to a more extreme distribution of precipitation making, in general, wet areas wetter and dry areas dryer. Another consequence is a transition towards more intense precipitation. It is to be expected that the changes in the hydrological cycle as a consequence of climate warming may be more severe that the temperature changes.

In this study, we have investigated contributions of tropical Indian Ocean (IO) sea surface temperature (SST) warming and El Niño—Southern Oscillation (ENSO) to the interannual variability of tropical cyclone (TC) genesis frequency over the western North Pacific (WNP) between 1948 and 2010 and the involved physical mechanisms. Both ENSO and tropical IO Basin Mode (IOBM) warming are found to play important roles in modulating the WNP TC genesis frequency, but their effects are significantly different. The time series of seasonal empirical orthogonal function of tropical IO and tropical Pacific SST with trend and multi-decadal variability removed are defined as the IOBM index and ENSO index, respectively. The results show that the IO warming year is usually the El Niño decaying year. The number of total TCs, especially weak TCs, decreases during the tropical IO warming year when an anomalous anticyclonic circulation is observed over the tropical Northwest Pacific off the equator. On the other hand, the number of intense TCs increases in the El Niño developing year because of the eastward shifts of both the western Pacific monsoon trough and the cyclonic shear of the equatorial westerlies, and thus the eastward shift of the main TC genesis region. It is also found that the relationship between ENSO and the frequency of intense TCs has a decadal variation. During 1968–1987, the number of intense TCs was not related to ENSO with a correlation coefficient of only 0.19, while the correlation coefficient is 0.63 and 0.73 during 1948–1967 and 1988–2007, respectively. The extent to which the WNP anomalous anticyclone is forced by IO warming is investigated by using the global climate model (European Centre Hamburg Model, ECHAM) with imposed SST anomalies over the tropical IO. The results suggest that the WNP anomalous anticyclone that develops from June to September results mainly from the northward shift of the tropical IO warming from boreal spring to boreal summer.

This study examines the variation in tropical cyclone (TC) intensity for different phases of the El Niño–Southern Oscillation (ENSO) phenomenon in the Fiji, Samoa, and Tonga (FST) region. The variation in TC intensity is inferred from the accumulated cyclone energy (ACE), which is constructed from the 6-hourly Joint Typhoon Warning Center best-track data for the period 1985–2006. Overall, results suggest that ACE in the FST region is considerably influenced by the ENSO signal. A substantial contribution to this ENSO signal in ACE comes from the region equatorward of 15°S where TC numbers, lifetime, and intensity all play a significant role. However, the ACE–ENSO relationship weakens substantially poleward of 15°S where large-scale environmental variables affecting TC intensity are found to be less favorable during El Niño years than during La Niña years; in the region equatorward of 15°S, the reverse is true. Therefore, TCs entering this region poleward of 15°S are able to sustain their intensity for a longer period of time during La Niña years as opposed to TCs entering the region during El Niño years, when they decay more rapidly.

The tropical cyclone (TC) power dissipation index (PDI) in May over the western North Pacific (WNP) region shows a remarkable increase from the pre-1999 years (1979–1999) to the post-1999 years (2000–2011). Both increased TC numbers and enhanced TC intensity contributed to the change in the PDI. The averaged TC number in May increased from 1.05 per year in the pre-1999 years to 1.75 per year in the post-1999 years. In particular, the number of intense typhoon goes up from 0.14 per year to 0.83 per year, implying a sharp increase of TC intensity. Examination of the large scale background circulation in May shows that the epochal increase of TC number is caused by a significant increase of the genesis potential index (GPI), which has increased by about 33 % from the first (1979–1998) to the second (1999–2011) epoch over the TC genesis region (110°E–160°E, 5°N–20°N). The higher TC intensity is related to the increased maximum potential intensity and reduced TC ambient vertical wind shear in the second epoch. These decadal changes in background conditions over the WNP are the results of the enhanced summer monsoon in May over the both South Asia and South China Sea.

This paper assesses the impact of air–sea coupling on Indian Ocean tropical cyclones (TCs) by comparing a 20-year long simulation of a ¼° regional coupled ocean–atmosphere model with a twin experiment, where the atmospheric component is forced by sea surface temperature from the coupled simulation. The coupled simulation reproduces the observed spatio-temporal TCs distribution and TC-induced surface cooling reasonably well, but overestimates the number of TCs. Air–sea coupling does not affect the cyclogenesis spatial distribution but reduces the number of TCs by ~ 20% and yields a better-resolved bimodal seasonal distribution in the northern hemisphere. Coupling also affects intensity distribution, inducing a four-fold decrease in the proportion of intense TCs (Cat-2 and stronger). Air–sea coupling damps TCs growth through a reduction of inner-core upward enthalpy fluxes due to the TC-induced cooling. This reduction is particularly large for the most intense TCs of the northern Indian Ocean (up to 250 W m−2), due to higher ambient surface temperatures and larger TC-induced cooling there. The negative feedback of air–sea coupling on strongest TCs is mainly associated with slow-moving storms, which spend more time over the cold wake they induce. Sensitivity experiments using a different convective parameterization yield qualitatively similar results, with a larger (~ 65%) reduction in the number of TCs. Because of their relatively coarse resolution (¼°), both set of experiments however fail to reproduce the most intense observed TCs. Further studies with finer resolution models in the Bay of Bengal will be needed to assess the expectedly large impact of air–sea coupling on those intense and deadly TCs.

<p>Global warming influences tropical cyclones (TC) and their impacts in different ways. Warmer sea surface temperatures (SST) are expected to lead to stronger intensification, the increased water holding capacity of warmer air increases the precipitation brought by TCs. These are thermodynamic changes that are rather well understood.</p><p>When it comes to the influence of circulation changes on tropical cyclone activity open questions remain: Will there be more or less TCs in a warmer world? And what would be the physical mechanism for a change in TC frequencies?</p><p>TC formation and intensification not only depends on the available energy but also on the large-scale atmospheric circulation. For instance, TC development is strongly hampered when the vertical wind shear (difference between upper and lower level wind speeds) is high.</p><p>Here we present a tropical cyclone season emulator for the Atlantic basin that produces TCs based on SSTs averaged over the Atlantic main development region and daily time series of weather patterns obtained from a self-organizing map clustering. The emulator is based on probabilities for storm genesis, storm length and intensity changes that were empirically assessed using the ERA5 reanalysis and IBTrACS TC observations.</p><p>We see different applications for this emulator: <br>1) While most global circulation models (GCM) fail to adequately simulate TCs, their projections for SSTs and large-scale weather patterns contains valuable information. Using our emulator, we could indirectly analyse TC activity projections for all available GCMs. <br>2) In the emulator thermodynamic (SSTs) and dynamic influences (weather patterns) are distinct inputs. This allows us to construct different counterfactuals to attribute changes in TC activity to thermodynamic or dynamic changes. For example, the emulator could be used to simulate TC seasons with large scale circulation as observed in 2017 but with preindustrial SSTs, so as to analyse the extent to which warming of the ocean surface had contributed to the extreme hurricane season of 2017.</p>

In this study, the relationship between tropical cyclone (TC) intensity and rain rate over the ocean is investigated using a full-physics numerical model (WRF) and a physics-based TC rainfall model (TCR). TC intensity is found to be nearly linearly correlated with the average rain rate in the inner core [∼0.97 (mm h−1 m−2)/(m s−1)], while the correlation is weak at outer radii. This difference is induced because TC intensity is significantly correlated with both the vertical velocity and specific humidity in the inner core but is not significantly correlated with the vertical velocity in the outer radii. Further investigation shows that the intensity–rain-rate relationship at the outer radii is influenced by the TC evolution stage. The rain rate for the outer radii is positively correlated with TC intensity for nondecaying TCs, while this correlation is reduced for decaying TCs due to systematic downdrafts in the outer radii. In the context of climate change, the sensitivity of the TC rain rate to sea surface temperature (SST) is found to be +9% per 1 K increase of SST, roughly the product of the sensitivity of TC intensity to SST (+3%) and the Clausius-Clapeyron scaling (+7%). Coupled with synthetic storms, evolution of the TC rain rate over the twenty-first century under the SSP5-8.5 scenario is projected by the TCR (calibrated with the WRF simulations). The annual increase rates of averaged TC rain rate are 0.17% and 0.20% for the inner core and outer radii, respectively, larger than the annual increase rate of TC intensity (0.046%) but comparable to that of cube of intensity (0.18%).

Chapter 21 - Trends in frequency and intensity of tropical cyclones in the Bay of Bengal: 1972–2015

Tropical cyclone (TC) intensity is controlled by both environmental factors and its internal structure. This paper investigates the influence of inner core features derived from satellite data on TC intensity changes and explores effective methods to improve TC intensity forecast accuracy. We construct models for forecasting TC intensity over the next 5 days using the light gradient boosting machine (LGBM) algorithm in the northwestern Pacific. The models integrate climatological and persistence predictors, large-scale environmental variables at the initial time, inner core features extracted from satellite data, and variables related to the forecasted TC location. The models are trained on TC data from 2005 to 2019, tested using best track data from 2020 to 2022 and real-time data in 2023. Results show that the inner core features derived from satellite data are helpful for intensity forecasts within 36 h, and variables related to the forecasted location are helpful for improving TC intensity forecast accuracy in most cases, especially for the forecasts beyond 48 h. Compared with the National Centers for Environmental Prediction (NCEP) and European Centre for Medium-Range Weather Forecasts (ECMWF) models, our models demonstrate 4%–48% and 19%–70% decreases in mean absolute errors (MAEs) in real-time intensity forecasts. The most important predictors identified include potential future intensity change, intensity changes during the previous 12 h, vertical wind shear, and sea–land ratio. The inner core feature extracted from satellite data is also among the top 10 important variables for short-time intensity forecasts. Significance Statement This study advances tropical cyclone (TC) intensity forecasting by integrating climatological and persistence predictors, large-scale environmental variables at the initial time, satellite-derived inner core features, and variables related to the forecasted TC location into the light gradient boosting machine (LGBM) models. Our models significantly improve forecast accuracy, reducing mean absolute errors by 4%–48% compared with the National Centers for Environmental Prediction (NCEP) and 19%–70% compared with the European Centre for Medium-Range Weather Forecasts (ECMWF). Results denote that the inner core features improve the intensity prediction in the short time, and variables related to the forecasted TC location improve the intensity forecasts in most cases, especially for the forecasts beyond 48 h. This study provides valuable insights for enhancing operational TC intensity forecasting.

This study examines the potential limit in predicting tropical cyclone (TC) intensity under idealized conditions. Using the phase-space reconstruction method for TC intensity time series obtained from the CM1 idealized simulations, it is found that CM1 axisymmetric dynamics contain low-dimensional chaos at the maximum intensity equilibrium. Examination of several attractor invariants including the largest Lyapunov exponent, the Sugihara–May correlation, and the correlation dimension captures a consistent range of the chaotic attractor dimension between 4 and 5 for TC intensity at the maximum intensity equilibrium. In addition, the intensity error doubling time estimated from the largest Lyapunov exponent is roughly 1–3 h, which accords with the decay time obtained from the Sugihara–May correlation. Furthermore, the findings in this study reveal a relatively short TC intensity predictability limit for CM1, which is ∼3–9 h based on the maximum tangential wind but noticeably longer for the minimum central pressure (∼12–18 h) after reaching the mature stage. So long as the traditional metrics for TC intensity such as the maximum surface wind or the minimum central pressure is used for intensity forecast, our results support that TC intensity forecast errors will not be reduced indefinitely in any model, even in the absence of all model and observational errors. As such, the future improvement of TC intensity forecast should be based on different metrics beyond the absolute intensity errors that are currently used in real-time intensity verification. Significance Statement Using the phase-space reconstruction method for tropical cyclone (TC) intensity time series obtained from idealized axisymmetric simulations, we show that TC axisymmetric dynamics in CM1 possesses low-dimensional chaos at the maximum intensity equilibrium. This low-dimensional dynamics explains the long tradition of representing TC intensity by a few measures as in the current practice. The chaotic property of CM1 axisymmetric dynamics also suggests a relatively short predictability range for TC intensity at the maximum intensity equilibrium. The potential existence of low-dimensional chaos for TC intensity in CM1 idealized simulations as found in this study supports the use of different intensity verification metrics beyond the traditional absolute intensity errors currently used in operational model evaluation.

Using primitive equations with adiabatic, non‐friction non‐environmental steering, the dynamical equilibrium features of tropical cyclones (TC) are investigated. The parameter, dI/dt, was obtained and its dynamical balance formulation describing TC intensity change. The results of the we discussed the characteristics of TC motion and intensity change in barotropic and baroclinic model showed that the stationary motion of TC possess “equivalent‐geostrophic equilibrium” and isolines of potential vorticity and E(E = φ + (u2 + v2)/2) coincide with streamlines. The TC intensity will be weakened by “ventilation flow” in “beta (β) gyres” and “shear gyres” from the positive (negative) wind vertical shear at high‐ (low‐) level. The positive (negative) vorticity vertical convection of high‐ (low‐) level strengthens TC intensity. Generally, the TC center has the tendency to drift poleward and there is a gradient (ascendent) direction of vorticity vertical convection at high‐ (low‐) level. The TC motion is connected with the asymmetry structure of vertical shear and vertical motion, the “γ effect” (γ = ∂β/∂y) that is one of the dynamical mechanisms of “ventilation flow” steering TC center motion.

Several key issues in the simple time-dependent theories of tropical cyclone (TC) intensification developed in recent years remain, including the lack of a closure for the pressure dependence of saturation enthalpy at sea surface temperature (SST) under the eyewall and the definition of environmental conditions, such as the boundary layer enthalpy in TC environment and the TC outflow-layer temperature. In this study, some refinements to the most recent time-dependent theory of TC intensification have been accomplished to resolve those issues. The first is the construction of a functional relationship between the surface pressure under the eyewall and the TC intensity, which is derived using the cyclostrophic wind balance and calibrated using full-physics axisymmetric model simulations. The second is the definition of TC environment that explicitly includes the air–sea temperature difference. The third is the TC outflow-layer temperature parameterized as a linear function of SST based on global reanalysis data. With these refinements, the updated time-dependent theory becomes self-contained and can give both the intensity-dependent TC intensification rate (IR) and the maximum potential intensity (MPI) under given environmental thermodynamic conditions. It is shown that the pressure dependence of saturation enthalpy at SST can lead to an increase in the TC MPI and IR by about half of that induced by dissipative heating due to surface friction. Results also show that both MPI and IR increase with increasing SST, surface enthalpy exchange coefficient, environmental air–sea temperature difference, and decreasing environmental boundary layer relative humidity, but the maximum IR is insensitive to surface drag coefficient. Significance Statement A new advancement in the recent decade is the development of simple time-dependent theories of tropical cyclone (TC) intensification, which can provide quantitative understanding of TC intensity change. However, several key issues in these simple time-dependent theories remain, including the lack of a closure for the pressure dependence of saturation enthalpy at sea surface temperature under the eyewall and the definition of environmental conditions. These are resolved in this study with several refinements, which make the most recent time-dependent theory of TC intensification self-contained and practical.

A tropical cyclone intensity prediction model using conditional generative adversarial network

Evaluation of Tropical Cyclone Forecasts from Operational Global Models Over the Western North Pacific in 2013