Cyclone Intensity Research Articles

A Review of the Interactions between Tropical Cyclones and Environmental Vertical Wind Shear

Abstract Tropical cyclone (TC) structure and intensity are strongly modulated by interactions with deep-layer vertical wind shear (VWS)—the vector difference between horizontal winds at 200 and 850 hPa. This paper presents a comprehensive review of more than a century of research on TC–VWS interactions. The literature broadly agrees that a TC vortex becomes vertically tilted, precipitation organizes into a wavenumber-1 asymmetric pattern, and thermal and kinematic asymmetries emerge when a TC encounters an environmental sheared flow. However, these responses depend on other factors, including the magnitude and direction of horizontal winds at other vertical levels between 200 and 850 hPa, the amount and location of dry environmental air, and the underlying sea surface temperature. While early studies investigated how VWS weakens TCs, an emerging line of research has focused on understanding how TCs intensify under moderate and strong VWS (i.e., shear magnitudes greater than 5 m s−1). Modeling and observational studies have identified four pathways to intensification: vortex tilt reduction, vortex reformation, axisymmetrization of precipitation, and outflow blocking. These pathways may not be uniquely different because convection and vortex asymmetries are strongly coupled to each other. In addition to discussing these topics, this review presents open questions and recommendations for future research on TC–VWS interactions.

Developing climate services for vulnerable islands in the Southwest Indian Ocean: A combined statistical and dynamical CMIP6 downscaling approach for climate change assessment

Climate change is a global challenge necessitating adaptation at the local level. Small island developing states (SIDS) in the southwest Indian Ocean (SWIO) basin are particularly vulnerable and already facing significant challenges due to climate variability and extreme weather events like tropical cyclones (TCs). Tailored climate services, catering to their specific needs and contexts, are crucial for formulating appropriate adaptation strategies. This study aims to fill the gap of localized and reliable information for climate services in the SWIO region. A 12-km resolution regional climate model is dynamically downscaled from a CMIP6 model to capture the climatology of tropical cyclones. Outputs are bias-corrected at kilometer-scale resolution over multiple islands. A subset of CMIP6 simulations is also statistically downscaled over La Réunion to quantify model uncertainties at the local scale and compare statistical and dynamical downscaling methods.CMIP6 models project an average increase in daily mean temperatures over small islands ranging from 1.2 °C (SSP1-2.6) to 3.7 °C (SSP5-8.5) by the end of the century compared to the reference period of 1981–2010, and up to 4.4 °C on Madagascar (SSP5-8.5). The dry season in the SWIO region is anticipated to become significantly drier, with precipitation deficits ranging from 10 % to 40 %, primarily due to a delayed onset of the rainy season. The cyclonic risk is expected to increase due to stronger cyclone intensities, a higher proportion of strong TCs, and the poleward migration of very intense TCs by one to two degrees latitude, further amplifying the risk faced by the Mascarene islands.

The upstream–downstream connection of North Atlantic and Mediterranean cyclones in semi-idealized simulations

Abstract. Cyclogenesis in the Mediterranean is typically triggered by the intrusion of a potential vorticity (PV) streamer over the Mediterranean. The intrusion of the PV streamer results from a preceding Rossby wave breaking (RWB) upstream over the North Atlantic. The ridge leading to the RWB is typically amplified by the presence of warm conveyor belts (WCBs) in at least one North Atlantic cyclone about 4 d prior to Mediterranean cyclogenesis. Thus, the sequence of these four main events (namely a North Atlantic cyclone, WCBs, RWB, and the resulting PV streamers) forms an archetypal scenario leading to Mediterranean cyclogenesis. However, they rarely occur in a spatially consistent, fully repetitive pattern for real cyclone cases. To more systematically study this connection between upstream North Atlantic cyclones and Mediterranean cyclogenesis, we perform a set of semi-idealized simulations over the Euro-Atlantic domain. For these simulations, we prescribe a constant climatological atmospheric state in the initial and boundary conditions. To trigger the downstream Mediterranean cyclogenesis scenario, we perturb the climatological polar jet through the inversion of a positive upper-level PV anomaly. The amplitude of this perturbation determines the intensity of the triggered North Atlantic cyclone. This cyclone provokes RWB, the intrusion of a PV streamer over the Mediterranean, and thereby the formation of a Mediterranean cyclone. Therefore, our results show a direct connection between the presence of a North Atlantic cyclone and the downstream intrusion of a PV streamer into the Mediterranean, which causes cyclogenesis about 4 d after perturbing the polar jet. We refer to this as the upstream–downstream connection of North Atlantic and Mediterranean cyclones. To investigate the sensitivity of this connection, we vary the position and amplitude of the upper-level PV anomaly. In all simulations, cyclogenesis occurs in the Mediterranean. Nevertheless, the tracks and intensity of the Mediterranean cyclones may vary by up to 20° and 10 hPa (at the time of the mature stage), respectively. This indicates that the Mediterranean cyclone dynamics are sensitive to the dynamical structure and amplitude of the intruding PV streamer, which itself is sensitive to the interaction of the upstream cyclone and the RW(B). By applying different seasonal climatological atmospheric states as initial conditions we show that cyclogenesis occurs in distinct regions in different seasons. Thus, the seasonal cycle of Mediterranean cyclogenesis might be partly determined by the large-scale atmospheric circulation, i.e., the seasonal location of the polar jet. Furthermore, we show that the Mediterranean cyclones in these semi-idealized simulations show characteristics that agree with the observed climatology of Mediterranean cyclones in the respective season.

Can cyclone exposure explain behavioural and demographic variation among lemur species?

Madagascar has a harsh and stochastic climate because of regular natural disturbances. This history of regular cyclones has been hypothesised to have directed evolutionary changes to lemur behaviour and morphology that make them more resilient to sudden environmental change. These adaptations may include: small group sizes, high degrees of energy-conserving behaviours, generalist habitat use, small home ranges, small body size, and a limited number of frugivorous species. To date, however, no one has tested how variation in cyclone exposure across Madagascar is associated with variation in these resilience traits. In this study, we created a detailed cyclone impact map for Madagascar using Koppen-Geiger climate class, historical cyclone tracks, the Saffir Class of cyclone and hurricane intensity, and precipitation data. We also used existing literature to calculate a resilience score for 26 lemur species for which data existed on resilience traits. Our cyclone impact map was then overlaid on known geographic ranges of these species and compared to resilience score while controlling for phylogenetic non-independence and spatial autocorrelation. We found no association between cyclone impact in a lemur range and their resilience score. When assessing traits individually, however, we found that cyclone impact was positively associated with body size, suggesting that the more impacted a species is by cyclones the smaller they are. We also found cyclone impact to be negatively associated with frugivory, with species in higher impact zones eating more fruit. While unexpected, this could reflect an increased production in fruit in tree fall gaps following cyclones. While we did not find a pattern between cyclone impact and behavioural resilience in lemurs, we suggest a similar study at a global scale across all primates would allow for more taxonomic variation and reveal larger patterns key to understanding past and future vulnerability to natural disturbances in primates.

Trends in the ocean mixed‐layer depth in the western North Pacific tropical cyclone basin

AbstractThe upper ocean mixed‐layer depth (MLD) has been recognized as a crucial factor in understanding the impact of climate change on tropical cyclone (TC) intensity, while the specific MLD variations in the western North Pacific (WNP) basin have received comparatively little attention. Using two ocean reanalysis datasets and the output of 28 CMIP6 models, the climatological mean MLD and its trend in the TC active region are examined. Compared to the ORAS4 and EN4 datasets, the spatial pattern of the climatological mean MLD can be well simulated in the multi‐model ensemble (MME). The mean MLD decreases with increasing latitude and maintains the maximum in the equatorial region. The spatial patterns of MLD long‐term (1958–2017) and short‐term (1979–2017) trends are deepening in the TC active region, with the relatively large positive trends occurring to the southeastern WNP primarily between 5°N and 15°N. However, the simulated trend in the MME is dominant with shoaling MLD, and the shoaling of the MLD is also projected under the SSP5‐8.5 scenario. It is suggested that the bias on the simulated shoaling of the MLD in CMIP6 models may result from the overestimated enhancement of the upper‐ocean stratification. Thus, there is a discrepancy between the observed and simulated MLD trends in the WNP basin, which may have implications for TC intensity change under global warming scenarios.

Impact of Extratropical Circulation in East Asia on Western North Pacific Tropical Cyclone Frequency and Intensity

Abstract This study examines the East Asia and western North Pacific (WNP) monsoon circulation patterns for strong and weak WNP tropical cyclone (TC) numbers in summer. It suggested that years with more intense TCs are coupled with the tropical monsoon circulations, including the northward cross-equatorial airflow and the extending tropical monsoon trough toward the central-eastern WNP. However, a higher frequency of weak TCs can be largely attributed to the mutual interactions among the tropical monsoon trough west of 140°E, the westward South Asia high, and the high pressure anomaly in Northeast Asia (NEA). Then the potential influence of the NEA extratropical system is focused on. The resultant local negative potential vorticity (PV) anomaly is carried southeastward by the prevailing flow. It stimulates a descending flow around 30°N, which favors the westward retreat of the South Asian high and the decreased zonal vertical wind shear around 20°N. The associated lower-level outflow converges in the tropical WNP and reinforces the ascending motion around 10°–20°N. Meanwhile, the warm air column in NEA also contributes to anomalous easterlies in a band around 30°N, intensifying the lower-level cyclonic vorticity in the northwestern WNP. Consequently, the ascending motion, cyclonic vorticity, and the weakened zonal vertical wind shear in northwestern WNP promote the WTC formation. A set of physically based empirical models is developed using various physically based predictors to reconstruct the number of intense and weak TCs. Cross-validated hindcasts suggest that the NEA extratropical circulation can serve as an additional source of predictability for the weak TC variability. Significance Statement Tropical cyclones (TCs) are a highly destructive type of natural disaster that have garnered widespread attention. By comparison with intense TCs (ITCs), weak TCs (WTCs) are much more numerous and often form closer to the coastal regions of East Asia, whose mechanism has not been fully understood. In this study, we suggest that more ITCs are controlled by tropical monsoon circulations, while the WTC variability is closely coupled with both tropical and extratropical monsoon systems. In addition to the tropical monsoon trough west of 140°E and the westward South Asian high, the Northeast Asian circulation can regulate the WTC number by changing the lower-level vorticity, vertical motion, and vertical wind shear in the WTC genesis-prone region, which can be applied to improve the seasonal prediction skill of WTCs.

Improving our understanding of future tropical cyclone intensities in the Caribbean using a high-resolution regional climate model

The Caribbean region is prone to the strong winds and low air pressures of tropical cyclones and their corresponding storm surge that driving coastal flooding. To protect coastal communities from the impacts of tropical cyclones, it is important to understand how this impact of tropical cyclones might change towards the future. This study applies the storyline approach to show what tropical cyclones Maria (2017) and Dorian (2019) could look like in a 2 °C and 3.4 °C warmer future climate. These two possible future climates are simulated with a high-resolution regional climate model using the pseudo global warming approach. Using the climate response from these simulations we apply a Delta-quantile mapping technique to derive future changes in wind speed and mean sea level pressure. We apply this Delta technique to tropical cyclones Maria and Dorian’s observed wind and pressure fields to force a hydrodynamic model for simulating storm surge levels under historical and future climate conditions. Results show that the maximum storm surge heights of Maria and Dorian could increase by up to 0.31 m and 0.56 m, respectively. These results clearly show that future changes in storm surge heights are not negligible compared to end-of-the-century sea level rise projections, something that is sometimes overlooked in large-scale assessments of future coastal flood risk.

Combined use of HYSPLIT model and MODIS aerosols optical depth to study the spatiotemporal circulation patterns of Saharan dust events over Central Europe

Mineral dust released from the desert region and transported into the atmosphere has a crucial impact on the Earth's climate system's biogeochemical cycle. It has serious adverse effects on human health. The Sahara is one of the world's dustiest areas. This investigation intends to uncover the underlying reasons for atmospheric dust dispersion throughout the year by tracking the dusttransport and deposition in Central Europe, focusing on arid areas of North Africa. In this paper, we use the GDAS (Global Data Assimilation System) archival meteorological database to compute the analytical forward trajectories and configure the particle concentrations using the HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) model. Besides, we investigate the synoptic meteorological conditions of acute Saharan dust episodes to determine the dynamic atmospheric system during their onset. The forward trajectories reveal the seasonality of wind-blown dust throughout the year. Dust storms are typically more prevalent in the spring, with a second peak in the Summer. As a result, particle transport takes various paths as the seasons and climatic conditions change. The most dust-laden masses, which reach high altitudes from the source areas, are often transported to Central Europe, where their seasonal distribution is relatively similar to that of the studied African region. However, the intensity and frequency of Saharan dust events (SDEs) have significantly changed in the previous decades, with an increased number of intense winter storms. According to the synoptic analysis, this variability is strongly linked to two factors. (1) The intensity and lifetime variation of the Mediterranean cyclones and (2) Climate change triggered lee-side (Sharav) cyclogenesis modified by the topographic complexity of Atlas. This study also confirmed the effectiveness of the HYSPLIT model in simulating atmospheric dust after comparing it with annual aerosol optical depth measurements from MODIS (Moderate-Resolution Imaging Spectroradiometer) data.

Bridging satellite missions: deep transfer learning for enhanced tropical cyclone intensity estimation

ABSTRACT Geostationary satellites are valuable tools for monitoring the entire lifetime of tropical cyclones (TCs). Although the most widely used method for TC intensity estimation is manual, several automatic methods, particularly artificial intelligence (AI)-based algorithms, have been proposed and have achieved significant performance. However, AI-based techniques often require large amounts of input data, making it challenging to adopt newly introduced data such as those from recently launched satellites. This study proposed a transfer-learning-based TC intensity estimation method to combine different source data. The pre-trained model was built using the Swin Transformer (Swin-T) model, utilizing data from the Communication Ocean and Meteorological Satellite Meteorological Imager sensor, which has been in operation for an extensive period (2011–2021) and provides a large dataset. Subsequently, a transfer learning model was developed by fine-tuning the pre-trained model using the GEO-KOMPSAT-2A Advanced Meteorological Imager, which has been operational since 2019. The transfer learning approach was tested in three different ways depending on the fine-tuning ratio, with the optimal performance achieved when all layers were fine-tuned. The pre-trained model employed TC observations from 2011 to 2017 for training and 2018 for testing, whereas the transfer learning model utilized data from 2019 and 2020 for training and 2021 for testing to evaluate the model performance. The best pre-trained and transfer learning models achieved mean absolute error of 6.46 kts and 6.48 kts, respectively. Our proposed model showed a 7–52% improvement compared to the control models without transfer learning. This implies that the transfer learning approach for TC intensity estimation using different satellite observations is significant. Moreover, by employing a deep learning model visualization approach known as Eigen-class activation map, the spatial characteristics of the developed model were validated according to the intensity levels. This analysis revealed features corresponding to the Dvorak technique, demonstrating the interpretability of the Swin-T-based TC intensity estimation algorithm. This study successfully demonstrated the effectiveness of transfer learning in developing a deep learning-based TC intensity estimation model for newly acquired data.

Advanced hybrid CNN-Bi-LSTM model augmented with GA and FFO for enhanced cyclone intensity forecasting

Predicting cyclone intensity is an important aspect of weather forecasting since it influences disaster preparation and response. This framework addresses the pressing need for precise cyclone intensity prediction by presenting a unique predictive model based on a hybrid CNN and Bi-LSTM architecture optimized using a Genetic Algorithm (GA) enhanced Fruit Fly Optimizer (FFO). Existing methods have primarily relied on traditional machine learning models and meteorological data, demonstrating limitations in capturing the complex spatial-temporal patterns inherent in cyclone evolution. These drawbacks include insufficient feature extraction abilities, underutilization of convolutional neural networks (CNN), and poor model tuning. This unique method incorporates a hybrid CNN and Bi-LSTM architecture that is tuned by a Genetic Algorithm (GA) enhanced Fruit Fly Optimizer (FFO), resulting in higher cyclone intensity prediction accuracy. The experimental results are implemented in Python software, and they reveal that this method outperforms current models by an average of 21% when compared to existing methods such as VGG-16 achieved an accuracy of 78% and Ty 5-CNN (95.23%). The suggested CNN-Bi-LSTM model predicts cyclone strength with an excellent accuracy of 99.4%. This unique approach offers a possible avenue for increasing cyclone intensity prediction, hence improving disaster preparedness and risk mitigation efforts in sensitive locations.

Why does tropical cyclone intensify faster under weaker parameterized horizontal diffusion in three-dimensional numerical simulations?

The mechanisms by which the parameterized horizontal diffusion impacts the tropical cyclone (TC) intensification are investigated via a series of numerical simulations of Supertyphoon Lekima (2019) with different horizontal mixing lengths (Lh). Consistent with previous studies, the TC intensifies faster and attains a higher peak intensity as Lh decreases, which is attributed to a more compact wind structure and the stronger eyewall convective heating. The azimuthal-mean tangential wind and vertical momentum budgets are conducted to explain the differences in TC size and convective strength between the simulations. It is found that when horizontal diffusion weakens, the eddy mixing of tangential momentum becomes larger inside the radius of maximum wind, therefore promoting size contraction. The stronger eddy mixing is attributed to the more active eyewall mesovortices whose growth is suppressed when horizontal diffusion strengthens. The vertical momentum budget results indicate that the air parcels in the simulation with smaller Lh experience stronger upward buoyancy force in the lower-to-mid troposphere (3–7 km) than those in the larger-Lh simulation, leading to more vigorous eyewall convection. It is further revealed that the reduced horizontal diffusion helps maintain the strength of virtual potential temperature perturbations and therefore the buoyancy in the eyewall updrafts. The findings from this study imply that the horizontal diffusion plays an important role in regulating the mesoscale and convective-scale processes in the inner-core region and improvements in its parameterization are urged for improving TC intensity forecast.

Reducing a Tropical Cyclone Weak-Intensity Bias in a Global Numerical Weather Prediction System

Abstract The operational Canadian Global Deterministic Prediction System suffers from a weak-intensity bias for simulated tropical cyclones. The presence of this bias is confirmed in progressively simplified experiments using a hierarchical system development technique. Within a semi-idealized, simplified-physics framework, an unexpected insensitivity to the representation of relevant physical processes leads to investigation of the model’s semi-Lagrangian dynamical core. The root cause of the weak-intensity bias is identified as excessive numerical dissipation caused by substantial off-centering in the two time-level time integration scheme used to solve the governing equations. Any (semi)implicit semi-Lagrangian model that employs such off-centering to enhance numerical stability will be afflicted by a misalignment of the pressure gradient force in strong vortices. Although the associated drag is maximized in the tropical cyclone eyewall, the impact on storm intensity can be mitigated through an intercomparison-constrained adjustment of the model’s temporal discretization. The revised configuration is more sensitive to changes in physical parameterizations and simulated tropical cyclone intensities are improved at each step of increasing experimental complexity. Although some rebalancing of the operational system may be required to adapt to the increased effective resolution, significant reduction of the weak-intensity bias will improve the quality of Canadian guidance for global tropical cyclone forecasting. Significance Statement Global numerical weather prediction systems provide important guidance to forecasters about tropical cyclone development, motion, and intensity. Despite recent improvements in the Canadian operational model’s ability to predict tropical cyclone formation, the system systematically underpredicts the intensity of these storms. In this study, we use a set of increasingly simplified experiments to identify the source of this error, which lies in the numerical time-stepping scheme used to solve the model equations. By decreasing numerical drag on the tropical cyclone circulation, intensity predictions that resemble those of other global modeling systems are achieved. This will improve the quality of Canadian tropical cyclone guidance for forecasters around the world.

СВЯЗЬ МОРСКОГО ВОЛНЕНИЯ С ЦИКЛОНИЧЕСКОЙ АКТИВНОСТЬЮ В АТМОСФЕРЕ СЕВЕРНОГО ПОЛУШАРИЯ ПО ДАННЫМ РЕАНАЛИЗА ERA5

Based on the ERA5 reanalysis data for the period 1979-2021, the authors have quantified the seasonal and regional connections between significant wave heights and changes in cyclone activity in the atmosphere of the Northern Hemisphere. The contribution of extratropical cyclones to the formation of the corresponding features and variations of sea waves is evaluated. The maxima of the extreme sea wave occurrence frequency in winter and summer corresponds to sea areas with an increased frequency of cyclones, in particular, over the Pacific and Atlantic oceans. It has been found that the contribution of extratropical cyclones to the generation of significant wave heights reaches 70% in winter and 50% in summer. The largest contribution is associated with intense cyclones: 90% in winter and 40% in summer.

An Adaptive Channel Selection Method for Assimilating the Hyperspectral Infrared Radiances

Abstract Hyperspectral infrared (IR) satellites can provide high-resolution vertical profiles of the atmospheric state, which significantly contributes to the forecast skill of numerical weather prediction, especially for regions with sparse observations. One challenge in assimilating the hyperspectral radiances is how to effectively extract the observation information, due to the interchannel correlations and correlated observation errors. An adaptive channel selection method is proposed, which is implemented within the data assimilation scheme and selects the radiance observation with the maximum reduction of variance in observation space. Compared to the commonly used channel selection method based on the maximum entropy reduction (ER), the adaptive method can provide flow-dependent and time-varying channel selections. The performance of the adaptive selection method is evaluated by assimilating only the synthetic Fengyun-4A (FY-4A) GIIRS IR radiances in an observing system simulation experiment (OSSE), with model resolutions from 7.5 to 1.5 km and then 300 m. For both clear-sky and all-sky conditions, the adaptive method generally produces smaller RMS errors of state variables than the ER-based method given similar amounts of assimilated radiances, especially with fine model resolutions. Moreover, the adaptive method has minimum RMS errors smaller than or approaching those with all channels assimilated. For the intensity of the tropical cyclone, the adaptive method also produces smaller errors of the minimum dry air mass and maximal wind speed at different levels, compared to the ER-based selection method. Significance Statement Assimilating satellite radiances has been essential for numerical weather prediction. Hyperspectral infrared satellites provide high-resolution vertical profiles for the atmospheric state and can further improve the numerical weather prediction. Due to limited computational resources, and correlated observations and associated errors, efficient and effective ways to assimilate the hyperspectral radiances are needed. An adaptive channel selection method that is incorporated with data assimilation is proposed. The adaptive channel selection can effectively extract the information from hyperspectral radiances under both clear- and all-sky conditions, with increased model resolutions from kilometers to subkilometers.

Effects of Background Synoptic Environment in Controlling South China Sea Tropical Cyclone Intensity and Size Changes in Pseudo–Global Warming Experiments

Abstract Assessing how global warming affects tropical cyclones (TC) is immensely important for climate change adaptation and hazard mitigation. However, projected intensity and size change can vary greatly among different individual storms, even under the same forcing in pseudo–global warming (PGW) experiments. Here we hypothesize that these variations are related to the historical environment in which each TC was embedded. Twenty-five TCs in the South China Sea (SCS) region were simulated using the Weather Research and Forecasting (WRF) Model. Their changes in the near (2036–65) and far future (2075–99) following the representative concentration pathways 8.5 (RCP8.5) and 4.5 (RCP4.5) under phase 5 of the Coupled Model Intercomparison Project (CMIP5) were investigated by the PGW technique. The mean changes in TC intensity and gale-force wind radius (R17) in the SCS were +6.4% and +1.5% for a 2°C warming, respectively. Multiple linear regression and stepwise regression analysis revealed that storm intensity variations were positively correlated with historical sea surface temperature and negatively with outer (i.e., outside the TC’s R17) atmospheric instability, while the R17 variations correlated positively with outer midtropospheric relative humidity (RH) and surface outer wind speed (OWS). Ertel potential vorticity (EPV) diagnostics further showed a moister SCS background can cause stronger diabatic heating and EPV production at the spiral rainbands under PGW, which increases R17. Additionally, stronger background absolute angular momentum (AAM) promoted stronger AAM influx, leading to larger R17. Implications were drawn to explain the uncertainties in projected TC intensity and size due to natural variability. Significance Statement Changes in the intensity and size of individual tropical cyclones in future climates are highly variable. This study aims to understand the environmental factors influencing these variations. We selected 25 storms that entered the South China Sea region and modeled them in both present and future climates. The mean intensity and size were projected to increase by 6.4% and 1.5% for a 2°C warming, respectively. We found that tropical cyclones embedded in historically warmer oceans and more stable atmospheres intensified more than the others, while historically wetter and windier environments promoted larger size growth. Our results suggest that certain tropical cyclones can exhibit a greater increase in intensity and size in a warmer climate under favorable environmental conditions.

Tropical Cyclone Changes in Convection‐Permitting Regional Climate Projections: A Study Over the Shanghai Region

AbstractChanges in tropical cyclones due to greenhouse‐gas forcing in the Shanghai area have been studied in a double‐nesting regional model experiment using the Met Office convection‐permitting model HadREM3‐RA1T at 4 km resolution and the regional model HadREM3‐GA7.05 at 12 km for the intermediate nest. Boundary conditions for the experiment have been constructed from HadGEM2‐ES, a General Circulation Model (GCM) from the 5th Coupled Model Intercomparison Project (CMIP5), directly using high‐frequency data for the atmosphere (6‐hourly) and the ocean (daily), for the historical period (1981–2000) and under the Representative Concentration Pathway 8.5 (2080–2099). These choices identify one of the warmest climate scenarios available from CMIP5. Given the direct use of GCM data for the baseline, large scale conditions relevant for tropical cyclones have been analyzed, demonstrating a realistic representation of environmental conditions off the coast of eastern China. GCM large scale changes show a reduction in wind shear in addition to the expected strong increase in sea‐surface temperature. Tropical cyclones from the 4 km historical simulation have a negative bias in intensity, not exceeding Category 4, and a wet bias in the rainfall associated with these cyclones. However, there is a clear improvement in cyclone intensity and rainfall at 4 km in comparison with the 12 km simulation. Climate change responses in the 4 km simulation include an extension of the tropical cyclone season, and strong increases in frequency of the most intense cyclones (approximately by a factor of 10) and associated rainfall. These are consistent with the results from the 12 km simulation.

A Deep Learning Structure for Forecasting Cyclone Intensity

A Deep Learning Structure for Forecasting Cyclone Intensity

Influence of Spatial Heterogeneity in Sea Surface Temperature on Tropical Cyclone Intensity Over the Western North Pacific

AbstractThis study explores the impact of sea surface temperature (SST) spatial heterogeneity on tropical cyclone (TC) intensity through a combination of observations and simulations, aiming to provide a reference for further improving TC intensity forecasting skills. Two distinct patterns of SST spatial heterogeneity are identified based on a statistical analysis of observational data, when the SST at the TC center is above and below 29.3°C, respectively. One is a warm‐core pattern (WCP) with a warm peak SST at the TC center decreasing centrifugally which favors TC development, and the other one is a poleward‐decreasing pattern (PDP) with a warm SST at the south decreasing poleward which suppresses TC development. The numerical simulations confirm the opposite influence of the WCP and the PDP on TC intensity. The WCP intensifies TC intensity by strengthening TC secondary circulation, increasing the conversion from ocean heat energy to TC kinetic energy, and compacting TC structure. In contrast, the PDP weakens TC intensity by inducing opposing responses of these processes. The magnitude of TC intensity change caused by SST spatial heterogeneity is comparable to those caused by a 1°C change in SST at the TC center. These findings offer valuable insights into the role of SST spatial heterogeneity in TC development and provide a new perspective to improve TC intensity forecasting by incorporating SST spatial heterogeneity into statistical‐dynamic models.

Increase in western North Pacific tropical cyclone intensification rates and their northwestward shifts

The tropical cyclone intensification rates (TCIRs) over the western North Pacific (WNP) are investigated on the basis of 6-hourly atmospheric and oceanic reanalyses and TC best track data from 1982 to 2020. Results indicate that 24-h-TCIRs over the WNP have increased remarkably by ∼17.2% in the past four decades. A remarkable difference before and after the changepoint 2004 is detected in 24-h TCIRs over the WNP basin. The correlation between the TCIR and sea surface temperature (SST) during 2005–2020 shows a significant positive correlation over the western Pacific. Composite analyses of atmospheric and oceanic environments between P1 (1982–2004) and P2 (2005–2020) suggest greater contributions of the underlying SST and relative vorticity (VORT) than those of vertical wind shear (VWS) and mid-tropospheric relative humidity (RH) to TCIR increase. The maximum potential intensity (MPI) has increased since the 1980s, with a significant change from P1 to P2, which further demonstrates that the environmental fields since 2004 are more favorable for TC intensification. At the same time, TCIR geolocation shows a northwestward shift over the TC-active region bounded by 10° ∼ 25°N, 125° ∼ 150°E since 2004, which is possibly modulated by the interdecadal difference of steering flow and ocean state. This study may provide inspirations to clarify the mechanisms of WNP-TCIR interdecadal increase for general TC intensity forecast.

The Contribution of United States Aircraft Reconnaissance Data to the China Meteorological Administration Tropical Cyclone Intensity Data: An Evaluation of Homogeneity

The Contribution of United States Aircraft Reconnaissance Data to the China Meteorological Administration Tropical Cyclone Intensity Data: An Evaluation of Homogeneity