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Regional climate models (RCMs) from the CORDEX enable further investigations of the regional aspects of climate change impacts in South America. Here, we assess the CORDEX‐RCMs' present and future projections of extratropical cyclones, focusing on their frequency, early‐stage synoptic features, and added value relative to the global climate models (GCMs). Cyclones were tracked using a common algorithm in the present (1985–2005) and future RCP8.5 scenarios (2080–2099). ERA5 reanalysis was used as reference data in the present climate. Both GCMs and RCMs can identify the three major cyclone hot spots in South America: Argentina (ARG), La Plata Basin (LPB), and the south‐southeast Brazilian coast (SBR). RCMs improve GCMs' representation of the cyclogenesis frequency, adding value by decreasing the biases (~10%). Early‐stage cyclone synoptic structure also indicates RCMs' improvement of the low‐level fields by presenting mesoscale structures of warm/cold advection and moisture flux convergence/divergence in greater agreement with ERA5 (except for moisture flux divergence for LPB). RCMs and GCMs project a general decrease in cyclogenesis for the end of the century. For the cyclogenesis cores, GCMs' and RCMs' projections agree on the trend signals in SBR, LPB, and ARG in austral winter and disagree in ARG in austral summer. For LPB and SBR cyclogenesis, the RCMs and GCMs suggest a future increase in moisture flux convergence and warm advection at low levels, while a decrease in upper level divergence is projected. This indicates a reinforcement of cyclogenesis (negative sea‐level pressure trend) in the future due to the low‐level features and associated diabatic processes. For ARG, the future trends in the mean structure of cyclogenesis are relatively weak. Following other studies, cyclogenesis frequency may decrease; however, changes could occur in some important physical processes, such as low‐level moisture flux convergence and warm advection, suggesting more intense events in the future. [ABSTRACT FROM AUTHOR]

Medicanes are rare cyclones in the Mediterranean Sea, with intensifying trends partly attributed to climate change. Despite progress, challenges persist in understanding and predicting these storms due to limited historical tracking data and their infrequent occurrence, which make monitoring and forecasting difficult. In response to this issue, we present an AI-based system for tracking and forecasting Medicanes, employing machine learning techniques to identify cyclone positions and key evolving spatio-temporal structural features of the cloud system that are associated with their intensification and potential extreme development. While the forecasting model currently operates with limited training data, it can predict extreme Medicane events up to two days in advance, with precision rates ranging from 65% to 80%. These innovative data-driven methods for tracking and forecasting provide a foundation for refining AI models and enhancing our ability to respond effectively to such events. [ABSTRACT FROM AUTHOR]

Climate change is associated with the modification of the polar jet stream, cyclone tracks and corresponding circulation patterns over midlatitudes. To apply these synoptic changes on regional climate, the changing sensitivity of a specific location to different pressure centre regions must be studied. An automated, objective circulation pattern detection method was developed to investigate the evolution of cyclonic and anticyclonic influence at any specific point within the European domain. The algorithm was used to assign each location to influencing low‐ or high‐pressure centres within the domain. Pressure centre displacements and the frequency redistribution among different centres were studied for each location. The 180‐year (January 1836–December 2015) mean sea level pressure dataset on the European domain with a 0.703° × 0.702° spatial and daily temporal resolution was obtained from NOAA 20th Century Reanalysis project. The presented method can apply the continental‐scale changes to specific locations. A significant increase of anticyclonic influence was found in southern and central Europe, in line with the northward displacement of Atlantic cyclones. Hundred and eighty year (180‐year) change of the number of days with anticyclonic versus cyclonic influence was found to be between +10% and 15% in the Mediterranean and +2% and 10% in most of Europe. The increasing anticyclonic influence in central Europe was strongest in the spring and the winter and was most attributable to the eastern European anticyclone. Results highlight the importance of research on the dynamical climate response of anticyclonic pressure systems. [ABSTRACT FROM AUTHOR]

Extreme precipitation events induced by tropical cyclones have increased frequency and intensity, significantly impacting human socioeconomic activities and ecological environments. This study systematically examines the spatiotemporal characteristics of these events across Hainan Island and their influencing factors using GsMAP satellite precipitation data and tropical cyclone track data. The results indicate that while the frequency of typhoon events in Hainan decreased by 0.3 events decade−1 from 1949 to 2020, extreme precipitation events have increased significantly since 2000, especially in the eastern and central regions. Different typhoon tracks have distinct impacts on the island, with Track 1 (Northeastern track) and Track 2 (Central track) primarily affecting the western and central regions and Track 3 (Southern track) impacting the western region. The impact of typhoon precipitation on extreme events increased over time, being the greatest in the eastern region, followed by the central and western regions. Incorporating typhoon precipitation data shortened the recurrence interval of extreme precipitation in the central and eastern regions. Diurnal peaks occur in the early morning and late evening, primarily affecting coastal areas. Typhoon duration (CC_max = 0.850) and wind speed (CC_max = 0.369) positively correlated with extreme precipitation, while the pressure was negatively correlated. High sea surface temperature areas were closely associated with extreme precipitation events. The atmospheric circulation indices showed a significant negative correlation with extreme precipitation, particularly in the western and central regions. ENSO events, especially sea surface temperature changes in the Niño 1 + 2 region (−0.340 to −0.406), have significantly influenced typhoon precipitation characteristics. These findings can inform region-specific disaster prevention and mitigation strategies for Hainan Island. [ABSTRACT FROM AUTHOR]

Extratropical cyclones play an important role in shaping the weather and climate over vast regions across the globe. To effectively understand and manage the impact of these meteorological events, it is crucial to explore deeper into their structure and behaviour. Here, we have evaluated the characteristics and spatial distribution of extratropical cyclones that had their genesis in the Southern Ocean (SO) in the present climate, based on data from the HadGEM3‐GC3.1‐MM (HG3) global model and the ERA5 reanalysis. Both in winter and summer, cyclone tracks are spatially structured, forming a belt around the entire Antarctic continent, with greater concentration in the SO sector adjacent to the southern Pacific Ocean. The regions of the Somov, Amundsen and Bellingshausen seas exhibited a higher track density of moderate and strong cyclones, indicating a correlation with the strongest baroclinicity in these areas. In both datasets, the maximum occurrence of cyclogenesis was located over the regions of the Somov Sea and the Antarctic Peninsula, making these regions very important in the general configuration of cyclones along the SO. Despite underestimating the total number of cyclones along the SO, the HG3 model showed a good ability to represent the main patterns of cyclonic activity around the Antarctic continent, as well as its average behaviour. Knowing the characteristics and the behaviour of extratropical cyclones in such an important area for global climate is essential for understanding their role in weather and future climate resulting from climate change. [ABSTRACT FROM AUTHOR]

Extratropical cyclones (ETCs) are responsible for the majority of cool‐season extreme events in the northeastern United States (NEUS), often leading to high‐impact weather conditions that can have wide‐ranging socioeconomic impacts. Evaluating the ability of climate models to adequately simulate ETC dynamics is essential for improving model performance and increasing confidence in future projections used by stakeholders and policymakers. ETCs are traditionally studied using techniques such as case studies and synoptic typing, however, these approaches can be time‐consuming, require subjective analysis, and do not necessarily identify the coincident large‐scale meteorological patterns (LSMPs). Here, we apply self‐organizing maps (SOMs) as an automated machine‐learning approach to characterize the LSMPs and associated frequency and intensity of discrete ETC events over NEUS. The dominant patterns of geopotential height variability are identified through SOM analysis of five reanalysis products during the last four decades. ETC events are tracked using TempestExtremes and are integrated with SOMs to classify the accumulated cyclone activity (ACA) associated with each pattern. We then evaluate the skill of CMIP6 historical experiments in simulating the LSMPs and ETC events identified in the SOM. Our results identify a robust bias toward more zonal patterns, with models struggling to reproduce the more amplified patterns typically associated with the highest cyclone activity. While model resolution has some impact on simulation credibility, model configuration appears to be more important in LSMP representation. The vast majority of CMIP6 models produce too few ETCs, although model errors are distributed around historical reanalyses when ACA is normalized by storm frequency. Plain Language Summary: Winter storms can have devastating socioeconomic impacts across the United States. Climate models are used to understand and predict these winter storms and how they might change in the future, therefore helping to inform climate policy and emergency services. It is essential that we evaluate these climate models so that their performance and accuracy can be optimized. One way of evaluating climate models is to assess their ability in reproducing the large‐scale atmospheric conditions which occur during extreme events. Here we apply a cyclone tracking algorithm and self‐organizing maps, a machine‐learning approach, to automate the process of identifying key patterns associated with historical winter storm activity. We then use this approach to assess if CMIP6 climate models are able to reproduce the same patterns including the winter storm frequency and intensity. Our results show that, regardless of resolution, most CMIP6 models struggle to simulate the more extreme patterns and tend to favor weaker patterns that are not as conducive to cyclone formation. As a result, most models simulate too few winter storms, however, the error in storm intensity is more varied, with some models producing stronger storms and others producing weaker storms on average. Key Points: Despite resolution, CMIP6 models struggle to reproduce amplified synoptic patterns over the US, with a robust bias toward zonal patternsMost CMIP6 models produce too few cyclones over the northeastern US, while model errors are more varied when considering cyclone intensityIncreased resolution increases the number and intensity of simulated extratropical cyclones but does not improve model representation of synoptic patterns [ABSTRACT FROM AUTHOR]

Climate and extreme hydrometeorological studies are required to reduce risk and vulnerabilities. This study uses different cumulus and microphysics schemes in Weather Research and Forecasting (WRF) model to simulate heavy rainfall events and Cyclone Sidr in Bangladesh, where many extreme events occur. Results show that WRF can capture the cyclone track, intensity, and landfall position. In addition, regionalization and an ensemble method through Bayesian regression model (BRM) are used to improve WRF rainfall simulations. Although regionalization can improve results of the experiments with different schemes, BRM leads to the best performance. To consider uncertainties and evaluate hazards, a probabilistic framework and proper indices based on distributions are used. Spatiotemporal precipitation distributions are used to develop the flash flood index (FFI) to compare the intensity of heavy rainfall events. Results show a large FFI over the central and southeast divisions that indicates the areas prone to the flash flood hazards and high-level risk. We use standardized precipitation index (SPI) in 6- and 12-month time scales based on monthly precipitation of ACCESS-CM2 in 2015–2100 under two scenarios (SSP-126 and 585) to evaluate long-term precipitation changes and drought/flood tendency. In addition, the probability distributions of the precipitation and wind speed are used in reliability analysis of the infrastructure. Target reliability indices determine the proper design rainfall (105 mm d−1) and wind speed (60 m s−1) that leads to a safe design of infrastructure. This study provides an integrated analysis of extreme hydrometeorological events, which is crucial for sustainable adaptation and mitigation plans. [ABSTRACT FROM AUTHOR]

Clouds are one of the most influential components of Earth’s climate system. Specifically, the midlatitude clouds play a vital role in shaping Earth’s albedo. This study investigates the connection between baroclinic activity, which dominates the midlatitude climate, and cloud-albedo and how it relates to Earth’s existing hemispheric albedo symmetry. We show that baroclinic activity and cloud-albedo are highly correlated. By using Lagrangian tracking of cyclones and anticyclones and analyzing their individual cloud properties at different vertical levels, we explain why their cloud-albedo increases monotonically with intensity. We find that while for anticyclones, the relation between strength and cloudiness is mostly linear, for cyclones, in which clouds are more prevalent, the relation saturates with strength. Using the cloud-albedo strength relationships and the climatology of baroclinic activity, we demonstrate that the observed hemispheric difference in cloud-albedo is well explained by the difference in the population of cyclones and anticyclones, which counter-balances the difference in clear-sky albedo. Finally, we discuss the robustness of the hemispheric albedo symmetry in the future climate. Seemingly, the symmetry should break, as the northern hemisphere’s storm track response differs from that of the southern hemisphere due to Arctic amplification. However, we show that the saturation of the cloud response to storm intensity implies that the increase in the skewness of the southern hemisphere storm distribution toward strong storms will decrease future cloud-albedo in the southern hemisphere. This complex response explains how albedo symmetry might persist even with the predicted asymmetric hemispheric change in baroclinicity under climate change. [ABSTRACT FROM AUTHOR]

A better understanding of expected future cyclonic activity, especially in winter in the Mediterranean basin, is essential in developing scientifically based adaptation and mitigation methods to study extreme precipitation and wind anomalies. The aim of this study was to analyze the changes in winter cyclonic activity in the Mediterranean–Black Sea region, as part of the North Atlantic–European sector, at three 15 year periods: the beginning, middle, and end of the 21st century. Our projections were based on an ensemble of seven Coupled Model Intercomparison Project (CMIP), phase 6, models, which showed the best agreement with NCEP/NCAR and ERA5 reanalyses under the intermediate SSP2-4.5 and highest-emission SSP5-8.5 scenarios. The results showed a consistent increase in the frequency of cyclones over Central Europe and the British Isles, which was associated with shifts in cyclone tracks: northward from the western Mediterranean region and southward from the Icelandic Low region. The latter shift led to a decrease in the frequency in the northern Atlantic–European region. At the same time, there was a reduction in the frequency of cyclones over the eastern region of the Mediterranean Sea, consistent with the decrease in cyclogenesis events. Area-averaged cyclone numbers in the western and eastern Mediterranean and Black Sea subregions reduced at the end of the century under the highest-emission scenario, but not constantly. There was a rise in the middle of the 21st century under both scenarios, which may be linked to long-term multidecadal variability or regional features. In general, our study showed that the future winter cyclonic activity in the Mediterranean–Black Sea region will respond unevenly to global climate changes, due to regional and monthly features and long-term quasiperiodic variability. [ABSTRACT FROM AUTHOR]

Tropical cyclone (TC) track characteristics in a changing climate remain uncertain. Here, we investigate the genesis, tracks, and termination of >35,000 synthetic TCs traveling within 250 km of New York City (NYC) from the pre‐industrial era (850–1800 CE) to the modern era (1970–2005 CE) to the future (2080–2100 CE). Under a very high‐emissions scenario (RCP8.5), TCs are more likely to form closer to the United States (U.S.) southeast coast (>15% increase), terminate in the northeastern Atlantic (>6% increase), and move most slowly along the U.S. Atlantic coast (>15% increase) from the pre‐industrial to future. Under our modeled scenarios, TCs are more likely to travel within 100 km of Boston, MA, USA (p = 0.01) and Norfolk, VA, USA (p = 0.05) than within 100 km of NYC in the future. We identify reductions in the time between genesis and the time when TCs come within 100 km of NYC, Boston, or Norfolk, as well as increased duration of TC impacts from individual storms at all three cities in the future. Plain Language Summary: Future economic and human costs of tropical cyclones (TCs; i.e., hurricanes) will depend upon changing storm tracks. To better understand the potential hazard facing coastal communities along the United States (U.S.) Atlantic coast, >35,000 TCs are simulated under pre‐industrial, modern, and very high‐emissions future climates. Over time, TCs tend to travel closer to the cities of Boston and Norfolk than New York City (NYC). As the climate warms, TCs also form closer to the United States southeast coast, reach their slowest forward speed along the U.S. Atlantic coast, and persist farther north and east in the Atlantic basin. The time required for TCs to reach cities, such as Boston, Norfolk, and NYC is reduced, and the typical duration of TC conditions increases at each of these locations. Key Points: Tropical cyclone (TC) characteristics (genesis, tracks, and termination) vary from pre‐industrial to modern to future high‐emissions climatesMore TCs travel within 100 km of Boston and Norfolk than New York City under a high‐emissions futureFrom the pre‐industrial era to 2100 CE (high emissions), US east coast cities see reduced TC warning times and longer duration [ABSTRACT FROM AUTHOR]

For the last few decades, the generalized pattern of tropical cyclones has gone through an unstable system transformation in the global changing climatic scenario. Thus, the broad aim of this research work was to explore the spatio-temporal changing pattern of tropical cyclones in the basin of the Bay of Bengal between 1985 and 2019. Cyclone track information data have been collected from Emergency Events Database (EM-DAT) server and Bangladesh Meteorological Department. The loss and damage statistics has been collected from different published sources. Geographical distributional characteristics such as mean center and standard directional distribution have been explored using the spatial statistical tool of ArcMap. The mean geographic center has been identified near the district of Bhola and Patuakhali. The cyclonic occurrences in the research area are oriented north-west to south-east according to standard directional distribution. Hot spot analysis was used to identify the most affected parts in the study area and found that there are no significant hotspots, but the distribution pattern is rather random. However, there are two minor concentration zones in the study area, one near Barguna and another one near Sandwip coast. SPSS software was also used here to analyze the relationship between cyclonic events and the loss/damage scenarios of the study area. The relationship between cyclonic velocity and damage of life and livelihood showed a strong correlation of .804 with a significance level of 99% (p < .01). Random cyclonic trends and patterns indicate a change in this region's climatic variability over the past 35 years. [ABSTRACT FROM AUTHOR]

Changes in the characteristics of austral winter (June–July–August) synoptic activity in three domains (Africa, Australia and South America) of the extratropical Southern Hemisphere projected with the Regional Climate Model version 4 (RegCM4) are presented. The model is nested in three global climate models (GCMs) from the Coupled Model Intercomparison Project phase 5 (CMIP5) under the Representative Concentration Pathway 8.5. The model grid spacing is 25 km and the simulations cover the period 1970–2100. Synoptic activity is analyzed using both Eulerian and Lagrangian approaches. The Eulerian analysis shows an increase of the synoptic activity south of 40° S in the RegCM4 and GCMs ensembles for the future (2080–2099) compared to the present (1995–2014), but this signal does not necessarily indicate an increase in the cyclone frequency since it includes cyclonic and anticyclonic features. The Lagrangian analysis, however, indicates a decrease in the frequency of cyclones, with a positive tendency towards stronger systems, although the latter is not statistically significant at 95% confidence level. Lifetime, traveled distance and mean speed of the cyclones do not present statistically significant changes in the future climate. On the other hand, a significant increase in both intensity and extension of areas affected by precipitation associated with cyclones is found. As a consequence, there is a statistically significant trend of individual cyclones to produce more rainfall in the future. [ABSTRACT FROM AUTHOR]

Physics-based deterministic tropical cyclone (TC) simulation models play an important role in TC risk analysis, for their unique capability to represent physical principles and incorporate climate change impacts. However, establishing effective deterministic models can be challenging. In this paper, we present a simple yet powerful framework that distills physics-based TC models from historical TC data. By treating TC evolutions as dynamical systems, we adaptively discover the TC track and intensity governing equations from historical TC and environmental data via the Sparse Identification of Nonlinear Dynamics (SINDy) approach. Our proposed TC-SINDy approach is able to identify parsimonious, interpretable yet effective physics-based TC models. Compared to alternative physics-based deterministic models, our models match historical records much better in terms of the intensity evolution, prevailing tracks, and key parameter statistics across the coastlines of the Western North Pacific (WNP) basin and the North Atlantic (NA) basin. Our proposed models were finally coupled with a widely used parametric wind field, and the obtained probabilistic distribution of the surface wind also matched the historical histograms. Overall, the proposed method presents a general data-driven framework for discovering physics-based TC models, enabling reliable effective TC simulations while reserving the capacity to accommodate the changing climate. • Data-driven improvement to physics-based deterministic tropical cyclone (TC) models. • Maintain physical consistency and applicability to climate change. • Sparse machine learning to discover TC governing equations from historical data. • Results outperform existing deterministic models in both WNP and NA basins. [ABSTRACT FROM AUTHOR]

A conventional empirical orthogonal function (EOF) analysis is performed on summertime (May-October) western North Pacific (WNP) tropical cyclone (TC) track density anomalies during 1970-2012. The first leading EOF mode is characterized by a consistent spatial distribution across the WNP basin, which is closely related to an El Niño-Southern Oscillation (ENSO)-like pattern that prevails on both interannual and interdecadal time scales. The second EOF mode is represented by a tripole pattern with consistent changes in westward and recurving tracks but with an opposite change for west-northwestward TC tracks. This second EOF pattern is dominated by consistent global sea surface temperature anomaly (SSTA) patterns on interannual and interdecadal time scales, along with a long-term increasing global temperature trend. ObservedWNP TC tracks have three distinct interdecadal epochs (1970-86, 1987-97, and 1998-2012) based on EOF analyses. The interdecadal change is largely determined by the changing impact of ENSO-like and consistent global SSTA patterns. When global SSTAs are cool (warm) during 1970-86 (1998-2012), these SSTAs exert a dominant impact and generate a tripole track pattern that is similar to the positive (negative) second EOF mode. In contrast, a predominately El Niño-like SSTA pattern during 1987-97 contributed to increasing TC occurrences across most of theWNPduring this 11-yr period. These findings are consistent with long-term trends in TC tracks, with a tripole track pattern observed as global SSTs increase. This study reveals the potential large-scale physical mechanisms driving the changes of WNP TC tracks in association with climate change. [ABSTRACT FROM AUTHOR]

Under global climate change, the frequency of typhoons and their strong wind, heavy rain, and storm surge increase, seriously threatening the life and property of human society. However, traditional tropical cyclone track prediction methods have difficulties in processing large amounts of complex data in terms of prediction efficiency and accuracy. Recently, deep learning methods have shown a potential capability to process complex data efficiently and accurately. In this paper, we propose a novel data-driven approach based on auto-encoder (AE) and gated recurrent unit (GRU) models to forecast tropical cyclone landing locations using the historical tropical cyclone tracks and various meteorological attributes. This approach fuses a data preprocessing layer, an AE layer, and a GRU layer with a customized batch process. The model is trained on a real-world tropical cyclone dataset from the years 1945–2017. Through a comparison with existing forecasting methods, the results verified that our proposed model performed around 15%, 42%, and 56% better than the Numerical Weather Prediction model (NWP) in 24, 48, and 72 h forecasts, and 27%, 13%, 17%, and 17% better than RNN, AE-RNN, GRU, and LSTM, respectively, in 24 h forecasts, using the absolute position error. In addition, a comparison of the meteorological variables indicated that the variable maximum sustained wind speed had the most significant effect on tropical cyclone track prediction. [ABSTRACT FROM AUTHOR]

The North American Regional Climate Change Assessment Program (NARCCAP) represents the next step in investigating the behavior of weather phenomena in current and future climate. Specifically, variations in mid-latitude cyclone tracks attributable to a warming climate have potential socio-economic consequences via the redistribution of precipitation on regional spatial scales. This manuscript assesses the impacts of a warming climate on cyclone tracks in the NARCCAP model suite. Specifically, cyclones are generated from eight 33-year simulations for the twentieth Century (1968–2000) and eight 33-year simulations for the A2 greenhouse scenario (2068–2100). To provide comparison, cyclone tracks are also generated from the Climate Forecast System Reanalysis (CFSR) and ERA Interim (ERA_INT) reanalysis datasets from 1979 to 2016. The results support that the NARCCAP model suite is capable of producing a reasonable cyclone frequency and intensity climatology when compared with the reanalysis datasets. Comparison of the ensemble twentieth Century cyclone (20C) tracks with the ensemble A2 cyclone tracks demonstrate a zonally-oriented poleward shift in cyclone track frequency in response to a warming climate. Intensity differences were regionally oriented, with cyclones being more intense in the A2 relative to the twentieth Century scenarios west of the Appalachians, suggesting cyclones acquire greater latent heat from warmer western Atlantic/Gulf of Mexico moisture sources in A2. A sector analysis revealed a higher total frequency of cyclones in both reanalysis datasets relative to either NARCCAP scenario. For intense cyclones, the NARCCAP model simulations produced more frequent cyclones in the Great Lakes and East Coast sectors. In contrast, reanalysis produced a higher frequency of weak cyclones for all sectors except Atlantic Canada. In addition, NARCCAP simulations were found to be capable of reproducing the broadness of intensity distributions in the reanalysis datasets, likely due to the fine spatial gridding in the NARCCAP models. Sector analysis for frequency and intensity affirmed the ensemble results, with individual model simulations showed a reduction in frequency for all sectors except the Canadian Maritimes for A2 relative to 20C. For intensity, cyclones were once again overall more intense for the upper Midwest/Great Lakes sector for A2 relative to 20C. The results of this research demonstrates the ability for regional climate models to be used to assess changes in synoptic-scale phenomena in a warming climate. Future work will focus on assessing cyclone structure including changes in moisture transport, precipitation, and the low-level jet. [ABSTRACT FROM AUTHOR]

Indian coasts are often influenced by life-threatening water levels caused by tropical cyclones. To have a better long-term planning for the coastal districts due to tropical cyclones, the extreme water levels for different climate change scenarios are important to compute. For this, finite-element mesh is generated with high resolution near the coast to simulate maximum water elevations (MWE) as a response to the nonlinear storm surge interaction at the time of local high tide. Based on the historical cyclone data (1891–2016), the return periods are calculated using the values of pressure drop of the cyclones for each maritime state along the Indian coasts. Synthetic tracks are also generated based on inverse distance weighted method using the inventory of cyclone tracks, ensuring that each coastal district is covered. Experiments are carried out for each return period with possible climate change scenarios by considering wind enhancement of 7% (moderate scenario) and of 11% (extreme scenario) over the normal (present) scenario. The simulations for MWE are performed at every 10 km along the Indian coast. The computed averaged extreme water levels of about 10 m are simulated in the northernmost part of the east coast and Gulf of Khambhat in the west coast of India. An average increase of about 20% and 30% in MWE is estimated in the moderate and extreme climate change scenarios, respectively. The southern Indian peninsular region is seen significantly affected from the extreme scenario. [ABSTRACT FROM AUTHOR]

Vb cyclones are major drivers of extreme precipitation and floods in the study area of hydrological Bavaria (Germany). When assessing climate change impacts on Vb cyclones, internal variability of the climate system is an important underlying uncertainty. Here, we employ a 50‐member single‐model initial‐condition large ensemble of a regional climate model to study climate variability and forced change on Vb cyclones. An artificial neural network detects cutoff lows over central Europe, which are associated with extreme precipitation Vb cyclones. Thus, machine learning filters the large ensemble prior to cyclone tracking. Our results show a striking change in Vb seasonality with a strong decrease of Vb cyclones in summer (−52%) and a large increase in spring (+73%) under the Representative Concentration Pathway 8.5. This change exceeds the noise of internal variability and leads to a peak shift from summer to spring. Additionally, we show significant increases in the daily precipitation intensity during Vb cyclones in all seasons. Plain Language Summary: Bavaria, a state in the southeast of Germany, has been hit by several devastating floods in recent decades triggered by a storm type called Vb. For future flood risk in Bavaria it is crucial to understand how climate change affects Vb storms. This study uses high‐resolution climate simulations over Europe to study changes in the frequency of Vb storms, their seasonal occurrence, and their rainfall intensity under a high greenhouse gas concentration scenario. However, Vb storms are rare events and a single simulation may not provide enough events to distinguish between climate change and random, natural variations. Therefore, we employ a large database of 50 climate simulations with the same settings and greenhouse gas concentration scenario, but slightly different starting conditions, in order to robustly estimate climate change effects on Vb storms. The drawback of using 50 simulations is the high amount of data. Therefore, we apply machine learning for pattern recognition to detect the low‐pressure systems related to extreme precipitation Vb storms in the climate simulations. Our results show that climate change considerably affects the seasonal occurrence of Vb storms with a shift from summer to spring. Furthermore, the daily rainfall intensity in Bavaria increases during Vb storms significantly with climate change. Key Points: Machine learning is employed to filter a single‐model ensemble for cutoff low related Vb cyclones with high accuracyThe seasonality of Vb cyclones changes considerably under the RCP8.5 scenario with a peak shift from summer to springThe daily precipitation intensity of Vb cyclones significantly increases in all seasons [ABSTRACT FROM AUTHOR]

A recently validated algorithm for detecting and tracking tropical cyclones (TCs) in coarse resolution climate models was applied to a selected group of 12 models from the Coupled Model Intercomparison Project (CMIP5) to assess potential changes in TC track characteristics in the Southern Hemisphere (SH) due to greenhouse warming. Current-climate simulations over the period 1970–2000 are first evaluated against observations using measures of TC genesis location and frequency, as well as track trajectory and lifetime in seven objectively defined genesis regions. The 12-model (12-M) ensemble showed substantial skill in reproducing a realistic TC climatology over the evaluation period. To address potential biases associated with model interdependency, analyses were repeated with an ensemble of five independent models (5-M). Results from both the 12-M and 5-M ensembles were very similar, instilling confidence in the models for climate projections if the current TC-climate relationship is to remain stationary. Projected changes in TC track density between the current- and future-climate (2070–2100) simulations under the Representatives Concentration 8.5 Pathways (RCP8.5) are also assessed. Overall, projection results showed a substantial decrease (~ 1–3 per decade) in track density over most parts of the SH by the end of the twenty-first century. This decrease is attributed to a significant reduction in TC numbers (~ 15–42%) consistent with changes in large-scale environmental parameters such as relative vorticity, environmental vertical wind shear and relative humidity. This study may assist with adaption pathways and implications for regional-scale climate change for vulnerable regions in the SH. [ABSTRACT FROM AUTHOR]

The multi-decadal variations of wintertime extra-tropical cyclones during the last century are studied using a vorticity-based tracking algorithm applied to the long-term ERA-20C reanalysis from ECMWF. The variability of moderate-to-deep extra-tropical winter cyclones in ERA-20C show three distinct periods. Two at the beginning and at the end of the century (1900-1935 and 1980-2010) present weak or no significant trends in the Northern Hemisphere as a whole and only some regional trends. The period in between (1935-1980) is marked by a significant increase in Northern Hemisphere moderate-to-deep cyclones frequency. During the latter period, polar regions underwent a significant cooling over the whole troposphere that increased and shifted poleward the mid-latitude meridional temperature gradient and the baroclinicity. This is linked to positive-to-negative shifts of the PDO between 1935 and 1957 and of the AMO between 1957 and 1980 which mainly reinforced the storm-track eddy generation in the North Pacific and North Atlantic regions respectively, as seen from baroclinic conversion from mean to eddy potential energy. As a result, both the North Pacific and North Atlantic extra-tropical storms increase in frequency during the two subperiods (1935-1957 and 1957-1980), together with other storm-track quantities such as the high-frequency eddy kinetic energy. In contrast, the first and third periods are characterized by a warming of the polar temperatures. However, as the stronger warming is confined to the lower troposphere, the baroclinicity do not uniformly increase in the whole troposphere. This may explain why the recent rapid increase in polar temperatures has not affected the behaviour of extratropical cyclones very much. Finally, the large magnitude of the positive trend found in moderate-to-deep cyclone frequency during the second period is still questioned as the period is marked by an important increase in the number of assimilated observations. However, the dynamical link between changes in cyclone frequency, changes in large-scale baroclinicity and ocean decadal variability found in the present study makes us confident on the sign of the detected cyclone trend. [ABSTRACT FROM AUTHOR]

The IBTrACS global best track data set endorsed by the World Meteorological Organization provides a valuable global record of tropical cyclone genesis, track and intensity, and spans 1842 to the present. The record is significantly more robust from the late 1970s onwards, as it is supported by satellite imagery. These records indicate that the first tropical cyclone in the South Indian Ocean to intensify to CAT5 status did so in 1994. This date is significantly later than the first CAT5 storms recorded in the IBTrACS database for the Atlantic Ocean (1924) and the North Pacific (1951) recorded from ship records, and half a decade later than those of the North Indian Ocean (1989) and South Pacific (1988), captured from satellite imagery. Following this late emergence, in the period 1990-2000, eight CAT5 tropical cyclones were recorded for the South Indian Ocean. A further four have been recorded for the period 2010-2015. This recent emergence of tropical cyclones attaining category five intensity in the South Indian Ocean is of significance for the forecasting of tropical cyclone landfall and the anticipation of storm damage for the developing economies that characterise the region. Although an increase in tropical cyclone intensity is frequently projected under global climate change scenarios, the dynamics for the South Indian Ocean have remained poorly understood. Notable are early results indicating an increased frequency and poleward migration of these CAT5 storms, concurrent with a poleward migration in the position of the 26.5 °C, 28 °C and 29 °C sea surface temperature isotherms in the South Indian Ocean. [ABSTRACT FROM AUTHOR]

Suursaar, Ü.; Sepp, M.; Post, P., and Mäll, M., 2018. An inventory of historic storms and cyclone tracks that have caused met-ocean and coastal risks in the eastern Baltic Sea. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 531–535. Coconut Creek (Florida), ISSN 0749-0208. Located on relatively high latitudes, the eastern section of the practically tideless Baltic Sea is frequently battered by extratropical cyclones that have caused storm surges of up to 421 cm (at St. Petersburg, Russia), and 275 cm at Pärnu (Estonia). The analysis of storms includes the events that have yielded the highest sea levels at Pärnu and Narva-Jõesuu tide gauges on an annual basis from 1950–2016. For each event, corresponding cyclone tracks have been extracted from the cyclone database, which is based on NCEP/NCAR reanalysis of air pressure fields in a six–hour interval. Track matches for 109 surge cases were found, including 43 for Pärnu, 42 for Narva-Jõesuu, and 24 common for both locations. Although cyclones from several distinct directions can approach Estonia and the Gulf of Finland area, the most serious meteorological, oceanographic (met-ocean), as well as coastal impacts were connected to westerly approaching deep cyclones with tracks crossing Scandinavia and Southern Finland. A suitable course for the cyclone and a pre-elevated (by up to 70 cm) average Baltic Sea level as a result of preceding series of cyclones are among the important factors which may result in destructive event. [ABSTRACT FROM AUTHOR]

Comprehensive models of climate change projections have shown that the latitudinal band of extratropical storms will likely shift poleward under global warming. Here we study this poleward shift from a Lagrangian storm perspective, through simulations with an idealized general circulation model. By employing a feature tracking technique to identify the storms, we demonstrate that the poleward motion of individual cyclones increases with increasing global mean temperature. A potential vorticity tendency analysis of the cyclone composites highlights two leading mechanisms responsible for enhanced poleward motion: nonlinear horizontal advection and diabatic heating associated with latent heat release. Our results imply that for a 4 K rise in the global mean surface temperature, the mean poleward displacement of cyclones increases by about 0.85° of latitude, and this occurs in addition to a poleward shift of about 0.6° in their mean genesis latitude. Changes in cyclone tracks may have a significant impact on midlatitude climate, especially in localized storm tracks such as the Atlantic and Pacific storm tracks, which may exhibit a more poleward deflected shape. [ABSTRACT FROM AUTHOR]

Medicanes or 'Mediterranean hurricanes' represent a rare and physically unique type of Mediterranean mesoscale cyclone. There are similarities with tropical cyclones with regard to their development (based on the thermodynamical disequilibrium between the warm sea and the overlying troposphere) and their kinematic and thermodynamical properties (medicanes are intense vortices with a warm core and even a cloud-free eye). Although medicanes are smaller and their wind speeds are lower than in tropical cyclones, the severity of their winds can cause substantial damage to islands and coastal areas. Concern about how human-induced climate change will affect extreme events is increasing. This includes the future impacts on medicanes due to the warming of the Mediterranean waters and the projected changes in regional atmospheric circulation. However, most global climate models do not have high enough spatial resolution to adequately represent small features such as medicanes. In this study, a cyclone tracking algorithm is applied to high resolution global climate model data with a horizontal grid resolution of approximately 25 km over the Mediterranean region. After a validation of the climatology of general Mediterranean mesoscale cyclones, changes in medicanes are determined using climate model experiments with present and future forcing. The magnitude of the changes in the winds, frequency and location of medicanes is assessed. While no significant changes in the total number of Mediterranean mesoscale cyclones are found, medicanes tend to decrease in number but increase in intensity. The model simulation suggests that medicanes tend to form more frequently in the Gulf of Lion-Genoa and South of Sicily. [ABSTRACT FROM AUTHOR]

ABSTRACT The statistical law that governs the drift velocity of tropical cyclones in the Northwest Pacific Ocean is investigated. The investigation is based on data published by China Meteorological Administration for historical tracks of 2146 cyclone events that occurred during 1949-2012. Empirical formulae are obtained to relate the magnitude, the direction, the meridional and zonal components of the averaged cyclone drift velocity with latitude. As the latitude effect is excluded, it is found that the cyclone drift velocity is governed by simple statistical laws, i.e. the magnitude and direction of the deviated drift velocity approximately satisfy a gamma distribution and a symmetric bimodal distribution, respectively, while the meridional and zonal components of the deviated drift velocity satisfy the same type of symmetric probability distribution represented by the hyperbolic secant function but with different deviations. The results obtained are potentially applicable to the enhancement of current tropical cyclone track forecasting techniques. They are also useful in risk management over the coastal areas where tropical cyclones may cause serious damages. [ABSTRACT FROM AUTHOR]

ABSTRACT This study is the first one to objectively identify 'parent-daughter' relationships between cyclones and to apply it to Mediterranean cyclones ( MCs). The methodology includes cyclone detection, tracking and mapping the area of influence of a cyclone; here daughter cyclones are expected to be found. Cyclone detection and tracking is based on standard algorithms, which were modified to cope with irregularities in intensity and trajectory shapes of MCs. We have developed our own algorithm for mapping cyclones' area of influence. Application of our methodology to the ERA-Interim data for 33 mid-winter seasons identified parents for 97.5% of the MCs. While previous studies claimed that most MC parents are situated over Europe, this study found the majority of MCs' parents (56%) positioned over the Mediterranean itself. This disagreement stems from the fine spatial resolution used here (0.75° × 0.75°), which enabled uncovering smaller cyclones than noticed previously, thus revealing earlier stages of cyclogenesis. The parenthood analysis identified two main types of cyclogenesis within the Mediterranean; one driven by parent MCs, the other driven by Atlantic or European cyclones. The latter is manifested either by directly generating a new MC or by intensifying existing weak MCs. Cyclone generations were explored through backtracking chains of parents down to the ninth generation, the longest chain found. The results indicate that the primary source of MCs is the Atlantic (2/3 of the MCs) and then Equatorial Africa and the Red Sea (1/3). The results also imply that although native MCs owe their existence to the Atlantic-European cyclone track, regional cyclogenetic effects, such as topographic, thermal and baroclinic, are even more influential. The innovative methodology for objective identification of cyclone parents can be used to characterize cyclogenetic scenarios, in particular away from main storm tracks and over complex terrain. [ABSTRACT FROM AUTHOR]

In recent years, tropical cyclones on the Pacific Northwest have decreased. We cannot infer that tropical cyclones impact China have reduced, because the Pacific Northwest is not homogeneous, and the variation characteristics of tropical cyclones in different sea areas are not clear. This paper uses gray relational density clustering algorithm to cluster tropical cyclone data sets between 1949 and 2008, according to the generated position of tropical cyclones, generated density and the possibility of landing. The Pacific Northwest is divided into different sea areas. Then, we analyze the risk of tropical cyclones generated in these sea areas. The results show that the probability of tropical cyclones landing generated in some sea areas is very high, reached 74 %, but the probability of tropical cyclones landing generated in other sea areas is only 2 %. Tropical cyclones generated in some sea areas are more likely to develop into typhoons, strong typhoons and so on, but the intensity of tropical cyclones generated in other sea areas is lower, there is little risk for China. Finally, according to the climate change stage trends, we divide the period 1949-2008 into three stages and analyze the tropical cyclone risk of each sea areas. [ABSTRACT FROM AUTHOR]

Projections of storm-track changes over the continental United States and southern Canada made by 23 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) have been compared to changes projected by 11 models from phase 3 of CMIP (CMIP3). Overall, under representative concentration pathway 8.5 (RCP8.5) forcing, CMIP5 models project much more significant decreases in North American storm-track activity than CMIP3 models under the Special Report on Emission Scenarios (SRES) A2 scenario, with the largest decrease in summer and the smallest decrease in spring. The decrease is found both in temporal variance and cyclone statistics, with the frequency of strong cyclones projected to decrease by 15.9%, 6.6%, 32.6%, and 16.9% for winter, spring, summer, and fall, respectively. There is a strong consensus among the 23 models regarding the sign of the projected change, with less than 20% of the models projecting changes in the opposite sign in any of the storm-track parameters examined. Nevertheless, there are also significant model-to-model differences in the magnitude of the projected changes. Projected changes in mean flow baroclinicity have also been examined. Model-to-model differences in the projected storm-track change are found to correlate significantly with model-to-model differences in the projected change in a locally defined mean available potential energy (MAPE) across the ensemble of 34 CMIP5 and CMIP3 models, suggesting that the differences in the projected change in local MAPE can partly account for not only the model-to-model differences but also the differences between CMIP5 and CMIP3 projections. Examination of projected precipitation change suggests that models projecting larger decrease in North American storm-track activity also project a farther northward intrusion of the decrease in subtropical precipitation. [ABSTRACT FROM AUTHOR]

Earth's storm tracks are instrumental for transporting heat, momentum, and moisture and thus strongly influence the surface climate. Climate models, supported by a growing body of observational data, have demonstrated that storm tracks shift poleward as the climate warms. But the dynamical mechanisms responsible for this shift remain unclear. To isolate what portion of the storm track shift may be accounted for by large-scale dry dynamics alone, disregarding the latent heat released in phase changes of water, this study investigates the storm track shift under various kinds of climate change in an idealized dry general circulation model (GCM) with an adjustable but constant convective stability. It is found that increasing the mean surface temperature or the convective stability leads to poleward shifts of storm tracks, even if the convective stability is increased only in a narrow band around the equator. Under warming and convective stability changes roughly corresponding to a doubling of CO2 concentrations from a present-day Earthlike climate, storm tracks shift about 0.8° poleward, somewhat less than but in qualitative agreement with studies using moist GCMs. About 63% (0.5°) of the poleward shift is shown to be caused by tropical convective stability variations. This demonstrates that tropical processes alone (the increased dry static stability of a warmer moist adiabat) can account for part of the poleward shift of storm tracks under global warming. This poleward shift generally occurs in tandem with a poleward expansion of the Hadley circulation; however, the Hadley circulation expansion does not always parallel the storm track shift. [ABSTRACT FROM AUTHOR]

A method to estimate objectively the surface wind fields associated with tropical cyclones using only data from multiple satellite platforms and satellite-based wind retrieval techniques is described. The analyses are computed on a polar grid using a variational data-fitting method that allows for the application of variable data weights to input data. The combination of gross quality control and the weighted variational analysis also produces wind estimates that have generally smaller errors than do the raw input data. The resulting surface winds compare well to the NOAA Hurricane Research Division H**Wind aircraft reconnaissance-based surface wind analyses, and operationally important wind radii estimated from these wind fields are shown to be generally more accurate than those based on climatological data. Most important, the analysis system produces global tropical cyclone surface wind analyses and related products every 6 h-without aircraft reconnaissance data. Also, the analysis and products are available in time for consideration by forecasters at the Joint Typhoon Warning Center, the Central Pacific Hurricane Center, and the National Hurricane Center in preparing their forecasts and advisories. This Multiplatform Tropical Cyclone Surface Wind Analysis (MTCSWA) product is slated to become an operationally supported product at the National Environmental Satellite Data and Information Service (NESDIS). The input data, analysis method, products, and verification statistics associated with the MTCSWA are discussed within. [ABSTRACT FROM AUTHOR]

The wave climate along the Indian coast is mostly influenced by the dynamics of the Indian Ocean in the south, Bay of Bengal (BoB) in the east and the Arabian Sea in the west. The BoB is the region of frequent cyclonic occurrence. In the futuristic climate change scenario, it is found that the intensity of cyclones in the BoB is getting increased (Reddy et al., 2021). The cyclonic wind induced wave climate could make a substantial impact on coastal infrastructures. The severe cyclonic storm, Vardah which made landfall in 2016 has been chosen as a test case for the present study. The behaviour of Vardah cyclone under different Representative Concentration Pathway (RCP) scenarios of RC4.5, RCP6.0, RCP8.5 in the Near-Future (2035) and Far-Future (2075) categories has been considered. The wave climate has been simulated using the WAM (The WAMDI group, 1988). A coarse model covering the entire Indian Ocean with a grid resolution of 0.25° × 0.25° and a nested BoB domain with a finer grid of 2.5 km × 2.5 km have been setup. The surface wind above 10 m height which is obtained from the WRF model, is forced into the WAM to predict the wave climate. The variation in the wave characteristics has been analysed and discussed in detail with a focus on the future climate scenarios. The significant wave height (H s) obtained for the far-future category of RCP6.0 and RCP8.5 is found to be higher of the order of 6–8%. However, RCP4.5 has an insignificant influence on the wave climate. • The projection of cyclone Vardah for the Far-Future categories of RCP6.0 and RCP8.5 shows an increase of 6–8% in the significant wave height than the present scenario. • RCP4.5 has insignificant influence on the wave climate. • The maximum H s occurs to the north of the cyclone track. • After landfall, the high energy spreads northward of the coast. [ABSTRACT FROM AUTHOR]

Cyclone activity and life cycle are analysed in the coupled GCMs ECHAM5/OM and ECHAM4/OPYC3. First, the results for the present climate (1978–1999) are compared with ERA-40 and NCEP/NCAR reanalyses, showing a drastic improvement in the representation of cyclone activity in ECHAM5/OM compared to ECHAM4/OPYC3. The total number of cyclones, cyclone intensity, propagation velocity and deepening rates are found to be much more realistic in ECHAM5/OM relative to ECHAM4/OPYC3. Then, changes in extra tropical cyclone characteristics are compared between present day climate and future climate under the emission-scenario A1B using ECHAM5/OM. This comparison is performed using the 20-year time slices 1978–1999, 2070–2090 and 2170–2190, which were considered to be representative for the various climate conditions. The total number of cyclones does not undergo significant changes in a warmer climate. However, regional changes in cyclone numbers and frequencies are evident. One example is the Mediterranean region where the number of cyclones in summer increases almost by factor 2. Some noticeable changes are also found in cyclone life cycle characteristics (deepening rate and propagation velocity). Cyclones in the future climate scenario tend to move slower and their deepening rate becomes stronger, while cyclone intensity does not undergo significant change in a warmer climate. Generally, our results do not support the hypothesis of enhanced storminess under future climate conditions. [ABSTRACT FROM AUTHOR]

Cyclone Larry (category 4) was the most severe cyclone to impact on the Wet Tropics bioregion since the devastating 1918 Innisfail cyclone. Based on an analysis of earlier cyclones impacting on this region over the period 1856–2006, it was determined that Larry was a ‘1 in 50 year’ event. This paper provides an overview of the landscape-scale impacts of Larry on the forest ecosystems of the Wet Tropics region, based on low-level helicopter surveys 2 weeks after the event. Cyclone Larry has been described as a ‘midget’ cyclone. Severe forest damage only extended about 30 km from the central track of the cyclone while moderate to severe damage extended some 50 km. Moderate to slight canopy disturbance was rarely identified more than 75 km from the centre of the cyclone's track. Beyond 75 km, forest damage was restricted to exposed areas of elevated terrain and in places exposed to strong lee (gravity) waves from the west. The ecological role of cyclones as important disturbance agents affecting the structure and function of forest ecosystems in the region is discussed, followed by an evaluation of likely effects of climate change on cyclone frequency and intensity. [ABSTRACT FROM AUTHOR]

Objectively derived resolution-dependent criteria are defined for the detection of tropical cyclones in model simulations and observationally based analyses. These criteria are derived from the wind profiles of observed tropical cyclones, averaged at various resolutions. Both an analytical wind profile model and two-dimensional observed wind analyses are used. The results show that the threshold wind speed of an observed tropical cyclone varies roughly linearly with resolution. The criteria derived here are compared to the numerous different criteria previously employed in climate model simulations. The resulting method provides a simple means of comparing climate model simulations and reanalyses. [ABSTRACT FROM AUTHOR]

In this study, a cyclone detection/tracking algorithm was used to identify cyclones from two gridded 6-hourly mean sea level pressure datasets: the 40-yr ECMWF Re-Analysis (ERA-40) and the NCEP–NCAR reanalysis (NNR) for 1958–2001. The cyclone activity climatology and changes inferred from the two reanalyses are intercompared. The cyclone climatologies and trends are found to be in reasonably good agreement with each other over northern Europe and eastern North America, while ERA-40 shows systematically stronger cyclone activity over the boreal extratropical oceans than does NNR. However, significant differences between ERA-40 and NNR are seen over the austral extratropics. In particular, ERA-40 shows significantly greater strong-cyclone activity and less weak-cyclone activity over all oceanic areas south of 40°S in all seasons, while it shows significantly stronger cyclone activity over most areas of the austral subtropics in the warm seasons. The most notable historical trends in cyclone activity are found to be associated with strong-cyclone activity. Over the boreal extratropics, both ERA-40 and NNR show a significant increasing trend in January–March (JFM) strong-cyclone activity over the high-latitude North Atlantic and over the midlatitude North Pacific, with a significant decreasing trend over the midlatitude North Atlantic and a small increasing trend over northern Europe. The JFM changes over the North Atlantic are associated with the mean position of the storm track shifting about 181 km northward. Importantly, there is no evidence of abrupt changes identified for the boreal extratropics, although previous studies have suggested that the upward trend found in the NNR data could be biased high. However, there exist a few abrupt changes over the austral extratropics, which appear to be attributable to the increasing availability of observations assimilated in the reanalyses. After diminishing the effects of these abrupt changes, strong-cyclone activity over the austral circumpolar oceanic region is identified to have an increasing trend in October–December (OND) and July–September (JAS), with a decreasing trend over the 40°–60°S zone in JAS. [ABSTRACT FROM AUTHOR]

A detailed view of Southern Hemisphere storm tracks is obtained based on the application of filtered variance and modern feature-tracking techniques to a wide range of 45-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) data. It has been checked that the conclusions drawn in this study are valid even if data from only the satellite era are used. The emphasis of the paper is on the winter season, but results for the four seasons are also discussed. Both upper- and lower-tropospheric fields are used. The tracking analysis focuses on systems that last longer than 2 days and are mobile (move more than 1000 km). Many of the results support previous ideas about the storm tracks, but some new insights are also obtained. In the summer there is a rather circular, strong, deep high-latitude storm track. In winter the high-latitude storm track is more asymmetric with a spiral from the Atlantic and Indian Oceans in toward Antarctica and a subtropical jet–related lower-latitude storm track over the Pacific, again tending to spiral poleward. At all times of the year, maximum storm activity in the higher-latitude storm track is in the Atlantic and Indian Ocean regions. In the winter upper troposphere, the relative importance of, and interplay between, the subtropical and subpolar storm tracks is discussed. The genesis, lysis, and growth rate of lower-tropospheric winter cyclones together lead to a vivid picture of their behavior that is summarized as a set of overlapping plates, each composed of cyclone life cycles. Systems in each plate appear to feed the genesis in the next plate through downstream development in the upper-troposphere spiral storm track. In the lee of the Andes in South America, there is cyclogenesis associated with the subtropical jet and also, poleward of this, cyclogenesis largely associated with system decay on the upslope and regeneration on the downslope. The genesis and lysis of cyclones and anticyclones have a definite spatial relationship with each other and with the Andes. At 500 hPa, their relative longitudinal positions are consistent with vortex-stretching ideas for simple flow over a large-scale mountain. Cyclonic systems near Antarctica have generally spiraled in from lower latitudes. However, cyclogenesis associated with mobile cyclones occurs around the Antarctic coast with an interesting genesis maximum over the sea ice near 150°E. The South Pacific storm track emerges clearly from the tracking as a coherent deep feature spiraling from Australia to southern South America. A feature of the summer season is the genesis of eastward-moving cyclonic systems near the tropic of Capricorn off Brazil, in the central Pacific and, to a lesser extent, off Madagascar, followed by movement along the southwest flanks of the subtropical anticyclones and contribution to the “convergence zone” cloud bands seen in these regions. [ABSTRACT FROM AUTHOR]

In this study, we evaluate the effect of climate change on explosive cyclones (ECs) using mega-ensemble projection data (d4PDF), which has 50 members of 60-years present climate experiments and 90 members of 60-years +4K future climate experiments. Subsequently, we evaluate the future change of coastal hazards due to high-swell waves, called Yorimawari waves, caused by strong and stagnant ECs around Japan. The number of ECs passing over the Sea of Japan increased, but the number passing over the Pacific Ocean decreased under future climate. The annual average of the minimum central pressure (MCP) of the EC did not change, but the 10- to 60-year probability value increased for the future. Wave simulations with the d4PDF wind conditions for ECs with an MCP of the 10-year probability value that stagnated for over 24 h around Hokkaido, were conducted. The ensemble average of the maximum significant wave height increased from 0.5 to 1.0 m along the Sea of Japan. The significant wave period increased by over 0.25 s. However, the standard deviation was as large as the wave height of future change. The wave height of high waves depends on the characteristics of the EC. • Future change of explosive cyclone is investigated from mega-ensemble projection data. • Track of explosive cyclone shifted to the north in +4K future climate. • 10- to 60-year probability value of central pressure increased for the future. [ABSTRACT FROM AUTHOR]

The article offers information concerning the reliability of global tropical cyclone databases in detecting the trends of tropical cyclone intensity, particularly the frequency of extreme tropical cyclones. It has been stated that recent studies discover a large, sudden increased in the tropical cyclone intensities which are linked to warming sea surface temperatures, possibly associated with global warming. Tropical cyclone intensity is formed through the maximum sustained surface wind that occurs in the eyewall of a tropical cyclone over an area of a just a few dozen square kilometers. Moreover, Dvorak technique is a satellite-based pattern recognition scheme used to estimate globally the tropical cyclone intensity.

Arctic climate change is strongly influenced by changed surface conditions like declining sea ice cover and rising sea surface temperatures. These changes are not confined to the Arctic, but interact with the global climate system. We performed time-slice model experiments with changed sea ice and sea surface temperature conditions. These experiments are analyzed in relation to reanalysis data aiming at a separation between the effects of sea ice and sea surface temperature and focusing on linkages between the Arctic and mid-latitudes in winter. The diagnostics involve cyclone tracking, blocking analysis and vertical wave propagation analysis. This framework allows to further characterize the relevance of tropospheric and stratospheric pathways. Results show that reanalysis results are best reproduced with the combined effect of sea ice and sea surface temperatures. Anyway, the reproduction is far from perfect and additional insights on further experiments and model improvements will be given considering the boundary layer as well as the stratosphere. [ABSTRACT FROM AUTHOR]

Extreme precipitation and floods, triggered by large scale atmospheric drivers, are of high societal importance. Scientific knowledge on how the dynamics of such large-scale drivers will be affected by climate change is still limited, especially due to the uncertainty of internal variability. An improved understanding of the role of internal variability can be supported by the analysis of large initial-conditions ensembles of a single climate model.The ClimEx project (Climate Change and Extreme Events, www.climex-project.org) has developed an initial-conditions 50-member ensemble (CRCM5-LE) at 12-km resolution using the Canadian Regional Climate Model (CRCM5) driven by the CanESM2 global climate model with the Representative Concentration Pathway (RCP) 8.5 as external forcing. This dataset enables the assessment of climate change effects on meteorological and hydrological extreme events over the European domain, while considering internal climate variability as an important underlying uncertainty.We analyze the synoptic situation of a cut-off low over Central Europe and its concomitant cyclone of type Vb – a rare cyclone type that has triggered several devastating floods in the study area of Bavaria. An artificial neural network approach is employed to address the major challenges involved in evaluating the vast amount of CRCM5-LE-data for the dynamics of Vb-cyclones. Prior to cyclone tracking, the artificial neural network filters the CRCM5-LE specifically and efficiently for the synoptic pattern of a cut-off low over central Europe, which is associated with the development of strong Vb-cyclones.Our results demonstrate the performance of the procedure and its capacity to detect historic Vb-events in a reanalysis-driven model run. Using the large ensemble, the particular relevance of considering internal variability in climate change impact assessment is highlighted by presenting the ratio between climate change signal and internal noise. Finally, the long-term effects of climate change are illustrated in terms of higher frequencies, shifting seasonality and increasing precipitation rates related to Vb-cyclones. AcknowledgementFunding of the ClimEx project by the Bavarian State Ministry for the Environment and Consumer Protection is gratefully acknowledged. [ABSTRACT FROM AUTHOR]

The article provides an analysis on the memory of a tropical cyclone (TC) affected by climate change in the Northern Hemisphere between 1985 to 2002. Examination of atmospheric and oceanic evolution quantifies the memory of TC 20 days before its arrival and 60 days after the passage. However, prior works argued that TCs serves as one of the balancing mechanisms in redistributing excess tropical heat poleward within the atmosphere by convection, eddy heat transport, and upwelling in the ocean. The author concluded the result of the research as combined to the arguments on tracking TCs stimulates the global climate to accurately stimulates the intensity and track of TCs within models. Several graphs showing the measurement of the memory of TC are also presented. INSET: ONE VERY RAINY DAY.

The article reports that researchers from the Meteorological Research Institute in Tsukuba, Japan have simulated tropical-cyclone patterns and found that the number of tropical cyclones into the Hawaiian Islands during 2075-2099 will be about double than in 1979-2003 due to climate change.