Hasil untuk "Meteorology. Climatology"

Ganga Shreedhar, Joshua Hinton, Laura Thomas-Walters

Abstract Collective climate action may be vital for shaping societal-level change and alleviating climate anxiety. We examined how climate movements can utilise social media to promote local public engagement, as the language and social imagery used by climate activists could affect public willingness to engage. Collaborating with Extinction Rebellion (XR)-United Kingdom (UK), we conducted a randomised controlled field trial with over 350,000 Facebook users in three cities: Birmingham, Oxford, and Cardiff. We evaluated the impact of messaging and imagery on engagement with information about climate events by comparing willingness to click links to attend local climate talks based on requests versus exhortations, alongside protest, impact, and diversity images. We found that exhortations were more effective than requests, especially when paired with climate impact imagery. Message effectiveness varied across cities, being the strongest in Birmingham and weakest in Cardiff, indicating the importance of tailoring strategies to local contexts.

Vito Telesca, Gianfranco Castronuovo, Gianfranco Favia et al.

ABSTRACT The COVID‐19 pandemic has generated significant global impacts on health and society, imposing a comprehensive analysis of its influencing factors, including weather variables. This study investigates the interaction between meteorological conditions and the spread of COVID‐19 in three Italian regions: Lombardia, Emilia‐Romagna, and Puglia. Effects of weather variables, such as air temperature, relative humidity, dew point, solar radiation, wind speed, and barometric pressure, are explored in the incidence of disease. Observed meteorological and health data are taken from various sources, such as the citizen‐science Meteonetwork Association and the National Department of Civil Protection, respectively, and they are analyzed with statistical methods and machine learning algorithms. The study emphasizes the necessity of carefully considering key meteorological quantities as primary drivers in illness diffusion and prevention strategies, offering valuable insights to address challenges to the pandemic and ensure the safety of global communities. The results reveal a significant correlation between specific atmospheric variables and the spread of COVID‐19, with dew point temperature as the most influential parameter at low air temperature values.

Andreas Lehmann, Piia Post

The winter climate of northern Europe is influenced by the variability of large-scale pressure systems that control the airflow over the region, namely NAO+, NAO-, SCAND, and the Atlantic Ridge. The positive phase of the North Atlantic Oscillation (NAO+) is associated with westerly winds that bring mild and moist air to the Baltic Sea region, while the negative phase (NAO-) is characterised by easterly winds and the advection of cold, dry air. Both phases are linked to shifts in the centres of action and changes in storm track pathways. The third mode, the East Atlantic or Atlantic Ridge pattern, is structurally similar to the NAO but features a north–south dipole with anomaly centres shifted southward. This pattern reflects variations in the north–south positioning of the NAO. The fourth dominant mode, the Scandinavian, Eurasian, or Blocking pattern, influences the Baltic region by generating high-pressure conditions over Scandinavia. These conditions are typically accompanied by dry, cold weather and weak easterly winds. Severe winters in the Baltic, characterised by extensive ice cover, are often associated not only with NAO- conditions but also with blocking situations.This study examines the relationship between changes or shifts in large-scale atmospheric winter conditions and their impact on regional-scale variability over the Baltic Sea area from 1950 to 2022. The primary objective is to identify the dominant large-scale atmospheric circulation patterns, specifically North Atlantic winter climate regimes, on monthly and seasonal timescales that drive the development of regional atmospheric weather types over the Baltic Sea area. These weather types, in turn, are linked to different Baltic Sea circulation patterns and the exchange of water masses with the North Sea.Using cluster analysis, we identify the prevailing large-scale atmospheric patterns that directly affect regional climate variability in the Baltic Sea area, as determined through weather type classification. In the next step, typical barotropic circulation patterns in the Baltic Sea are associated with dominant regional weather types. This approach enables the downscaling of large-scale atmospheric circulation variability to barotropic circulation variability within the Baltic Sea basin.

Colin M. Zarzycki, Paul A. Ullrich, Kevin A. Reed

Hans Van de Vyver

Widespread extreme climate events cause many fatalities, economic losses and have a huge impact on critical infrastructure. It is therefore of utmost importance to estimate the frequency and associated consequences of spatially concurrent extremes. Impact studies of climate extremes are severely hampered by the lack of extreme observations, and even large ensembles of climate simulations often do not include enough extreme or record-breaking climate events for robust analysis. On the other hand, weather generators specifically fitted to extreme observations can quickly generate many physically or statistically plausible extreme events, even with intensities that have never been observed before. We propose a Fourier-based algorithm for generating high-resolution synthetic datasets of rare events, using essential concepts of classical modelling of (spatial) extremes. Here, the key feature is that the stochastically generated datasets have the same spatial dependence as the observed extreme events. Using high-resolution gridded precipitation and temperature datasets, we show that the new algorithm produces realistic spatial patterns, and is particularly attractive compared to other existing methods for spatial extremes. It is exceptionally fast, easy to implement, scalable to high dimensions and, in principle, applicable for any spatial resolution. We generated datasets with 10,000 gridpoints, a number that can be increased without difficulty. Since current impact models often require high-resolution climate inputs, the new algorithm is particularly useful for improved impact and vulnerability assessment.

Romy Schlögel, Romy Schlögel, Romy Schlögel et al.

Introduction: This study aims to differentiate local and regional ground uplift, as well as sub-regional subsidence induced by groundwater level drawdown, which are possibly enhanced across fault structures, as monitored by various synthetic aperture radar interferometry (InSAR) processing methods. A buoyant mantle plume under the Eifel may be responsible for the regional ground uplift, including the Weser–Geul (BE) and South Limburg regions (NL), which could negatively affect the area proposed for the future Einstein Telescope.Methods: Different InSAR processing techniques are compared to evaluate their limits in tracking fault structures on a time series of Copernicus Sentinel-1 images while detecting and measuring ground motion based on their phase signature. The results present an overall stable ground for the Euregio Meuse–Rhine region, especially at the Belgian–Dutch border, while tectonic activity is observed along the German side of the Rhine Graben.Results: As the current neotectonic activity in the target area was not well known, we performed a spatiotemporal analysis of ground deformation associated with the presence of NW–SE-trending normal faults where karst also develops, as well as along the Variscan NE–SW-trending thrust faults. This work demonstrates that the identification of deformation hazards using satellite remote sensing (and connected seismological) techniques is challenging mainly due to (very) small regional scale deformation, terrain conditions, and SAR properties.Discussion: Thus, the results mostly indicate ground stability over the area; however, also some agricultural activities were observed, as was deformation along some infrastructure such as railways. Displacements of millimetric order measured along the faults located near the Geul valley (BE) are probably related to old mining activities.

Wenbo Li, Xinya Zhao, Fengbo Guo et al.

To characterize seasonal carbonaceous aerosol pollution in Taiyuan, a typical city in North China that mainly relies heavily on coal, a total of 124 PM_2.5 samples were collected from August 2018 to the next May. The annual mean PM_2.5 concentration was 83.8 ± 48.5 μg m⁻³, with a seasonal rank of winter (117.4 ± 47.6 μg m⁻³) > spring (79.2 ± 34.3 μg m⁻³) > fall (67.3 ± 34.7 μg m⁻³) > summer (31.8 ± 6.5 μg m⁻³), suggesting that fine particulate pollution was still serious in cold seasons. Organic carbon (OC) and elemental carbon (EC) showed similar seasonal patterns with PM_2.5. The mean concentration values of OC in summer, fall, winter, and spring were 5.1 ± 0.9, 11.8 ± 6.4, 22.1 ± 14.9, and 12.2 ± 6.7 μg m⁻³, respectively. The mean concentration values of EC in summer, fall, winter, and spring were 1.5 ± 0.3, 2.5 ± 1.6, 4.4 ± 2.8, and 2.4 ± 1.5 μg m⁻³, respectively. The proportion of total carbon aerosol (TCA) was about 31.7%, 33.8%, 30.0%, and 27.0% in PM_2.5 in summer, fall, winter, and spring, respectively. The good correlation between OC vs. EC and the high value of OC/EC suggests that coal and biomass combustion were the main emissions in cold seasons, aggravated by adverse meteorological conditions and the dustpan-shaped terrain. The mean annual secondary organic carbon (SOC) concentration was 6.1 ± 7.1μg m⁻³, representing 38.7% of the OC content. The present results presented the serious carbonaceous particulate pollution, which might affect haze pollution in cold seasons.

Ismael Casotti Rienda, Célia A. Alves, Teresa Nunes et al.

The thoracic fraction of road dust (PM₁₀) was measured for the first time in Portugal in parking areas, both outdoors and indoors, with the aim of completing existing studies carried out in active lanes of various roads. An in situ resuspension chamber was used to collect a total of 23 samples in three parking areas of Aveiro, whilst the laboratory procedures included determination of carbonaceous content (OC and EC) by a thermo-optical technique, elemental composition by ICP-MS and ICP-OES after acid digestion, and the <i>Aliivribrio fisherii</i> bioluminescent bacteria ecotoxicity bioassay. Dust loadings (DL10) obtained were 18.5 ± 9.8 mg PM₁₀ m⁻², in outdoor parking, and 1.8–23.7 mg PM₁₀ m⁻² for indoor parking, corresponding to emission factors of 476 and 75–589 mg veh⁻¹ km⁻¹, respectively. OC represented 9–30 % of PM₁₀ for the indoor parking areas. However, for the outdoor samples, the high iron oxide content jeopardised the OC-EC separation. In those samples, carbonates accounted for 10.0 ± 3.3% of the PM₁₀ mass. The analysis of elemental components focused on major elements (Al, Ca, Fe, K, and Mg) as well as minor elements. The total mass fraction of element oxides accounted for 27.1% (outdoor) and 23.6–34.3% (indoor). Σ_PAH calculated for all parking areas accounted for 8.38–36.9 μg g⁻¹ PM₁₀. The ecotoxicological bioassay showed that all aqueous solutions were toxic to bioluminescent bacteria, whereas no clear correlations could be made with specific component groups, with the exception of Σ_PAH and EC₅₀.

Zhan Tian, Xin-Yang Lyu, Huan Zou et al.

One of the key issues in climate risk management is to develop climate resilient infrastructure so as to ensure safety and sustainability of urban functioning systems as well as mitigate the adverse impacts associated with increasing climate hazards. However, conventional methods of assessing risks do not fully address the interaction of various subsystems within the city system and are unable to consolidate diverse opinions of various stakeholders on their assessments of sector-specific risks posed by climate change. To address this gap, this study advances an integrated-systems-analysis tool - Climate Risk Assessment of Infrastructure Tool (CRAIT), and applies it to analyze and compare the extent of risk factor exposure and vulnerability over time across five critical urban infrastructure sectors in Shanghai and Shenzhen, two cities that have distinctive geo-climate profiles and histories of infrastructure development. The results show significantly higher level of variation between the two cities in terms of vulnerability levels than that of exposure. More specifically, the sectors of critical buildings, water, energy, and information &amp; communication in Shenzhen have significantly higher vulnerability levels than Shanghai in both the 2000s and the 2050s. We further discussed the vulnerability levels of subsystems in each sector and proposed twelve potential adaptation options for the roads system based on four sets of criteria: technical feasibility, flexibility, co-benefits, and policy compatibility. The application of CRAIT is bound to be a knowledge co-production process with the local experts and stakeholders. This knowledge co-production process highlights the importance of management advancements and nature-based green solutions in managing climate change risk in the future though differences are observed across the efficacy categories due to the geographical and meteorological conditions in the two cities. This study demonstrates that this knowledge co-creation process is valuable in facilitating policymakers' decision-making and their feedback to scientific understanding in climate risk assessment, and that this approach has general applicability for cities in other regions and countries.

Han Wang, Zan‐Yang Xing, Nanan Balan et al.

Abstract Geomagnetically induced current (GIC) in utility systems such as electric power grids occurring during extreme geomagnetic storms can exceed the tolerance limit of the systems, which can cause serious system damages. It has therefore been important to evaluate the GIC levels in the utility systems. This study presents the simulation and analysis of GIC levels in the Shandong 500 kV power grid system consisting of 34 substations under a variety of uniform induced geoelectric fields. The line type, substation grounding resistance, and other influencing factors are included in the simulations. The results show that the GIC level varies largely in the 34 substations. In 11 substations, the GIC exceeds 100 A and it reaches up to ∼200 A in two substations for an assumed 1 V/km induced electric field. The changes in the GIC distribution are found consistent with the direction changes of the electric field. Utilizing the directional sensitivity, we calculate the maximum GIC level for the optimum direction for all substations. By combining this information with statistical tools, we propose a method for identifying the key substations which are most vulnerable. The result can provide suggestions for GIC disaster prevention and mitigation, substation site selection, monitoring equipment installation, and so on, in Shandong province.

Alessandra Boggio-Marzet, Andrés Monzón, Pablo Luque-Rodríguez et al.

Cities are experiencing a process of suburbanization and last-mile delivery has grown, worsening traffic congestion, pollutant emissions, and citizens’ quality of life. Based on a real-life case study, this research compares the environmental performance of different delivery routes carried out by Diesel Light-Duty Vehicles (LDV) according to delivery area, city center or peri-urban. Some 242 delivery routes performed by thirteen drivers were recorded for one month, including instantaneous GPS position, speed, and other parameters (7262 km travelled). Four different delivery routes typologies were compared, and the drag function of the vehicles was characterized. It enabled calibration and modelling dynamics to calculate fuel consumption and pollutant emissions according to delivery routes. The results show that pedestrian crossings, traffic lights, and traffic congestion reduce the average operating speed by up to 57% in the city center and consequently overall energy efficiency. Our results highlight the urgency of replacing diesel LDV for deliveries in the city center with no-motorized transport modes and of implementing intermodality to cover deliveries in residential peri-urban areas. Due to low speeds and frequent start-stops, the efficiency of vehicles in these areas is reduced to a minimum and pollutant emissions increase. The outputs set a basis for recommendations for using LDV only for delivery routes with less traffic interruptions and foster intermodal solutions.

V. Kholodovsky, X.-Z. Liang, X.-Z. Liang

<p>Extreme weather and climate events such as floods, droughts, and heat waves can cause extensive societal damages. While various statistical and climate models have been developed for the purpose of simulating extremes, a consistent definition of extreme events is still lacking. Furthermore, to better assess the performance of the climate models, a variety of spatial forecast verification measures have been developed. However, in most cases, the spatial verification measures that are widely used to compare mean states do not have sufficient theoretical justification to benchmark extreme events. In order to alleviate inconsistencies when defining extreme events within different scientific communities, we propose a new generalized Spatio-Temporal Threshold Clustering method for the identification of extreme event episodes, which uses machine learning techniques to couple existing pattern recognition indices with high or low threshold choices. The method consists of five main steps: (1) construction of essential field quantities; (2) dimension reduction; (3) spatial domain mapping; (4) time series clustering; and (5) threshold selection. We develop and apply this method using a gridded daily precipitation dataset derived from rain gauge stations over the contiguous United States. We observe changes in the distribution of conditional frequency of extreme precipitation from large-scale well-connected spatial patterns to smaller-scale more isolated rainfall clusters, possibly leading to more localized droughts and heat waves, especially during the summer months. The proposed method automates the threshold selection process through a clustering algorithm and can be directly applicable in conjunction with modeling and spatial forecast verification of extremes. Additionally, it allows for the identification of synoptic-scale spatial patterns that can be directly traced to the individual extreme episodes, and it offers users the flexibility to select an extreme threshold that is linked to the desired geometrical properties. The approach can be applied to broad scientific disciplines.</p>

Russell L. Elsberry, Hsiao-Chung Tsai, Wei-Chia Chin et al.

When the environmental conditions over the western North Pacific are favorable for tropical cyclone formation, a rapid intensification event will frequently follow formation. In this extension of our combined three-stage 7-day Weighted Analog Intensity Pacific prediction technique, the European Centre for Medium-range Weather Prediction ensemble predictions of the warm core magnitudes of pre-tropical cyclone circulations are utilized to define the Time-to-Formation (35 knots) and to estimate the Likely Storm Category. If that category is a Typhoon, the bifurcation version of our technique is modified to better predict the peak intensity by selecting only Cluster 1 analog storms with the largest peak intensities that are most likely to have under-gone rapid intensification. A second modification to improve the peak intensity magnitude and timing was to fit a cubic spline curve through the weighted-mean peak intensities of the Cluster 1 analogs. The performance of this modified technique has been evaluated for a sequence of western North Pacific tropical cyclones during 2019 in terms of: (i) Detection time in advance of formation; (ii) Accuracy of Time-to-Formation; (iii) Intensification stage prediction; and (iv) Peak intensity magnitude/timing. This modified technique would provide earlier guidance as to the threat of a Typhoon along the 15-day ensemble storm track forecast, which would be a benefit for risk management officials.

Islam Abou El-Magd, Naglaa Zanaty, Elham M. Ali et al.

Egypt experiences high rates of air pollution, which is a major threat to human health and the eco-environment and therefore needs to be tackled by defining major causes to hinder or mitigate their impacts. The major driving forces of air pollution are either of local and/or regional origin. In addition, seasonal aerosols may be natural, such as dust particles transported from the western desert, or anthropogenic aerosols which are transported from industrial areas and smoke particles from seasonal biomass burning. Monitoring the optical properties of aerosols and their pattern in the atmosphere on a daily basis requires a robust source of information and professional analytical tools. This research explored the potential of using time series of Moderate Resolution Imaging Spectroradiometer (MODIS) and Aerosol Robotic Network (AERONET) data to comprehensively investigate the aerosol optical depth (AOD) and variability for the period 2012–2018 on a daily basis. The data show that spring, summer and autumn seasons experienced the highest anomaly originating from regional and national sources. The high AOD in spring associated with a low Ångström exponent (AE) indicates the presence of coarse particles which naturally originate from desert dust or sea spray. In contrast, the high AE in summer and autumn demonstrated the dominance of fine anthropogenic aerosols such as smoke particles from local biomass burning. The observation of a high number of fire incidents over Egypt in October and November 2018, during the months of rice crop harvesting, showed that these incidents contribute to the presence of autumn aerosols across the country. In-situ measurements of Particulate Matter (PM₁₀) from local stations from an environmental based network as well as the AERONET AOD were used to validate the MODIS AOD, providing a high correlation coefficient of r = 0.73.

Jie Luo, Yongming Zhang, Qixing Zhang

In this work, the absorption Ångström exponent (AAE), extinction Ångström exponent (EAE), and single-scattering albedo (SSA) of black carbon (BC) with different coating materials are numerically investigated. BC with different coating materials can provide explanations for the small AAE, small EAE, and large AAE observed in the atmosphere, which is difficult to be explained by bare BC aggregate models. The addition of organic carbon (OC) does not necessarily increase AAE due to the transformation of BC morphologies and the existence of non-absorbing OC. The addition of coating materials does also not necessarily decrease EAE. While the addition of coating materials can increase the total size of BC-containing particles, the effective refractive index can be modified by introducing the coating materials, so increases the EAE. We found that it is not possible to differentiate between thinly- and heavily-coated BC based on EAE or AAE alone. On the other hand, SSA is much less sensitive to the size and can provide much more information for distinguishing heavily-coated BC from thinly-coated BC. For BC with different coating materials and mixing states, AAE, EAE, and SSA show rather different sensitivities to particle size and composition ratios, and their spectral-dependences also exhibit distinct differences. Different AAE and EAE trends with BC/OC ratio were also found for BC with different coating materials and mixing states. Furthermore, we also found empirical fittings for AAE, EAE, SSA, and optical cross-sections, which may be useful for retrieving the size information based on the optical measurements.

Lanhui Li, Yili Zhang, Wei Qi et al.

Climate warming on the Tibetan Plateau has been regarded as an important driving force of regional environmental change. Although several studies have analyzed the shift of warming trends on this plateau within the context of a recent global warming &#8220;hiatus&#8221; since 1998, their disparate findings have hindered a comprehensive and regional understanding. Based on the daily mean temperature (<i>T</i>_mean), maximum temperature (<i>T</i>_max), and minimum temperature (<i>T</i>_min) collected from meteorological stations on the period of 1961&#8722;2017, we re-examined the timing and magnitude of temperature phase change using piecewise linear regression on the mid-south of Tibetan Plateau. The results show that among the trends in regional annual <i>T</i>_mean, <i>T</i>_max and <i>T</i>_min, the statistically significant change-point was observed only in annual <i>T</i>_max (<i>p</i> &lt; 0.01)_. The warming trend of annual <i>T</i>_max has accelerated significantly since 1992 and has exceeded that of annual <i>T</i>_min after 2000, causing a remarkable reversal from decline to increase in diurnal temperature range (DTR) (<i>p</i> &lt; 0.01). Spatially, the occurrence time of change-points in <i>T</i>_mean, <i>T</i>_max, and <i>T</i>_min varied among stations, but most of them occurred before the mid-1990s. Besides, the trend shifts in <i>T</i>_max/DTR during the cold season played a primary role in the significant trend shifts in annual <i>T</i>_max/DTR. This study underscores that there is no significant shift of warming trends over the last two decades on the mid-south of Tibetan Plateau.

Mona Kurppa, Antti Hellsten, Mikko Auvinen et al.

Buildings and vegetation alter the wind and pollutant transport in urban environments. This comparative study investigates the role of orientation and shape of perimeter blocks on the dispersion and ventilation of traffic-related air pollutants, and the street-level concentrations along a planned city boulevard. A large-eddy simulation (LES) model PALM is employed over a highly detailed representation of the urban domain including street trees and forested areas. Air pollutants are represented by massless and passive particles (non-reactive gases), which are released with traffic-related emission rates. High-resolution simulations for four different city-block-structures are conducted over a 8.2 km 2 domain under two contrasting inflow conditions with neutral and stable atmospheric stratification corresponding the general and wintry meteorological conditions. Variation in building height together with multiple cross streets along the boulevard improves ventilation, resulting in 7–9% lower mean concentrations at pedestrian level. The impact of smaller scale variability in building shape was negligible. Street trees further complicate the flow and dispersion. Notwithstanding the surface roughness, atmospheric stability controls the concentration levels with higher values under stably stratified inflow. Little traffic emissions are transported to courtyards. The results provide urban planners direct information to reduce air pollution by proper structural layout of perimeter blocks.

DENIS VOYTENKO, TIMOTHY H. DIXON, DAVID M. HOLLAND et al.

Outlet glaciers undergo rapid spatial and temporal changes in flow velocity during calving events. Observing such changes requires both high temporal and high spatial resolution methods, something now possible with terrestrial radar interferometry. While a single such radar provides line-of-sight velocity, two radars define both components of the horizontal flow field. To assess the feasibility of obtaining the two-dimensional (2-D) flow field, we deployed two terrestrial radar interferometers at Jakobshavn Isbrae, a major outlet glacier on Greenland's west coast, in the summer of 2012. Here, we develop and demonstrate a method to combine the line-of-sight velocity data from two synchronized radars to produce a 2-D velocity field from a single (3 min) interferogram. Results are compared with the more traditional feature-tracking data obtained from the same radar, averaged over a longer period. We demonstrate the potential and limitations of this new dual-radar approach for obtaining high spatial and temporal resolution 2-D velocity fields at outlet glaciers.

Leydson Galvíncio Dantas, Carlos Antonio Costa dos Santos, Ricardo Alves de Olinda

RESUMO Devido à rápida expansão urbana e potencial turístico da região, o objetivo deste estudo foi a obtenção da distribuição temporal dos índices de extremos climáticos dependentes de dados diários de temperatura e precipitação, definido pela OMM, para o período de 1975 a 2011, e utilizando os testes estatísticos não paramétricos obter a magnitude das tendências dos referidos índices para a cidade de Campina Grande - PB. Os resultados mostram que as temperaturas mínimas e máxima diárias têm aumentado gradativamente ao longo das últimas décadas, apresentando tendências sazonais crescentes ao longo dos anos e que as temperaturas mínimas tiveram maior aumento. O número de dias e noites quentes por ano tem aumentado, proporcionando assim uma redução significativa dos dias e noites frias. Foi observado que as temperaturas mínimas e máximas apresentam maiores tendências de aumento nas estações do outono e primavera, respectivamente. Baseado nos índices extremos de precipitação, mesmo sem significância estatística, foi observado que as chuvas intensas tendem a aumentar, ocorrendo em um período menor de tempo.

Timothy Paul Eichler, Jon Gottschalck

Southern Hemisphere (SH) extratropical cyclones have received less study than their Northern Hemisphere (NH) counterparts. Generating SH cyclone tracks from global reanalysis datasets is problematic due to data reliability, especially prior to 1979. It is therefore prudent to compare the climatology and variability of SH cyclone tracks from different reanalysis datasets. We generate cyclone track frequency and intensity climatologies from three reanalysis datasets: The National Center for Environmental Prediction’s Reanalysis I and Reanalysis II datasets and the European Centre for Medium Range Weather Forecasts ERA-40 dataset. Our results show that ERA-40 produces more intense cyclones in the SH active cyclone region compared to NCEP reanalyses. More intense storms are also found in the SH active cyclone region in NCEP reanalyses data post-1979 reflecting the positive trend in the AAO in the past few decades. When evaluating interannual variability, our results show Rossby wave trains including the Pacific South American (PSA) and the East Indian Ocean pattern in response to anomalous heating linked to El Niño and the Indian Ocean Dipole (IOD), respectively. Response to the AAO shows a robust annular structure for cyclone track frequency, but not intensity suggesting a weak relationship between cyclone frequency and cyclone intensity.